From 31f1fbe55f97208ab395a67333d68dc2096cf5c4 Mon Sep 17 00:00:00 2001 From: Karl Lessard Date: Fri, 18 Oct 2024 15:59:35 -0400 Subject: [PATCH 01/11] Upgrade to TF 2.18.0-rc2 --- .../scripts/test_download.sh | 3 + .../src/api/api_def_XlaCallModule.pbtxt | 2 +- .../tensorflow-core-native/WORKSPACE | 151 +++++---- .../scripts/dist_download.sh | 2 +- .../tensorflow-core-native/tensorflow.bazelrc | 298 ++++++++++-------- 5 files changed, 261 insertions(+), 195 deletions(-) diff --git a/tensorflow-core/tensorflow-core-api/scripts/test_download.sh b/tensorflow-core/tensorflow-core-api/scripts/test_download.sh index 5f47ee00115..01345823683 100755 --- a/tensorflow-core/tensorflow-core-api/scripts/test_download.sh +++ b/tensorflow-core/tensorflow-core-api/scripts/test_download.sh @@ -10,6 +10,9 @@ case ${PLATFORM:-} in 'macosx-x86_64') TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/6d/69/9999c2d9e8a3b08dfcfc7e9259a05fb1da5f700936091d2eb4a7985c2776/tensorflow-2.16.2-cp311-cp311-macosx_10_15_x86_64.whl' ;; + 'macosx-arm64') + TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/e7/0d/20b259aadf5f98bad45d55dcd3a7e2690058bb4bc1188dd9e36ab9bdd2ec/tensorflow_text-2.18.0rc0-cp310-cp310-macosx_11_0_arm64.whl' + ;; *) echo "TensorFlow Text distribution for ${PLATFORM} is not supported for download" exit 0; diff --git a/tensorflow-core/tensorflow-core-api/src/api/api_def_XlaCallModule.pbtxt b/tensorflow-core/tensorflow-core-api/src/api/api_def_XlaCallModule.pbtxt index ae152ae6245..b195d388983 100644 --- a/tensorflow-core/tensorflow-core-api/src/api/api_def_XlaCallModule.pbtxt +++ b/tensorflow-core/tensorflow-core-api/src/api/api_def_XlaCallModule.pbtxt @@ -1,6 +1,6 @@ op { graph_op_name: "XlaCallModule" - visibility: HIDDEN + visibility: VISIBLE endpoint { name: "xla.XlaCallModule" } diff --git a/tensorflow-core/tensorflow-core-native/WORKSPACE b/tensorflow-core/tensorflow-core-native/WORKSPACE index 1a745b13613..f321c83b831 100644 --- a/tensorflow-core/tensorflow-core-native/WORKSPACE +++ b/tensorflow-core/tensorflow-core-native/WORKSPACE @@ -18,10 +18,10 @@ http_archive( "find tensorflow third_party/xla/third_party/tsl -name \\*.proto | xargs sed -i.bak 's/^package tensorflow\\([^;]*\\).*$/package tensorflow\\1;\\noption java_package = \"org.tensorflow.proto\\1\";/'", ], urls = [ - "https://github.com/tensorflow/tensorflow/archive/refs/tags/v2.16.2.tar.gz", + "https://github.com/tensorflow/tensorflow/archive/refs/tags/v2.18.0-rc2.tar.gz", ], - sha256 = "023849bf253080cb1e4f09386f5eb900492da2288274086ed6cfecd6d99da9eb", - strip_prefix = "tensorflow-2.16.2" + sha256 = "ed371d42f69b9029175b0a70667c4c65d02a269887353520d5cfca5ce8eb7855", + strip_prefix = "tensorflow-2.18.0-rc2" ) ##### Copy content of tensorflow/WORKSPACE here (make sure to change references of default package "//" to "@org_tensorflow//") @@ -30,80 +30,56 @@ http_archive( load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive") http_archive( - name = "bazel_skylib", - sha256 = "74d544d96f4a5bb630d465ca8bbcfe231e3594e5aae57e1edbf17a6eb3ca2506", - urls = [ - "https://storage.googleapis.com/mirror.tensorflow.org/github.com/bazelbuild/bazel-skylib/releases/download/1.3.0/bazel-skylib-1.3.0.tar.gz", - "https://github.com/bazelbuild/bazel-skylib/releases/download/1.3.0/bazel-skylib-1.3.0.tar.gz", - ], + name = "rules_java", + sha256 = "c73336802d0b4882e40770666ad055212df4ea62cfa6edf9cb0f9d29828a0934", + url = "https://github.com/bazelbuild/rules_java/releases/download/5.3.5/rules_java-5.3.5.tar.gz", ) -http_archive( - name = "rules_python", - sha256 = "9d04041ac92a0985e344235f5d946f71ac543f1b1565f2cdbc9a2aaee8adf55b", - strip_prefix = "rules_python-0.26.0", - url = "https://github.com/bazelbuild/rules_python/releases/download/0.26.0/rules_python-0.26.0.tar.gz", -) - -load("@rules_python//python:repositories.bzl", "py_repositories") +# Initialize the TensorFlow repository and all dependencies. +# +# The cascade of load() statements and tf_workspace?() calls works around the +# restriction that load() statements need to be at the top of .bzl files. +# E.g. we can not retrieve a new repository with http_archive and then load() +# a macro from that repository in the same file. +load("@org_tensorflow//tensorflow:workspace3.bzl", "tf_workspace3") -py_repositories() +tf_workspace3() -load("@rules_python//python:repositories.bzl", "python_register_toolchains") -load( - "@org_tensorflow//tensorflow/tools/toolchains/python:python_repo.bzl", - "python_repository", -) +# Initialize hermetic Python +load("@local_xla//third_party/py:python_init_rules.bzl", "python_init_rules") -python_repository(name = "python_version_repo") +python_init_rules() -load("@python_version_repo//:py_version.bzl", "TF_PYTHON_VERSION") +load("@local_xla//third_party/py:python_init_repositories.bzl", "python_init_repositories") -python_register_toolchains( - name = "python", - ignore_root_user_error = True, - python_version = TF_PYTHON_VERSION, +python_init_repositories( + default_python_version = "system", + local_wheel_dist_folder = "dist", + local_wheel_inclusion_list = [ + "tensorflow*", + "tf_nightly*", + ], + local_wheel_workspaces = ["//:WORKSPACE"], + requirements = { + "3.9": "@org_tensorflow//:requirements_lock_3_9.txt", + "3.10": "@org_tensorflow//:requirements_lock_3_10.txt", + "3.11": "@org_tensorflow//:requirements_lock_3_11.txt", + "3.12": "@org_tensorflow//:requirements_lock_3_12.txt", + }, ) -load("@python//:defs.bzl", "interpreter") -load("@rules_python//python:pip.bzl", "package_annotation", "pip_parse") +load("@local_xla//third_party/py:python_init_toolchains.bzl", "python_init_toolchains") -NUMPY_ANNOTATIONS = { - "numpy": package_annotation( - additive_build_content = """\ -filegroup( - name = "includes", - srcs = glob(["site-packages/numpy/core/include/**/*.h"]), -) -cc_library( - name = "numpy_headers", - hdrs = [":includes"], - strip_include_prefix="site-packages/numpy/core/include/", -) -""", - ), -} - -#pip_parse( -# name = "pypi", -# annotations = NUMPY_ANNOTATIONS, -# python_interpreter_target = interpreter, -# requirements = "//:requirements_lock_" + HERMETIC_PYTHON_VERSION.replace(".", "_") + ".txt", -#) +python_init_toolchains() -#load("@pypi//:requirements.bzl", "install_deps") +load("@local_xla//third_party/py:python_init_pip.bzl", "python_init_pip") -#install_deps() +python_init_pip() -# Initialize the TensorFlow repository and all dependencies. -# -# The cascade of load() statements and tf_workspace?() calls works around the -# restriction that load() statements need to be at the top of .bzl files. -# E.g. we can not retrieve a new repository with http_archive and then load() -# a macro from that repository in the same file. -load("@org_tensorflow//tensorflow:workspace3.bzl", "tf_workspace3") +load("@pypi//:requirements.bzl", "install_deps") -tf_workspace3() +install_deps() +# End hermetic Python initialization load("@org_tensorflow//tensorflow:workspace2.bzl", "tf_workspace2") @@ -115,4 +91,51 @@ tf_workspace1() load("@org_tensorflow//tensorflow:workspace0.bzl", "tf_workspace0") -tf_workspace0() \ No newline at end of file +tf_workspace0() + +load( + "@local_tsl//third_party/gpus/cuda/hermetic:cuda_json_init_repository.bzl", + "cuda_json_init_repository", +) + +cuda_json_init_repository() + +load( + "@cuda_redist_json//:distributions.bzl", + "CUDA_REDISTRIBUTIONS", + "CUDNN_REDISTRIBUTIONS", +) +load( + "@local_tsl//third_party/gpus/cuda/hermetic:cuda_redist_init_repositories.bzl", + "cuda_redist_init_repositories", + "cudnn_redist_init_repository", +) + +cuda_redist_init_repositories( + cuda_redistributions = CUDA_REDISTRIBUTIONS, +) + +cudnn_redist_init_repository( + cudnn_redistributions = CUDNN_REDISTRIBUTIONS, +) + +load( + "@local_tsl//third_party/gpus/cuda/hermetic:cuda_configure.bzl", + "cuda_configure", +) + +cuda_configure(name = "local_config_cuda") + +load( + "@local_tsl//third_party/nccl/hermetic:nccl_redist_init_repository.bzl", + "nccl_redist_init_repository", +) + +nccl_redist_init_repository() + +load( + "@local_tsl//third_party/nccl/hermetic:nccl_configure.bzl", + "nccl_configure", +) + +nccl_configure(name = "local_config_nccl") diff --git a/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh b/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh index 7727faefaed..8c3b0d7d288 100755 --- a/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh +++ b/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh @@ -14,7 +14,7 @@ case ${PLATFORM:-} in WHEEL_URL='https://files.pythonhosted.org/packages/6d/69/9999c2d9e8a3b08dfcfc7e9259a05fb1da5f700936091d2eb4a7985c2776/tensorflow-2.16.2-cp311-cp311-macosx_10_15_x86_64.whl' ;; 'macosx-arm64') - WHEEL_URL='https://files.pythonhosted.org/packages/9d/72/6f09443493b9df2fd8a9585c9af4d9453762906a8e5735a8a5efa6e3d1e3/tensorflow-2.16.2-cp311-cp311-macosx_12_0_arm64.whl' + WHEEL_URL='https://files.pythonhosted.org/packages/20/91/4358b8f5c83ff0dff679fdcdde0f7d6020dd47ef0c00d3e815ec3ceae426/tensorflow-2.18.0rc2-cp312-cp312-macosx_12_0_arm64.whl' ;; 'windows-x86_64') WHEEL_URL='https://files.pythonhosted.org/packages/46/87/c3e4e9fe7c630f38a6984afdd1d4ed531ef9c74dc66b86f46f6bdd89d608/tensorflow_intel-2.16.2-cp311-cp311-win_amd64.whl' diff --git a/tensorflow-core/tensorflow-core-native/tensorflow.bazelrc b/tensorflow-core/tensorflow-core-native/tensorflow.bazelrc index 1e1bc4461f7..f48811d13d2 100644 --- a/tensorflow-core/tensorflow-core-native/tensorflow.bazelrc +++ b/tensorflow-core/tensorflow-core-native/tensorflow.bazelrc @@ -41,26 +41,20 @@ # cuda_clang Build with CUDA Clang support. # rocm: Build with AMD GPU support (rocm) # mkl: Enable full mkl support. -# tensorrt: Enable Tensorrt support. -# noaws: Disable AWS S3 storage support # nogcp: Disable GCS support. -# nohdfs: Disable hadoop hdfs support. # nonccl: Disable nccl support. # # # Remote build execution options (only configured to work with TF team projects for now.) # rbe_base: General RBE options shared by all flavors. # rbe_linux: General RBE options used on all linux builds. -# rbe_win: General RBE options used on all windows builds. +# rbe_win_base: General RBE options used on all Windows builds. Not to be used standalone. +# rbe_win_clang: Options specific to compiling using Clang. # # rbe_linux_cpu: RBE options to build with only CPU support. # rbe_linux_cuda: RBE options to build with GPU support using clang. # rbe_linux_cuda_nvcc: RBE options to build with GPU support using nvcc. # -# rbe_win_py39: Windows Python 3.9 RBE config -# -# tensorflow_testing_rbe_win: RBE options to use RBE with tensorflow-testing project on windows -# # Embedded Linux options (experimental and only tested with TFLite build yet) # elinux: General Embedded Linux options shared by all flavors. # elinux_aarch64: Embedded Linux options for aarch64 (ARM64) CPU support. @@ -120,10 +114,6 @@ build --config=short_logs # TODO(mihaimaruseac): Document this option or remove if no longer needed build --config=v2 -# Disable AWS/HDFS support by default -build --define=no_aws_support=true -build --define=no_hdfs_support=true - # TF now has `cc_shared_library` targets, so it needs the experimental flag # TODO(rostam): Remove when `cc_shared_library` is enabled by default build --experimental_cc_shared_library @@ -160,6 +150,8 @@ build:android_x86_64 --fat_apk_cpu=x86_64 # Build everything statically for Android since all static libs are later # bundled together into a single .so for deployment. build:android --dynamic_mode=off +# TODO(belitskiy): Remove once on Clang 20. +build:android --define=xnn_enable_avxvnniint8=false # Sets the default Apple platform to macOS. build:macos --apple_platform_type=macos @@ -228,13 +220,19 @@ build:mkl_aarch64_threadpool -c opt build:cuda --repo_env TF_NEED_CUDA=1 build:cuda --crosstool_top=@local_config_cuda//crosstool:toolchain build:cuda --@local_config_cuda//:enable_cuda +# Default CUDA and CUDNN versions. +build:cuda --repo_env=HERMETIC_CUDA_VERSION="12.5.1" +build:cuda --repo_env=HERMETIC_CUDNN_VERSION="9.3.0" +# This flag is needed to include CUDA libraries. +build:cuda --@local_config_cuda//cuda:include_cuda_libs=true + +# This configuration is used for building the wheels. +build:cuda_wheel --@local_config_cuda//cuda:include_cuda_libs=false # CUDA: This config refers to building CUDA op kernels with clang. build:cuda_clang --config=cuda -# Enable TensorRT optimizations https://developer.nvidia.com/tensorrt -build:cuda_clang --config=tensorrt -build:cuda_clang --action_env=TF_CUDA_CLANG="1" build:cuda_clang --@local_config_cuda//:cuda_compiler=clang +build:cuda_clang --copt=-Qunused-arguments # Select supported compute capabilities (supported graphics cards). # This is the same as the official TensorFlow builds. # See https://developer.nvidia.com/cuda-gpus#compute @@ -243,22 +241,22 @@ build:cuda_clang --@local_config_cuda//:cuda_compiler=clang # release while SASS is only forward compatible inside the current # major release. Example: sm_80 kernels can run on sm_89 GPUs but # not on sm_90 GPUs. compute_80 kernels though can also run on sm_90 GPUs. -build:cuda_clang --repo_env=TF_CUDA_COMPUTE_CAPABILITIES="sm_50,sm_60,sm_70,sm_80,compute_90" +build:cuda_clang --repo_env=HERMETIC_CUDA_COMPUTE_CAPABILITIES="sm_60,sm_70,sm_80,sm_89,compute_90" +# Set lld as the linker. +build:cuda_clang --host_linkopt="-fuse-ld=lld" +build:cuda_clang --host_linkopt="-lm" +build:cuda_clang --linkopt="-fuse-ld=lld" +build:cuda_clang --linkopt="-lm" # Set up compilation CUDA version and paths and use the CUDA Clang toolchain. build:cuda_clang_official --config=cuda_clang -build:cuda_clang_official --action_env=TF_CUDA_VERSION="12" -build:cuda_clang_official --action_env=TF_CUDNN_VERSION="8" -build:cuda_clang_official --action_env=CUDA_TOOLKIT_PATH="/usr/local/cuda-12.3" -build:cuda_clang_official --action_env=GCC_HOST_COMPILER_PATH="/dt9/usr/bin/gcc" -build:cuda_clang_official --action_env=CLANG_CUDA_COMPILER_PATH="/usr/lib/llvm-17/bin/clang" -build:cuda_clang_official --action_env=LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64" -build:cuda_clang_official --crosstool_top="@sigbuild-r2.16-clang_config_cuda//crosstool:toolchain" +build:cuda_clang_official --repo_env=HERMETIC_CUDA_VERSION="12.5.1" +build:cuda_clang_official --repo_env=HERMETIC_CUDNN_VERSION="9.3.0" +build:cuda_clang_official --action_env=CLANG_CUDA_COMPILER_PATH="/usr/lib/llvm-18/bin/clang" +build:cuda_clang_official --crosstool_top="@local_config_cuda//crosstool:toolchain" # Build with nvcc for CUDA and clang for host build:nvcc_clang --config=cuda -# Unfortunately, cuda_configure.bzl demands this for using nvcc + clang -build:nvcc_clang --action_env=TF_CUDA_CLANG="1" build:nvcc_clang --action_env=TF_NVCC_CLANG="1" build:nvcc_clang --@local_config_cuda//:cuda_compiler=nvcc @@ -286,17 +284,18 @@ build:tpu --define=framework_shared_object=true build:tpu --copt=-DLIBTPU_ON_GCE build:tpu --define=enable_mlir_bridge=true -build:tensorrt --repo_env TF_NEED_TENSORRT=1 - build:rocm --crosstool_top=@local_config_rocm//crosstool:toolchain build:rocm --define=using_rocm_hipcc=true build:rocm --define=tensorflow_mkldnn_contraction_kernel=0 build:rocm --repo_env TF_NEED_ROCM=1 +build:sycl --crosstool_top=@local_config_sycl//crosstool:toolchain +build:sycl --define=using_sycl=true +build:sycl --define=tensorflow_mkldnn_contraction_kernel=0 +build:sycl --repo_env TF_NEED_SYCL=1 + # Options to disable default on features -build:noaws --define=no_aws_support=true build:nogcp --define=no_gcp_support=true -build:nohdfs --define=no_hdfs_support=true build:nonccl --define=no_nccl_support=true # Modular TF build options @@ -357,6 +356,13 @@ build:windows --features=archive_param_file build:windows --copt=/d2ReducedOptimizeHugeFunctions build:windows --host_copt=/d2ReducedOptimizeHugeFunctions +# Before VS 2017 15.8, the member "type" would non-conformingly have an +# alignment of only alignof(max_align_t). VS 2017 15.8 was fixed to handle this +# correctly, but the fix inherently changes layout and breaks binary +# compatibility (*only* for uses of aligned_storage with extended alignments). +build:windows --copt=-D_ENABLE_EXTENDED_ALIGNED_STORAGE +build:windows --host_copt=-D_ENABLE_EXTENDED_ALIGNED_STORAGE + # Enable the runfiles symlink tree on Windows. This makes it possible to build # the pip package on Windows without an intermediate data-file archive, as the # build_pip_package script in its current form (as of Aug 2023) uses the @@ -445,10 +451,25 @@ build:win_clang --host_linkopt=/FORCE:MULTIPLE test:win_clang --linkopt=/FORCE:MULTIPLE test:win_clang --host_linkopt=/FORCE:MULTIPLE +# Same config as above but for XLA, which has different toolchain paths +build:win_clang_xla --copt=/clang:-Weverything +build:win_clang_xla --extra_toolchains=@local_config_cc//:cc-toolchain-x64_windows-clang-cl +build:win_clang_xla --extra_execution_platforms=//tools/toolchains/win:x64_windows-clang-cl +build:win_clang_xla --host_platform=//tools/toolchains/win:x64_windows-clang-cl +build:win_clang_xla --compiler=clang-cl +build:win_clang_xla --linkopt=/FORCE:MULTIPLE +build:win_clang_xla --host_linkopt=/FORCE:MULTIPLE +test:win_clang_xla --action_env=PATHEXT=.COM;.EXE;.BAT;.CMD;.VBS;.VBE;.JS;.JSE;.WSF;.WSH;.MSC;.PY;.PYW +test:win_clang_xla --linkopt=/FORCE:MULTIPLE +test:win_clang_xla --host_linkopt=/FORCE:MULTIPLE + # Options to build TensorFlow 1.x or 2.x. # TODO(kanglan): Change v2's define to default behavior build:v2 --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1 +# Enable all targets in XLA +build:cpu_cross --define=with_cross_compiler_support=true + # Disable XLA on mobile. build:xla --define=with_xla_support=true # TODO: remove, it's on by default. build:android --define=with_xla_support=false @@ -494,12 +515,14 @@ build:rbe_linux --host_linkopt=-lm build:rbe_linux_cpu --config=rbe_linux # Linux cpu and cuda builds share the same toolchain now. -build:rbe_linux_cpu --host_crosstool_top="@sigbuild-r2.16-clang_config_cuda//crosstool:toolchain" -build:rbe_linux_cpu --crosstool_top="@sigbuild-r2.16-clang_config_cuda//crosstool:toolchain" -build:rbe_linux_cpu --extra_toolchains="@sigbuild-r2.16-clang_config_cuda//crosstool:toolchain-linux-x86_64" -build:rbe_linux_cpu --extra_execution_platforms="@sigbuild-r2.16-clang_config_platform//:platform" -build:rbe_linux_cpu --host_platform="@sigbuild-r2.16-clang_config_platform//:platform" -build:rbe_linux_cpu --platforms="@sigbuild-r2.16-clang_config_platform//:platform" +build:rbe_linux_cpu --host_crosstool_top="@local_config_cuda//crosstool:toolchain" +build:rbe_linux_cpu --crosstool_top="@local_config_cuda//crosstool:toolchain" +build:rbe_linux_cpu --extra_toolchains="@local_config_cuda//crosstool:toolchain-linux-x86_64" +build:rbe_linux_cpu --repo_env=CC="/usr/lib/llvm-18/bin/clang" +build:rbe_linux_cpu --repo_env=TF_SYSROOT="/dt9" +build:rbe_linux_cpu --extra_execution_platforms="@sigbuild-r2.17-clang_config_platform//:platform" +build:rbe_linux_cpu --host_platform="@sigbuild-r2.17-clang_config_platform//:platform" +build:rbe_linux_cpu --platforms="@sigbuild-r2.17-clang_config_platform//:platform" # This is needed for all Clang17 builds but must not be present in GCC builds. build:rbe_linux_cpu --copt=-Wno-error=unused-command-line-argument # This was added in clang-16 by https://reviews.llvm.org/D133574. @@ -508,7 +531,6 @@ build:rbe_linux_cpu --copt=-Wno-error=unused-command-line-argument # See https://github.com/protocolbuffers/upb/blob/9effcbcb27f0a665f9f345030188c0b291e32482/upb/upb.c#L183. build:rbe_linux_cpu --copt=-Wno-gnu-offsetof-extensions # Python config is the same across all containers because the binary is the same -build:rbe_linux_cpu --repo_env=TF_PYTHON_CONFIG_REPO="@sigbuild-r2.16-clang_config_python" build:rbe_linux_cpu --python_path="/usr/bin/python3" # These you may need to change for your own GCP project. common:rbe_linux_cpu --remote_instance_name=projects/tensorflow-testing/instances/default_instance @@ -522,54 +544,39 @@ build:rbe_linux_cpu_old --extra_execution_platforms="@ubuntu20.04-gcc9_manylinux build:rbe_linux_cpu_old --host_platform="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform" build:rbe_linux_cpu_old --platforms="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform" build:rbe_linux_cpu_old --python_path="/usr/local/bin/python3.9" -build:rbe_linux_cpu_old --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.9" common:rbe_linux_cpu_old --remote_instance_name=projects/tensorflow-testing/instances/default_instance build:rbe_linux_cuda --config=cuda_clang_official build:rbe_linux_cuda --config=rbe_linux_cpu # For Remote build execution -- GPU configuration build:rbe_linux_cuda --repo_env=REMOTE_GPU_TESTING=1 -build:rbe_linux_cuda --repo_env=TF_CUDA_CONFIG_REPO="@sigbuild-r2.16-clang_config_cuda" -build:rbe_linux_cuda --repo_env=TF_TENSORRT_CONFIG_REPO="@sigbuild-r2.16-clang_config_tensorrt" -build:rbe_linux_cuda --repo_env=TF_NCCL_CONFIG_REPO="@sigbuild-r2.16-clang_config_nccl" -test:rbe_linux_cuda --test_env=LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64" build:rbe_linux_cuda_nvcc --config=rbe_linux_cuda build:rbe_linux_cuda_nvcc --config=nvcc_clang build:rbe_linux_cuda_nvcc --repo_env TF_NCCL_USE_STUB=1 -# TODO(kanglan): Remove rbe_win and rbe_win_py3* after b/289091160 is fixed -build:rbe_win --config=rbe_base -build:rbe_win --crosstool_top="//tensorflow/tools/toolchains/win/tf_win_05022023:toolchain" -build:rbe_win --extra_toolchains="//tensorflow/tools/toolchains/win/tf_win_05022023:cc-toolchain-x64_windows" -build:rbe_win --extra_execution_platforms="//tensorflow/tools/toolchains/win:rbe_windows_ltsc2019" -build:rbe_win --host_platform="//tensorflow/tools/toolchains/win:rbe_windows_ltsc2019" -build:rbe_win --platforms="//tensorflow/tools/toolchains/win:rbe_windows_ltsc2019" -build:rbe_win --shell_executable=C:\\tools\\msys64\\usr\\bin\\bash.exe -build:rbe_win --experimental_strict_action_env=true - -# TODO(gunan): Remove once we use MSVC 2019 with latest patches. -build:rbe_win --define=override_eigen_strong_inline=true - +build:rbe_win_base --config=rbe_base +build:rbe_win_base --shell_executable=C:\\tools\\msys64\\usr\\bin\\bash.exe +build:rbe_win_base --remote_instance_name=projects/tensorflow-testing/instances/windows # Don't build the python zip archive in the RBE build. -build:rbe_win --remote_download_minimal -build:rbe_win --enable_runfiles -build:rbe_win --nobuild_python_zip - -build:rbe_win_py38 --config=rbe_base -build:rbe_win_py38 --repo_env=PYTHON_BIN_PATH=C:\\Python38\\python.exe -build:rbe_win_py38 --repo_env=PYTHON_LIB_PATH=C:\\Python38\\lib\\site-packages -build:rbe_win_py38 --repo_env=TF_PYTHON_CONFIG_REPO=//tensorflow/tools/toolchains/win_1803/py38 -build:rbe_win_py38 --python_path=C:\\Python38\\python.exe - -build:rbe_win_py39 --config=rbe_base -build:rbe_win_py39 --repo_env=PYTHON_BIN_PATH=C:\\Python39\\python.exe -build:rbe_win_py39 --repo_env=PYTHON_LIB_PATH=C:\\Python39\\lib\\site-packages -build:rbe_win_py39 --repo_env=TF_PYTHON_CONFIG_REPO=//tensorflow/tools/toolchains/win_1803/py39 -build:rbe_win_py39 --python_path=C:\\Python39\\python.exe - -# TODO(kanglan): Merge tensorflow_testing_rbe_win into rbe_win -common:tensorflow_testing_rbe_win --remote_instance_name=projects/tensorflow-testing/instances/windows +build:rbe_win_base --remote_download_minimal +build:rbe_win_base --enable_runfiles +build:rbe_win_base --nobuild_python_zip +build:rbe_win_base --define=override_eigen_strong_inline=true + +build:rbe_win_clang --config=rbe_win_base +build:rbe_win_clang --crosstool_top="//tensorflow/tools/toolchains/win/20240424:toolchain" +build:rbe_win_clang --extra_toolchains="//tensorflow/tools/toolchains/win/20240424:cc-toolchain-x64_windows-clang-cl" +build:rbe_win_clang --extra_execution_platforms="//tensorflow/tools/toolchains/win:x64_windows-clang-cl" +build:rbe_win_clang --host_platform="//tensorflow/tools/toolchains/win:x64_windows-clang-cl" +build:rbe_win_clang --platforms="//tensorflow/tools/toolchains/win:x64_windows-clang-cl" +build:rbe_win_clang --compiler=clang-cl +build:rbe_win_clang --linkopt=/FORCE:MULTIPLE +build:rbe_win_clang --host_linkopt=/FORCE:MULTIPLE + +# TODO(belitskiy): Rename `rbe_win_clang` to this, once done switching presubmits. +build:rbe_windows_x86_cpu --config=rbe_win_clang + # END TF REMOTE BUILD EXECUTION OPTIONS # TFLite build configs for generic embedded Linux @@ -595,8 +602,11 @@ try-import %workspace%/.bazelrc.user test:release_base --test_size_filters=small,medium test:release_base --flaky_test_attempts=3 -# Target the AVX instruction set -build:release_linux_base --config=avx_linux +# Enable support for all targets +build:release_base --config=cpu_cross + +# Ensure release_base is set on linux +build:release_linux_base --config=release_base # Disable clang extension that rejects type definitions within offsetof. # This was added in clang-16 by https://reviews.llvm.org/D133574. @@ -620,24 +630,25 @@ build:release_linux_base --action_env PYTHON_BIN_PATH="/usr/bin/python3" build:release_linux_base --action_env PYTHON_LIB_PATH="/usr/lib/tf_python" build:release_linux_base --python_path="/usr/bin/python3" # Set Clang as compiler. Use the actual path to clang installed in container. -build:release_cpu_linux_base --repo_env=CC="/usr/lib/llvm-17/bin/clang" -build:release_cpu_linux_base --repo_env=BAZEL_COMPILER="/usr/lib/llvm-17/bin/clang" +build:release_linux_base --repo_env=CC="/usr/lib/llvm-18/bin/clang" +build:release_linux_base --repo_env=BAZEL_COMPILER="/usr/lib/llvm-18/bin/clang" # Test-related settings below this point. test:release_linux_base --build_tests_only --keep_going --test_output=errors --verbose_failures=true test:release_linux_base --local_test_jobs=HOST_CPUS -test:release_linux_base --test_env=LD_LIBRARY_PATH # Give only the list of failed tests at the end of the log test:release_linux_base --test_summary=short # Use the Clang toolchain to compile build:release_cpu_linux --config=release_linux_base -build:release_cpu_linux --crosstool_top="@sigbuild-r2.16-clang_config_cuda//crosstool:toolchain" +build:release_cpu_linux --crosstool_top="@local_config_cuda//crosstool:toolchain" +build:release_cpu_linux --repo_env=TF_SYSROOT="/dt9" +# Target the AVX instruction set +build:release_cpu_linux --config=avx_linux build:release_gpu_linux --config=release_cpu_linux # Set up compilation CUDA version and paths and use the CUDA Clang toolchain. # Note that linux cpu and cuda builds share the same toolchain now. build:release_gpu_linux --config=cuda_clang_official -test:release_gpu_linux --test_env=LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64" # Local test jobs has to be 4 because parallel_gpu_execute is fragile, I think test:release_gpu_linux --test_timeout=300,450,1200,3600 --local_test_jobs=4 --run_under=//tensorflow/tools/ci_build/gpu_build:parallel_gpu_execute @@ -648,39 +659,15 @@ build:release_arm64_linux --config=mkl_aarch64_threadpool build:release_arm64_linux --copt=-flax-vector-conversions test:release_arm64_linux --flaky_test_attempts=3 -# The old gcc linux build options are preserved in the unsupported_*_linux -# configs. If your project fails to build with Clang, you can use these -# unsupported flags to replace the release flags in your build command. -# However, please note that the old toolchain is no longer officially supported -# by TensorFlow and the unsupported configs will be removed soon b/299962977. We -# strongly recommend that you migrate to Clang as your compiler for TensorFlow -# Linux builds. Instructions are available in the official documentation: -# https://www.tensorflow.org/install/source#install_clang_recommended_linux_only -# Another good option is to use our Docker containers to build and test TF: -# https://github.com/tensorflow/tensorflow/tree/master/tensorflow/tools/tf_sig_build_dockerfiles. -build:unsupported_cpu_linux --config=avx_linux -build:unsupported_cpu_linux --crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain" -test:unsupported_cpu_linux --test_env=LD_LIBRARY_PATH -test:unsupported_cpu_linux --config=release_base - -build:unsupported_gpu_linux --config=cuda -build:unsupported_gpu_linux --config=unsupported_cpu_linux -build:unsupported_gpu_linux --action_env=TF_CUDA_VERSION="11" -build:unsupported_gpu_linux --action_env=TF_CUDNN_VERSION="8" -build:unsupported_gpu_linux --repo_env=TF_CUDA_COMPUTE_CAPABILITIES="sm_35,sm_50,sm_60,sm_70,sm_75,compute_80" -build:unsupported_gpu_linux --config=tensorrt -build:unsupported_gpu_linux --action_env=CUDA_TOOLKIT_PATH="/usr/local/cuda-11.2" -build:unsupported_gpu_linux --action_env=LD_LIBRARY_PATH="/usr/local/cuda:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda-11.1/lib64:/usr/local/tensorrt/lib" -build:unsupported_gpu_linux --action_env=GCC_HOST_COMPILER_PATH="/dt9/usr/bin/gcc" -build:unsupported_gpu_linux --crosstool_top=@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain - build:release_cpu_macos --config=avx_linux -test:release_cpu_macos --config=release_base # Base build configs for macOS build:release_macos_base --action_env DEVELOPER_DIR=/Applications/Xcode.app/Contents/Developer build:release_macos_base --define=no_nccl_support=true --output_filter=^$ +# Ensure release_base is set on mac +build:release_macos_base --config=release_base + # Build configs for macOS x86 build:release_macos_x86 --config=release_macos_base # Build with the AVX instruction set when on macOS x86 @@ -710,10 +697,12 @@ test:release_macos_x86 --config=release_macos_base # Test configs for macOS Arm64 test:release_macos_arm64 --config=release_macos_base +# Ensure release_base is set on windows +build:release_cpu_windows --config=release_base + # TODO(kanglan): Update windows configs after b/289091160 is fixed build:release_cpu_windows --config=avx_win build:release_cpu_windows --define=no_tensorflow_py_deps=true -test:release_cpu_windows --config=release_base # Exclude TFRT integration for anything but Linux. build:android --config=no_tfrt @@ -743,8 +732,8 @@ build:tf_public_macos_cache_push --config=tf_public_macos_cache --remote_upload_ # at the scripts of ci/official/ to see how TF's CI uses them. # LIBTENSORFLOW TESTS are for building Libtensorflow archives. These are CUDA/CPU-agnostic. -test:linux_libtensorflow_test -- //tensorflow/tools/lib_package:libtensorflow_test //tensorflow/tools/lib_package:libtensorflow_java_test -build:linux_libtensorflow_build -- //tensorflow/tools/lib_package:libtensorflow.tar.gz //tensorflow/tools/lib_package:libtensorflow_jni.tar.gz //tensorflow/java:libtensorflow.jar //tensorflow/java:libtensorflow-src.jar //tensorflow/tools/lib_package:libtensorflow_proto.zip +test:linux_libtensorflow_test --config=cuda_wheel -- //tensorflow/tools/lib_package:libtensorflow_test //tensorflow/tools/lib_package:libtensorflow_java_test +build:linux_libtensorflow_build --config=cuda_wheel -- //tensorflow/tools/lib_package:libtensorflow.tar.gz //tensorflow/tools/lib_package:libtensorflow_jni.tar.gz //tensorflow/java:libtensorflow.jar //tensorflow/java:libtensorflow-src.jar //tensorflow/tools/lib_package:libtensorflow_proto.zip # PYTHON TESTS run a suite of Python tests intended for verifying that the Python wheel # will work properly. These are usually run Nightly or upon Release. @@ -752,41 +741,43 @@ build:linux_libtensorflow_build -- //tensorflow/tools/lib_package:libtensorflow. test:linux_cpu_wheel_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_oss_py38,-no_oss_py39,-no_oss_py310 test:linux_cpu_wheel_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_oss_py38,-no_oss_py39,-no_oss_py310 test:linux_cpu_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium -test:linux_cpu_wheel_test --config=linux_cpu_wheel_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... +test:linux_cpu_wheel_test --config=linux_cpu_wheel_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... # CUDA WHEEL test:linux_cuda_wheel_test_filters --test_tag_filters=gpu,requires-gpu,-no_gpu,-no_oss,-oss_excluded,-oss_serial,-benchmark-test,-no_cuda11,-no_oss_py38,-no_oss_py39,-no_oss_py310 test:linux_cuda_wheel_test_filters --build_tag_filters=gpu,requires-gpu,-no_gpu,-no_oss,-oss_excluded,-oss_serial,-benchmark-test,-no_cuda11,-no_oss_py38,-no_oss_py39,-no_oss_py310 test:linux_cuda_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium -test:linux_cuda_wheel_test --config=linux_cuda_wheel_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... +test:linux_cuda_wheel_test --config=linux_cuda_wheel_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... # ARM64 WHEEL test:linux_arm64_wheel_test_filters --test_tag_filters=-no_oss,-no_aarch64,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_oss_py38,-no_oss_py39,-no_oss_py310 test:linux_arm64_wheel_test_filters --build_tag_filters=-no_oss,-no_aarch64,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_oss_py38,-no_oss_py39,-no_oss_py310 test:linux_arm64_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium -test:linux_arm64_wheel_test --config=linux_arm64_wheel_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/core/grappler/optimizers:auto_mixed_precision_test_cpu -//tensorflow/core/grappler/optimizers:remapper_test_cpu -//tensorflow/core/kernels/image:resize_bicubic_op_test -//tensorflow/compiler/mlir/tfr/examples/customization:test_ops_test -//tensorflow/compiler/mlir/tfr/examples/mnist:mnist_ops_test -//tensorflow/compiler/mlir/tfr/examples/pad:pad_ops_test +test:linux_arm64_wheel_test --config=linux_arm64_wheel_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/core/grappler/optimizers:auto_mixed_precision_test_cpu -//tensorflow/core/grappler/optimizers:remapper_test_cpu -//tensorflow/core/kernels/image:resize_bicubic_op_test # MACOS ARM64 WHEEL test:macos_arm64_wheel_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test,-no_mac_arm64,-no_aarch64 test:macos_arm64_wheel_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test,-no_mac_arm64,-no_aarch64 test:macos_arm64_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium -test:macos_arm64_wheel_test --config=macos_arm64_wheel_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/compiler/aot/... +test:macos_arm64_wheel_test --config=macos_arm64_wheel_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/compiler/aot/... # MACOS X86 WHEEL test:macos_x86_wheel_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py38,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test test:macos_x86_wheel_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py38,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test test:macos_x86_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium -test:macos_x86_wheel_test --config=macos_x86_wheel_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/compiler/aot/... +test:macos_x86_wheel_test --config=macos_x86_wheel_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/compiler/aot/... # PYCPP TESTS run a suite of Python and C++ tests to verify general correctness over # the whole TF code base. These are usually run continuously or upon presubmit. -# CPU PYCPP: +# LINUX CPU PYCPP: test:linux_cpu_pycpp_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only test:linux_cpu_pycpp_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only test:linux_cpu_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium -test:linux_cpu_pycpp_test --config=linux_cpu_pycpp_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -# CUDA PYCPP: +test:linux_cpu_pycpp_test --config=linux_cpu_pycpp_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... + +# LINUX CUDA PYCPP: test:linux_cuda_pycpp_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-benchmark-test,-v1only,gpu,-no_gpu,-no_gpu_presubmit,-no_cuda11 test:linux_cuda_pycpp_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-benchmark-test,-v1only,gpu,-no_gpu,-no_gpu_presubmit,-no_cuda11 test:linux_cuda_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium -test:linux_cuda_pycpp_test --config=linux_cuda_pycpp_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -# ARM64 PYCPP +test:linux_cuda_pycpp_test --config=linux_cuda_pycpp_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... + +# LINUX ARM64 PYCPP # In Linux Arm64 presubmit/continuous build, we cross-compile the binaries on # Linux x86 so that we can use RBE. Since tests still need to run on the single # host Arm64 machine, the build becomes too slow (~30 min) to be a presubmit. @@ -799,7 +790,7 @@ build:linux_arm64_pycpp_test_filters --test_tag_filters=-no_oss,-no_aarch64,-oss build:linux_arm64_pycpp_test_filters --build_tag_filters=-no_oss,-no_aarch64,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only build:linux_arm64_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium --flaky_test_attempts=3 # TODO(michaelhudgins): Why do we need to specifically omit go and java here? -build:linux_arm64_pycpp_test --config=linux_arm64_pycpp_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/core/grappler/optimizers:auto_mixed_precision_test_cpu -//tensorflow/core/grappler/optimizers:remapper_test_cpu -//tensorflow/core/kernels/image:resize_bicubic_op_test -//tensorflow/compiler/mlir/tfr/examples/customization:test_ops_test -//tensorflow/compiler/mlir/tfr/examples/mnist:mnist_ops_test -//tensorflow/compiler/mlir/tfr/examples/pad:pad_ops_test -//tensorflow/python/tools:aot_compiled_test +build:linux_arm64_pycpp_test --config=linux_arm64_pycpp_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/core/grappler/optimizers:auto_mixed_precision_test_cpu -//tensorflow/core/grappler/optimizers:remapper_test_cpu -//tensorflow/core/kernels/image:resize_bicubic_op_test -//tensorflow/python/tools:aot_compiled_test # CROSS-COMPILE ARM64 PYCPP build:cross_compile_linux_arm64_pycpp_test --config=linux_arm64_pycpp_test # Tests that fail only when cross-compiled @@ -808,15 +799,24 @@ build:cross_compile_linux_arm64_pycpp_test -//tensorflow/compiler/mlir/quantizat test:macos_arm64_pycpp_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test,-no_mac_arm64,-no_aarch64 test:macos_arm64_pycpp_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test,-no_mac_arm64,-no_aarch64 test:macos_arm64_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium -test:macos_arm64_pycpp_test --config=macos_arm64_pycpp_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/compiler/aot/... -//tensorflow/core/kernels/image:resize_bicubic_op_test +test:macos_arm64_pycpp_test --config=macos_arm64_pycpp_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/compiler/aot/... -//tensorflow/core/kernels/image:resize_bicubic_op_test # MACOS X86 PYCPP -test:macos_x86_pycpp_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py38,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test -test:macos_x86_pycpp_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py38,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test -test:macos_x86_pycpp_test_filters --keep_going --test_lang_filters=cc,py --test_size_filters=small,medium -test:macos_x86_pycpp_test --config=macos_x86_pycpp_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/python/integration_testing/... -//tensorflow/tools/toolchains/... -//tensorflow/lite/... -//tensorflow/compiler/aot/... +# These are defined as build configs so that we can run a build only job. See +# the note under "ARM64 PYCPP" for more details. +build:macos_x86_pycpp_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py38,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test +build:macos_x86_pycpp_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py38,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test +build:macos_x86_pycpp_test_filters --keep_going --test_lang_filters=cc,py --test_size_filters=small,medium +build:macos_x86_pycpp_test --config=macos_x86_pycpp_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/tools/toolchains/... -//tensorflow/lite/... -//tensorflow/compiler/aot/... # CROSS-COMPILE MACOS X86 PYCPP -test:cross_compile_macos_x86_pycpp_test --config=macos_x86_pycpp_test -test:cross_compile_macos_x86_pycpp_test -//tensorflow/core/kernels:quantized_conv_ops_test -//tensorflow/core/kernels:quantized_matmul_op_test -//tensorflow/python/ops:quantized_conv_ops_test -//tensorflow/tools/graph_transforms:transforms_test -//tensorflow/python/tools:aot_compiled_test +build:cross_compile_macos_x86_pycpp_test --config=macos_x86_pycpp_test +build:cross_compile_macos_x86_pycpp_test -//tensorflow/core/kernels:quantized_conv_ops_test -//tensorflow/core/kernels:quantized_matmul_op_test -//tensorflow/python/ops:quantized_conv_ops_test -//tensorflow/tools/graph_transforms:transforms_test -//tensorflow/python/tools:aot_compiled_test +# WINDOWS X86-64 CPU PYCPP +test:windows_x86_cpu_pycpp_test_filters --test_tag_filters=-no_windows,-windows_excluded,-no_oss,-oss_excluded,-gpu,-tpu,-benchmark-test +test:windows_x86_cpu_pycpp_test_filters --build_tag_filters=-no_windows,-windows_excluded,-no_oss,-oss_excluded,-benchmark-test +test:windows_x86_cpu_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium --test_timeout="300,450,1200,3600" +test:windows_x86_cpu_pycpp_test_opts --copt=/d2ReducedOptimizeHugeFunctions --host_copt=/d2ReducedOptimizeHugeFunctions --dynamic_mode=off --build_tests_only +test:windows_x86_cpu_pycpp_test --config=windows_x86_cpu_pycpp_test_opts --config=windows_x86_cpu_pycpp_test_filters -- //tensorflow/... -//tensorflow/java/... -//tensorflow/lite/... -//tensorflow/compiler/... + # END TF TEST SUITE OPTIONS # START CROSS-COMPILE CONFIGS @@ -829,15 +829,38 @@ build:cross_compile_base --host_cpu=k8 build:cross_compile_base --host_crosstool_top=//tensorflow/tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite build:cross_compile_base --extra_execution_platforms=//tensorflow/tools/toolchains/cross_compile/config:linux_x86_64 +# XLA related settings for cross-compiled build. Certain paths are +# different in the XLA repo. +build:cross_compile_base_xla --host_cpu=k8 +build:cross_compile_base_xla --host_crosstool_top=//tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite +build:cross_compile_base_xla --extra_execution_platforms=//tools/toolchains/cross_compile/config:linux_x86_64 + build:rbe_cross_compile_base --config=rbe_base build:rbe_cross_compile_base --remote_instance_name=projects/tensorflow-testing/instances/default_instance +# XLA depends on some local Python headers that are configured as Genrule. They +# are present on the local host machine but not on the remote execution machine, +# leading to build failures. To resolve the issue, the following line is added +# to make sure all Genrule targets are excuted locally. +build:rbe_cross_compile_base_xla --config=rbe_cross_compile_base +build:rbe_cross_compile_base_xla --strategy=Genrule=standalone + +# Due to the above strategy, all Genrule commands are executed locally, but the +# following actions invoke tools (E.g `flatc`, `llvm-tblgen`, etc.) that are +# only executabe on the RBE (x86) machine, so the strategy_regexp options are +# added to override and run the actions using remote strategy. +build:rbe_cross_compile_base_xla --strategy_regexp='Generating code from table.*=remote' +build:rbe_cross_compile_base_xla --strategy_regexp='Generating flatbuffer files.*=remote' +build:rbe_cross_compile_base_xla --strategy_regexp='Executing genrule @llvm-project.*=remote' + # Test-related settings below this point # We cannot run cross-compiled tests on the remote Linux x86 VMs so we need to # force all tests to run locally on the Aarch64 host. test:rbe_cross_compile_base --strategy=TestRunner=local --build_tests_only test:rbe_cross_compile_base --verbose_failures=true --local_test_jobs=HOST_CPUS --test_output=errors +test:rbe_cross_compile_base_xla --config=rbe_cross_compile_base + # START LINUX AARCH64 CROSS-COMPILE CONFIGS build:cross_compile_linux_arm64 --config=cross_compile_base @@ -846,10 +869,21 @@ build:cross_compile_linux_arm64 --platforms=//tensorflow/tools/toolchains/cross_ build:cross_compile_linux_arm64 --cpu=aarch64 build:cross_compile_linux_arm64 --crosstool_top=//tensorflow/tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite +# XLA uses different paths for platforms and crosstool_top. +build:cross_compile_linux_arm64_xla --config=cross_compile_base_xla +build:cross_compile_linux_arm64_xla --platforms=//tools/toolchains/cross_compile/config:linux_aarch64 +build:cross_compile_linux_arm64_xla --crosstool_top=//tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite + # RBE cross-compile configs for Linux Aarch64 build:rbe_cross_compile_linux_arm64 --config=cross_compile_linux_arm64 build:rbe_cross_compile_linux_arm64 --config=rbe_cross_compile_base test:rbe_cross_compile_linux_arm64 --config=rbe_cross_compile_base + +# RBE cross-compile configs for XLA Linux Aarch64 +build:rbe_cross_compile_linux_arm64_xla --config=cross_compile_linux_arm64_xla +build:rbe_cross_compile_linux_arm64_xla --config=rbe_cross_compile_base_xla +test:rbe_cross_compile_linux_arm64_xla --config=rbe_cross_compile_base_xla + # END LINUX AARCH64 CROSS-COMPILE CONFIGS # START MACOS CROSS-COMPILE CONFIGS @@ -871,8 +905,11 @@ build:cross_compile_macos_x86 --extra_toolchains=//tensorflow/tools/toolchains/c build:cross_compile_macos_x86 --platform_mappings=tensorflow/tools/toolchains/cross_compile/config/platform_mappings # RBE cross-compile configs for Darwin x86 -build:rbe_cross_compile_macos_x86 --config=cross_compile_macos_x86 +build:rbe_cross_compile_macos_x86 --config=cross_compile_macos_x86 --remote_download_minimal +build:rbe_cross_compile_macos_x86 --bes_backend="" --bes_results_url="" --bes_timeout="0s" +build:rbe_cross_compile_macos_x86 --experimental_remote_build_event_upload="minimal" build:rbe_cross_compile_macos_x86 --config=rbe_cross_compile_base +build:rbe_cross_compile_macos_x86 --bes_upload_mode=nowait_for_upload_complete test:rbe_cross_compile_macos_x86 --config=rbe_cross_compile_base # Increase the test timeout as tests often take longer on mac. test:rbe_cross_compile_macos_x86 --test_timeout=300,450,1200,3600 @@ -880,4 +917,7 @@ test:rbe_cross_compile_macos_x86 --test_timeout=300,450,1200,3600 build:rbe_cross_compile_macos_x86 --jobs=100 test:rbe_cross_compile_macos_x86 --jobs=100 # END MACOS CROSS-COMPILE CONFIGS -# END CROSS-COMPILE CONFIGS \ No newline at end of file +# END CROSS-COMPILE CONFIGS + +# Try to load the XLA warnings config if available +try-import %workspace%/warnings.bazelrc From 118a96cc9a6bc8ab9a836eb0279e442ceff1838f Mon Sep 17 00:00:00 2001 From: Karl Lessard Date: Fri, 21 Mar 2025 15:29:34 -0400 Subject: [PATCH 02/11] Upgrade to 2.18 (still failing) --- CONTRIBUTING.md | 2 +- .../scripts/test_download.sh | 8 +- .../tensorflow-core-native/WORKSPACE | 10 +- .../scripts/dist_download.sh | 17 +- .../internal/c_api/global/tensorflow.java | 180 +- .../tensorflow/proto/AvailableDeviceInfo.java | 985 ---- .../proto/AvailableDeviceInfoOrBuilder.java | 79 - .../tensorflow/proto/BenchmarkEntries.java | 752 --- .../proto/BenchmarkEntriesOrBuilder.java | 33 - .../org/tensorflow/proto/BenchmarkEntry.java | 1709 ------ .../proto/BenchmarkEntryOrBuilder.java | 176 - .../org/tensorflow/proto/BfcMemoryMap.java | 5154 ----------------- .../tensorflow/proto/BuildConfiguration.java | 1044 ---- .../proto/BuildConfigurationOrBuilder.java | 111 - .../java/org/tensorflow/proto/CPUInfo.java | 1281 ---- .../tensorflow/proto/CPUInfoOrBuilder.java | 129 - .../java/org/tensorflow/proto/CommitId.java | 1021 ---- .../tensorflow/proto/CommitIdOrBuilder.java | 79 - .../org/tensorflow/proto/ConfigProto.java | 326 ++ .../proto/ConfigProtoOrBuilder.java | 27 + .../org/tensorflow/proto/ConfigProtos.java | 270 +- .../tensorflow/proto/CoordinationConfig.java | 111 +- .../java/org/tensorflow/proto/EntryValue.java | 745 --- .../tensorflow/proto/EntryValueOrBuilder.java | 39 - .../java/org/tensorflow/proto/GPUInfo.java | 896 --- .../tensorflow/proto/GPUInfoOrBuilder.java | 69 - .../java/org/tensorflow/proto/GPUOptions.java | 1263 +++- .../proto/MachineConfiguration.java | 2257 -------- .../proto/MachineConfigurationOrBuilder.java | 206 - .../java/org/tensorflow/proto/MemoryInfo.java | 563 -- .../tensorflow/proto/MemoryInfoOrBuilder.java | 29 - .../org/tensorflow/proto/MetricEntry.java | 1108 ---- .../proto/MetricEntryOrBuilder.java | 93 - .../org/tensorflow/proto/PlatformInfo.java | 1391 ----- .../proto/PlatformInfoOrBuilder.java | 129 - .../tensorflow/proto/ResourceHandleProto.java | 96 + .../org/tensorflow/proto/RewriterConfig.java | 28 +- .../proto/RewriterConfigOrBuilder.java | 8 +- .../tensorflow/proto/RunConfiguration.java | 922 --- .../proto/RunConfigurationOrBuilder.java | 90 - .../org/tensorflow/proto/SignatureDef.java | 195 +- .../proto/SignatureDefOrBuilder.java | 26 +- .../org/tensorflow/proto/TensorProto.java | 28 + .../proto/TensorProtoOrBuilder.java | 8 + .../org/tensorflow/proto/TestLogProtos.java | 287 - .../org/tensorflow/proto/TestResults.java | 2685 --------- .../proto/TestResultsOrBuilder.java | 267 - .../tensorflow/proto/data/DatasetOptions.java | 1490 ++++- .../data/experimental/ServiceConfig.java | 238 +- .../tensorflow/proto/dummy/BfcMemoryMap.java | 14 +- .../org/tensorflow/proto/dummy/TestLog.java | 10 +- .../api_def_AssignVariableXlaConcatND.pbtxt | 6 +- .../base_api/api_def_BatchMatrixInverse.pbtxt | 9 +- .../base_api/api_def_CheckPinned.pbtxt | 9 + .../api_def_ComputeDedupDataSizeV2.pbtxt | 40 + .../api_def_ComputeDedupDataTupleMaskV2.pbtxt | 45 + .../base_api/api_def_ConcatOffset.pbtxt | 2 +- ..._ConvertToListOfSparseCoreCooTensors.pbtxt | 4 + ...nvertToSparseCoreCsrWrappedCooTensor.pbtxt | 4 + ..._def_FakeQuantWithMinMaxArgsGradient.pbtxt | 35 + .../api_def_FakeQuantWithMinMaxVars.pbtxt | 21 + .../api_def_FinalizeTPUEmbeddingV2.pbtxt | 33 + .../base_api/api_def_GatherNd.pbtxt | 12 +- .../base_api/api_def_GatherV2.pbtxt | 4 + ...tStatsFromListOfSparseCoreCooTensors.pbtxt | 4 + .../base_api/api_def_GetTpuTaskId.pbtxt | 14 + .../api_def_GlobalShuffleDataset.pbtxt | 4 + .../api_def_IndexFlatMapDataset.pbtxt | 4 + .../api_def_IteratorGetModelProto.pbtxt | 20 + .../api_def_ReadVariableXlaSplitND.pbtxt | 1 + .../base_api/api_def_ScatterNd.pbtxt | 10 +- ...i_def_SortListOfSparseCoreCooTensors.pbtxt | 4 + .../base_api/api_def_TensorScatterAdd.pbtxt | 12 +- .../api_def_TensorScatterUpdate.pbtxt | 11 +- ...i_def_UpdateTaskIdAndGlobalCoreArray.pbtxt | 20 + .../api_def_WeightedFlatMapDataset.pbtxt | 4 + .../base_api/api_def_XlaConcatND.pbtxt | 1 + ...def_XlaRecvTPUEmbeddingActivationsV2.pbtxt | 61 + ...aRecvTPUEmbeddingDeduplicationDataV2.pbtxt | 37 + ...i_def_XlaSendTPUEmbeddingGradientsV2.pbtxt | 74 + ...ulGradWithAdagradAndStaticBufferSize.pbtxt | 4 + ...thAdagradMomentumAndStaticBufferSize.pbtxt | 4 + ...atmulGradWithAdamAndStaticBufferSize.pbtxt | 4 + ...XlaSparseDenseMatmulGradWithCsrInput.pbtxt | 4 + ...atmulGradWithFtrlAndStaticBufferSize.pbtxt | 4 + ...MatmulGradWithSgdAndStaticBufferSize.pbtxt | 4 + ...parseDenseMatmulWithStaticBufferSize.pbtxt | 4 + .../base_api/api_def_XlaSplitND.pbtxt | 1 + .../gen/resources/org/tensorflow/ops.pbtxt | 1539 ++++- .../internal/c_api/presets/tensorflow.java | 7 +- .../tensorflow-core-native/tensorflow.bazelrc | 2 +- 91 files changed, 5671 insertions(+), 25095 deletions(-) delete mode 100644 tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/AvailableDeviceInfo.java delete mode 100644 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tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RunConfigurationOrBuilder.java delete mode 100644 tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestLogProtos.java delete mode 100644 tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestResults.java delete mode 100644 tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestResultsOrBuilder.java create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_CheckPinned.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_ComputeDedupDataSizeV2.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_ComputeDedupDataTupleMaskV2.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_ConvertToListOfSparseCoreCooTensors.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_ConvertToSparseCoreCsrWrappedCooTensor.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_FinalizeTPUEmbeddingV2.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_GetStatsFromListOfSparseCoreCooTensors.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_GetTpuTaskId.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_GlobalShuffleDataset.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_IndexFlatMapDataset.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_IteratorGetModelProto.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_SortListOfSparseCoreCooTensors.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_UpdateTaskIdAndGlobalCoreArray.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_WeightedFlatMapDataset.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_XlaRecvTPUEmbeddingActivationsV2.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_XlaRecvTPUEmbeddingDeduplicationDataV2.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_XlaSendTPUEmbeddingGradientsV2.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_XlaSparseDenseMatmulGradWithCsrInput.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize.pbtxt create mode 100644 tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_XlaSparseDenseMatmulWithStaticBufferSize.pbtxt diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 874bdddaf52..9da8b9603aa 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -82,7 +82,7 @@ To upgrade the version of TensorFlow that is embedded within TensorFlow Java, pl 3. Update `urls`, `sha256` and `strip_prefix` fields of the `org_tensorflow` archive rule in Bazel [workspace](https://github.com/tensorflow/java/blob/master/tensorflow-core/tensorflow-core-native/WORKSPACE#L19) 4. Extract the archive in a temporary folder 5. Copy the content of `tensorflow-x.x.x/.bazelrc` file to `tensorflow-core/tensorflow-core-native/tensorflow.bazelrc` under TensorFlow Java source tree -6. Copy the content of `tensorflow-x.x.x/WORKSPACE` after the "###### Copy content of..." notice if `tensorflow-core/tensorflow-core-native/WORKSPACE`, read notice for more details +6. Copy the content of `tensorflow-x.x.x/WORKSPACE` after the "###### Copy content of..." notice to `tensorflow-core/tensorflow-core-native/WORKSPACE`, read notice for more details 7. Copy the content of `tensorflow-x.x.x/.bazelversion` file to `tensorflow-core/tensorflow-core-native/.bazelversion` 8. Validate that options in `tensorflow-core/tensorflow-core-native/.bazelrc` are still accurate or update them accordingly 9. Update URLs of existing TensorFlow binaries in the `tensorflow-core/tensorflow-core-native/scripts/dist_download` script diff --git a/tensorflow-core/tensorflow-core-api/scripts/test_download.sh b/tensorflow-core/tensorflow-core-api/scripts/test_download.sh index 01345823683..5d1c2988d7e 100755 --- a/tensorflow-core/tensorflow-core-api/scripts/test_download.sh +++ b/tensorflow-core/tensorflow-core-api/scripts/test_download.sh @@ -5,13 +5,13 @@ DOWNLOAD_FOLDER="$1" case ${PLATFORM:-} in 'linux-x86_64') - TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/43/dd/8f03331107b76e63313d2089ddfbd13f15e51fb8ed73517cdd0ab3341928/tensorflow-2.16.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl' + TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/f3/73/3a906feb0d71d9353c6fb2363d4052856cc6eff5a78a097b1a6002d4e908/tensorflow_text-2.18.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl' ;; - 'macosx-x86_64') - TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/6d/69/9999c2d9e8a3b08dfcfc7e9259a05fb1da5f700936091d2eb4a7985c2776/tensorflow-2.16.2-cp311-cp311-macosx_10_15_x86_64.whl' + 'linux-arm64') + TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/8a/9a/ebba9f6274f8b51e5fe1ac2411b8b6bf680a32d10bd6e9c54be1faeec062/tensorflow_text-2.18.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl' ;; 'macosx-arm64') - TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/e7/0d/20b259aadf5f98bad45d55dcd3a7e2690058bb4bc1188dd9e36ab9bdd2ec/tensorflow_text-2.18.0rc0-cp310-cp310-macosx_11_0_arm64.whl' + TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/18/b6/8ad233edb0732847db1da538cea941dcccc42f59304ff6fb449676e6dd5a/tensorflow_text-2.18.1-cp311-cp311-macosx_11_0_arm64.whl' ;; *) echo "TensorFlow Text distribution for ${PLATFORM} is not supported for download" diff --git a/tensorflow-core/tensorflow-core-native/WORKSPACE b/tensorflow-core/tensorflow-core-native/WORKSPACE index f321c83b831..555fb375ac2 100644 --- a/tensorflow-core/tensorflow-core-native/WORKSPACE +++ b/tensorflow-core/tensorflow-core-native/WORKSPACE @@ -18,14 +18,16 @@ http_archive( "find tensorflow third_party/xla/third_party/tsl -name \\*.proto | xargs sed -i.bak 's/^package tensorflow\\([^;]*\\).*$/package tensorflow\\1;\\noption java_package = \"org.tensorflow.proto\\1\";/'", ], urls = [ - "https://github.com/tensorflow/tensorflow/archive/refs/tags/v2.18.0-rc2.tar.gz", + "https://github.com/tensorflow/tensorflow/archive/refs/tags/v2.18.0.tar.gz", ], - sha256 = "ed371d42f69b9029175b0a70667c4c65d02a269887353520d5cfca5ce8eb7855", - strip_prefix = "tensorflow-2.18.0-rc2" + sha256 = "d7876f4bb0235cac60eb6316392a7c48676729860da1ab659fb440379ad5186d", + strip_prefix = "tensorflow-2.18.0" ) ##### Copy content of tensorflow/WORKSPACE here (make sure to change references of default package "//" to "@org_tensorflow//") +# buildifier: disable=load-on-top + # We must initialize hermetic python first. load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive") @@ -138,4 +140,4 @@ load( "nccl_configure", ) -nccl_configure(name = "local_config_nccl") +nccl_configure(name = "local_config_nccl") \ No newline at end of file diff --git a/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh b/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh index 8c3b0d7d288..2cc3a49dec0 100755 --- a/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh +++ b/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh @@ -5,23 +5,20 @@ DOWNLOAD_FOLDER="$1" case ${PLATFORM:-} in 'linux-x86_64') - WHEEL_URL='https://files.pythonhosted.org/packages/c6/d9/f2ff325194b8e8acb6b69f303c838b0486f41b8028ec42261f2eb037a031/tensorflow_cpu-2.16.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl' + WHEEL_URL='https://files.pythonhosted.org/packages/aa/1d/032a9d40762895e51cad06f382135c14d16487a0ad9dcc65aae5bd89c968/tensorflow_cpu-2.18.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl' ;; 'linux-x86_64-gpu') - WHEEL_URL='https://files.pythonhosted.org/packages/43/dd/8f03331107b76e63313d2089ddfbd13f15e51fb8ed73517cdd0ab3341928/tensorflow-2.16.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl' + WHEEL_URL='https://files.pythonhosted.org/packages/84/76/c55967ac9968ddaede25a4dce37aba37e9030656f02c12676151ce1b6f22/tensorflow-2.18.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl' ;; - 'macosx-x86_64') - WHEEL_URL='https://files.pythonhosted.org/packages/6d/69/9999c2d9e8a3b08dfcfc7e9259a05fb1da5f700936091d2eb4a7985c2776/tensorflow-2.16.2-cp311-cp311-macosx_10_15_x86_64.whl' + 'linux-arm64') + WHEEL_URL='https://files.pythonhosted.org/packages/56/e4/55aaac2b15af4dad079e5af329a79d961e5206589d0e02b1e8da221472ed/tensorflow-2.18.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl' ;; 'macosx-arm64') - WHEEL_URL='https://files.pythonhosted.org/packages/20/91/4358b8f5c83ff0dff679fdcdde0f7d6020dd47ef0c00d3e815ec3ceae426/tensorflow-2.18.0rc2-cp312-cp312-macosx_12_0_arm64.whl' + WHEEL_URL='https://files.pythonhosted.org/packages/26/08/556c4159675c1a30e077ec2a942eeeb81b457cc35c247a5b4a59a1274f05/tensorflow-2.18.0-cp311-cp311-macosx_12_0_arm64.whl' ;; 'windows-x86_64') - WHEEL_URL='https://files.pythonhosted.org/packages/46/87/c3e4e9fe7c630f38a6984afdd1d4ed531ef9c74dc66b86f46f6bdd89d608/tensorflow_intel-2.16.2-cp311-cp311-win_amd64.whl' - CLIB_URL='https://storage.googleapis.com/tensorflow/versions/2.16.2/libtensorflow-cpu-windows-x86_64.zip' - ;; - 'linux-arm64') - WHEEL_URL='https://files.pythonhosted.org/packages/b5/01/c03e98c8e97d151d9ce075fae210f838832eb53d8aa55669d384cb72925b/tensorflow-2.16.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl' + WHEEL_URL='https://files.pythonhosted.org/packages/76/ad/fa6c508a15ff79cb5409294c293388e0999b7d480f84b65e4287277434fe/tensorflow_intel-2.18.0-cp311-cp311-win_amd64.whl' + CLIB_URL='https://storage.googleapis.com/tensorflow/versions/2.18.0/libtensorflow-cpu-windows-x86_64.zip' ;; *) echo "TensorFlow distribution for ${PLATFORM} is not supported for download" diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/internal/c_api/global/tensorflow.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/internal/c_api/global/tensorflow.java index 2a80e6bb86d..8461874c1bc 100644 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/internal/c_api/global/tensorflow.java +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/internal/c_api/global/tensorflow.java @@ -274,9 +274,9 @@ public static native void TF_TString_Copy(TF_TString dst, String src, // #endif // TENSORFLOW_TSL_PLATFORM_CTSTRING_H_ -// Parsed from tsl/c/tsl_status.h +// Parsed from tsl/platform/status.h -/* Copyright 2019 The TensorFlow Authors. All Rights Reserved. +/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. @@ -291,67 +291,130 @@ public static native void TF_TString_Copy(TF_TString dst, String src, limitations under the License. ==============================================================================*/ -// #ifndef TENSORFLOW_TSL_C_TSL_STATUS_H_ -// #define TENSORFLOW_TSL_C_TSL_STATUS_H_ +// #ifndef TENSORFLOW_TSL_PLATFORM_STATUS_H_ +// #define TENSORFLOW_TSL_PLATFORM_STATUS_H_ -// #ifdef __cplusplus +// #include +// #include +// #include +// #include +// #include +// #include +// #include +// #include + +// #include "absl/base/attributes.h" +// #include "absl/base/macros.h" +// #include "absl/functional/function_ref.h" +// #include "absl/status/status.h" +// #include "absl/strings/cord.h" +// #include "absl/strings/string_view.h" +// #include "absl/types/optional.h" +// #include "tsl/platform/logging.h" +// #include "tsl/platform/macros.h" +// #include "tsl/platform/platform.h" +// #include "tsl/platform/stack_frame.h" +// #include "tsl/platform/types.h" +// #include "tsl/protobuf/error_codes.pb.h" + +// Include appropriate platform-dependent parts of status. +// #if defined(PLATFORM_GOOGLE) +// #include "tsl/platform/google/status.h" // IWYU pragma: export +// #else +// #include "tsl/platform/default/status.h" // IWYU pragma: export // #endif -// -------------------------------------------------------------------------- -// TSL_Code holds an error code. The enum values here are identical to -// corresponding values in error_codes.proto. -/** enum TSL_Code */ -public static final int - TSL_OK = 0, - TSL_CANCELLED = 1, - TSL_UNKNOWN = 2, - TSL_INVALID_ARGUMENT = 3, - TSL_DEADLINE_EXCEEDED = 4, - TSL_NOT_FOUND = 5, - TSL_ALREADY_EXISTS = 6, - TSL_PERMISSION_DENIED = 7, - TSL_UNAUTHENTICATED = 16, - TSL_RESOURCE_EXHAUSTED = 8, - TSL_FAILED_PRECONDITION = 9, - TSL_ABORTED = 10, - TSL_OUT_OF_RANGE = 11, - TSL_UNIMPLEMENTED = 12, - TSL_INTERNAL = 13, - TSL_UNAVAILABLE = 14, - TSL_DATA_LOSS = 15; +// TODO: b/323943471 - This macro should eventually be provided by Abseil. +// #ifndef ABSL_DEPRECATE_AND_INLINE +// #define ABSL_DEPRECATE_AND_INLINE() +// #endif -// -------------------------------------------------------------------------- +// Since April 2023, tensorflow::Status is an alias to absl::Status. The first +// TF release including this change will be TF 2.14 (the latest release in +// April 2023 is 2.13). +// At the same time `tsl::errors::Code` aliases `absl::StatusCode`. +// +// Here is a set of correspondences: +// - Use `absl::OkStatus()` instead of `tsl::OkStatus()`. + // namespace errors + // namespace error + // namespace tsl + +// Transparent comparison between tensorflow::error::Code protobuf enum and +// absl::Status. +// +// The longer term objective is to delete these when we have done the transition +// to absl::Status. +@Namespace("tensorflow::error") public static native @Cast("bool") @Name("operator ==") boolean equals(@Const @ByRef Code c1, + @Const @ByRef StatusCode c2); + +@Namespace("tensorflow::error") public static native @Cast("bool") @Name("operator !=") boolean notEquals(@Const @ByRef Code c1, + @Const @ByRef StatusCode c2); + // namespace tensorflow::error +@Namespace("absl") public static native @Cast("bool") @Name("operator ==") boolean equals(@Const @ByRef StatusCode c1, + @Const @ByRef Code c2); + +@Namespace("absl") public static native @Cast("bool") @Name("operator !=") boolean notEquals(@Const @ByRef StatusCode c1, + @Const @ByRef Code c2); + // namespace absl + +// OkStatus() +// +// Returns an OK status, equivalent to a default constructed instance. Prefer +// usage of `OkStatus()` when constructing such an OK status. +@Namespace("tsl") public static native @ByVal Status OkStatus(); + +@Namespace("tsl") public static native @ByVal Status FromAbslStatus(@Const @ByRef Status s); +@Namespace("tsl") public static native @ByVal Status ToAbslStatus(@Const @ByRef Status s); + +// Given `Status.message()` does not guarantee to be always backed by a +// null-terminated string, we have this utility function when it's needed for +// the Tensorflow C-API. +// A more robust API would be to get both a `char*` of the beginning of the +// string, plus the size (see e.g. `XlaCustomCallStatusSetFailure`). +// NB: This Windows-only implementation is exists only to avoid a linker error. +// Remove if this is resolved. +// #ifdef _WIN32 +@Namespace("tsl") public static native @Cast("const char*") BytePointer NullTerminatedMessage(@Const @ByRef Status status); +// #else +// #endif -// Return a new status object. +// TODO(b/197552541) Move this namespace to errors.h. -// Delete a previously created status object. +@Namespace("tsl::errors") public static native void SetStackTrace(@ByRef Status status, @StdVector StackFrame stack_trace); -// Record in *s. Any previous information is lost. -// A common use is to clear a status: TSL_SetStatus(s, TSL_OK, ""); +@Namespace("tsl::errors") public static native @StdVector StackFrame GetStackTrace(@Const @ByRef Status status); + // namespace errors -// Record as a payload in *s. The previous payload having the -// same key (if any) is overwritten. Payload will not be added if the Status -// is OK. +// Helper class to manage multiple child status values. -// Iterates over the stored payloads and calls the `visitor(key, value)` -// callable for each one. `key` and `value` is only usable during the callback. -// `capture` will be passed to the callback without modification. +@Namespace("tsl") public static native string TfCheckOpHelperOutOfLine(@Const @ByRef Status v, + @Cast("const char*") BytePointer msg); +@Namespace("tsl") public static native string TfCheckOpHelperOutOfLine(@Const @ByRef Status v, + String msg); -// Convert from an I/O error code (e.g., errno) to a TSL_Status value. -// Any previous information is lost. Prefer to use this instead of TSL_SetStatus -// when the error comes from I/O operations. +@Namespace("tsl") public static native string TfCheckOpHelper(@ByVal Status v, @Cast("const char*") BytePointer msg); +@Namespace("tsl") public static native string TfCheckOpHelper(@ByVal Status v, String msg); -// Return the code record in *s. +// #define TF_DO_CHECK_OK(val, level) +// while (auto* _result = ::tsl::TfCheckOpHelper(val, #val)) +// LOG(level) << *(_result) -// Return a pointer to the (null-terminated) error message in *s. The -// return value points to memory that is only usable until the next -// mutation to *s. Always returns an empty string if TSL_GetCode(s) is -// TSL_OK. +// #define TF_CHECK_OK(val) TF_DO_CHECK_OK(val, FATAL) +// #define TF_QCHECK_OK(val) TF_DO_CHECK_OK(val, QFATAL) -// #ifdef __cplusplus /* end extern "C" */ +// DEBUG only version of TF_CHECK_OK. Compiler still parses 'val' even in opt +// mode. +// #ifndef NDEBUG +// #define TF_DCHECK_OK(val) TF_CHECK_OK(val) +// #else +// #define TF_DCHECK_OK(val) +// while (false && (::tsl::OkStatus() == (val))) LOG(FATAL) // #endif -// #endif // TENSORFLOW_TSL_C_TSL_STATUS_H_ + // namespace tsl + +// #endif // TENSORFLOW_TSL_PLATFORM_STATUS_H_ // Parsed from tensorflow/c/c_api_macros.h @@ -507,7 +570,7 @@ public static native void TF_TString_Copy(TF_TString dst, String src, // #define TENSORFLOW_C_TF_STATUS_H_ // #include "tensorflow/c/c_api_macros.h" -// #include "tsl/c/tsl_status.h" +// #include "xla/tsl/c/tsl_status.h" // #ifdef __cplusplus // Targeting ../TF_Status.java @@ -547,9 +610,9 @@ public static native void TF_TString_Copy(TF_TString dst, String src, // Record in *s. Any previous information is lost. // A common use is to clear a status: TF_SetStatus(s, TF_OK, ""); -public static native void TF_SetStatus(TF_Status s, @Cast("TF_Code") int code, +public static native void TF_SetStatus(TF_Status s, @ByVal @Cast("TF_Code*") TSL_Code code, @Cast("const char*") BytePointer msg); -public static native void TF_SetStatus(TF_Status s, @Cast("TF_Code") int code, +public static native void TF_SetStatus(TF_Status s, @ByVal @Cast("TF_Code*") TSL_Code code, String msg); // Record as a payload in *s. The previous payload having the @@ -575,7 +638,7 @@ public static native void TF_SetStatusFromIOError(TF_Status s, int error_code, String context); // Return the code record in *s. -public static native @Cast("TF_Code") int TF_GetCode(@Const TF_Status s); +public static native @ByVal @Cast("TF_Code*") TSL_Code TF_GetCode(@Const TF_Status s); // Return a pointer to the (null-terminated) error message in *s. The // return value points to memory that is only usable until the next @@ -689,6 +752,13 @@ public static native TF_Tensor TF_NewTensor( Deallocator_Pointer_long_Pointer deallocator, Pointer deallocator_arg); +// Returns the alignment, in bytes, required for allocating aligned tensors. +// +// This can be used in combination with TF_NewTensor to manually manage +// memory while ensuring the resulting tensors satisfy TensorFlow's +// memory alignment preferences. +public static native @Cast("size_t") long TF_TensorDefaultAlignment(); + // Allocate and return a new Tensor. // // This function is an alternative to TF_NewTensor and should be used when @@ -4367,7 +4437,8 @@ public static native void TFE_ContextUpdateServerDefWithTimeout( // This API is for experimental usage and may be subject to change. public static native void TFE_ContextSetServerDefWithTimeout( TFE_Context ctx, int keep_alive_secs, @Const Pointer proto, @Cast("size_t") long proto_len, - @Cast("int64_t") long init_timeout_in_ms, TF_Status status); + @Cast("int64_t") long init_timeout_in_ms, TF_Status status, + @Cast("bool") boolean clear_existing_contexts); // Set server def with retries and timeout. This is helpful for fault-tolerant // initial connection in high-preemption environments, such as @@ -4375,7 +4446,8 @@ public static native void TFE_ContextSetServerDefWithTimeout( // This API is for experimental usage and may be subject to change. public static native void TFE_ContextSetServerDefWithTimeoutAndRetries( TFE_Context ctx, int keep_alive_secs, @Const Pointer proto, @Cast("size_t") long proto_len, - @Cast("int64_t") long init_timeout_in_ms, int retries, TF_Status status); + @Cast("int64_t") long init_timeout_in_ms, int retries, TF_Status status, + @Cast("bool") boolean clear_existing_contexts); // Checks whether a remote worker is alive or not. This will return true even if // the context doesn't exist on the remote worker. diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/AvailableDeviceInfo.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/AvailableDeviceInfo.java deleted file mode 100644 index e71192c47b2..00000000000 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/AvailableDeviceInfo.java +++ /dev/null @@ -1,985 +0,0 @@ -// Generated by the protocol buffer compiler. DO NOT EDIT! -// source: tsl/protobuf/test_log.proto - -package org.tensorflow.proto; - -/** - * 
- * Matches DeviceAttributes
- *
- * - * Protobuf type {@code tensorflow.AvailableDeviceInfo} - */ -public final class AvailableDeviceInfo extends - com.google.protobuf.GeneratedMessageV3 implements - // @@protoc_insertion_point(message_implements:tensorflow.AvailableDeviceInfo) - AvailableDeviceInfoOrBuilder { -private static final long serialVersionUID = 0L; - // Use AvailableDeviceInfo.newBuilder() to construct. - private AvailableDeviceInfo(com.google.protobuf.GeneratedMessageV3.Builder builder) { - super(builder); - } - private AvailableDeviceInfo() { - name_ = ""; - type_ = ""; - physicalDescription_ = ""; - } - - @java.lang.Override - @SuppressWarnings({"unused"}) - protected java.lang.Object newInstance( - UnusedPrivateParameter unused) { - return new AvailableDeviceInfo(); - } - - @java.lang.Override - public final com.google.protobuf.UnknownFieldSet - getUnknownFields() { - return this.unknownFields; - } - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_AvailableDeviceInfo_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_AvailableDeviceInfo_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.AvailableDeviceInfo.class, org.tensorflow.proto.AvailableDeviceInfo.Builder.class); - } - - public static final int NAME_FIELD_NUMBER = 1; - private volatile java.lang.Object name_; - /** - * 
-   * Device name.
-   *
- * - * string name = 1; - * @return The name. - */ - @java.lang.Override - public java.lang.String getName() { - java.lang.Object ref = name_; - if (ref instanceof java.lang.String) { - return (java.lang.String) ref; - } else { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - name_ = s; - return s; - } - } - /** - * 
-   * Device name.
-   *
- * - * string name = 1; - * @return The bytes for name. - */ - @java.lang.Override - public com.google.protobuf.ByteString - getNameBytes() { - java.lang.Object ref = name_; - if (ref instanceof java.lang.String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - name_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - - public static final int TYPE_FIELD_NUMBER = 2; - private volatile java.lang.Object type_; - /** - * 
-   * Device type, e.g. 'CPU' or 'GPU'.
-   *
- * - * string type = 2; - * @return The type. - */ - @java.lang.Override - public java.lang.String getType() { - java.lang.Object ref = type_; - if (ref instanceof java.lang.String) { - return (java.lang.String) ref; - } else { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - type_ = s; - return s; - } - } - /** - * 
-   * Device type, e.g. 'CPU' or 'GPU'.
-   *
- * - * string type = 2; - * @return The bytes for type. - */ - @java.lang.Override - public com.google.protobuf.ByteString - getTypeBytes() { - java.lang.Object ref = type_; - if (ref instanceof java.lang.String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - type_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - - public static final int MEMORY_LIMIT_FIELD_NUMBER = 3; - private long memoryLimit_; - /** - * 
-   * Memory capacity in bytes.
-   *
- * - * int64 memory_limit = 3; - * @return The memoryLimit. - */ - @java.lang.Override - public long getMemoryLimit() { - return memoryLimit_; - } - - public static final int PHYSICAL_DESCRIPTION_FIELD_NUMBER = 4; - private volatile java.lang.Object physicalDescription_; - /** - * 
-   * The physical description of this device.
-   *
- * - * string physical_description = 4; - * @return The physicalDescription. - */ - @java.lang.Override - public java.lang.String getPhysicalDescription() { - java.lang.Object ref = physicalDescription_; - if (ref instanceof java.lang.String) { - return (java.lang.String) ref; - } else { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - physicalDescription_ = s; - return s; - } - } - /** - * 
-   * The physical description of this device.
-   *
- * - * string physical_description = 4; - * @return The bytes for physicalDescription. - */ - @java.lang.Override - public com.google.protobuf.ByteString - getPhysicalDescriptionBytes() { - java.lang.Object ref = physicalDescription_; - if (ref instanceof java.lang.String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - physicalDescription_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - - private byte memoizedIsInitialized = -1; - @java.lang.Override - public final boolean isInitialized() { - byte isInitialized = memoizedIsInitialized; - if (isInitialized == 1) return true; - if (isInitialized == 0) return false; - - memoizedIsInitialized = 1; - return true; - } - - @java.lang.Override - public void writeTo(com.google.protobuf.CodedOutputStream output) - throws java.io.IOException { - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) { - com.google.protobuf.GeneratedMessageV3.writeString(output, 1, name_); - } - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(type_)) { - com.google.protobuf.GeneratedMessageV3.writeString(output, 2, type_); - } - if (memoryLimit_ != 0L) { - output.writeInt64(3, memoryLimit_); - } - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(physicalDescription_)) { - com.google.protobuf.GeneratedMessageV3.writeString(output, 4, physicalDescription_); - } - getUnknownFields().writeTo(output); - } - - @java.lang.Override - public int getSerializedSize() { - int size = memoizedSize; - if (size != -1) return size; - - size = 0; - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) { - size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, name_); - } - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(type_)) { - size += com.google.protobuf.GeneratedMessageV3.computeStringSize(2, type_); - } - if (memoryLimit_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(3, memoryLimit_); - } - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(physicalDescription_)) { - size += com.google.protobuf.GeneratedMessageV3.computeStringSize(4, physicalDescription_); - } - size += getUnknownFields().getSerializedSize(); - memoizedSize = size; - return size; - } - - @java.lang.Override - public boolean equals(final java.lang.Object obj) { - if (obj == this) { - return true; - } - if (!(obj instanceof org.tensorflow.proto.AvailableDeviceInfo)) { - return super.equals(obj); - } - org.tensorflow.proto.AvailableDeviceInfo other = (org.tensorflow.proto.AvailableDeviceInfo) obj; - - if (!getName() - .equals(other.getName())) return false; - if (!getType() - .equals(other.getType())) return false; - if (getMemoryLimit() - != other.getMemoryLimit()) return false; - if (!getPhysicalDescription() - .equals(other.getPhysicalDescription())) return false; - if (!getUnknownFields().equals(other.getUnknownFields())) return false; - return true; - } - - @java.lang.Override - public int hashCode() { - if (memoizedHashCode != 0) { - return memoizedHashCode; - } - int hash = 41; - hash = (19 * hash) + getDescriptor().hashCode(); - hash = (37 * hash) + NAME_FIELD_NUMBER; - hash = (53 * hash) + getName().hashCode(); - hash = (37 * hash) + TYPE_FIELD_NUMBER; - hash = (53 * hash) + getType().hashCode(); - hash = (37 * hash) + MEMORY_LIMIT_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getMemoryLimit()); - hash = (37 * hash) + PHYSICAL_DESCRIPTION_FIELD_NUMBER; - hash = (53 * hash) + getPhysicalDescription().hashCode(); - hash = (29 * hash) + getUnknownFields().hashCode(); - memoizedHashCode = hash; - return hash; - } - - public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( - java.nio.ByteBuffer data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( - java.nio.ByteBuffer data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( - com.google.protobuf.ByteString data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( - com.google.protobuf.ByteString data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.AvailableDeviceInfo parseFrom(byte[] data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( - byte[] data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.AvailableDeviceInfo parseFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.AvailableDeviceInfo parseDelimitedFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input); - } - public static org.tensorflow.proto.AvailableDeviceInfo parseDelimitedFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( - com.google.protobuf.CodedInputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - - @java.lang.Override - public Builder newBuilderForType() { return newBuilder(); } - public static Builder newBuilder() { - return DEFAULT_INSTANCE.toBuilder(); - } - public static Builder newBuilder(org.tensorflow.proto.AvailableDeviceInfo prototype) { - return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); - } - @java.lang.Override - public Builder toBuilder() { - return this == DEFAULT_INSTANCE - ? new Builder() : new Builder().mergeFrom(this); - } - - @java.lang.Override - protected Builder newBuilderForType( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - Builder builder = new Builder(parent); - return builder; - } - /** - * 
-   * Matches DeviceAttributes
-   *
- * - * Protobuf type {@code tensorflow.AvailableDeviceInfo} - */ - public static final class Builder extends - com.google.protobuf.GeneratedMessageV3.Builder implements - // @@protoc_insertion_point(builder_implements:tensorflow.AvailableDeviceInfo) - org.tensorflow.proto.AvailableDeviceInfoOrBuilder { - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_AvailableDeviceInfo_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_AvailableDeviceInfo_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.AvailableDeviceInfo.class, org.tensorflow.proto.AvailableDeviceInfo.Builder.class); - } - - // Construct using org.tensorflow.proto.AvailableDeviceInfo.newBuilder() - private Builder() { - - } - - private Builder( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - super(parent); - - } - @java.lang.Override - public Builder clear() { - super.clear(); - name_ = ""; - - type_ = ""; - - memoryLimit_ = 0L; - - physicalDescription_ = ""; - - return this; - } - - @java.lang.Override - public com.google.protobuf.Descriptors.Descriptor - getDescriptorForType() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_AvailableDeviceInfo_descriptor; - } - - @java.lang.Override - public org.tensorflow.proto.AvailableDeviceInfo getDefaultInstanceForType() { - return org.tensorflow.proto.AvailableDeviceInfo.getDefaultInstance(); - } - - @java.lang.Override - public org.tensorflow.proto.AvailableDeviceInfo build() { - org.tensorflow.proto.AvailableDeviceInfo result = buildPartial(); - if (!result.isInitialized()) { - throw newUninitializedMessageException(result); - } - return result; - } - - @java.lang.Override - public org.tensorflow.proto.AvailableDeviceInfo buildPartial() { - org.tensorflow.proto.AvailableDeviceInfo result = new org.tensorflow.proto.AvailableDeviceInfo(this); - result.name_ = name_; - result.type_ = type_; - result.memoryLimit_ = memoryLimit_; - result.physicalDescription_ = physicalDescription_; - onBuilt(); - return result; - } - - @java.lang.Override - public Builder clone() { - return super.clone(); - } - @java.lang.Override - public Builder setField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.setField(field, value); - } - @java.lang.Override - public Builder clearField( - com.google.protobuf.Descriptors.FieldDescriptor field) { - return super.clearField(field); - } - @java.lang.Override - public Builder clearOneof( - com.google.protobuf.Descriptors.OneofDescriptor oneof) { - return super.clearOneof(oneof); - } - @java.lang.Override - public Builder setRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - int index, java.lang.Object value) { - return super.setRepeatedField(field, index, value); - } - @java.lang.Override - public Builder addRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.addRepeatedField(field, value); - } - @java.lang.Override - public Builder mergeFrom(com.google.protobuf.Message other) { - if (other instanceof org.tensorflow.proto.AvailableDeviceInfo) { - return mergeFrom((org.tensorflow.proto.AvailableDeviceInfo)other); - } else { - super.mergeFrom(other); - return this; - } - } - - public Builder mergeFrom(org.tensorflow.proto.AvailableDeviceInfo other) { - if (other == org.tensorflow.proto.AvailableDeviceInfo.getDefaultInstance()) return this; - if (!other.getName().isEmpty()) { - name_ = other.name_; - onChanged(); - } - if (!other.getType().isEmpty()) { - type_ = other.type_; - onChanged(); - } - if (other.getMemoryLimit() != 0L) { - setMemoryLimit(other.getMemoryLimit()); - } - if (!other.getPhysicalDescription().isEmpty()) { - physicalDescription_ = other.physicalDescription_; - onChanged(); - } - this.mergeUnknownFields(other.getUnknownFields()); - onChanged(); - return this; - } - - @java.lang.Override - public final boolean isInitialized() { - return true; - } - - @java.lang.Override - public Builder mergeFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - if (extensionRegistry == null) { - throw new java.lang.NullPointerException(); - } - try { - boolean done = false; - while (!done) { - int tag = input.readTag(); - switch (tag) { - case 0: - done = true; - break; - case 10: { - name_ = input.readStringRequireUtf8(); - - break; - } // case 10 - case 18: { - type_ = input.readStringRequireUtf8(); - - break; - } // case 18 - case 24: { - memoryLimit_ = input.readInt64(); - - break; - } // case 24 - case 34: { - physicalDescription_ = input.readStringRequireUtf8(); - - break; - } // case 34 - default: { - if (!super.parseUnknownField(input, extensionRegistry, tag)) { - done = true; // was an endgroup tag - } - break; - } // default: - } // switch (tag) - } // while (!done) - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.unwrapIOException(); - } finally { - onChanged(); - } // finally - return this; - } - - private java.lang.Object name_ = ""; - /** - * 
-     * Device name.
-     *
- * - * string name = 1; - * @return The name. - */ - public java.lang.String getName() { - java.lang.Object ref = name_; - if (!(ref instanceof java.lang.String)) { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - name_ = s; - return s; - } else { - return (java.lang.String) ref; - } - } - /** - * 
-     * Device name.
-     *
- * - * string name = 1; - * @return The bytes for name. - */ - public com.google.protobuf.ByteString - getNameBytes() { - java.lang.Object ref = name_; - if (ref instanceof String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - name_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - /** - * 
-     * Device name.
-     *
- * - * string name = 1; - * @param value The name to set. - * @return This builder for chaining. - */ - public Builder setName( - java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - - name_ = value; - onChanged(); - return this; - } - /** - * 
-     * Device name.
-     *
- * - * string name = 1; - * @return This builder for chaining. - */ - public Builder clearName() { - - name_ = getDefaultInstance().getName(); - onChanged(); - return this; - } - /** - * 
-     * Device name.
-     *
- * - * string name = 1; - * @param value The bytes for name to set. - * @return This builder for chaining. - */ - public Builder setNameBytes( - com.google.protobuf.ByteString value) { - if (value == null) { - throw new NullPointerException(); - } - checkByteStringIsUtf8(value); - - name_ = value; - onChanged(); - return this; - } - - private java.lang.Object type_ = ""; - /** - * 
-     * Device type, e.g. 'CPU' or 'GPU'.
-     *
- * - * string type = 2; - * @return The type. - */ - public java.lang.String getType() { - java.lang.Object ref = type_; - if (!(ref instanceof java.lang.String)) { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - type_ = s; - return s; - } else { - return (java.lang.String) ref; - } - } - /** - * 
-     * Device type, e.g. 'CPU' or 'GPU'.
-     *
- * - * string type = 2; - * @return The bytes for type. - */ - public com.google.protobuf.ByteString - getTypeBytes() { - java.lang.Object ref = type_; - if (ref instanceof String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - type_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - /** - * 
-     * Device type, e.g. 'CPU' or 'GPU'.
-     *
- * - * string type = 2; - * @param value The type to set. - * @return This builder for chaining. - */ - public Builder setType( - java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - - type_ = value; - onChanged(); - return this; - } - /** - * 
-     * Device type, e.g. 'CPU' or 'GPU'.
-     *
- * - * string type = 2; - * @return This builder for chaining. - */ - public Builder clearType() { - - type_ = getDefaultInstance().getType(); - onChanged(); - return this; - } - /** - * 
-     * Device type, e.g. 'CPU' or 'GPU'.
-     *
- * - * string type = 2; - * @param value The bytes for type to set. - * @return This builder for chaining. - */ - public Builder setTypeBytes( - com.google.protobuf.ByteString value) { - if (value == null) { - throw new NullPointerException(); - } - checkByteStringIsUtf8(value); - - type_ = value; - onChanged(); - return this; - } - - private long memoryLimit_ ; - /** - * 
-     * Memory capacity in bytes.
-     *
- * - * int64 memory_limit = 3; - * @return The memoryLimit. - */ - @java.lang.Override - public long getMemoryLimit() { - return memoryLimit_; - } - /** - * 
-     * Memory capacity in bytes.
-     *
- * - * int64 memory_limit = 3; - * @param value The memoryLimit to set. - * @return This builder for chaining. - */ - public Builder setMemoryLimit(long value) { - - memoryLimit_ = value; - onChanged(); - return this; - } - /** - * 
-     * Memory capacity in bytes.
-     *
- * - * int64 memory_limit = 3; - * @return This builder for chaining. - */ - public Builder clearMemoryLimit() { - - memoryLimit_ = 0L; - onChanged(); - return this; - } - - private java.lang.Object physicalDescription_ = ""; - /** - * 
-     * The physical description of this device.
-     *
- * - * string physical_description = 4; - * @return The physicalDescription. - */ - public java.lang.String getPhysicalDescription() { - java.lang.Object ref = physicalDescription_; - if (!(ref instanceof java.lang.String)) { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - physicalDescription_ = s; - return s; - } else { - return (java.lang.String) ref; - } - } - /** - * 
-     * The physical description of this device.
-     *
- * - * string physical_description = 4; - * @return The bytes for physicalDescription. - */ - public com.google.protobuf.ByteString - getPhysicalDescriptionBytes() { - java.lang.Object ref = physicalDescription_; - if (ref instanceof String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - physicalDescription_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - /** - * 
-     * The physical description of this device.
-     *
- * - * string physical_description = 4; - * @param value The physicalDescription to set. - * @return This builder for chaining. - */ - public Builder setPhysicalDescription( - java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - - physicalDescription_ = value; - onChanged(); - return this; - } - /** - * 
-     * The physical description of this device.
-     *
- * - * string physical_description = 4; - * @return This builder for chaining. - */ - public Builder clearPhysicalDescription() { - - physicalDescription_ = getDefaultInstance().getPhysicalDescription(); - onChanged(); - return this; - } - /** - * 
-     * The physical description of this device.
-     *
- * - * string physical_description = 4; - * @param value The bytes for physicalDescription to set. - * @return This builder for chaining. - */ - public Builder setPhysicalDescriptionBytes( - com.google.protobuf.ByteString value) { - if (value == null) { - throw new NullPointerException(); - } - checkByteStringIsUtf8(value); - - physicalDescription_ = value; - onChanged(); - return this; - } - @java.lang.Override - public final Builder setUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.setUnknownFields(unknownFields); - } - - @java.lang.Override - public final Builder mergeUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.mergeUnknownFields(unknownFields); - } - - - // @@protoc_insertion_point(builder_scope:tensorflow.AvailableDeviceInfo) - } - - // @@protoc_insertion_point(class_scope:tensorflow.AvailableDeviceInfo) - private static final org.tensorflow.proto.AvailableDeviceInfo DEFAULT_INSTANCE; - static { - DEFAULT_INSTANCE = new org.tensorflow.proto.AvailableDeviceInfo(); - } - - public static org.tensorflow.proto.AvailableDeviceInfo getDefaultInstance() { - return DEFAULT_INSTANCE; - } - - private static final com.google.protobuf.Parser - PARSER = new com.google.protobuf.AbstractParser() { - @java.lang.Override - public AvailableDeviceInfo parsePartialFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - Builder builder = newBuilder(); - try { - builder.mergeFrom(input, extensionRegistry); - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.setUnfinishedMessage(builder.buildPartial()); - } catch (com.google.protobuf.UninitializedMessageException e) { - throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); - } catch (java.io.IOException e) { - throw new com.google.protobuf.InvalidProtocolBufferException(e) - .setUnfinishedMessage(builder.buildPartial()); - } - return builder.buildPartial(); - } - }; - - public static com.google.protobuf.Parser parser() { - return PARSER; - } - - @java.lang.Override - public com.google.protobuf.Parser getParserForType() { - return PARSER; - } - - @java.lang.Override - public org.tensorflow.proto.AvailableDeviceInfo getDefaultInstanceForType() { - return DEFAULT_INSTANCE; - } - -} - diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/AvailableDeviceInfoOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/AvailableDeviceInfoOrBuilder.java deleted file mode 100644 index ef9f13504d3..00000000000 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/AvailableDeviceInfoOrBuilder.java +++ /dev/null @@ -1,79 +0,0 @@ -// Generated by the protocol buffer compiler. DO NOT EDIT! -// source: tsl/protobuf/test_log.proto - -package org.tensorflow.proto; - -public interface AvailableDeviceInfoOrBuilder extends - // @@protoc_insertion_point(interface_extends:tensorflow.AvailableDeviceInfo) - com.google.protobuf.MessageOrBuilder { - - /** - * 
-   * Device name.
-   *
- * - * string name = 1; - * @return The name. - */ - java.lang.String getName(); - /** - * 
-   * Device name.
-   *
- * - * string name = 1; - * @return The bytes for name. - */ - com.google.protobuf.ByteString - getNameBytes(); - - /** - * 
-   * Device type, e.g. 'CPU' or 'GPU'.
-   *
- * - * string type = 2; - * @return The type. - */ - java.lang.String getType(); - /** - * 
-   * Device type, e.g. 'CPU' or 'GPU'.
-   *
- * - * string type = 2; - * @return The bytes for type. - */ - com.google.protobuf.ByteString - getTypeBytes(); - - /** - * 
-   * Memory capacity in bytes.
-   *
- * - * int64 memory_limit = 3; - * @return The memoryLimit. - */ - long getMemoryLimit(); - - /** - * 
-   * The physical description of this device.
-   *
- * - * string physical_description = 4; - * @return The physicalDescription. - */ - java.lang.String getPhysicalDescription(); - /** - * 
-   * The physical description of this device.
-   *
- * - * string physical_description = 4; - * @return The bytes for physicalDescription. - */ - com.google.protobuf.ByteString - getPhysicalDescriptionBytes(); -} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntries.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntries.java deleted file mode 100644 index b3ed52d11c0..00000000000 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntries.java +++ /dev/null @@ -1,752 +0,0 @@ -// Generated by the protocol buffer compiler. DO NOT EDIT! -// source: tsl/protobuf/test_log.proto - -package org.tensorflow.proto; - -/** - * Protobuf type {@code tensorflow.BenchmarkEntries} - */ -public final class BenchmarkEntries extends - com.google.protobuf.GeneratedMessageV3 implements - // @@protoc_insertion_point(message_implements:tensorflow.BenchmarkEntries) - BenchmarkEntriesOrBuilder { -private static final long serialVersionUID = 0L; - // Use BenchmarkEntries.newBuilder() to construct. - private BenchmarkEntries(com.google.protobuf.GeneratedMessageV3.Builder builder) { - super(builder); - } - private BenchmarkEntries() { - entry_ = java.util.Collections.emptyList(); - } - - @java.lang.Override - @SuppressWarnings({"unused"}) - protected java.lang.Object newInstance( - UnusedPrivateParameter unused) { - return new BenchmarkEntries(); - } - - @java.lang.Override - public final com.google.protobuf.UnknownFieldSet - getUnknownFields() { - return this.unknownFields; - } - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntries_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntries_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BenchmarkEntries.class, org.tensorflow.proto.BenchmarkEntries.Builder.class); - } - - public static final int ENTRY_FIELD_NUMBER = 1; - private java.util.List entry_; - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - @java.lang.Override - public java.util.List getEntryList() { - return entry_; - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - @java.lang.Override - public java.util.List - getEntryOrBuilderList() { - return entry_; - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - @java.lang.Override - public int getEntryCount() { - return entry_.size(); - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - @java.lang.Override - public org.tensorflow.proto.BenchmarkEntry getEntry(int index) { - return entry_.get(index); - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - @java.lang.Override - public org.tensorflow.proto.BenchmarkEntryOrBuilder getEntryOrBuilder( - int index) { - return entry_.get(index); - } - - private byte memoizedIsInitialized = -1; - @java.lang.Override - public final boolean isInitialized() { - byte isInitialized = memoizedIsInitialized; - if (isInitialized == 1) return true; - if (isInitialized == 0) return false; - - memoizedIsInitialized = 1; - return true; - } - - @java.lang.Override - public void writeTo(com.google.protobuf.CodedOutputStream output) - throws java.io.IOException { - for (int i = 0; i < entry_.size(); i++) { - output.writeMessage(1, entry_.get(i)); - } - getUnknownFields().writeTo(output); - } - - @java.lang.Override - public int getSerializedSize() { - int size = memoizedSize; - if (size != -1) return size; - - size = 0; - for (int i = 0; i < entry_.size(); i++) { - size += com.google.protobuf.CodedOutputStream - .computeMessageSize(1, entry_.get(i)); - } - size += getUnknownFields().getSerializedSize(); - memoizedSize = size; - return size; - } - - @java.lang.Override - public boolean equals(final java.lang.Object obj) { - if (obj == this) { - return true; - } - if (!(obj instanceof org.tensorflow.proto.BenchmarkEntries)) { - return super.equals(obj); - } - org.tensorflow.proto.BenchmarkEntries other = (org.tensorflow.proto.BenchmarkEntries) obj; - - if (!getEntryList() - .equals(other.getEntryList())) return false; - if (!getUnknownFields().equals(other.getUnknownFields())) return false; - return true; - } - - @java.lang.Override - public int hashCode() { - if (memoizedHashCode != 0) { - return memoizedHashCode; - } - int hash = 41; - hash = (19 * hash) + getDescriptor().hashCode(); - if (getEntryCount() > 0) { - hash = (37 * hash) + ENTRY_FIELD_NUMBER; - hash = (53 * hash) + getEntryList().hashCode(); - } - hash = (29 * hash) + getUnknownFields().hashCode(); - memoizedHashCode = hash; - return hash; - } - - public static org.tensorflow.proto.BenchmarkEntries parseFrom( - java.nio.ByteBuffer data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BenchmarkEntries parseFrom( - java.nio.ByteBuffer data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BenchmarkEntries parseFrom( - com.google.protobuf.ByteString data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BenchmarkEntries parseFrom( - com.google.protobuf.ByteString data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BenchmarkEntries parseFrom(byte[] data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BenchmarkEntries parseFrom( - byte[] data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BenchmarkEntries parseFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BenchmarkEntries parseFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BenchmarkEntries parseDelimitedFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BenchmarkEntries parseDelimitedFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BenchmarkEntries parseFrom( - com.google.protobuf.CodedInputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BenchmarkEntries parseFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - - @java.lang.Override - public Builder newBuilderForType() { return newBuilder(); } - public static Builder newBuilder() { - return DEFAULT_INSTANCE.toBuilder(); - } - public static Builder newBuilder(org.tensorflow.proto.BenchmarkEntries prototype) { - return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); - } - @java.lang.Override - public Builder toBuilder() { - return this == DEFAULT_INSTANCE - ? new Builder() : new Builder().mergeFrom(this); - } - - @java.lang.Override - protected Builder newBuilderForType( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - Builder builder = new Builder(parent); - return builder; - } - /** - * Protobuf type {@code tensorflow.BenchmarkEntries} - */ - public static final class Builder extends - com.google.protobuf.GeneratedMessageV3.Builder implements - // @@protoc_insertion_point(builder_implements:tensorflow.BenchmarkEntries) - org.tensorflow.proto.BenchmarkEntriesOrBuilder { - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntries_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntries_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BenchmarkEntries.class, org.tensorflow.proto.BenchmarkEntries.Builder.class); - } - - // Construct using org.tensorflow.proto.BenchmarkEntries.newBuilder() - private Builder() { - - } - - private Builder( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - super(parent); - - } - @java.lang.Override - public Builder clear() { - super.clear(); - if (entryBuilder_ == null) { - entry_ = java.util.Collections.emptyList(); - } else { - entry_ = null; - entryBuilder_.clear(); - } - bitField0_ = (bitField0_ & ~0x00000001); - return this; - } - - @java.lang.Override - public com.google.protobuf.Descriptors.Descriptor - getDescriptorForType() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntries_descriptor; - } - - @java.lang.Override - public org.tensorflow.proto.BenchmarkEntries getDefaultInstanceForType() { - return org.tensorflow.proto.BenchmarkEntries.getDefaultInstance(); - } - - @java.lang.Override - public org.tensorflow.proto.BenchmarkEntries build() { - org.tensorflow.proto.BenchmarkEntries result = buildPartial(); - if (!result.isInitialized()) { - throw newUninitializedMessageException(result); - } - return result; - } - - @java.lang.Override - public org.tensorflow.proto.BenchmarkEntries buildPartial() { - org.tensorflow.proto.BenchmarkEntries result = new org.tensorflow.proto.BenchmarkEntries(this); - int from_bitField0_ = bitField0_; - if (entryBuilder_ == null) { - if (((bitField0_ & 0x00000001) != 0)) { - entry_ = java.util.Collections.unmodifiableList(entry_); - bitField0_ = (bitField0_ & ~0x00000001); - } - result.entry_ = entry_; - } else { - result.entry_ = entryBuilder_.build(); - } - onBuilt(); - return result; - } - - @java.lang.Override - public Builder clone() { - return super.clone(); - } - @java.lang.Override - public Builder setField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.setField(field, value); - } - @java.lang.Override - public Builder clearField( - com.google.protobuf.Descriptors.FieldDescriptor field) { - return super.clearField(field); - } - @java.lang.Override - public Builder clearOneof( - com.google.protobuf.Descriptors.OneofDescriptor oneof) { - return super.clearOneof(oneof); - } - @java.lang.Override - public Builder setRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - int index, java.lang.Object value) { - return super.setRepeatedField(field, index, value); - } - @java.lang.Override - public Builder addRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.addRepeatedField(field, value); - } - @java.lang.Override - public Builder mergeFrom(com.google.protobuf.Message other) { - if (other instanceof org.tensorflow.proto.BenchmarkEntries) { - return mergeFrom((org.tensorflow.proto.BenchmarkEntries)other); - } else { - super.mergeFrom(other); - return this; - } - } - - public Builder mergeFrom(org.tensorflow.proto.BenchmarkEntries other) { - if (other == org.tensorflow.proto.BenchmarkEntries.getDefaultInstance()) return this; - if (entryBuilder_ == null) { - if (!other.entry_.isEmpty()) { - if (entry_.isEmpty()) { - entry_ = other.entry_; - bitField0_ = (bitField0_ & ~0x00000001); - } else { - ensureEntryIsMutable(); - entry_.addAll(other.entry_); - } - onChanged(); - } - } else { - if (!other.entry_.isEmpty()) { - if (entryBuilder_.isEmpty()) { - entryBuilder_.dispose(); - entryBuilder_ = null; - entry_ = other.entry_; - bitField0_ = (bitField0_ & ~0x00000001); - entryBuilder_ = - com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ? - getEntryFieldBuilder() : null; - } else { - entryBuilder_.addAllMessages(other.entry_); - } - } - } - this.mergeUnknownFields(other.getUnknownFields()); - onChanged(); - return this; - } - - @java.lang.Override - public final boolean isInitialized() { - return true; - } - - @java.lang.Override - public Builder mergeFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - if (extensionRegistry == null) { - throw new java.lang.NullPointerException(); - } - try { - boolean done = false; - while (!done) { - int tag = input.readTag(); - switch (tag) { - case 0: - done = true; - break; - case 10: { - org.tensorflow.proto.BenchmarkEntry m = - input.readMessage( - org.tensorflow.proto.BenchmarkEntry.parser(), - extensionRegistry); - if (entryBuilder_ == null) { - ensureEntryIsMutable(); - entry_.add(m); - } else { - entryBuilder_.addMessage(m); - } - break; - } // case 10 - default: { - if (!super.parseUnknownField(input, extensionRegistry, tag)) { - done = true; // was an endgroup tag - } - break; - } // default: - } // switch (tag) - } // while (!done) - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.unwrapIOException(); - } finally { - onChanged(); - } // finally - return this; - } - private int bitField0_; - - private java.util.List entry_ = - java.util.Collections.emptyList(); - private void ensureEntryIsMutable() { - if (!((bitField0_ & 0x00000001) != 0)) { - entry_ = new java.util.ArrayList(entry_); - bitField0_ |= 0x00000001; - } - } - - private com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.BenchmarkEntry, org.tensorflow.proto.BenchmarkEntry.Builder, org.tensorflow.proto.BenchmarkEntryOrBuilder> entryBuilder_; - - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public java.util.List getEntryList() { - if (entryBuilder_ == null) { - return java.util.Collections.unmodifiableList(entry_); - } else { - return entryBuilder_.getMessageList(); - } - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public int getEntryCount() { - if (entryBuilder_ == null) { - return entry_.size(); - } else { - return entryBuilder_.getCount(); - } - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public org.tensorflow.proto.BenchmarkEntry getEntry(int index) { - if (entryBuilder_ == null) { - return entry_.get(index); - } else { - return entryBuilder_.getMessage(index); - } - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public Builder setEntry( - int index, org.tensorflow.proto.BenchmarkEntry value) { - if (entryBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureEntryIsMutable(); - entry_.set(index, value); - onChanged(); - } else { - entryBuilder_.setMessage(index, value); - } - return this; - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public Builder setEntry( - int index, org.tensorflow.proto.BenchmarkEntry.Builder builderForValue) { - if (entryBuilder_ == null) { - ensureEntryIsMutable(); - entry_.set(index, builderForValue.build()); - onChanged(); - } else { - entryBuilder_.setMessage(index, builderForValue.build()); - } - return this; - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public Builder addEntry(org.tensorflow.proto.BenchmarkEntry value) { - if (entryBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureEntryIsMutable(); - entry_.add(value); - onChanged(); - } else { - entryBuilder_.addMessage(value); - } - return this; - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public Builder addEntry( - int index, org.tensorflow.proto.BenchmarkEntry value) { - if (entryBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureEntryIsMutable(); - entry_.add(index, value); - onChanged(); - } else { - entryBuilder_.addMessage(index, value); - } - return this; - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public Builder addEntry( - org.tensorflow.proto.BenchmarkEntry.Builder builderForValue) { - if (entryBuilder_ == null) { - ensureEntryIsMutable(); - entry_.add(builderForValue.build()); - onChanged(); - } else { - entryBuilder_.addMessage(builderForValue.build()); - } - return this; - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public Builder addEntry( - int index, org.tensorflow.proto.BenchmarkEntry.Builder builderForValue) { - if (entryBuilder_ == null) { - ensureEntryIsMutable(); - entry_.add(index, builderForValue.build()); - onChanged(); - } else { - entryBuilder_.addMessage(index, builderForValue.build()); - } - return this; - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public Builder addAllEntry( - java.lang.Iterable values) { - if (entryBuilder_ == null) { - ensureEntryIsMutable(); - com.google.protobuf.AbstractMessageLite.Builder.addAll( - values, entry_); - onChanged(); - } else { - entryBuilder_.addAllMessages(values); - } - return this; - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public Builder clearEntry() { - if (entryBuilder_ == null) { - entry_ = java.util.Collections.emptyList(); - bitField0_ = (bitField0_ & ~0x00000001); - onChanged(); - } else { - entryBuilder_.clear(); - } - return this; - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public Builder removeEntry(int index) { - if (entryBuilder_ == null) { - ensureEntryIsMutable(); - entry_.remove(index); - onChanged(); - } else { - entryBuilder_.remove(index); - } - return this; - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public org.tensorflow.proto.BenchmarkEntry.Builder getEntryBuilder( - int index) { - return getEntryFieldBuilder().getBuilder(index); - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public org.tensorflow.proto.BenchmarkEntryOrBuilder getEntryOrBuilder( - int index) { - if (entryBuilder_ == null) { - return entry_.get(index); } else { - return entryBuilder_.getMessageOrBuilder(index); - } - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public java.util.List - getEntryOrBuilderList() { - if (entryBuilder_ != null) { - return entryBuilder_.getMessageOrBuilderList(); - } else { - return java.util.Collections.unmodifiableList(entry_); - } - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public org.tensorflow.proto.BenchmarkEntry.Builder addEntryBuilder() { - return getEntryFieldBuilder().addBuilder( - org.tensorflow.proto.BenchmarkEntry.getDefaultInstance()); - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public org.tensorflow.proto.BenchmarkEntry.Builder addEntryBuilder( - int index) { - return getEntryFieldBuilder().addBuilder( - index, org.tensorflow.proto.BenchmarkEntry.getDefaultInstance()); - } - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - public java.util.List - getEntryBuilderList() { - return getEntryFieldBuilder().getBuilderList(); - } - private com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.BenchmarkEntry, org.tensorflow.proto.BenchmarkEntry.Builder, org.tensorflow.proto.BenchmarkEntryOrBuilder> - getEntryFieldBuilder() { - if (entryBuilder_ == null) { - entryBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.BenchmarkEntry, org.tensorflow.proto.BenchmarkEntry.Builder, org.tensorflow.proto.BenchmarkEntryOrBuilder>( - entry_, - ((bitField0_ & 0x00000001) != 0), - getParentForChildren(), - isClean()); - entry_ = null; - } - return entryBuilder_; - } - @java.lang.Override - public final Builder setUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.setUnknownFields(unknownFields); - } - - @java.lang.Override - public final Builder mergeUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.mergeUnknownFields(unknownFields); - } - - - // @@protoc_insertion_point(builder_scope:tensorflow.BenchmarkEntries) - } - - // @@protoc_insertion_point(class_scope:tensorflow.BenchmarkEntries) - private static final org.tensorflow.proto.BenchmarkEntries DEFAULT_INSTANCE; - static { - DEFAULT_INSTANCE = new org.tensorflow.proto.BenchmarkEntries(); - } - - public static org.tensorflow.proto.BenchmarkEntries getDefaultInstance() { - return DEFAULT_INSTANCE; - } - - private static final com.google.protobuf.Parser - PARSER = new com.google.protobuf.AbstractParser() { - @java.lang.Override - public BenchmarkEntries parsePartialFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - Builder builder = newBuilder(); - try { - builder.mergeFrom(input, extensionRegistry); - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.setUnfinishedMessage(builder.buildPartial()); - } catch (com.google.protobuf.UninitializedMessageException e) { - throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); - } catch (java.io.IOException e) { - throw new com.google.protobuf.InvalidProtocolBufferException(e) - .setUnfinishedMessage(builder.buildPartial()); - } - return builder.buildPartial(); - } - }; - - public static com.google.protobuf.Parser parser() { - return PARSER; - } - - @java.lang.Override - public com.google.protobuf.Parser getParserForType() { - return PARSER; - } - - @java.lang.Override - public org.tensorflow.proto.BenchmarkEntries getDefaultInstanceForType() { - return DEFAULT_INSTANCE; - } - -} - diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntriesOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntriesOrBuilder.java deleted file mode 100644 index b99b30bf045..00000000000 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntriesOrBuilder.java +++ /dev/null @@ -1,33 +0,0 @@ -// Generated by the protocol buffer compiler. DO NOT EDIT! -// source: tsl/protobuf/test_log.proto - -package org.tensorflow.proto; - -public interface BenchmarkEntriesOrBuilder extends - // @@protoc_insertion_point(interface_extends:tensorflow.BenchmarkEntries) - com.google.protobuf.MessageOrBuilder { - - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - java.util.List - getEntryList(); - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - org.tensorflow.proto.BenchmarkEntry getEntry(int index); - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - int getEntryCount(); - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - java.util.List - getEntryOrBuilderList(); - /** - * repeated .tensorflow.BenchmarkEntry entry = 1; - */ - org.tensorflow.proto.BenchmarkEntryOrBuilder getEntryOrBuilder( - int index); -} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntry.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntry.java deleted file mode 100644 index 0c470285827..00000000000 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntry.java +++ /dev/null @@ -1,1709 +0,0 @@ -// Generated by the protocol buffer compiler. DO NOT EDIT! -// source: tsl/protobuf/test_log.proto - -package org.tensorflow.proto; - -/** - * 
- * Each unit test or benchmark in a test or benchmark run provides
- * some set of information.  Here we provide some reasonable keys
- * one would expect to see, with optional key/value pairs for things
- * we haven't considered.
- * This BenchmarkEntry should be emitted by each unit test or benchmark
- * reporter.
- *
- * - * Protobuf type {@code tensorflow.BenchmarkEntry} - */ -public final class BenchmarkEntry extends - com.google.protobuf.GeneratedMessageV3 implements - // @@protoc_insertion_point(message_implements:tensorflow.BenchmarkEntry) - BenchmarkEntryOrBuilder { -private static final long serialVersionUID = 0L; - // Use BenchmarkEntry.newBuilder() to construct. - private BenchmarkEntry(com.google.protobuf.GeneratedMessageV3.Builder builder) { - super(builder); - } - private BenchmarkEntry() { - name_ = ""; - metrics_ = java.util.Collections.emptyList(); - } - - @java.lang.Override - @SuppressWarnings({"unused"}) - protected java.lang.Object newInstance( - UnusedPrivateParameter unused) { - return new BenchmarkEntry(); - } - - @java.lang.Override - public final com.google.protobuf.UnknownFieldSet - getUnknownFields() { - return this.unknownFields; - } - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntry_descriptor; - } - - @SuppressWarnings({"rawtypes"}) - @java.lang.Override - protected com.google.protobuf.MapField internalGetMapField( - int number) { - switch (number) { - case 6: - return internalGetExtras(); - default: - throw new RuntimeException( - "Invalid map field number: " + number); - } - } - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntry_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BenchmarkEntry.class, org.tensorflow.proto.BenchmarkEntry.Builder.class); - } - - public static final int NAME_FIELD_NUMBER = 1; - private volatile java.lang.Object name_; - /** - * 
-   * The name of the specific benchmark or test
-   * (e.g. BM_AdjustContrast_gpu_B_W_H)
-   *
- * - * string name = 1; - * @return The name. - */ - @java.lang.Override - public java.lang.String getName() { - java.lang.Object ref = name_; - if (ref instanceof java.lang.String) { - return (java.lang.String) ref; - } else { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - name_ = s; - return s; - } - } - /** - * 
-   * The name of the specific benchmark or test
-   * (e.g. BM_AdjustContrast_gpu_B_W_H)
-   *
- * - * string name = 1; - * @return The bytes for name. - */ - @java.lang.Override - public com.google.protobuf.ByteString - getNameBytes() { - java.lang.Object ref = name_; - if (ref instanceof java.lang.String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - name_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - - public static final int ITERS_FIELD_NUMBER = 2; - private long iters_; - /** - * 
-   * If a benchmark, how many iterations it was run for
-   *
- * - * int64 iters = 2; - * @return The iters. - */ - @java.lang.Override - public long getIters() { - return iters_; - } - - public static final int CPU_TIME_FIELD_NUMBER = 3; - private double cpuTime_; - /** - * 
-   * Total cpu time used for all iterations (in seconds)
-   *
- * - * double cpu_time = 3; - * @return The cpuTime. - */ - @java.lang.Override - public double getCpuTime() { - return cpuTime_; - } - - public static final int WALL_TIME_FIELD_NUMBER = 4; - private double wallTime_; - /** - * 
-   * Total wall time used for all iterations (in seconds)
-   *
- * - * double wall_time = 4; - * @return The wallTime. - */ - @java.lang.Override - public double getWallTime() { - return wallTime_; - } - - public static final int THROUGHPUT_FIELD_NUMBER = 5; - private double throughput_; - /** - * 
-   * Throughput (in MB/s)
-   *
- * - * double throughput = 5; - * @return The throughput. - */ - @java.lang.Override - public double getThroughput() { - return throughput_; - } - - public static final int EXTRAS_FIELD_NUMBER = 6; - private static final class ExtrasDefaultEntryHolder { - static final com.google.protobuf.MapEntry< - java.lang.String, org.tensorflow.proto.EntryValue> defaultEntry = - com.google.protobuf.MapEntry - .newDefaultInstance( - org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntry_ExtrasEntry_descriptor, - com.google.protobuf.WireFormat.FieldType.STRING, - "", - com.google.protobuf.WireFormat.FieldType.MESSAGE, - org.tensorflow.proto.EntryValue.getDefaultInstance()); - } - private com.google.protobuf.MapField< - java.lang.String, org.tensorflow.proto.EntryValue> extras_; - private com.google.protobuf.MapField - internalGetExtras() { - if (extras_ == null) { - return com.google.protobuf.MapField.emptyMapField( - ExtrasDefaultEntryHolder.defaultEntry); - } - return extras_; - } - - public int getExtrasCount() { - return internalGetExtras().getMap().size(); - } - /** - * 
-   * Generic map from result key to value.
-   *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - - @java.lang.Override - public boolean containsExtras( - java.lang.String key) { - if (key == null) { throw new NullPointerException("map key"); } - return internalGetExtras().getMap().containsKey(key); - } - /** - * Use {@link #getExtrasMap()} instead. - */ - @java.lang.Override - @java.lang.Deprecated - public java.util.Map getExtras() { - return getExtrasMap(); - } - /** - * 
-   * Generic map from result key to value.
-   *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - @java.lang.Override - - public java.util.Map getExtrasMap() { - return internalGetExtras().getMap(); - } - /** - * 
-   * Generic map from result key to value.
-   *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - @java.lang.Override - - public org.tensorflow.proto.EntryValue getExtrasOrDefault( - java.lang.String key, - org.tensorflow.proto.EntryValue defaultValue) { - if (key == null) { throw new NullPointerException("map key"); } - java.util.Map map = - internalGetExtras().getMap(); - return map.containsKey(key) ? map.get(key) : defaultValue; - } - /** - * 
-   * Generic map from result key to value.
-   *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - @java.lang.Override - - public org.tensorflow.proto.EntryValue getExtrasOrThrow( - java.lang.String key) { - if (key == null) { throw new NullPointerException("map key"); } - java.util.Map map = - internalGetExtras().getMap(); - if (!map.containsKey(key)) { - throw new java.lang.IllegalArgumentException(); - } - return map.get(key); - } - - public static final int METRICS_FIELD_NUMBER = 7; - private java.util.List metrics_; - /** - * 
-   * Metric name, value and expected range. This can include accuracy metrics
-   * typically used to determine whether the accuracy test has passed
-   *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - @java.lang.Override - public java.util.List getMetricsList() { - return metrics_; - } - /** - * 
-   * Metric name, value and expected range. This can include accuracy metrics
-   * typically used to determine whether the accuracy test has passed
-   *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - @java.lang.Override - public java.util.List - getMetricsOrBuilderList() { - return metrics_; - } - /** - * 
-   * Metric name, value and expected range. This can include accuracy metrics
-   * typically used to determine whether the accuracy test has passed
-   *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - @java.lang.Override - public int getMetricsCount() { - return metrics_.size(); - } - /** - * 
-   * Metric name, value and expected range. This can include accuracy metrics
-   * typically used to determine whether the accuracy test has passed
-   *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - @java.lang.Override - public org.tensorflow.proto.MetricEntry getMetrics(int index) { - return metrics_.get(index); - } - /** - * 
-   * Metric name, value and expected range. This can include accuracy metrics
-   * typically used to determine whether the accuracy test has passed
-   *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - @java.lang.Override - public org.tensorflow.proto.MetricEntryOrBuilder getMetricsOrBuilder( - int index) { - return metrics_.get(index); - } - - private byte memoizedIsInitialized = -1; - @java.lang.Override - public final boolean isInitialized() { - byte isInitialized = memoizedIsInitialized; - if (isInitialized == 1) return true; - if (isInitialized == 0) return false; - - memoizedIsInitialized = 1; - return true; - } - - @java.lang.Override - public void writeTo(com.google.protobuf.CodedOutputStream output) - throws java.io.IOException { - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) { - com.google.protobuf.GeneratedMessageV3.writeString(output, 1, name_); - } - if (iters_ != 0L) { - output.writeInt64(2, iters_); - } - if (java.lang.Double.doubleToRawLongBits(cpuTime_) != 0) { - output.writeDouble(3, cpuTime_); - } - if (java.lang.Double.doubleToRawLongBits(wallTime_) != 0) { - output.writeDouble(4, wallTime_); - } - if (java.lang.Double.doubleToRawLongBits(throughput_) != 0) { - output.writeDouble(5, throughput_); - } - com.google.protobuf.GeneratedMessageV3 - .serializeStringMapTo( - output, - internalGetExtras(), - ExtrasDefaultEntryHolder.defaultEntry, - 6); - for (int i = 0; i < metrics_.size(); i++) { - output.writeMessage(7, metrics_.get(i)); - } - getUnknownFields().writeTo(output); - } - - @java.lang.Override - public int getSerializedSize() { - int size = memoizedSize; - if (size != -1) return size; - - size = 0; - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) { - size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, name_); - } - if (iters_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(2, iters_); - } - if (java.lang.Double.doubleToRawLongBits(cpuTime_) != 0) { - size += com.google.protobuf.CodedOutputStream - .computeDoubleSize(3, cpuTime_); - } - if (java.lang.Double.doubleToRawLongBits(wallTime_) != 0) { - size += com.google.protobuf.CodedOutputStream - .computeDoubleSize(4, wallTime_); - } - if (java.lang.Double.doubleToRawLongBits(throughput_) != 0) { - size += com.google.protobuf.CodedOutputStream - .computeDoubleSize(5, throughput_); - } - for (java.util.Map.Entry entry - : internalGetExtras().getMap().entrySet()) { - com.google.protobuf.MapEntry - extras__ = ExtrasDefaultEntryHolder.defaultEntry.newBuilderForType() - .setKey(entry.getKey()) - .setValue(entry.getValue()) - .build(); - size += com.google.protobuf.CodedOutputStream - .computeMessageSize(6, extras__); - } - for (int i = 0; i < metrics_.size(); i++) { - size += com.google.protobuf.CodedOutputStream - .computeMessageSize(7, metrics_.get(i)); - } - size += getUnknownFields().getSerializedSize(); - memoizedSize = size; - return size; - } - - @java.lang.Override - public boolean equals(final java.lang.Object obj) { - if (obj == this) { - return true; - } - if (!(obj instanceof org.tensorflow.proto.BenchmarkEntry)) { - return super.equals(obj); - } - org.tensorflow.proto.BenchmarkEntry other = (org.tensorflow.proto.BenchmarkEntry) obj; - - if (!getName() - .equals(other.getName())) return false; - if (getIters() - != other.getIters()) return false; - if (java.lang.Double.doubleToLongBits(getCpuTime()) - != java.lang.Double.doubleToLongBits( - other.getCpuTime())) return false; - if (java.lang.Double.doubleToLongBits(getWallTime()) - != java.lang.Double.doubleToLongBits( - other.getWallTime())) return false; - if (java.lang.Double.doubleToLongBits(getThroughput()) - != java.lang.Double.doubleToLongBits( - other.getThroughput())) return false; - if (!internalGetExtras().equals( - other.internalGetExtras())) return false; - if (!getMetricsList() - .equals(other.getMetricsList())) return false; - if (!getUnknownFields().equals(other.getUnknownFields())) return false; - return true; - } - - @java.lang.Override - public int hashCode() { - if (memoizedHashCode != 0) { - return memoizedHashCode; - } - int hash = 41; - hash = (19 * hash) + getDescriptor().hashCode(); - hash = (37 * hash) + NAME_FIELD_NUMBER; - hash = (53 * hash) + getName().hashCode(); - hash = (37 * hash) + ITERS_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getIters()); - hash = (37 * hash) + CPU_TIME_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - java.lang.Double.doubleToLongBits(getCpuTime())); - hash = (37 * hash) + WALL_TIME_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - java.lang.Double.doubleToLongBits(getWallTime())); - hash = (37 * hash) + THROUGHPUT_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - java.lang.Double.doubleToLongBits(getThroughput())); - if (!internalGetExtras().getMap().isEmpty()) { - hash = (37 * hash) + EXTRAS_FIELD_NUMBER; - hash = (53 * hash) + internalGetExtras().hashCode(); - } - if (getMetricsCount() > 0) { - hash = (37 * hash) + METRICS_FIELD_NUMBER; - hash = (53 * hash) + getMetricsList().hashCode(); - } - hash = (29 * hash) + getUnknownFields().hashCode(); - memoizedHashCode = hash; - return hash; - } - - public static org.tensorflow.proto.BenchmarkEntry parseFrom( - java.nio.ByteBuffer data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BenchmarkEntry parseFrom( - java.nio.ByteBuffer data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BenchmarkEntry parseFrom( - com.google.protobuf.ByteString data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BenchmarkEntry parseFrom( - com.google.protobuf.ByteString data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BenchmarkEntry parseFrom(byte[] data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BenchmarkEntry parseFrom( - byte[] data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BenchmarkEntry parseFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BenchmarkEntry parseFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BenchmarkEntry parseDelimitedFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BenchmarkEntry parseDelimitedFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BenchmarkEntry parseFrom( - com.google.protobuf.CodedInputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BenchmarkEntry parseFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - - @java.lang.Override - public Builder newBuilderForType() { return newBuilder(); } - public static Builder newBuilder() { - return DEFAULT_INSTANCE.toBuilder(); - } - public static Builder newBuilder(org.tensorflow.proto.BenchmarkEntry prototype) { - return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); - } - @java.lang.Override - public Builder toBuilder() { - return this == DEFAULT_INSTANCE - ? new Builder() : new Builder().mergeFrom(this); - } - - @java.lang.Override - protected Builder newBuilderForType( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - Builder builder = new Builder(parent); - return builder; - } - /** - * 
-   * Each unit test or benchmark in a test or benchmark run provides
-   * some set of information.  Here we provide some reasonable keys
-   * one would expect to see, with optional key/value pairs for things
-   * we haven't considered.
-   * This BenchmarkEntry should be emitted by each unit test or benchmark
-   * reporter.
-   *
- * - * Protobuf type {@code tensorflow.BenchmarkEntry} - */ - public static final class Builder extends - com.google.protobuf.GeneratedMessageV3.Builder implements - // @@protoc_insertion_point(builder_implements:tensorflow.BenchmarkEntry) - org.tensorflow.proto.BenchmarkEntryOrBuilder { - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntry_descriptor; - } - - @SuppressWarnings({"rawtypes"}) - protected com.google.protobuf.MapField internalGetMapField( - int number) { - switch (number) { - case 6: - return internalGetExtras(); - default: - throw new RuntimeException( - "Invalid map field number: " + number); - } - } - @SuppressWarnings({"rawtypes"}) - protected com.google.protobuf.MapField internalGetMutableMapField( - int number) { - switch (number) { - case 6: - return internalGetMutableExtras(); - default: - throw new RuntimeException( - "Invalid map field number: " + number); - } - } - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntry_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BenchmarkEntry.class, org.tensorflow.proto.BenchmarkEntry.Builder.class); - } - - // Construct using org.tensorflow.proto.BenchmarkEntry.newBuilder() - private Builder() { - - } - - private Builder( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - super(parent); - - } - @java.lang.Override - public Builder clear() { - super.clear(); - name_ = ""; - - iters_ = 0L; - - cpuTime_ = 0D; - - wallTime_ = 0D; - - throughput_ = 0D; - - internalGetMutableExtras().clear(); - if (metricsBuilder_ == null) { - metrics_ = java.util.Collections.emptyList(); - } else { - metrics_ = null; - metricsBuilder_.clear(); - } - bitField0_ = (bitField0_ & ~0x00000002); - return this; - } - - @java.lang.Override - public com.google.protobuf.Descriptors.Descriptor - getDescriptorForType() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntry_descriptor; - } - - @java.lang.Override - public org.tensorflow.proto.BenchmarkEntry getDefaultInstanceForType() { - return org.tensorflow.proto.BenchmarkEntry.getDefaultInstance(); - } - - @java.lang.Override - public org.tensorflow.proto.BenchmarkEntry build() { - org.tensorflow.proto.BenchmarkEntry result = buildPartial(); - if (!result.isInitialized()) { - throw newUninitializedMessageException(result); - } - return result; - } - - @java.lang.Override - public org.tensorflow.proto.BenchmarkEntry buildPartial() { - org.tensorflow.proto.BenchmarkEntry result = new org.tensorflow.proto.BenchmarkEntry(this); - int from_bitField0_ = bitField0_; - result.name_ = name_; - result.iters_ = iters_; - result.cpuTime_ = cpuTime_; - result.wallTime_ = wallTime_; - result.throughput_ = throughput_; - result.extras_ = internalGetExtras(); - result.extras_.makeImmutable(); - if (metricsBuilder_ == null) { - if (((bitField0_ & 0x00000002) != 0)) { - metrics_ = java.util.Collections.unmodifiableList(metrics_); - bitField0_ = (bitField0_ & ~0x00000002); - } - result.metrics_ = metrics_; - } else { - result.metrics_ = metricsBuilder_.build(); - } - onBuilt(); - return result; - } - - @java.lang.Override - public Builder clone() { - return super.clone(); - } - @java.lang.Override - public Builder setField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.setField(field, value); - } - @java.lang.Override - public Builder clearField( - com.google.protobuf.Descriptors.FieldDescriptor field) { - return super.clearField(field); - } - @java.lang.Override - public Builder clearOneof( - com.google.protobuf.Descriptors.OneofDescriptor oneof) { - return super.clearOneof(oneof); - } - @java.lang.Override - public Builder setRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - int index, java.lang.Object value) { - return super.setRepeatedField(field, index, value); - } - @java.lang.Override - public Builder addRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.addRepeatedField(field, value); - } - @java.lang.Override - public Builder mergeFrom(com.google.protobuf.Message other) { - if (other instanceof org.tensorflow.proto.BenchmarkEntry) { - return mergeFrom((org.tensorflow.proto.BenchmarkEntry)other); - } else { - super.mergeFrom(other); - return this; - } - } - - public Builder mergeFrom(org.tensorflow.proto.BenchmarkEntry other) { - if (other == org.tensorflow.proto.BenchmarkEntry.getDefaultInstance()) return this; - if (!other.getName().isEmpty()) { - name_ = other.name_; - onChanged(); - } - if (other.getIters() != 0L) { - setIters(other.getIters()); - } - if (other.getCpuTime() != 0D) { - setCpuTime(other.getCpuTime()); - } - if (other.getWallTime() != 0D) { - setWallTime(other.getWallTime()); - } - if (other.getThroughput() != 0D) { - setThroughput(other.getThroughput()); - } - internalGetMutableExtras().mergeFrom( - other.internalGetExtras()); - if (metricsBuilder_ == null) { - if (!other.metrics_.isEmpty()) { - if (metrics_.isEmpty()) { - metrics_ = other.metrics_; - bitField0_ = (bitField0_ & ~0x00000002); - } else { - ensureMetricsIsMutable(); - metrics_.addAll(other.metrics_); - } - onChanged(); - } - } else { - if (!other.metrics_.isEmpty()) { - if (metricsBuilder_.isEmpty()) { - metricsBuilder_.dispose(); - metricsBuilder_ = null; - metrics_ = other.metrics_; - bitField0_ = (bitField0_ & ~0x00000002); - metricsBuilder_ = - com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ? - getMetricsFieldBuilder() : null; - } else { - metricsBuilder_.addAllMessages(other.metrics_); - } - } - } - this.mergeUnknownFields(other.getUnknownFields()); - onChanged(); - return this; - } - - @java.lang.Override - public final boolean isInitialized() { - return true; - } - - @java.lang.Override - public Builder mergeFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - if (extensionRegistry == null) { - throw new java.lang.NullPointerException(); - } - try { - boolean done = false; - while (!done) { - int tag = input.readTag(); - switch (tag) { - case 0: - done = true; - break; - case 10: { - name_ = input.readStringRequireUtf8(); - - break; - } // case 10 - case 16: { - iters_ = input.readInt64(); - - break; - } // case 16 - case 25: { - cpuTime_ = input.readDouble(); - - break; - } // case 25 - case 33: { - wallTime_ = input.readDouble(); - - break; - } // case 33 - case 41: { - throughput_ = input.readDouble(); - - break; - } // case 41 - case 50: { - com.google.protobuf.MapEntry - extras__ = input.readMessage( - ExtrasDefaultEntryHolder.defaultEntry.getParserForType(), extensionRegistry); - internalGetMutableExtras().getMutableMap().put( - extras__.getKey(), extras__.getValue()); - break; - } // case 50 - case 58: { - org.tensorflow.proto.MetricEntry m = - input.readMessage( - org.tensorflow.proto.MetricEntry.parser(), - extensionRegistry); - if (metricsBuilder_ == null) { - ensureMetricsIsMutable(); - metrics_.add(m); - } else { - metricsBuilder_.addMessage(m); - } - break; - } // case 58 - default: { - if (!super.parseUnknownField(input, extensionRegistry, tag)) { - done = true; // was an endgroup tag - } - break; - } // default: - } // switch (tag) - } // while (!done) - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.unwrapIOException(); - } finally { - onChanged(); - } // finally - return this; - } - private int bitField0_; - - private java.lang.Object name_ = ""; - /** - * 
-     * The name of the specific benchmark or test
-     * (e.g. BM_AdjustContrast_gpu_B_W_H)
-     *
- * - * string name = 1; - * @return The name. - */ - public java.lang.String getName() { - java.lang.Object ref = name_; - if (!(ref instanceof java.lang.String)) { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - name_ = s; - return s; - } else { - return (java.lang.String) ref; - } - } - /** - * 
-     * The name of the specific benchmark or test
-     * (e.g. BM_AdjustContrast_gpu_B_W_H)
-     *
- * - * string name = 1; - * @return The bytes for name. - */ - public com.google.protobuf.ByteString - getNameBytes() { - java.lang.Object ref = name_; - if (ref instanceof String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - name_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - /** - * 
-     * The name of the specific benchmark or test
-     * (e.g. BM_AdjustContrast_gpu_B_W_H)
-     *
- * - * string name = 1; - * @param value The name to set. - * @return This builder for chaining. - */ - public Builder setName( - java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - - name_ = value; - onChanged(); - return this; - } - /** - * 
-     * The name of the specific benchmark or test
-     * (e.g. BM_AdjustContrast_gpu_B_W_H)
-     *
- * - * string name = 1; - * @return This builder for chaining. - */ - public Builder clearName() { - - name_ = getDefaultInstance().getName(); - onChanged(); - return this; - } - /** - * 
-     * The name of the specific benchmark or test
-     * (e.g. BM_AdjustContrast_gpu_B_W_H)
-     *
- * - * string name = 1; - * @param value The bytes for name to set. - * @return This builder for chaining. - */ - public Builder setNameBytes( - com.google.protobuf.ByteString value) { - if (value == null) { - throw new NullPointerException(); - } - checkByteStringIsUtf8(value); - - name_ = value; - onChanged(); - return this; - } - - private long iters_ ; - /** - * 
-     * If a benchmark, how many iterations it was run for
-     *
- * - * int64 iters = 2; - * @return The iters. - */ - @java.lang.Override - public long getIters() { - return iters_; - } - /** - * 
-     * If a benchmark, how many iterations it was run for
-     *
- * - * int64 iters = 2; - * @param value The iters to set. - * @return This builder for chaining. - */ - public Builder setIters(long value) { - - iters_ = value; - onChanged(); - return this; - } - /** - * 
-     * If a benchmark, how many iterations it was run for
-     *
- * - * int64 iters = 2; - * @return This builder for chaining. - */ - public Builder clearIters() { - - iters_ = 0L; - onChanged(); - return this; - } - - private double cpuTime_ ; - /** - * 
-     * Total cpu time used for all iterations (in seconds)
-     *
- * - * double cpu_time = 3; - * @return The cpuTime. - */ - @java.lang.Override - public double getCpuTime() { - return cpuTime_; - } - /** - * 
-     * Total cpu time used for all iterations (in seconds)
-     *
- * - * double cpu_time = 3; - * @param value The cpuTime to set. - * @return This builder for chaining. - */ - public Builder setCpuTime(double value) { - - cpuTime_ = value; - onChanged(); - return this; - } - /** - * 
-     * Total cpu time used for all iterations (in seconds)
-     *
- * - * double cpu_time = 3; - * @return This builder for chaining. - */ - public Builder clearCpuTime() { - - cpuTime_ = 0D; - onChanged(); - return this; - } - - private double wallTime_ ; - /** - * 
-     * Total wall time used for all iterations (in seconds)
-     *
- * - * double wall_time = 4; - * @return The wallTime. - */ - @java.lang.Override - public double getWallTime() { - return wallTime_; - } - /** - * 
-     * Total wall time used for all iterations (in seconds)
-     *
- * - * double wall_time = 4; - * @param value The wallTime to set. - * @return This builder for chaining. - */ - public Builder setWallTime(double value) { - - wallTime_ = value; - onChanged(); - return this; - } - /** - * 
-     * Total wall time used for all iterations (in seconds)
-     *
- * - * double wall_time = 4; - * @return This builder for chaining. - */ - public Builder clearWallTime() { - - wallTime_ = 0D; - onChanged(); - return this; - } - - private double throughput_ ; - /** - * 
-     * Throughput (in MB/s)
-     *
- * - * double throughput = 5; - * @return The throughput. - */ - @java.lang.Override - public double getThroughput() { - return throughput_; - } - /** - * 
-     * Throughput (in MB/s)
-     *
- * - * double throughput = 5; - * @param value The throughput to set. - * @return This builder for chaining. - */ - public Builder setThroughput(double value) { - - throughput_ = value; - onChanged(); - return this; - } - /** - * 
-     * Throughput (in MB/s)
-     *
- * - * double throughput = 5; - * @return This builder for chaining. - */ - public Builder clearThroughput() { - - throughput_ = 0D; - onChanged(); - return this; - } - - private com.google.protobuf.MapField< - java.lang.String, org.tensorflow.proto.EntryValue> extras_; - private com.google.protobuf.MapField - internalGetExtras() { - if (extras_ == null) { - return com.google.protobuf.MapField.emptyMapField( - ExtrasDefaultEntryHolder.defaultEntry); - } - return extras_; - } - private com.google.protobuf.MapField - internalGetMutableExtras() { - onChanged();; - if (extras_ == null) { - extras_ = com.google.protobuf.MapField.newMapField( - ExtrasDefaultEntryHolder.defaultEntry); - } - if (!extras_.isMutable()) { - extras_ = extras_.copy(); - } - return extras_; - } - - public int getExtrasCount() { - return internalGetExtras().getMap().size(); - } - /** - * 
-     * Generic map from result key to value.
-     *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - - @java.lang.Override - public boolean containsExtras( - java.lang.String key) { - if (key == null) { throw new NullPointerException("map key"); } - return internalGetExtras().getMap().containsKey(key); - } - /** - * Use {@link #getExtrasMap()} instead. - */ - @java.lang.Override - @java.lang.Deprecated - public java.util.Map getExtras() { - return getExtrasMap(); - } - /** - * 
-     * Generic map from result key to value.
-     *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - @java.lang.Override - - public java.util.Map getExtrasMap() { - return internalGetExtras().getMap(); - } - /** - * 
-     * Generic map from result key to value.
-     *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - @java.lang.Override - - public org.tensorflow.proto.EntryValue getExtrasOrDefault( - java.lang.String key, - org.tensorflow.proto.EntryValue defaultValue) { - if (key == null) { throw new NullPointerException("map key"); } - java.util.Map map = - internalGetExtras().getMap(); - return map.containsKey(key) ? map.get(key) : defaultValue; - } - /** - * 
-     * Generic map from result key to value.
-     *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - @java.lang.Override - - public org.tensorflow.proto.EntryValue getExtrasOrThrow( - java.lang.String key) { - if (key == null) { throw new NullPointerException("map key"); } - java.util.Map map = - internalGetExtras().getMap(); - if (!map.containsKey(key)) { - throw new java.lang.IllegalArgumentException(); - } - return map.get(key); - } - - public Builder clearExtras() { - internalGetMutableExtras().getMutableMap() - .clear(); - return this; - } - /** - * 
-     * Generic map from result key to value.
-     *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - - public Builder removeExtras( - java.lang.String key) { - if (key == null) { throw new NullPointerException("map key"); } - internalGetMutableExtras().getMutableMap() - .remove(key); - return this; - } - /** - * Use alternate mutation accessors instead. - */ - @java.lang.Deprecated - public java.util.Map - getMutableExtras() { - return internalGetMutableExtras().getMutableMap(); - } - /** - * 
-     * Generic map from result key to value.
-     *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - public Builder putExtras( - java.lang.String key, - org.tensorflow.proto.EntryValue value) { - if (key == null) { throw new NullPointerException("map key"); } - if (value == null) { - throw new NullPointerException("map value"); -} - - internalGetMutableExtras().getMutableMap() - .put(key, value); - return this; - } - /** - * 
-     * Generic map from result key to value.
-     *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - - public Builder putAllExtras( - java.util.Map values) { - internalGetMutableExtras().getMutableMap() - .putAll(values); - return this; - } - - private java.util.List metrics_ = - java.util.Collections.emptyList(); - private void ensureMetricsIsMutable() { - if (!((bitField0_ & 0x00000002) != 0)) { - metrics_ = new java.util.ArrayList(metrics_); - bitField0_ |= 0x00000002; - } - } - - private com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.MetricEntry, org.tensorflow.proto.MetricEntry.Builder, org.tensorflow.proto.MetricEntryOrBuilder> metricsBuilder_; - - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public java.util.List getMetricsList() { - if (metricsBuilder_ == null) { - return java.util.Collections.unmodifiableList(metrics_); - } else { - return metricsBuilder_.getMessageList(); - } - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public int getMetricsCount() { - if (metricsBuilder_ == null) { - return metrics_.size(); - } else { - return metricsBuilder_.getCount(); - } - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public org.tensorflow.proto.MetricEntry getMetrics(int index) { - if (metricsBuilder_ == null) { - return metrics_.get(index); - } else { - return metricsBuilder_.getMessage(index); - } - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public Builder setMetrics( - int index, org.tensorflow.proto.MetricEntry value) { - if (metricsBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureMetricsIsMutable(); - metrics_.set(index, value); - onChanged(); - } else { - metricsBuilder_.setMessage(index, value); - } - return this; - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public Builder setMetrics( - int index, org.tensorflow.proto.MetricEntry.Builder builderForValue) { - if (metricsBuilder_ == null) { - ensureMetricsIsMutable(); - metrics_.set(index, builderForValue.build()); - onChanged(); - } else { - metricsBuilder_.setMessage(index, builderForValue.build()); - } - return this; - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public Builder addMetrics(org.tensorflow.proto.MetricEntry value) { - if (metricsBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureMetricsIsMutable(); - metrics_.add(value); - onChanged(); - } else { - metricsBuilder_.addMessage(value); - } - return this; - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public Builder addMetrics( - int index, org.tensorflow.proto.MetricEntry value) { - if (metricsBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureMetricsIsMutable(); - metrics_.add(index, value); - onChanged(); - } else { - metricsBuilder_.addMessage(index, value); - } - return this; - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public Builder addMetrics( - org.tensorflow.proto.MetricEntry.Builder builderForValue) { - if (metricsBuilder_ == null) { - ensureMetricsIsMutable(); - metrics_.add(builderForValue.build()); - onChanged(); - } else { - metricsBuilder_.addMessage(builderForValue.build()); - } - return this; - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public Builder addMetrics( - int index, org.tensorflow.proto.MetricEntry.Builder builderForValue) { - if (metricsBuilder_ == null) { - ensureMetricsIsMutable(); - metrics_.add(index, builderForValue.build()); - onChanged(); - } else { - metricsBuilder_.addMessage(index, builderForValue.build()); - } - return this; - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public Builder addAllMetrics( - java.lang.Iterable values) { - if (metricsBuilder_ == null) { - ensureMetricsIsMutable(); - com.google.protobuf.AbstractMessageLite.Builder.addAll( - values, metrics_); - onChanged(); - } else { - metricsBuilder_.addAllMessages(values); - } - return this; - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public Builder clearMetrics() { - if (metricsBuilder_ == null) { - metrics_ = java.util.Collections.emptyList(); - bitField0_ = (bitField0_ & ~0x00000002); - onChanged(); - } else { - metricsBuilder_.clear(); - } - return this; - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public Builder removeMetrics(int index) { - if (metricsBuilder_ == null) { - ensureMetricsIsMutable(); - metrics_.remove(index); - onChanged(); - } else { - metricsBuilder_.remove(index); - } - return this; - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public org.tensorflow.proto.MetricEntry.Builder getMetricsBuilder( - int index) { - return getMetricsFieldBuilder().getBuilder(index); - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public org.tensorflow.proto.MetricEntryOrBuilder getMetricsOrBuilder( - int index) { - if (metricsBuilder_ == null) { - return metrics_.get(index); } else { - return metricsBuilder_.getMessageOrBuilder(index); - } - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public java.util.List - getMetricsOrBuilderList() { - if (metricsBuilder_ != null) { - return metricsBuilder_.getMessageOrBuilderList(); - } else { - return java.util.Collections.unmodifiableList(metrics_); - } - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public org.tensorflow.proto.MetricEntry.Builder addMetricsBuilder() { - return getMetricsFieldBuilder().addBuilder( - org.tensorflow.proto.MetricEntry.getDefaultInstance()); - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public org.tensorflow.proto.MetricEntry.Builder addMetricsBuilder( - int index) { - return getMetricsFieldBuilder().addBuilder( - index, org.tensorflow.proto.MetricEntry.getDefaultInstance()); - } - /** - * 
-     * Metric name, value and expected range. This can include accuracy metrics
-     * typically used to determine whether the accuracy test has passed
-     *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - public java.util.List - getMetricsBuilderList() { - return getMetricsFieldBuilder().getBuilderList(); - } - private com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.MetricEntry, org.tensorflow.proto.MetricEntry.Builder, org.tensorflow.proto.MetricEntryOrBuilder> - getMetricsFieldBuilder() { - if (metricsBuilder_ == null) { - metricsBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.MetricEntry, org.tensorflow.proto.MetricEntry.Builder, org.tensorflow.proto.MetricEntryOrBuilder>( - metrics_, - ((bitField0_ & 0x00000002) != 0), - getParentForChildren(), - isClean()); - metrics_ = null; - } - return metricsBuilder_; - } - @java.lang.Override - public final Builder setUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.setUnknownFields(unknownFields); - } - - @java.lang.Override - public final Builder mergeUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.mergeUnknownFields(unknownFields); - } - - - // @@protoc_insertion_point(builder_scope:tensorflow.BenchmarkEntry) - } - - // @@protoc_insertion_point(class_scope:tensorflow.BenchmarkEntry) - private static final org.tensorflow.proto.BenchmarkEntry DEFAULT_INSTANCE; - static { - DEFAULT_INSTANCE = new org.tensorflow.proto.BenchmarkEntry(); - } - - public static org.tensorflow.proto.BenchmarkEntry getDefaultInstance() { - return DEFAULT_INSTANCE; - } - - private static final com.google.protobuf.Parser - PARSER = new com.google.protobuf.AbstractParser() { - @java.lang.Override - public BenchmarkEntry parsePartialFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - Builder builder = newBuilder(); - try { - builder.mergeFrom(input, extensionRegistry); - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.setUnfinishedMessage(builder.buildPartial()); - } catch (com.google.protobuf.UninitializedMessageException e) { - throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); - } catch (java.io.IOException e) { - throw new com.google.protobuf.InvalidProtocolBufferException(e) - .setUnfinishedMessage(builder.buildPartial()); - } - return builder.buildPartial(); - } - }; - - public static com.google.protobuf.Parser parser() { - return PARSER; - } - - @java.lang.Override - public com.google.protobuf.Parser getParserForType() { - return PARSER; - } - - @java.lang.Override - public org.tensorflow.proto.BenchmarkEntry getDefaultInstanceForType() { - return DEFAULT_INSTANCE; - } - -} - diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntryOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntryOrBuilder.java deleted file mode 100644 index 476aae9ca10..00000000000 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntryOrBuilder.java +++ /dev/null @@ -1,176 +0,0 @@ -// Generated by the protocol buffer compiler. DO NOT EDIT! -// source: tsl/protobuf/test_log.proto - -package org.tensorflow.proto; - -public interface BenchmarkEntryOrBuilder extends - // @@protoc_insertion_point(interface_extends:tensorflow.BenchmarkEntry) - com.google.protobuf.MessageOrBuilder { - - /** - * 
-   * The name of the specific benchmark or test
-   * (e.g. BM_AdjustContrast_gpu_B_W_H)
-   *
- * - * string name = 1; - * @return The name. - */ - java.lang.String getName(); - /** - * 
-   * The name of the specific benchmark or test
-   * (e.g. BM_AdjustContrast_gpu_B_W_H)
-   *
- * - * string name = 1; - * @return The bytes for name. - */ - com.google.protobuf.ByteString - getNameBytes(); - - /** - * 
-   * If a benchmark, how many iterations it was run for
-   *
- * - * int64 iters = 2; - * @return The iters. - */ - long getIters(); - - /** - * 
-   * Total cpu time used for all iterations (in seconds)
-   *
- * - * double cpu_time = 3; - * @return The cpuTime. - */ - double getCpuTime(); - - /** - * 
-   * Total wall time used for all iterations (in seconds)
-   *
- * - * double wall_time = 4; - * @return The wallTime. - */ - double getWallTime(); - - /** - * 
-   * Throughput (in MB/s)
-   *
- * - * double throughput = 5; - * @return The throughput. - */ - double getThroughput(); - - /** - * 
-   * Generic map from result key to value.
-   *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - int getExtrasCount(); - /** - * 
-   * Generic map from result key to value.
-   *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - boolean containsExtras( - java.lang.String key); - /** - * Use {@link #getExtrasMap()} instead. - */ - @java.lang.Deprecated - java.util.Map - getExtras(); - /** - * 
-   * Generic map from result key to value.
-   *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - java.util.Map - getExtrasMap(); - /** - * 
-   * Generic map from result key to value.
-   *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - - /* nullable */ -org.tensorflow.proto.EntryValue getExtrasOrDefault( - java.lang.String key, - /* nullable */ -org.tensorflow.proto.EntryValue defaultValue); - /** - * 
-   * Generic map from result key to value.
-   *
- * - * map<string, .tensorflow.EntryValue> extras = 6; - */ - - org.tensorflow.proto.EntryValue getExtrasOrThrow( - java.lang.String key); - - /** - * 
-   * Metric name, value and expected range. This can include accuracy metrics
-   * typically used to determine whether the accuracy test has passed
-   *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - java.util.List - getMetricsList(); - /** - * 
-   * Metric name, value and expected range. This can include accuracy metrics
-   * typically used to determine whether the accuracy test has passed
-   *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - org.tensorflow.proto.MetricEntry getMetrics(int index); - /** - * 
-   * Metric name, value and expected range. This can include accuracy metrics
-   * typically used to determine whether the accuracy test has passed
-   *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - int getMetricsCount(); - /** - * 
-   * Metric name, value and expected range. This can include accuracy metrics
-   * typically used to determine whether the accuracy test has passed
-   *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - java.util.List - getMetricsOrBuilderList(); - /** - * 
-   * Metric name, value and expected range. This can include accuracy metrics
-   * typically used to determine whether the accuracy test has passed
-   *
- * - * repeated .tensorflow.MetricEntry metrics = 7; - */ - org.tensorflow.proto.MetricEntryOrBuilder getMetricsOrBuilder( - int index); -} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BfcMemoryMap.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BfcMemoryMap.java deleted file mode 100644 index fad0c98b837..00000000000 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BfcMemoryMap.java +++ /dev/null @@ -1,5154 +0,0 @@ -// Generated by the protocol buffer compiler. DO NOT EDIT! -// source: tsl/protobuf/bfc_memory_map.proto - -package org.tensorflow.proto; - -public final class BfcMemoryMap { - private BfcMemoryMap() {} - public static void registerAllExtensions( - com.google.protobuf.ExtensionRegistryLite registry) { - } - - public static void registerAllExtensions( - com.google.protobuf.ExtensionRegistry registry) { - registerAllExtensions( - (com.google.protobuf.ExtensionRegistryLite) registry); - } - public interface MemAllocatorStatsOrBuilder extends - // @@protoc_insertion_point(interface_extends:tensorflow.MemAllocatorStats) - com.google.protobuf.MessageOrBuilder { - - /** - * int64 num_allocs = 1; - * @return The numAllocs. - */ - long getNumAllocs(); - - /** - * int64 bytes_in_use = 2; - * @return The bytesInUse. - */ - long getBytesInUse(); - - /** - * int64 peak_bytes_in_use = 3; - * @return The peakBytesInUse. - */ - long getPeakBytesInUse(); - - /** - * int64 largest_alloc_size = 4; - * @return The largestAllocSize. - */ - long getLargestAllocSize(); - - /** - * float fragmentation_metric = 5; - * @return The fragmentationMetric. - */ - float getFragmentationMetric(); - } - /** - * 
-   * Some of the data from AllocatorStats
-   *
- * - * Protobuf type {@code tensorflow.MemAllocatorStats} - */ - public static final class MemAllocatorStats extends - com.google.protobuf.GeneratedMessageV3 implements - // @@protoc_insertion_point(message_implements:tensorflow.MemAllocatorStats) - MemAllocatorStatsOrBuilder { - private static final long serialVersionUID = 0L; - // Use MemAllocatorStats.newBuilder() to construct. - private MemAllocatorStats(com.google.protobuf.GeneratedMessageV3.Builder builder) { - super(builder); - } - private MemAllocatorStats() { - } - - @java.lang.Override - @SuppressWarnings({"unused"}) - protected java.lang.Object newInstance( - UnusedPrivateParameter unused) { - return new MemAllocatorStats(); - } - - @java.lang.Override - public final com.google.protobuf.UnknownFieldSet - getUnknownFields() { - return this.unknownFields; - } - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemAllocatorStats_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemAllocatorStats_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.class, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.Builder.class); - } - - public static final int NUM_ALLOCS_FIELD_NUMBER = 1; - private long numAllocs_; - /** - * int64 num_allocs = 1; - * @return The numAllocs. - */ - @java.lang.Override - public long getNumAllocs() { - return numAllocs_; - } - - public static final int BYTES_IN_USE_FIELD_NUMBER = 2; - private long bytesInUse_; - /** - * int64 bytes_in_use = 2; - * @return The bytesInUse. - */ - @java.lang.Override - public long getBytesInUse() { - return bytesInUse_; - } - - public static final int PEAK_BYTES_IN_USE_FIELD_NUMBER = 3; - private long peakBytesInUse_; - /** - * int64 peak_bytes_in_use = 3; - * @return The peakBytesInUse. - */ - @java.lang.Override - public long getPeakBytesInUse() { - return peakBytesInUse_; - } - - public static final int LARGEST_ALLOC_SIZE_FIELD_NUMBER = 4; - private long largestAllocSize_; - /** - * int64 largest_alloc_size = 4; - * @return The largestAllocSize. - */ - @java.lang.Override - public long getLargestAllocSize() { - return largestAllocSize_; - } - - public static final int FRAGMENTATION_METRIC_FIELD_NUMBER = 5; - private float fragmentationMetric_; - /** - * float fragmentation_metric = 5; - * @return The fragmentationMetric. - */ - @java.lang.Override - public float getFragmentationMetric() { - return fragmentationMetric_; - } - - private byte memoizedIsInitialized = -1; - @java.lang.Override - public final boolean isInitialized() { - byte isInitialized = memoizedIsInitialized; - if (isInitialized == 1) return true; - if (isInitialized == 0) return false; - - memoizedIsInitialized = 1; - return true; - } - - @java.lang.Override - public void writeTo(com.google.protobuf.CodedOutputStream output) - throws java.io.IOException { - if (numAllocs_ != 0L) { - output.writeInt64(1, numAllocs_); - } - if (bytesInUse_ != 0L) { - output.writeInt64(2, bytesInUse_); - } - if (peakBytesInUse_ != 0L) { - output.writeInt64(3, peakBytesInUse_); - } - if (largestAllocSize_ != 0L) { - output.writeInt64(4, largestAllocSize_); - } - if (java.lang.Float.floatToRawIntBits(fragmentationMetric_) != 0) { - output.writeFloat(5, fragmentationMetric_); - } - getUnknownFields().writeTo(output); - } - - @java.lang.Override - public int getSerializedSize() { - int size = memoizedSize; - if (size != -1) return size; - - size = 0; - if (numAllocs_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(1, numAllocs_); - } - if (bytesInUse_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(2, bytesInUse_); - } - if (peakBytesInUse_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(3, peakBytesInUse_); - } - if (largestAllocSize_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(4, largestAllocSize_); - } - if (java.lang.Float.floatToRawIntBits(fragmentationMetric_) != 0) { - size += com.google.protobuf.CodedOutputStream - .computeFloatSize(5, fragmentationMetric_); - } - size += getUnknownFields().getSerializedSize(); - memoizedSize = size; - return size; - } - - @java.lang.Override - public boolean equals(final java.lang.Object obj) { - if (obj == this) { - return true; - } - if (!(obj instanceof org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats)) { - return super.equals(obj); - } - org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats other = (org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats) obj; - - if (getNumAllocs() - != other.getNumAllocs()) return false; - if (getBytesInUse() - != other.getBytesInUse()) return false; - if (getPeakBytesInUse() - != other.getPeakBytesInUse()) return false; - if (getLargestAllocSize() - != other.getLargestAllocSize()) return false; - if (java.lang.Float.floatToIntBits(getFragmentationMetric()) - != java.lang.Float.floatToIntBits( - other.getFragmentationMetric())) return false; - if (!getUnknownFields().equals(other.getUnknownFields())) return false; - return true; - } - - @java.lang.Override - public int hashCode() { - if (memoizedHashCode != 0) { - return memoizedHashCode; - } - int hash = 41; - hash = (19 * hash) + getDescriptor().hashCode(); - hash = (37 * hash) + NUM_ALLOCS_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getNumAllocs()); - hash = (37 * hash) + BYTES_IN_USE_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getBytesInUse()); - hash = (37 * hash) + PEAK_BYTES_IN_USE_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getPeakBytesInUse()); - hash = (37 * hash) + LARGEST_ALLOC_SIZE_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getLargestAllocSize()); - hash = (37 * hash) + FRAGMENTATION_METRIC_FIELD_NUMBER; - hash = (53 * hash) + java.lang.Float.floatToIntBits( - getFragmentationMetric()); - hash = (29 * hash) + getUnknownFields().hashCode(); - memoizedHashCode = hash; - return hash; - } - - public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( - java.nio.ByteBuffer data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( - java.nio.ByteBuffer data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( - com.google.protobuf.ByteString data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( - com.google.protobuf.ByteString data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom(byte[] data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( - byte[] data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseDelimitedFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseDelimitedFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( - com.google.protobuf.CodedInputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - - @java.lang.Override - public Builder newBuilderForType() { return newBuilder(); } - public static Builder newBuilder() { - return DEFAULT_INSTANCE.toBuilder(); - } - public static Builder newBuilder(org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats prototype) { - return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); - } - @java.lang.Override - public Builder toBuilder() { - return this == DEFAULT_INSTANCE - ? new Builder() : new Builder().mergeFrom(this); - } - - @java.lang.Override - protected Builder newBuilderForType( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - Builder builder = new Builder(parent); - return builder; - } - /** - * 
-     * Some of the data from AllocatorStats
-     *
- * - * Protobuf type {@code tensorflow.MemAllocatorStats} - */ - public static final class Builder extends - com.google.protobuf.GeneratedMessageV3.Builder implements - // @@protoc_insertion_point(builder_implements:tensorflow.MemAllocatorStats) - org.tensorflow.proto.BfcMemoryMap.MemAllocatorStatsOrBuilder { - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemAllocatorStats_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemAllocatorStats_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.class, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.Builder.class); - } - - // Construct using org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.newBuilder() - private Builder() { - - } - - private Builder( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - super(parent); - - } - @java.lang.Override - public Builder clear() { - super.clear(); - numAllocs_ = 0L; - - bytesInUse_ = 0L; - - peakBytesInUse_ = 0L; - - largestAllocSize_ = 0L; - - fragmentationMetric_ = 0F; - - return this; - } - - @java.lang.Override - public com.google.protobuf.Descriptors.Descriptor - getDescriptorForType() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemAllocatorStats_descriptor; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats getDefaultInstanceForType() { - return org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.getDefaultInstance(); - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats build() { - org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats result = buildPartial(); - if (!result.isInitialized()) { - throw newUninitializedMessageException(result); - } - return result; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats buildPartial() { - org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats result = new org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats(this); - result.numAllocs_ = numAllocs_; - result.bytesInUse_ = bytesInUse_; - result.peakBytesInUse_ = peakBytesInUse_; - result.largestAllocSize_ = largestAllocSize_; - result.fragmentationMetric_ = fragmentationMetric_; - onBuilt(); - return result; - } - - @java.lang.Override - public Builder clone() { - return super.clone(); - } - @java.lang.Override - public Builder setField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.setField(field, value); - } - @java.lang.Override - public Builder clearField( - com.google.protobuf.Descriptors.FieldDescriptor field) { - return super.clearField(field); - } - @java.lang.Override - public Builder clearOneof( - com.google.protobuf.Descriptors.OneofDescriptor oneof) { - return super.clearOneof(oneof); - } - @java.lang.Override - public Builder setRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - int index, java.lang.Object value) { - return super.setRepeatedField(field, index, value); - } - @java.lang.Override - public Builder addRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.addRepeatedField(field, value); - } - @java.lang.Override - public Builder mergeFrom(com.google.protobuf.Message other) { - if (other instanceof org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats) { - return mergeFrom((org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats)other); - } else { - super.mergeFrom(other); - return this; - } - } - - public Builder mergeFrom(org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats other) { - if (other == org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.getDefaultInstance()) return this; - if (other.getNumAllocs() != 0L) { - setNumAllocs(other.getNumAllocs()); - } - if (other.getBytesInUse() != 0L) { - setBytesInUse(other.getBytesInUse()); - } - if (other.getPeakBytesInUse() != 0L) { - setPeakBytesInUse(other.getPeakBytesInUse()); - } - if (other.getLargestAllocSize() != 0L) { - setLargestAllocSize(other.getLargestAllocSize()); - } - if (other.getFragmentationMetric() != 0F) { - setFragmentationMetric(other.getFragmentationMetric()); - } - this.mergeUnknownFields(other.getUnknownFields()); - onChanged(); - return this; - } - - @java.lang.Override - public final boolean isInitialized() { - return true; - } - - @java.lang.Override - public Builder mergeFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - if (extensionRegistry == null) { - throw new java.lang.NullPointerException(); - } - try { - boolean done = false; - while (!done) { - int tag = input.readTag(); - switch (tag) { - case 0: - done = true; - break; - case 8: { - numAllocs_ = input.readInt64(); - - break; - } // case 8 - case 16: { - bytesInUse_ = input.readInt64(); - - break; - } // case 16 - case 24: { - peakBytesInUse_ = input.readInt64(); - - break; - } // case 24 - case 32: { - largestAllocSize_ = input.readInt64(); - - break; - } // case 32 - case 45: { - fragmentationMetric_ = input.readFloat(); - - break; - } // case 45 - default: { - if (!super.parseUnknownField(input, extensionRegistry, tag)) { - done = true; // was an endgroup tag - } - break; - } // default: - } // switch (tag) - } // while (!done) - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.unwrapIOException(); - } finally { - onChanged(); - } // finally - return this; - } - - private long numAllocs_ ; - /** - * int64 num_allocs = 1; - * @return The numAllocs. - */ - @java.lang.Override - public long getNumAllocs() { - return numAllocs_; - } - /** - * int64 num_allocs = 1; - * @param value The numAllocs to set. - * @return This builder for chaining. - */ - public Builder setNumAllocs(long value) { - - numAllocs_ = value; - onChanged(); - return this; - } - /** - * int64 num_allocs = 1; - * @return This builder for chaining. - */ - public Builder clearNumAllocs() { - - numAllocs_ = 0L; - onChanged(); - return this; - } - - private long bytesInUse_ ; - /** - * int64 bytes_in_use = 2; - * @return The bytesInUse. - */ - @java.lang.Override - public long getBytesInUse() { - return bytesInUse_; - } - /** - * int64 bytes_in_use = 2; - * @param value The bytesInUse to set. - * @return This builder for chaining. - */ - public Builder setBytesInUse(long value) { - - bytesInUse_ = value; - onChanged(); - return this; - } - /** - * int64 bytes_in_use = 2; - * @return This builder for chaining. - */ - public Builder clearBytesInUse() { - - bytesInUse_ = 0L; - onChanged(); - return this; - } - - private long peakBytesInUse_ ; - /** - * int64 peak_bytes_in_use = 3; - * @return The peakBytesInUse. - */ - @java.lang.Override - public long getPeakBytesInUse() { - return peakBytesInUse_; - } - /** - * int64 peak_bytes_in_use = 3; - * @param value The peakBytesInUse to set. - * @return This builder for chaining. - */ - public Builder setPeakBytesInUse(long value) { - - peakBytesInUse_ = value; - onChanged(); - return this; - } - /** - * int64 peak_bytes_in_use = 3; - * @return This builder for chaining. - */ - public Builder clearPeakBytesInUse() { - - peakBytesInUse_ = 0L; - onChanged(); - return this; - } - - private long largestAllocSize_ ; - /** - * int64 largest_alloc_size = 4; - * @return The largestAllocSize. - */ - @java.lang.Override - public long getLargestAllocSize() { - return largestAllocSize_; - } - /** - * int64 largest_alloc_size = 4; - * @param value The largestAllocSize to set. - * @return This builder for chaining. - */ - public Builder setLargestAllocSize(long value) { - - largestAllocSize_ = value; - onChanged(); - return this; - } - /** - * int64 largest_alloc_size = 4; - * @return This builder for chaining. - */ - public Builder clearLargestAllocSize() { - - largestAllocSize_ = 0L; - onChanged(); - return this; - } - - private float fragmentationMetric_ ; - /** - * float fragmentation_metric = 5; - * @return The fragmentationMetric. - */ - @java.lang.Override - public float getFragmentationMetric() { - return fragmentationMetric_; - } - /** - * float fragmentation_metric = 5; - * @param value The fragmentationMetric to set. - * @return This builder for chaining. - */ - public Builder setFragmentationMetric(float value) { - - fragmentationMetric_ = value; - onChanged(); - return this; - } - /** - * float fragmentation_metric = 5; - * @return This builder for chaining. - */ - public Builder clearFragmentationMetric() { - - fragmentationMetric_ = 0F; - onChanged(); - return this; - } - @java.lang.Override - public final Builder setUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.setUnknownFields(unknownFields); - } - - @java.lang.Override - public final Builder mergeUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.mergeUnknownFields(unknownFields); - } - - - // @@protoc_insertion_point(builder_scope:tensorflow.MemAllocatorStats) - } - - // @@protoc_insertion_point(class_scope:tensorflow.MemAllocatorStats) - private static final org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats DEFAULT_INSTANCE; - static { - DEFAULT_INSTANCE = new org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats(); - } - - public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats getDefaultInstance() { - return DEFAULT_INSTANCE; - } - - private static final com.google.protobuf.Parser - PARSER = new com.google.protobuf.AbstractParser() { - @java.lang.Override - public MemAllocatorStats parsePartialFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - Builder builder = newBuilder(); - try { - builder.mergeFrom(input, extensionRegistry); - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.setUnfinishedMessage(builder.buildPartial()); - } catch (com.google.protobuf.UninitializedMessageException e) { - throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); - } catch (java.io.IOException e) { - throw new com.google.protobuf.InvalidProtocolBufferException(e) - .setUnfinishedMessage(builder.buildPartial()); - } - return builder.buildPartial(); - } - }; - - public static com.google.protobuf.Parser parser() { - return PARSER; - } - - @java.lang.Override - public com.google.protobuf.Parser getParserForType() { - return PARSER; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats getDefaultInstanceForType() { - return DEFAULT_INSTANCE; - } - - } - - public interface MemChunkOrBuilder extends - // @@protoc_insertion_point(interface_extends:tensorflow.MemChunk) - com.google.protobuf.MessageOrBuilder { - - /** - * uint64 address = 1; - * @return The address. - */ - long getAddress(); - - /** - * int64 size = 2; - * @return The size. - */ - long getSize(); - - /** - * int64 requested_size = 3; - * @return The requestedSize. - */ - long getRequestedSize(); - - /** - * int32 bin = 4; - * @return The bin. - */ - int getBin(); - - /** - * string op_name = 5; - * @return The opName. - */ - java.lang.String getOpName(); - /** - * string op_name = 5; - * @return The bytes for opName. - */ - com.google.protobuf.ByteString - getOpNameBytes(); - - /** - * uint64 freed_at_count = 6; - * @return The freedAtCount. - */ - long getFreedAtCount(); - - /** - * uint64 action_count = 7; - * @return The actionCount. - */ - long getActionCount(); - - /** - * bool in_use = 8; - * @return The inUse. - */ - boolean getInUse(); - - /** - * uint64 step_id = 9; - * @return The stepId. - */ - long getStepId(); - } - /** - * Protobuf type {@code tensorflow.MemChunk} - */ - public static final class MemChunk extends - com.google.protobuf.GeneratedMessageV3 implements - // @@protoc_insertion_point(message_implements:tensorflow.MemChunk) - MemChunkOrBuilder { - private static final long serialVersionUID = 0L; - // Use MemChunk.newBuilder() to construct. - private MemChunk(com.google.protobuf.GeneratedMessageV3.Builder builder) { - super(builder); - } - private MemChunk() { - opName_ = ""; - } - - @java.lang.Override - @SuppressWarnings({"unused"}) - protected java.lang.Object newInstance( - UnusedPrivateParameter unused) { - return new MemChunk(); - } - - @java.lang.Override - public final com.google.protobuf.UnknownFieldSet - getUnknownFields() { - return this.unknownFields; - } - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemChunk_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemChunk_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BfcMemoryMap.MemChunk.class, org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder.class); - } - - public static final int ADDRESS_FIELD_NUMBER = 1; - private long address_; - /** - * uint64 address = 1; - * @return The address. - */ - @java.lang.Override - public long getAddress() { - return address_; - } - - public static final int SIZE_FIELD_NUMBER = 2; - private long size_; - /** - * int64 size = 2; - * @return The size. - */ - @java.lang.Override - public long getSize() { - return size_; - } - - public static final int REQUESTED_SIZE_FIELD_NUMBER = 3; - private long requestedSize_; - /** - * int64 requested_size = 3; - * @return The requestedSize. - */ - @java.lang.Override - public long getRequestedSize() { - return requestedSize_; - } - - public static final int BIN_FIELD_NUMBER = 4; - private int bin_; - /** - * int32 bin = 4; - * @return The bin. - */ - @java.lang.Override - public int getBin() { - return bin_; - } - - public static final int OP_NAME_FIELD_NUMBER = 5; - private volatile java.lang.Object opName_; - /** - * string op_name = 5; - * @return The opName. - */ - @java.lang.Override - public java.lang.String getOpName() { - java.lang.Object ref = opName_; - if (ref instanceof java.lang.String) { - return (java.lang.String) ref; - } else { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - opName_ = s; - return s; - } - } - /** - * string op_name = 5; - * @return The bytes for opName. - */ - @java.lang.Override - public com.google.protobuf.ByteString - getOpNameBytes() { - java.lang.Object ref = opName_; - if (ref instanceof java.lang.String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - opName_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - - public static final int FREED_AT_COUNT_FIELD_NUMBER = 6; - private long freedAtCount_; - /** - * uint64 freed_at_count = 6; - * @return The freedAtCount. - */ - @java.lang.Override - public long getFreedAtCount() { - return freedAtCount_; - } - - public static final int ACTION_COUNT_FIELD_NUMBER = 7; - private long actionCount_; - /** - * uint64 action_count = 7; - * @return The actionCount. - */ - @java.lang.Override - public long getActionCount() { - return actionCount_; - } - - public static final int IN_USE_FIELD_NUMBER = 8; - private boolean inUse_; - /** - * bool in_use = 8; - * @return The inUse. - */ - @java.lang.Override - public boolean getInUse() { - return inUse_; - } - - public static final int STEP_ID_FIELD_NUMBER = 9; - private long stepId_; - /** - * uint64 step_id = 9; - * @return The stepId. - */ - @java.lang.Override - public long getStepId() { - return stepId_; - } - - private byte memoizedIsInitialized = -1; - @java.lang.Override - public final boolean isInitialized() { - byte isInitialized = memoizedIsInitialized; - if (isInitialized == 1) return true; - if (isInitialized == 0) return false; - - memoizedIsInitialized = 1; - return true; - } - - @java.lang.Override - public void writeTo(com.google.protobuf.CodedOutputStream output) - throws java.io.IOException { - if (address_ != 0L) { - output.writeUInt64(1, address_); - } - if (size_ != 0L) { - output.writeInt64(2, size_); - } - if (requestedSize_ != 0L) { - output.writeInt64(3, requestedSize_); - } - if (bin_ != 0) { - output.writeInt32(4, bin_); - } - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(opName_)) { - com.google.protobuf.GeneratedMessageV3.writeString(output, 5, opName_); - } - if (freedAtCount_ != 0L) { - output.writeUInt64(6, freedAtCount_); - } - if (actionCount_ != 0L) { - output.writeUInt64(7, actionCount_); - } - if (inUse_ != false) { - output.writeBool(8, inUse_); - } - if (stepId_ != 0L) { - output.writeUInt64(9, stepId_); - } - getUnknownFields().writeTo(output); - } - - @java.lang.Override - public int getSerializedSize() { - int size = memoizedSize; - if (size != -1) return size; - - size = 0; - if (address_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeUInt64Size(1, address_); - } - if (size_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(2, size_); - } - if (requestedSize_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(3, requestedSize_); - } - if (bin_ != 0) { - size += com.google.protobuf.CodedOutputStream - .computeInt32Size(4, bin_); - } - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(opName_)) { - size += com.google.protobuf.GeneratedMessageV3.computeStringSize(5, opName_); - } - if (freedAtCount_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeUInt64Size(6, freedAtCount_); - } - if (actionCount_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeUInt64Size(7, actionCount_); - } - if (inUse_ != false) { - size += com.google.protobuf.CodedOutputStream - .computeBoolSize(8, inUse_); - } - if (stepId_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeUInt64Size(9, stepId_); - } - size += getUnknownFields().getSerializedSize(); - memoizedSize = size; - return size; - } - - @java.lang.Override - public boolean equals(final java.lang.Object obj) { - if (obj == this) { - return true; - } - if (!(obj instanceof org.tensorflow.proto.BfcMemoryMap.MemChunk)) { - return super.equals(obj); - } - org.tensorflow.proto.BfcMemoryMap.MemChunk other = (org.tensorflow.proto.BfcMemoryMap.MemChunk) obj; - - if (getAddress() - != other.getAddress()) return false; - if (getSize() - != other.getSize()) return false; - if (getRequestedSize() - != other.getRequestedSize()) return false; - if (getBin() - != other.getBin()) return false; - if (!getOpName() - .equals(other.getOpName())) return false; - if (getFreedAtCount() - != other.getFreedAtCount()) return false; - if (getActionCount() - != other.getActionCount()) return false; - if (getInUse() - != other.getInUse()) return false; - if (getStepId() - != other.getStepId()) return false; - if (!getUnknownFields().equals(other.getUnknownFields())) return false; - return true; - } - - @java.lang.Override - public int hashCode() { - if (memoizedHashCode != 0) { - return memoizedHashCode; - } - int hash = 41; - hash = (19 * hash) + getDescriptor().hashCode(); - hash = (37 * hash) + ADDRESS_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getAddress()); - hash = (37 * hash) + SIZE_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getSize()); - hash = (37 * hash) + REQUESTED_SIZE_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getRequestedSize()); - hash = (37 * hash) + BIN_FIELD_NUMBER; - hash = (53 * hash) + getBin(); - hash = (37 * hash) + OP_NAME_FIELD_NUMBER; - hash = (53 * hash) + getOpName().hashCode(); - hash = (37 * hash) + FREED_AT_COUNT_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getFreedAtCount()); - hash = (37 * hash) + ACTION_COUNT_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getActionCount()); - hash = (37 * hash) + IN_USE_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashBoolean( - getInUse()); - hash = (37 * hash) + STEP_ID_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getStepId()); - hash = (29 * hash) + getUnknownFields().hashCode(); - memoizedHashCode = hash; - return hash; - } - - public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( - java.nio.ByteBuffer data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( - java.nio.ByteBuffer data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( - com.google.protobuf.ByteString data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( - com.google.protobuf.ByteString data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom(byte[] data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( - byte[] data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseDelimitedFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseDelimitedFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( - com.google.protobuf.CodedInputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - - @java.lang.Override - public Builder newBuilderForType() { return newBuilder(); } - public static Builder newBuilder() { - return DEFAULT_INSTANCE.toBuilder(); - } - public static Builder newBuilder(org.tensorflow.proto.BfcMemoryMap.MemChunk prototype) { - return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); - } - @java.lang.Override - public Builder toBuilder() { - return this == DEFAULT_INSTANCE - ? new Builder() : new Builder().mergeFrom(this); - } - - @java.lang.Override - protected Builder newBuilderForType( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - Builder builder = new Builder(parent); - return builder; - } - /** - * Protobuf type {@code tensorflow.MemChunk} - */ - public static final class Builder extends - com.google.protobuf.GeneratedMessageV3.Builder implements - // @@protoc_insertion_point(builder_implements:tensorflow.MemChunk) - org.tensorflow.proto.BfcMemoryMap.MemChunkOrBuilder { - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemChunk_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemChunk_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BfcMemoryMap.MemChunk.class, org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder.class); - } - - // Construct using org.tensorflow.proto.BfcMemoryMap.MemChunk.newBuilder() - private Builder() { - - } - - private Builder( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - super(parent); - - } - @java.lang.Override - public Builder clear() { - super.clear(); - address_ = 0L; - - size_ = 0L; - - requestedSize_ = 0L; - - bin_ = 0; - - opName_ = ""; - - freedAtCount_ = 0L; - - actionCount_ = 0L; - - inUse_ = false; - - stepId_ = 0L; - - return this; - } - - @java.lang.Override - public com.google.protobuf.Descriptors.Descriptor - getDescriptorForType() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemChunk_descriptor; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemChunk getDefaultInstanceForType() { - return org.tensorflow.proto.BfcMemoryMap.MemChunk.getDefaultInstance(); - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemChunk build() { - org.tensorflow.proto.BfcMemoryMap.MemChunk result = buildPartial(); - if (!result.isInitialized()) { - throw newUninitializedMessageException(result); - } - return result; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemChunk buildPartial() { - org.tensorflow.proto.BfcMemoryMap.MemChunk result = new org.tensorflow.proto.BfcMemoryMap.MemChunk(this); - result.address_ = address_; - result.size_ = size_; - result.requestedSize_ = requestedSize_; - result.bin_ = bin_; - result.opName_ = opName_; - result.freedAtCount_ = freedAtCount_; - result.actionCount_ = actionCount_; - result.inUse_ = inUse_; - result.stepId_ = stepId_; - onBuilt(); - return result; - } - - @java.lang.Override - public Builder clone() { - return super.clone(); - } - @java.lang.Override - public Builder setField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.setField(field, value); - } - @java.lang.Override - public Builder clearField( - com.google.protobuf.Descriptors.FieldDescriptor field) { - return super.clearField(field); - } - @java.lang.Override - public Builder clearOneof( - com.google.protobuf.Descriptors.OneofDescriptor oneof) { - return super.clearOneof(oneof); - } - @java.lang.Override - public Builder setRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - int index, java.lang.Object value) { - return super.setRepeatedField(field, index, value); - } - @java.lang.Override - public Builder addRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.addRepeatedField(field, value); - } - @java.lang.Override - public Builder mergeFrom(com.google.protobuf.Message other) { - if (other instanceof org.tensorflow.proto.BfcMemoryMap.MemChunk) { - return mergeFrom((org.tensorflow.proto.BfcMemoryMap.MemChunk)other); - } else { - super.mergeFrom(other); - return this; - } - } - - public Builder mergeFrom(org.tensorflow.proto.BfcMemoryMap.MemChunk other) { - if (other == org.tensorflow.proto.BfcMemoryMap.MemChunk.getDefaultInstance()) return this; - if (other.getAddress() != 0L) { - setAddress(other.getAddress()); - } - if (other.getSize() != 0L) { - setSize(other.getSize()); - } - if (other.getRequestedSize() != 0L) { - setRequestedSize(other.getRequestedSize()); - } - if (other.getBin() != 0) { - setBin(other.getBin()); - } - if (!other.getOpName().isEmpty()) { - opName_ = other.opName_; - onChanged(); - } - if (other.getFreedAtCount() != 0L) { - setFreedAtCount(other.getFreedAtCount()); - } - if (other.getActionCount() != 0L) { - setActionCount(other.getActionCount()); - } - if (other.getInUse() != false) { - setInUse(other.getInUse()); - } - if (other.getStepId() != 0L) { - setStepId(other.getStepId()); - } - this.mergeUnknownFields(other.getUnknownFields()); - onChanged(); - return this; - } - - @java.lang.Override - public final boolean isInitialized() { - return true; - } - - @java.lang.Override - public Builder mergeFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - if (extensionRegistry == null) { - throw new java.lang.NullPointerException(); - } - try { - boolean done = false; - while (!done) { - int tag = input.readTag(); - switch (tag) { - case 0: - done = true; - break; - case 8: { - address_ = input.readUInt64(); - - break; - } // case 8 - case 16: { - size_ = input.readInt64(); - - break; - } // case 16 - case 24: { - requestedSize_ = input.readInt64(); - - break; - } // case 24 - case 32: { - bin_ = input.readInt32(); - - break; - } // case 32 - case 42: { - opName_ = input.readStringRequireUtf8(); - - break; - } // case 42 - case 48: { - freedAtCount_ = input.readUInt64(); - - break; - } // case 48 - case 56: { - actionCount_ = input.readUInt64(); - - break; - } // case 56 - case 64: { - inUse_ = input.readBool(); - - break; - } // case 64 - case 72: { - stepId_ = input.readUInt64(); - - break; - } // case 72 - default: { - if (!super.parseUnknownField(input, extensionRegistry, tag)) { - done = true; // was an endgroup tag - } - break; - } // default: - } // switch (tag) - } // while (!done) - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.unwrapIOException(); - } finally { - onChanged(); - } // finally - return this; - } - - private long address_ ; - /** - * uint64 address = 1; - * @return The address. - */ - @java.lang.Override - public long getAddress() { - return address_; - } - /** - * uint64 address = 1; - * @param value The address to set. - * @return This builder for chaining. - */ - public Builder setAddress(long value) { - - address_ = value; - onChanged(); - return this; - } - /** - * uint64 address = 1; - * @return This builder for chaining. - */ - public Builder clearAddress() { - - address_ = 0L; - onChanged(); - return this; - } - - private long size_ ; - /** - * int64 size = 2; - * @return The size. - */ - @java.lang.Override - public long getSize() { - return size_; - } - /** - * int64 size = 2; - * @param value The size to set. - * @return This builder for chaining. - */ - public Builder setSize(long value) { - - size_ = value; - onChanged(); - return this; - } - /** - * int64 size = 2; - * @return This builder for chaining. - */ - public Builder clearSize() { - - size_ = 0L; - onChanged(); - return this; - } - - private long requestedSize_ ; - /** - * int64 requested_size = 3; - * @return The requestedSize. - */ - @java.lang.Override - public long getRequestedSize() { - return requestedSize_; - } - /** - * int64 requested_size = 3; - * @param value The requestedSize to set. - * @return This builder for chaining. - */ - public Builder setRequestedSize(long value) { - - requestedSize_ = value; - onChanged(); - return this; - } - /** - * int64 requested_size = 3; - * @return This builder for chaining. - */ - public Builder clearRequestedSize() { - - requestedSize_ = 0L; - onChanged(); - return this; - } - - private int bin_ ; - /** - * int32 bin = 4; - * @return The bin. - */ - @java.lang.Override - public int getBin() { - return bin_; - } - /** - * int32 bin = 4; - * @param value The bin to set. - * @return This builder for chaining. - */ - public Builder setBin(int value) { - - bin_ = value; - onChanged(); - return this; - } - /** - * int32 bin = 4; - * @return This builder for chaining. - */ - public Builder clearBin() { - - bin_ = 0; - onChanged(); - return this; - } - - private java.lang.Object opName_ = ""; - /** - * string op_name = 5; - * @return The opName. - */ - public java.lang.String getOpName() { - java.lang.Object ref = opName_; - if (!(ref instanceof java.lang.String)) { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - opName_ = s; - return s; - } else { - return (java.lang.String) ref; - } - } - /** - * string op_name = 5; - * @return The bytes for opName. - */ - public com.google.protobuf.ByteString - getOpNameBytes() { - java.lang.Object ref = opName_; - if (ref instanceof String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - opName_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - /** - * string op_name = 5; - * @param value The opName to set. - * @return This builder for chaining. - */ - public Builder setOpName( - java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - - opName_ = value; - onChanged(); - return this; - } - /** - * string op_name = 5; - * @return This builder for chaining. - */ - public Builder clearOpName() { - - opName_ = getDefaultInstance().getOpName(); - onChanged(); - return this; - } - /** - * string op_name = 5; - * @param value The bytes for opName to set. - * @return This builder for chaining. - */ - public Builder setOpNameBytes( - com.google.protobuf.ByteString value) { - if (value == null) { - throw new NullPointerException(); - } - checkByteStringIsUtf8(value); - - opName_ = value; - onChanged(); - return this; - } - - private long freedAtCount_ ; - /** - * uint64 freed_at_count = 6; - * @return The freedAtCount. - */ - @java.lang.Override - public long getFreedAtCount() { - return freedAtCount_; - } - /** - * uint64 freed_at_count = 6; - * @param value The freedAtCount to set. - * @return This builder for chaining. - */ - public Builder setFreedAtCount(long value) { - - freedAtCount_ = value; - onChanged(); - return this; - } - /** - * uint64 freed_at_count = 6; - * @return This builder for chaining. - */ - public Builder clearFreedAtCount() { - - freedAtCount_ = 0L; - onChanged(); - return this; - } - - private long actionCount_ ; - /** - * uint64 action_count = 7; - * @return The actionCount. - */ - @java.lang.Override - public long getActionCount() { - return actionCount_; - } - /** - * uint64 action_count = 7; - * @param value The actionCount to set. - * @return This builder for chaining. - */ - public Builder setActionCount(long value) { - - actionCount_ = value; - onChanged(); - return this; - } - /** - * uint64 action_count = 7; - * @return This builder for chaining. - */ - public Builder clearActionCount() { - - actionCount_ = 0L; - onChanged(); - return this; - } - - private boolean inUse_ ; - /** - * bool in_use = 8; - * @return The inUse. - */ - @java.lang.Override - public boolean getInUse() { - return inUse_; - } - /** - * bool in_use = 8; - * @param value The inUse to set. - * @return This builder for chaining. - */ - public Builder setInUse(boolean value) { - - inUse_ = value; - onChanged(); - return this; - } - /** - * bool in_use = 8; - * @return This builder for chaining. - */ - public Builder clearInUse() { - - inUse_ = false; - onChanged(); - return this; - } - - private long stepId_ ; - /** - * uint64 step_id = 9; - * @return The stepId. - */ - @java.lang.Override - public long getStepId() { - return stepId_; - } - /** - * uint64 step_id = 9; - * @param value The stepId to set. - * @return This builder for chaining. - */ - public Builder setStepId(long value) { - - stepId_ = value; - onChanged(); - return this; - } - /** - * uint64 step_id = 9; - * @return This builder for chaining. - */ - public Builder clearStepId() { - - stepId_ = 0L; - onChanged(); - return this; - } - @java.lang.Override - public final Builder setUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.setUnknownFields(unknownFields); - } - - @java.lang.Override - public final Builder mergeUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.mergeUnknownFields(unknownFields); - } - - - // @@protoc_insertion_point(builder_scope:tensorflow.MemChunk) - } - - // @@protoc_insertion_point(class_scope:tensorflow.MemChunk) - private static final org.tensorflow.proto.BfcMemoryMap.MemChunk DEFAULT_INSTANCE; - static { - DEFAULT_INSTANCE = new org.tensorflow.proto.BfcMemoryMap.MemChunk(); - } - - public static org.tensorflow.proto.BfcMemoryMap.MemChunk getDefaultInstance() { - return DEFAULT_INSTANCE; - } - - private static final com.google.protobuf.Parser - PARSER = new com.google.protobuf.AbstractParser() { - @java.lang.Override - public MemChunk parsePartialFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - Builder builder = newBuilder(); - try { - builder.mergeFrom(input, extensionRegistry); - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.setUnfinishedMessage(builder.buildPartial()); - } catch (com.google.protobuf.UninitializedMessageException e) { - throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); - } catch (java.io.IOException e) { - throw new com.google.protobuf.InvalidProtocolBufferException(e) - .setUnfinishedMessage(builder.buildPartial()); - } - return builder.buildPartial(); - } - }; - - public static com.google.protobuf.Parser parser() { - return PARSER; - } - - @java.lang.Override - public com.google.protobuf.Parser getParserForType() { - return PARSER; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemChunk getDefaultInstanceForType() { - return DEFAULT_INSTANCE; - } - - } - - public interface BinSummaryOrBuilder extends - // @@protoc_insertion_point(interface_extends:tensorflow.BinSummary) - com.google.protobuf.MessageOrBuilder { - - /** - * int32 bin = 1; - * @return The bin. - */ - int getBin(); - - /** - * int64 total_bytes_in_use = 2; - * @return The totalBytesInUse. - */ - long getTotalBytesInUse(); - - /** - * int64 total_bytes_in_bin = 3; - * @return The totalBytesInBin. - */ - long getTotalBytesInBin(); - - /** - * int64 total_chunks_in_use = 4; - * @return The totalChunksInUse. - */ - long getTotalChunksInUse(); - - /** - * int64 total_chunks_in_bin = 5; - * @return The totalChunksInBin. - */ - long getTotalChunksInBin(); - } - /** - * Protobuf type {@code tensorflow.BinSummary} - */ - public static final class BinSummary extends - com.google.protobuf.GeneratedMessageV3 implements - // @@protoc_insertion_point(message_implements:tensorflow.BinSummary) - BinSummaryOrBuilder { - private static final long serialVersionUID = 0L; - // Use BinSummary.newBuilder() to construct. - private BinSummary(com.google.protobuf.GeneratedMessageV3.Builder builder) { - super(builder); - } - private BinSummary() { - } - - @java.lang.Override - @SuppressWarnings({"unused"}) - protected java.lang.Object newInstance( - UnusedPrivateParameter unused) { - return new BinSummary(); - } - - @java.lang.Override - public final com.google.protobuf.UnknownFieldSet - getUnknownFields() { - return this.unknownFields; - } - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_BinSummary_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_BinSummary_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BfcMemoryMap.BinSummary.class, org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder.class); - } - - public static final int BIN_FIELD_NUMBER = 1; - private int bin_; - /** - * int32 bin = 1; - * @return The bin. - */ - @java.lang.Override - public int getBin() { - return bin_; - } - - public static final int TOTAL_BYTES_IN_USE_FIELD_NUMBER = 2; - private long totalBytesInUse_; - /** - * int64 total_bytes_in_use = 2; - * @return The totalBytesInUse. - */ - @java.lang.Override - public long getTotalBytesInUse() { - return totalBytesInUse_; - } - - public static final int TOTAL_BYTES_IN_BIN_FIELD_NUMBER = 3; - private long totalBytesInBin_; - /** - * int64 total_bytes_in_bin = 3; - * @return The totalBytesInBin. - */ - @java.lang.Override - public long getTotalBytesInBin() { - return totalBytesInBin_; - } - - public static final int TOTAL_CHUNKS_IN_USE_FIELD_NUMBER = 4; - private long totalChunksInUse_; - /** - * int64 total_chunks_in_use = 4; - * @return The totalChunksInUse. - */ - @java.lang.Override - public long getTotalChunksInUse() { - return totalChunksInUse_; - } - - public static final int TOTAL_CHUNKS_IN_BIN_FIELD_NUMBER = 5; - private long totalChunksInBin_; - /** - * int64 total_chunks_in_bin = 5; - * @return The totalChunksInBin. - */ - @java.lang.Override - public long getTotalChunksInBin() { - return totalChunksInBin_; - } - - private byte memoizedIsInitialized = -1; - @java.lang.Override - public final boolean isInitialized() { - byte isInitialized = memoizedIsInitialized; - if (isInitialized == 1) return true; - if (isInitialized == 0) return false; - - memoizedIsInitialized = 1; - return true; - } - - @java.lang.Override - public void writeTo(com.google.protobuf.CodedOutputStream output) - throws java.io.IOException { - if (bin_ != 0) { - output.writeInt32(1, bin_); - } - if (totalBytesInUse_ != 0L) { - output.writeInt64(2, totalBytesInUse_); - } - if (totalBytesInBin_ != 0L) { - output.writeInt64(3, totalBytesInBin_); - } - if (totalChunksInUse_ != 0L) { - output.writeInt64(4, totalChunksInUse_); - } - if (totalChunksInBin_ != 0L) { - output.writeInt64(5, totalChunksInBin_); - } - getUnknownFields().writeTo(output); - } - - @java.lang.Override - public int getSerializedSize() { - int size = memoizedSize; - if (size != -1) return size; - - size = 0; - if (bin_ != 0) { - size += com.google.protobuf.CodedOutputStream - .computeInt32Size(1, bin_); - } - if (totalBytesInUse_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(2, totalBytesInUse_); - } - if (totalBytesInBin_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(3, totalBytesInBin_); - } - if (totalChunksInUse_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(4, totalChunksInUse_); - } - if (totalChunksInBin_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(5, totalChunksInBin_); - } - size += getUnknownFields().getSerializedSize(); - memoizedSize = size; - return size; - } - - @java.lang.Override - public boolean equals(final java.lang.Object obj) { - if (obj == this) { - return true; - } - if (!(obj instanceof org.tensorflow.proto.BfcMemoryMap.BinSummary)) { - return super.equals(obj); - } - org.tensorflow.proto.BfcMemoryMap.BinSummary other = (org.tensorflow.proto.BfcMemoryMap.BinSummary) obj; - - if (getBin() - != other.getBin()) return false; - if (getTotalBytesInUse() - != other.getTotalBytesInUse()) return false; - if (getTotalBytesInBin() - != other.getTotalBytesInBin()) return false; - if (getTotalChunksInUse() - != other.getTotalChunksInUse()) return false; - if (getTotalChunksInBin() - != other.getTotalChunksInBin()) return false; - if (!getUnknownFields().equals(other.getUnknownFields())) return false; - return true; - } - - @java.lang.Override - public int hashCode() { - if (memoizedHashCode != 0) { - return memoizedHashCode; - } - int hash = 41; - hash = (19 * hash) + getDescriptor().hashCode(); - hash = (37 * hash) + BIN_FIELD_NUMBER; - hash = (53 * hash) + getBin(); - hash = (37 * hash) + TOTAL_BYTES_IN_USE_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getTotalBytesInUse()); - hash = (37 * hash) + TOTAL_BYTES_IN_BIN_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getTotalBytesInBin()); - hash = (37 * hash) + TOTAL_CHUNKS_IN_USE_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getTotalChunksInUse()); - hash = (37 * hash) + TOTAL_CHUNKS_IN_BIN_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getTotalChunksInBin()); - hash = (29 * hash) + getUnknownFields().hashCode(); - memoizedHashCode = hash; - return hash; - } - - public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( - java.nio.ByteBuffer data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( - java.nio.ByteBuffer data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( - com.google.protobuf.ByteString data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( - com.google.protobuf.ByteString data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom(byte[] data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( - byte[] data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseDelimitedFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseDelimitedFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( - com.google.protobuf.CodedInputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - - @java.lang.Override - public Builder newBuilderForType() { return newBuilder(); } - public static Builder newBuilder() { - return DEFAULT_INSTANCE.toBuilder(); - } - public static Builder newBuilder(org.tensorflow.proto.BfcMemoryMap.BinSummary prototype) { - return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); - } - @java.lang.Override - public Builder toBuilder() { - return this == DEFAULT_INSTANCE - ? new Builder() : new Builder().mergeFrom(this); - } - - @java.lang.Override - protected Builder newBuilderForType( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - Builder builder = new Builder(parent); - return builder; - } - /** - * Protobuf type {@code tensorflow.BinSummary} - */ - public static final class Builder extends - com.google.protobuf.GeneratedMessageV3.Builder implements - // @@protoc_insertion_point(builder_implements:tensorflow.BinSummary) - org.tensorflow.proto.BfcMemoryMap.BinSummaryOrBuilder { - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_BinSummary_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_BinSummary_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BfcMemoryMap.BinSummary.class, org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder.class); - } - - // Construct using org.tensorflow.proto.BfcMemoryMap.BinSummary.newBuilder() - private Builder() { - - } - - private Builder( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - super(parent); - - } - @java.lang.Override - public Builder clear() { - super.clear(); - bin_ = 0; - - totalBytesInUse_ = 0L; - - totalBytesInBin_ = 0L; - - totalChunksInUse_ = 0L; - - totalChunksInBin_ = 0L; - - return this; - } - - @java.lang.Override - public com.google.protobuf.Descriptors.Descriptor - getDescriptorForType() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_BinSummary_descriptor; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.BinSummary getDefaultInstanceForType() { - return org.tensorflow.proto.BfcMemoryMap.BinSummary.getDefaultInstance(); - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.BinSummary build() { - org.tensorflow.proto.BfcMemoryMap.BinSummary result = buildPartial(); - if (!result.isInitialized()) { - throw newUninitializedMessageException(result); - } - return result; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.BinSummary buildPartial() { - org.tensorflow.proto.BfcMemoryMap.BinSummary result = new org.tensorflow.proto.BfcMemoryMap.BinSummary(this); - result.bin_ = bin_; - result.totalBytesInUse_ = totalBytesInUse_; - result.totalBytesInBin_ = totalBytesInBin_; - result.totalChunksInUse_ = totalChunksInUse_; - result.totalChunksInBin_ = totalChunksInBin_; - onBuilt(); - return result; - } - - @java.lang.Override - public Builder clone() { - return super.clone(); - } - @java.lang.Override - public Builder setField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.setField(field, value); - } - @java.lang.Override - public Builder clearField( - com.google.protobuf.Descriptors.FieldDescriptor field) { - return super.clearField(field); - } - @java.lang.Override - public Builder clearOneof( - com.google.protobuf.Descriptors.OneofDescriptor oneof) { - return super.clearOneof(oneof); - } - @java.lang.Override - public Builder setRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - int index, java.lang.Object value) { - return super.setRepeatedField(field, index, value); - } - @java.lang.Override - public Builder addRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.addRepeatedField(field, value); - } - @java.lang.Override - public Builder mergeFrom(com.google.protobuf.Message other) { - if (other instanceof org.tensorflow.proto.BfcMemoryMap.BinSummary) { - return mergeFrom((org.tensorflow.proto.BfcMemoryMap.BinSummary)other); - } else { - super.mergeFrom(other); - return this; - } - } - - public Builder mergeFrom(org.tensorflow.proto.BfcMemoryMap.BinSummary other) { - if (other == org.tensorflow.proto.BfcMemoryMap.BinSummary.getDefaultInstance()) return this; - if (other.getBin() != 0) { - setBin(other.getBin()); - } - if (other.getTotalBytesInUse() != 0L) { - setTotalBytesInUse(other.getTotalBytesInUse()); - } - if (other.getTotalBytesInBin() != 0L) { - setTotalBytesInBin(other.getTotalBytesInBin()); - } - if (other.getTotalChunksInUse() != 0L) { - setTotalChunksInUse(other.getTotalChunksInUse()); - } - if (other.getTotalChunksInBin() != 0L) { - setTotalChunksInBin(other.getTotalChunksInBin()); - } - this.mergeUnknownFields(other.getUnknownFields()); - onChanged(); - return this; - } - - @java.lang.Override - public final boolean isInitialized() { - return true; - } - - @java.lang.Override - public Builder mergeFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - if (extensionRegistry == null) { - throw new java.lang.NullPointerException(); - } - try { - boolean done = false; - while (!done) { - int tag = input.readTag(); - switch (tag) { - case 0: - done = true; - break; - case 8: { - bin_ = input.readInt32(); - - break; - } // case 8 - case 16: { - totalBytesInUse_ = input.readInt64(); - - break; - } // case 16 - case 24: { - totalBytesInBin_ = input.readInt64(); - - break; - } // case 24 - case 32: { - totalChunksInUse_ = input.readInt64(); - - break; - } // case 32 - case 40: { - totalChunksInBin_ = input.readInt64(); - - break; - } // case 40 - default: { - if (!super.parseUnknownField(input, extensionRegistry, tag)) { - done = true; // was an endgroup tag - } - break; - } // default: - } // switch (tag) - } // while (!done) - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.unwrapIOException(); - } finally { - onChanged(); - } // finally - return this; - } - - private int bin_ ; - /** - * int32 bin = 1; - * @return The bin. - */ - @java.lang.Override - public int getBin() { - return bin_; - } - /** - * int32 bin = 1; - * @param value The bin to set. - * @return This builder for chaining. - */ - public Builder setBin(int value) { - - bin_ = value; - onChanged(); - return this; - } - /** - * int32 bin = 1; - * @return This builder for chaining. - */ - public Builder clearBin() { - - bin_ = 0; - onChanged(); - return this; - } - - private long totalBytesInUse_ ; - /** - * int64 total_bytes_in_use = 2; - * @return The totalBytesInUse. - */ - @java.lang.Override - public long getTotalBytesInUse() { - return totalBytesInUse_; - } - /** - * int64 total_bytes_in_use = 2; - * @param value The totalBytesInUse to set. - * @return This builder for chaining. - */ - public Builder setTotalBytesInUse(long value) { - - totalBytesInUse_ = value; - onChanged(); - return this; - } - /** - * int64 total_bytes_in_use = 2; - * @return This builder for chaining. - */ - public Builder clearTotalBytesInUse() { - - totalBytesInUse_ = 0L; - onChanged(); - return this; - } - - private long totalBytesInBin_ ; - /** - * int64 total_bytes_in_bin = 3; - * @return The totalBytesInBin. - */ - @java.lang.Override - public long getTotalBytesInBin() { - return totalBytesInBin_; - } - /** - * int64 total_bytes_in_bin = 3; - * @param value The totalBytesInBin to set. - * @return This builder for chaining. - */ - public Builder setTotalBytesInBin(long value) { - - totalBytesInBin_ = value; - onChanged(); - return this; - } - /** - * int64 total_bytes_in_bin = 3; - * @return This builder for chaining. - */ - public Builder clearTotalBytesInBin() { - - totalBytesInBin_ = 0L; - onChanged(); - return this; - } - - private long totalChunksInUse_ ; - /** - * int64 total_chunks_in_use = 4; - * @return The totalChunksInUse. - */ - @java.lang.Override - public long getTotalChunksInUse() { - return totalChunksInUse_; - } - /** - * int64 total_chunks_in_use = 4; - * @param value The totalChunksInUse to set. - * @return This builder for chaining. - */ - public Builder setTotalChunksInUse(long value) { - - totalChunksInUse_ = value; - onChanged(); - return this; - } - /** - * int64 total_chunks_in_use = 4; - * @return This builder for chaining. - */ - public Builder clearTotalChunksInUse() { - - totalChunksInUse_ = 0L; - onChanged(); - return this; - } - - private long totalChunksInBin_ ; - /** - * int64 total_chunks_in_bin = 5; - * @return The totalChunksInBin. - */ - @java.lang.Override - public long getTotalChunksInBin() { - return totalChunksInBin_; - } - /** - * int64 total_chunks_in_bin = 5; - * @param value The totalChunksInBin to set. - * @return This builder for chaining. - */ - public Builder setTotalChunksInBin(long value) { - - totalChunksInBin_ = value; - onChanged(); - return this; - } - /** - * int64 total_chunks_in_bin = 5; - * @return This builder for chaining. - */ - public Builder clearTotalChunksInBin() { - - totalChunksInBin_ = 0L; - onChanged(); - return this; - } - @java.lang.Override - public final Builder setUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.setUnknownFields(unknownFields); - } - - @java.lang.Override - public final Builder mergeUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.mergeUnknownFields(unknownFields); - } - - - // @@protoc_insertion_point(builder_scope:tensorflow.BinSummary) - } - - // @@protoc_insertion_point(class_scope:tensorflow.BinSummary) - private static final org.tensorflow.proto.BfcMemoryMap.BinSummary DEFAULT_INSTANCE; - static { - DEFAULT_INSTANCE = new org.tensorflow.proto.BfcMemoryMap.BinSummary(); - } - - public static org.tensorflow.proto.BfcMemoryMap.BinSummary getDefaultInstance() { - return DEFAULT_INSTANCE; - } - - private static final com.google.protobuf.Parser - PARSER = new com.google.protobuf.AbstractParser() { - @java.lang.Override - public BinSummary parsePartialFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - Builder builder = newBuilder(); - try { - builder.mergeFrom(input, extensionRegistry); - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.setUnfinishedMessage(builder.buildPartial()); - } catch (com.google.protobuf.UninitializedMessageException e) { - throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); - } catch (java.io.IOException e) { - throw new com.google.protobuf.InvalidProtocolBufferException(e) - .setUnfinishedMessage(builder.buildPartial()); - } - return builder.buildPartial(); - } - }; - - public static com.google.protobuf.Parser parser() { - return PARSER; - } - - @java.lang.Override - public com.google.protobuf.Parser getParserForType() { - return PARSER; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.BinSummary getDefaultInstanceForType() { - return DEFAULT_INSTANCE; - } - - } - - public interface SnapShotOrBuilder extends - // @@protoc_insertion_point(interface_extends:tensorflow.SnapShot) - com.google.protobuf.MessageOrBuilder { - - /** - * uint64 action_count = 1; - * @return The actionCount. - */ - long getActionCount(); - - /** - * int64 size = 2; - * @return The size. - */ - long getSize(); - } - /** - * Protobuf type {@code tensorflow.SnapShot} - */ - public static final class SnapShot extends - com.google.protobuf.GeneratedMessageV3 implements - // @@protoc_insertion_point(message_implements:tensorflow.SnapShot) - SnapShotOrBuilder { - private static final long serialVersionUID = 0L; - // Use SnapShot.newBuilder() to construct. - private SnapShot(com.google.protobuf.GeneratedMessageV3.Builder builder) { - super(builder); - } - private SnapShot() { - } - - @java.lang.Override - @SuppressWarnings({"unused"}) - protected java.lang.Object newInstance( - UnusedPrivateParameter unused) { - return new SnapShot(); - } - - @java.lang.Override - public final com.google.protobuf.UnknownFieldSet - getUnknownFields() { - return this.unknownFields; - } - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_SnapShot_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_SnapShot_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BfcMemoryMap.SnapShot.class, org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder.class); - } - - public static final int ACTION_COUNT_FIELD_NUMBER = 1; - private long actionCount_; - /** - * uint64 action_count = 1; - * @return The actionCount. - */ - @java.lang.Override - public long getActionCount() { - return actionCount_; - } - - public static final int SIZE_FIELD_NUMBER = 2; - private long size_; - /** - * int64 size = 2; - * @return The size. - */ - @java.lang.Override - public long getSize() { - return size_; - } - - private byte memoizedIsInitialized = -1; - @java.lang.Override - public final boolean isInitialized() { - byte isInitialized = memoizedIsInitialized; - if (isInitialized == 1) return true; - if (isInitialized == 0) return false; - - memoizedIsInitialized = 1; - return true; - } - - @java.lang.Override - public void writeTo(com.google.protobuf.CodedOutputStream output) - throws java.io.IOException { - if (actionCount_ != 0L) { - output.writeUInt64(1, actionCount_); - } - if (size_ != 0L) { - output.writeInt64(2, size_); - } - getUnknownFields().writeTo(output); - } - - @java.lang.Override - public int getSerializedSize() { - int size = memoizedSize; - if (size != -1) return size; - - size = 0; - if (actionCount_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeUInt64Size(1, actionCount_); - } - if (size_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(2, size_); - } - size += getUnknownFields().getSerializedSize(); - memoizedSize = size; - return size; - } - - @java.lang.Override - public boolean equals(final java.lang.Object obj) { - if (obj == this) { - return true; - } - if (!(obj instanceof org.tensorflow.proto.BfcMemoryMap.SnapShot)) { - return super.equals(obj); - } - org.tensorflow.proto.BfcMemoryMap.SnapShot other = (org.tensorflow.proto.BfcMemoryMap.SnapShot) obj; - - if (getActionCount() - != other.getActionCount()) return false; - if (getSize() - != other.getSize()) return false; - if (!getUnknownFields().equals(other.getUnknownFields())) return false; - return true; - } - - @java.lang.Override - public int hashCode() { - if (memoizedHashCode != 0) { - return memoizedHashCode; - } - int hash = 41; - hash = (19 * hash) + getDescriptor().hashCode(); - hash = (37 * hash) + ACTION_COUNT_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getActionCount()); - hash = (37 * hash) + SIZE_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getSize()); - hash = (29 * hash) + getUnknownFields().hashCode(); - memoizedHashCode = hash; - return hash; - } - - public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( - java.nio.ByteBuffer data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( - java.nio.ByteBuffer data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( - com.google.protobuf.ByteString data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( - com.google.protobuf.ByteString data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom(byte[] data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( - byte[] data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseDelimitedFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseDelimitedFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( - com.google.protobuf.CodedInputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - - @java.lang.Override - public Builder newBuilderForType() { return newBuilder(); } - public static Builder newBuilder() { - return DEFAULT_INSTANCE.toBuilder(); - } - public static Builder newBuilder(org.tensorflow.proto.BfcMemoryMap.SnapShot prototype) { - return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); - } - @java.lang.Override - public Builder toBuilder() { - return this == DEFAULT_INSTANCE - ? new Builder() : new Builder().mergeFrom(this); - } - - @java.lang.Override - protected Builder newBuilderForType( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - Builder builder = new Builder(parent); - return builder; - } - /** - * Protobuf type {@code tensorflow.SnapShot} - */ - public static final class Builder extends - com.google.protobuf.GeneratedMessageV3.Builder implements - // @@protoc_insertion_point(builder_implements:tensorflow.SnapShot) - org.tensorflow.proto.BfcMemoryMap.SnapShotOrBuilder { - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_SnapShot_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_SnapShot_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BfcMemoryMap.SnapShot.class, org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder.class); - } - - // Construct using org.tensorflow.proto.BfcMemoryMap.SnapShot.newBuilder() - private Builder() { - - } - - private Builder( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - super(parent); - - } - @java.lang.Override - public Builder clear() { - super.clear(); - actionCount_ = 0L; - - size_ = 0L; - - return this; - } - - @java.lang.Override - public com.google.protobuf.Descriptors.Descriptor - getDescriptorForType() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_SnapShot_descriptor; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.SnapShot getDefaultInstanceForType() { - return org.tensorflow.proto.BfcMemoryMap.SnapShot.getDefaultInstance(); - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.SnapShot build() { - org.tensorflow.proto.BfcMemoryMap.SnapShot result = buildPartial(); - if (!result.isInitialized()) { - throw newUninitializedMessageException(result); - } - return result; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.SnapShot buildPartial() { - org.tensorflow.proto.BfcMemoryMap.SnapShot result = new org.tensorflow.proto.BfcMemoryMap.SnapShot(this); - result.actionCount_ = actionCount_; - result.size_ = size_; - onBuilt(); - return result; - } - - @java.lang.Override - public Builder clone() { - return super.clone(); - } - @java.lang.Override - public Builder setField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.setField(field, value); - } - @java.lang.Override - public Builder clearField( - com.google.protobuf.Descriptors.FieldDescriptor field) { - return super.clearField(field); - } - @java.lang.Override - public Builder clearOneof( - com.google.protobuf.Descriptors.OneofDescriptor oneof) { - return super.clearOneof(oneof); - } - @java.lang.Override - public Builder setRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - int index, java.lang.Object value) { - return super.setRepeatedField(field, index, value); - } - @java.lang.Override - public Builder addRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.addRepeatedField(field, value); - } - @java.lang.Override - public Builder mergeFrom(com.google.protobuf.Message other) { - if (other instanceof org.tensorflow.proto.BfcMemoryMap.SnapShot) { - return mergeFrom((org.tensorflow.proto.BfcMemoryMap.SnapShot)other); - } else { - super.mergeFrom(other); - return this; - } - } - - public Builder mergeFrom(org.tensorflow.proto.BfcMemoryMap.SnapShot other) { - if (other == org.tensorflow.proto.BfcMemoryMap.SnapShot.getDefaultInstance()) return this; - if (other.getActionCount() != 0L) { - setActionCount(other.getActionCount()); - } - if (other.getSize() != 0L) { - setSize(other.getSize()); - } - this.mergeUnknownFields(other.getUnknownFields()); - onChanged(); - return this; - } - - @java.lang.Override - public final boolean isInitialized() { - return true; - } - - @java.lang.Override - public Builder mergeFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - if (extensionRegistry == null) { - throw new java.lang.NullPointerException(); - } - try { - boolean done = false; - while (!done) { - int tag = input.readTag(); - switch (tag) { - case 0: - done = true; - break; - case 8: { - actionCount_ = input.readUInt64(); - - break; - } // case 8 - case 16: { - size_ = input.readInt64(); - - break; - } // case 16 - default: { - if (!super.parseUnknownField(input, extensionRegistry, tag)) { - done = true; // was an endgroup tag - } - break; - } // default: - } // switch (tag) - } // while (!done) - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.unwrapIOException(); - } finally { - onChanged(); - } // finally - return this; - } - - private long actionCount_ ; - /** - * uint64 action_count = 1; - * @return The actionCount. - */ - @java.lang.Override - public long getActionCount() { - return actionCount_; - } - /** - * uint64 action_count = 1; - * @param value The actionCount to set. - * @return This builder for chaining. - */ - public Builder setActionCount(long value) { - - actionCount_ = value; - onChanged(); - return this; - } - /** - * uint64 action_count = 1; - * @return This builder for chaining. - */ - public Builder clearActionCount() { - - actionCount_ = 0L; - onChanged(); - return this; - } - - private long size_ ; - /** - * int64 size = 2; - * @return The size. - */ - @java.lang.Override - public long getSize() { - return size_; - } - /** - * int64 size = 2; - * @param value The size to set. - * @return This builder for chaining. - */ - public Builder setSize(long value) { - - size_ = value; - onChanged(); - return this; - } - /** - * int64 size = 2; - * @return This builder for chaining. - */ - public Builder clearSize() { - - size_ = 0L; - onChanged(); - return this; - } - @java.lang.Override - public final Builder setUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.setUnknownFields(unknownFields); - } - - @java.lang.Override - public final Builder mergeUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.mergeUnknownFields(unknownFields); - } - - - // @@protoc_insertion_point(builder_scope:tensorflow.SnapShot) - } - - // @@protoc_insertion_point(class_scope:tensorflow.SnapShot) - private static final org.tensorflow.proto.BfcMemoryMap.SnapShot DEFAULT_INSTANCE; - static { - DEFAULT_INSTANCE = new org.tensorflow.proto.BfcMemoryMap.SnapShot(); - } - - public static org.tensorflow.proto.BfcMemoryMap.SnapShot getDefaultInstance() { - return DEFAULT_INSTANCE; - } - - private static final com.google.protobuf.Parser - PARSER = new com.google.protobuf.AbstractParser() { - @java.lang.Override - public SnapShot parsePartialFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - Builder builder = newBuilder(); - try { - builder.mergeFrom(input, extensionRegistry); - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.setUnfinishedMessage(builder.buildPartial()); - } catch (com.google.protobuf.UninitializedMessageException e) { - throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); - } catch (java.io.IOException e) { - throw new com.google.protobuf.InvalidProtocolBufferException(e) - .setUnfinishedMessage(builder.buildPartial()); - } - return builder.buildPartial(); - } - }; - - public static com.google.protobuf.Parser parser() { - return PARSER; - } - - @java.lang.Override - public com.google.protobuf.Parser getParserForType() { - return PARSER; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.SnapShot getDefaultInstanceForType() { - return DEFAULT_INSTANCE; - } - - } - - public interface MemoryDumpOrBuilder extends - // @@protoc_insertion_point(interface_extends:tensorflow.MemoryDump) - com.google.protobuf.MessageOrBuilder { - - /** - * string allocator_name = 1; - * @return The allocatorName. - */ - java.lang.String getAllocatorName(); - /** - * string allocator_name = 1; - * @return The bytes for allocatorName. - */ - com.google.protobuf.ByteString - getAllocatorNameBytes(); - - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - java.util.List - getBinSummaryList(); - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - org.tensorflow.proto.BfcMemoryMap.BinSummary getBinSummary(int index); - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - int getBinSummaryCount(); - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - java.util.List - getBinSummaryOrBuilderList(); - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - org.tensorflow.proto.BfcMemoryMap.BinSummaryOrBuilder getBinSummaryOrBuilder( - int index); - - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - java.util.List - getChunkList(); - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - org.tensorflow.proto.BfcMemoryMap.MemChunk getChunk(int index); - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - int getChunkCount(); - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - java.util.List - getChunkOrBuilderList(); - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - org.tensorflow.proto.BfcMemoryMap.MemChunkOrBuilder getChunkOrBuilder( - int index); - - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - java.util.List - getSnapShotList(); - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - org.tensorflow.proto.BfcMemoryMap.SnapShot getSnapShot(int index); - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - int getSnapShotCount(); - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - java.util.List - getSnapShotOrBuilderList(); - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - org.tensorflow.proto.BfcMemoryMap.SnapShotOrBuilder getSnapShotOrBuilder( - int index); - - /** - * .tensorflow.MemAllocatorStats stats = 5; - * @return Whether the stats field is set. - */ - boolean hasStats(); - /** - * .tensorflow.MemAllocatorStats stats = 5; - * @return The stats. - */ - org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats getStats(); - /** - * .tensorflow.MemAllocatorStats stats = 5; - */ - org.tensorflow.proto.BfcMemoryMap.MemAllocatorStatsOrBuilder getStatsOrBuilder(); - } - /** - * Protobuf type {@code tensorflow.MemoryDump} - */ - public static final class MemoryDump extends - com.google.protobuf.GeneratedMessageV3 implements - // @@protoc_insertion_point(message_implements:tensorflow.MemoryDump) - MemoryDumpOrBuilder { - private static final long serialVersionUID = 0L; - // Use MemoryDump.newBuilder() to construct. - private MemoryDump(com.google.protobuf.GeneratedMessageV3.Builder builder) { - super(builder); - } - private MemoryDump() { - allocatorName_ = ""; - binSummary_ = java.util.Collections.emptyList(); - chunk_ = java.util.Collections.emptyList(); - snapShot_ = java.util.Collections.emptyList(); - } - - @java.lang.Override - @SuppressWarnings({"unused"}) - protected java.lang.Object newInstance( - UnusedPrivateParameter unused) { - return new MemoryDump(); - } - - @java.lang.Override - public final com.google.protobuf.UnknownFieldSet - getUnknownFields() { - return this.unknownFields; - } - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemoryDump_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemoryDump_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BfcMemoryMap.MemoryDump.class, org.tensorflow.proto.BfcMemoryMap.MemoryDump.Builder.class); - } - - public static final int ALLOCATOR_NAME_FIELD_NUMBER = 1; - private volatile java.lang.Object allocatorName_; - /** - * string allocator_name = 1; - * @return The allocatorName. - */ - @java.lang.Override - public java.lang.String getAllocatorName() { - java.lang.Object ref = allocatorName_; - if (ref instanceof java.lang.String) { - return (java.lang.String) ref; - } else { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - allocatorName_ = s; - return s; - } - } - /** - * string allocator_name = 1; - * @return The bytes for allocatorName. - */ - @java.lang.Override - public com.google.protobuf.ByteString - getAllocatorNameBytes() { - java.lang.Object ref = allocatorName_; - if (ref instanceof java.lang.String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - allocatorName_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - - public static final int BIN_SUMMARY_FIELD_NUMBER = 2; - private java.util.List binSummary_; - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - @java.lang.Override - public java.util.List getBinSummaryList() { - return binSummary_; - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - @java.lang.Override - public java.util.List - getBinSummaryOrBuilderList() { - return binSummary_; - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - @java.lang.Override - public int getBinSummaryCount() { - return binSummary_.size(); - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.BinSummary getBinSummary(int index) { - return binSummary_.get(index); - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.BinSummaryOrBuilder getBinSummaryOrBuilder( - int index) { - return binSummary_.get(index); - } - - public static final int CHUNK_FIELD_NUMBER = 3; - private java.util.List chunk_; - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - @java.lang.Override - public java.util.List getChunkList() { - return chunk_; - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - @java.lang.Override - public java.util.List - getChunkOrBuilderList() { - return chunk_; - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - @java.lang.Override - public int getChunkCount() { - return chunk_.size(); - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemChunk getChunk(int index) { - return chunk_.get(index); - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemChunkOrBuilder getChunkOrBuilder( - int index) { - return chunk_.get(index); - } - - public static final int SNAP_SHOT_FIELD_NUMBER = 4; - private java.util.List snapShot_; - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - @java.lang.Override - public java.util.List getSnapShotList() { - return snapShot_; - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - @java.lang.Override - public java.util.List - getSnapShotOrBuilderList() { - return snapShot_; - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - @java.lang.Override - public int getSnapShotCount() { - return snapShot_.size(); - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.SnapShot getSnapShot(int index) { - return snapShot_.get(index); - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.SnapShotOrBuilder getSnapShotOrBuilder( - int index) { - return snapShot_.get(index); - } - - public static final int STATS_FIELD_NUMBER = 5; - private org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats stats_; - /** - * .tensorflow.MemAllocatorStats stats = 5; - * @return Whether the stats field is set. - */ - @java.lang.Override - public boolean hasStats() { - return stats_ != null; - } - /** - * .tensorflow.MemAllocatorStats stats = 5; - * @return The stats. - */ - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats getStats() { - return stats_ == null ? org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.getDefaultInstance() : stats_; - } - /** - * .tensorflow.MemAllocatorStats stats = 5; - */ - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStatsOrBuilder getStatsOrBuilder() { - return getStats(); - } - - private byte memoizedIsInitialized = -1; - @java.lang.Override - public final boolean isInitialized() { - byte isInitialized = memoizedIsInitialized; - if (isInitialized == 1) return true; - if (isInitialized == 0) return false; - - memoizedIsInitialized = 1; - return true; - } - - @java.lang.Override - public void writeTo(com.google.protobuf.CodedOutputStream output) - throws java.io.IOException { - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(allocatorName_)) { - com.google.protobuf.GeneratedMessageV3.writeString(output, 1, allocatorName_); - } - for (int i = 0; i < binSummary_.size(); i++) { - output.writeMessage(2, binSummary_.get(i)); - } - for (int i = 0; i < chunk_.size(); i++) { - output.writeMessage(3, chunk_.get(i)); - } - for (int i = 0; i < snapShot_.size(); i++) { - output.writeMessage(4, snapShot_.get(i)); - } - if (stats_ != null) { - output.writeMessage(5, getStats()); - } - getUnknownFields().writeTo(output); - } - - @java.lang.Override - public int getSerializedSize() { - int size = memoizedSize; - if (size != -1) return size; - - size = 0; - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(allocatorName_)) { - size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, allocatorName_); - } - for (int i = 0; i < binSummary_.size(); i++) { - size += com.google.protobuf.CodedOutputStream - .computeMessageSize(2, binSummary_.get(i)); - } - for (int i = 0; i < chunk_.size(); i++) { - size += com.google.protobuf.CodedOutputStream - .computeMessageSize(3, chunk_.get(i)); - } - for (int i = 0; i < snapShot_.size(); i++) { - size += com.google.protobuf.CodedOutputStream - .computeMessageSize(4, snapShot_.get(i)); - } - if (stats_ != null) { - size += com.google.protobuf.CodedOutputStream - .computeMessageSize(5, getStats()); - } - size += getUnknownFields().getSerializedSize(); - memoizedSize = size; - return size; - } - - @java.lang.Override - public boolean equals(final java.lang.Object obj) { - if (obj == this) { - return true; - } - if (!(obj instanceof org.tensorflow.proto.BfcMemoryMap.MemoryDump)) { - return super.equals(obj); - } - org.tensorflow.proto.BfcMemoryMap.MemoryDump other = (org.tensorflow.proto.BfcMemoryMap.MemoryDump) obj; - - if (!getAllocatorName() - .equals(other.getAllocatorName())) return false; - if (!getBinSummaryList() - .equals(other.getBinSummaryList())) return false; - if (!getChunkList() - .equals(other.getChunkList())) return false; - if (!getSnapShotList() - .equals(other.getSnapShotList())) return false; - if (hasStats() != other.hasStats()) return false; - if (hasStats()) { - if (!getStats() - .equals(other.getStats())) return false; - } - if (!getUnknownFields().equals(other.getUnknownFields())) return false; - return true; - } - - @java.lang.Override - public int hashCode() { - if (memoizedHashCode != 0) { - return memoizedHashCode; - } - int hash = 41; - hash = (19 * hash) + getDescriptor().hashCode(); - hash = (37 * hash) + ALLOCATOR_NAME_FIELD_NUMBER; - hash = (53 * hash) + getAllocatorName().hashCode(); - if (getBinSummaryCount() > 0) { - hash = (37 * hash) + BIN_SUMMARY_FIELD_NUMBER; - hash = (53 * hash) + getBinSummaryList().hashCode(); - } - if (getChunkCount() > 0) { - hash = (37 * hash) + CHUNK_FIELD_NUMBER; - hash = (53 * hash) + getChunkList().hashCode(); - } - if (getSnapShotCount() > 0) { - hash = (37 * hash) + SNAP_SHOT_FIELD_NUMBER; - hash = (53 * hash) + getSnapShotList().hashCode(); - } - if (hasStats()) { - hash = (37 * hash) + STATS_FIELD_NUMBER; - hash = (53 * hash) + getStats().hashCode(); - } - hash = (29 * hash) + getUnknownFields().hashCode(); - memoizedHashCode = hash; - return hash; - } - - public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( - java.nio.ByteBuffer data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( - java.nio.ByteBuffer data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( - com.google.protobuf.ByteString data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( - com.google.protobuf.ByteString data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom(byte[] data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( - byte[] data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseDelimitedFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseDelimitedFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( - com.google.protobuf.CodedInputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - - @java.lang.Override - public Builder newBuilderForType() { return newBuilder(); } - public static Builder newBuilder() { - return DEFAULT_INSTANCE.toBuilder(); - } - public static Builder newBuilder(org.tensorflow.proto.BfcMemoryMap.MemoryDump prototype) { - return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); - } - @java.lang.Override - public Builder toBuilder() { - return this == DEFAULT_INSTANCE - ? new Builder() : new Builder().mergeFrom(this); - } - - @java.lang.Override - protected Builder newBuilderForType( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - Builder builder = new Builder(parent); - return builder; - } - /** - * Protobuf type {@code tensorflow.MemoryDump} - */ - public static final class Builder extends - com.google.protobuf.GeneratedMessageV3.Builder implements - // @@protoc_insertion_point(builder_implements:tensorflow.MemoryDump) - org.tensorflow.proto.BfcMemoryMap.MemoryDumpOrBuilder { - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemoryDump_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemoryDump_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BfcMemoryMap.MemoryDump.class, org.tensorflow.proto.BfcMemoryMap.MemoryDump.Builder.class); - } - - // Construct using org.tensorflow.proto.BfcMemoryMap.MemoryDump.newBuilder() - private Builder() { - - } - - private Builder( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - super(parent); - - } - @java.lang.Override - public Builder clear() { - super.clear(); - allocatorName_ = ""; - - if (binSummaryBuilder_ == null) { - binSummary_ = java.util.Collections.emptyList(); - } else { - binSummary_ = null; - binSummaryBuilder_.clear(); - } - bitField0_ = (bitField0_ & ~0x00000001); - if (chunkBuilder_ == null) { - chunk_ = java.util.Collections.emptyList(); - } else { - chunk_ = null; - chunkBuilder_.clear(); - } - bitField0_ = (bitField0_ & ~0x00000002); - if (snapShotBuilder_ == null) { - snapShot_ = java.util.Collections.emptyList(); - } else { - snapShot_ = null; - snapShotBuilder_.clear(); - } - bitField0_ = (bitField0_ & ~0x00000004); - if (statsBuilder_ == null) { - stats_ = null; - } else { - stats_ = null; - statsBuilder_ = null; - } - return this; - } - - @java.lang.Override - public com.google.protobuf.Descriptors.Descriptor - getDescriptorForType() { - return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemoryDump_descriptor; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemoryDump getDefaultInstanceForType() { - return org.tensorflow.proto.BfcMemoryMap.MemoryDump.getDefaultInstance(); - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemoryDump build() { - org.tensorflow.proto.BfcMemoryMap.MemoryDump result = buildPartial(); - if (!result.isInitialized()) { - throw newUninitializedMessageException(result); - } - return result; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemoryDump buildPartial() { - org.tensorflow.proto.BfcMemoryMap.MemoryDump result = new org.tensorflow.proto.BfcMemoryMap.MemoryDump(this); - int from_bitField0_ = bitField0_; - result.allocatorName_ = allocatorName_; - if (binSummaryBuilder_ == null) { - if (((bitField0_ & 0x00000001) != 0)) { - binSummary_ = java.util.Collections.unmodifiableList(binSummary_); - bitField0_ = (bitField0_ & ~0x00000001); - } - result.binSummary_ = binSummary_; - } else { - result.binSummary_ = binSummaryBuilder_.build(); - } - if (chunkBuilder_ == null) { - if (((bitField0_ & 0x00000002) != 0)) { - chunk_ = java.util.Collections.unmodifiableList(chunk_); - bitField0_ = (bitField0_ & ~0x00000002); - } - result.chunk_ = chunk_; - } else { - result.chunk_ = chunkBuilder_.build(); - } - if (snapShotBuilder_ == null) { - if (((bitField0_ & 0x00000004) != 0)) { - snapShot_ = java.util.Collections.unmodifiableList(snapShot_); - bitField0_ = (bitField0_ & ~0x00000004); - } - result.snapShot_ = snapShot_; - } else { - result.snapShot_ = snapShotBuilder_.build(); - } - if (statsBuilder_ == null) { - result.stats_ = stats_; - } else { - result.stats_ = statsBuilder_.build(); - } - onBuilt(); - return result; - } - - @java.lang.Override - public Builder clone() { - return super.clone(); - } - @java.lang.Override - public Builder setField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.setField(field, value); - } - @java.lang.Override - public Builder clearField( - com.google.protobuf.Descriptors.FieldDescriptor field) { - return super.clearField(field); - } - @java.lang.Override - public Builder clearOneof( - com.google.protobuf.Descriptors.OneofDescriptor oneof) { - return super.clearOneof(oneof); - } - @java.lang.Override - public Builder setRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - int index, java.lang.Object value) { - return super.setRepeatedField(field, index, value); - } - @java.lang.Override - public Builder addRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.addRepeatedField(field, value); - } - @java.lang.Override - public Builder mergeFrom(com.google.protobuf.Message other) { - if (other instanceof org.tensorflow.proto.BfcMemoryMap.MemoryDump) { - return mergeFrom((org.tensorflow.proto.BfcMemoryMap.MemoryDump)other); - } else { - super.mergeFrom(other); - return this; - } - } - - public Builder mergeFrom(org.tensorflow.proto.BfcMemoryMap.MemoryDump other) { - if (other == org.tensorflow.proto.BfcMemoryMap.MemoryDump.getDefaultInstance()) return this; - if (!other.getAllocatorName().isEmpty()) { - allocatorName_ = other.allocatorName_; - onChanged(); - } - if (binSummaryBuilder_ == null) { - if (!other.binSummary_.isEmpty()) { - if (binSummary_.isEmpty()) { - binSummary_ = other.binSummary_; - bitField0_ = (bitField0_ & ~0x00000001); - } else { - ensureBinSummaryIsMutable(); - binSummary_.addAll(other.binSummary_); - } - onChanged(); - } - } else { - if (!other.binSummary_.isEmpty()) { - if (binSummaryBuilder_.isEmpty()) { - binSummaryBuilder_.dispose(); - binSummaryBuilder_ = null; - binSummary_ = other.binSummary_; - bitField0_ = (bitField0_ & ~0x00000001); - binSummaryBuilder_ = - com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ? - getBinSummaryFieldBuilder() : null; - } else { - binSummaryBuilder_.addAllMessages(other.binSummary_); - } - } - } - if (chunkBuilder_ == null) { - if (!other.chunk_.isEmpty()) { - if (chunk_.isEmpty()) { - chunk_ = other.chunk_; - bitField0_ = (bitField0_ & ~0x00000002); - } else { - ensureChunkIsMutable(); - chunk_.addAll(other.chunk_); - } - onChanged(); - } - } else { - if (!other.chunk_.isEmpty()) { - if (chunkBuilder_.isEmpty()) { - chunkBuilder_.dispose(); - chunkBuilder_ = null; - chunk_ = other.chunk_; - bitField0_ = (bitField0_ & ~0x00000002); - chunkBuilder_ = - com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ? - getChunkFieldBuilder() : null; - } else { - chunkBuilder_.addAllMessages(other.chunk_); - } - } - } - if (snapShotBuilder_ == null) { - if (!other.snapShot_.isEmpty()) { - if (snapShot_.isEmpty()) { - snapShot_ = other.snapShot_; - bitField0_ = (bitField0_ & ~0x00000004); - } else { - ensureSnapShotIsMutable(); - snapShot_.addAll(other.snapShot_); - } - onChanged(); - } - } else { - if (!other.snapShot_.isEmpty()) { - if (snapShotBuilder_.isEmpty()) { - snapShotBuilder_.dispose(); - snapShotBuilder_ = null; - snapShot_ = other.snapShot_; - bitField0_ = (bitField0_ & ~0x00000004); - snapShotBuilder_ = - com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ? - getSnapShotFieldBuilder() : null; - } else { - snapShotBuilder_.addAllMessages(other.snapShot_); - } - } - } - if (other.hasStats()) { - mergeStats(other.getStats()); - } - this.mergeUnknownFields(other.getUnknownFields()); - onChanged(); - return this; - } - - @java.lang.Override - public final boolean isInitialized() { - return true; - } - - @java.lang.Override - public Builder mergeFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - if (extensionRegistry == null) { - throw new java.lang.NullPointerException(); - } - try { - boolean done = false; - while (!done) { - int tag = input.readTag(); - switch (tag) { - case 0: - done = true; - break; - case 10: { - allocatorName_ = input.readStringRequireUtf8(); - - break; - } // case 10 - case 18: { - org.tensorflow.proto.BfcMemoryMap.BinSummary m = - input.readMessage( - org.tensorflow.proto.BfcMemoryMap.BinSummary.parser(), - extensionRegistry); - if (binSummaryBuilder_ == null) { - ensureBinSummaryIsMutable(); - binSummary_.add(m); - } else { - binSummaryBuilder_.addMessage(m); - } - break; - } // case 18 - case 26: { - org.tensorflow.proto.BfcMemoryMap.MemChunk m = - input.readMessage( - org.tensorflow.proto.BfcMemoryMap.MemChunk.parser(), - extensionRegistry); - if (chunkBuilder_ == null) { - ensureChunkIsMutable(); - chunk_.add(m); - } else { - chunkBuilder_.addMessage(m); - } - break; - } // case 26 - case 34: { - org.tensorflow.proto.BfcMemoryMap.SnapShot m = - input.readMessage( - org.tensorflow.proto.BfcMemoryMap.SnapShot.parser(), - extensionRegistry); - if (snapShotBuilder_ == null) { - ensureSnapShotIsMutable(); - snapShot_.add(m); - } else { - snapShotBuilder_.addMessage(m); - } - break; - } // case 34 - case 42: { - input.readMessage( - getStatsFieldBuilder().getBuilder(), - extensionRegistry); - - break; - } // case 42 - default: { - if (!super.parseUnknownField(input, extensionRegistry, tag)) { - done = true; // was an endgroup tag - } - break; - } // default: - } // switch (tag) - } // while (!done) - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.unwrapIOException(); - } finally { - onChanged(); - } // finally - return this; - } - private int bitField0_; - - private java.lang.Object allocatorName_ = ""; - /** - * string allocator_name = 1; - * @return The allocatorName. - */ - public java.lang.String getAllocatorName() { - java.lang.Object ref = allocatorName_; - if (!(ref instanceof java.lang.String)) { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - allocatorName_ = s; - return s; - } else { - return (java.lang.String) ref; - } - } - /** - * string allocator_name = 1; - * @return The bytes for allocatorName. - */ - public com.google.protobuf.ByteString - getAllocatorNameBytes() { - java.lang.Object ref = allocatorName_; - if (ref instanceof String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - allocatorName_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - /** - * string allocator_name = 1; - * @param value The allocatorName to set. - * @return This builder for chaining. - */ - public Builder setAllocatorName( - java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - - allocatorName_ = value; - onChanged(); - return this; - } - /** - * string allocator_name = 1; - * @return This builder for chaining. - */ - public Builder clearAllocatorName() { - - allocatorName_ = getDefaultInstance().getAllocatorName(); - onChanged(); - return this; - } - /** - * string allocator_name = 1; - * @param value The bytes for allocatorName to set. - * @return This builder for chaining. - */ - public Builder setAllocatorNameBytes( - com.google.protobuf.ByteString value) { - if (value == null) { - throw new NullPointerException(); - } - checkByteStringIsUtf8(value); - - allocatorName_ = value; - onChanged(); - return this; - } - - private java.util.List binSummary_ = - java.util.Collections.emptyList(); - private void ensureBinSummaryIsMutable() { - if (!((bitField0_ & 0x00000001) != 0)) { - binSummary_ = new java.util.ArrayList(binSummary_); - bitField0_ |= 0x00000001; - } - } - - private com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.BfcMemoryMap.BinSummary, org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder, org.tensorflow.proto.BfcMemoryMap.BinSummaryOrBuilder> binSummaryBuilder_; - - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public java.util.List getBinSummaryList() { - if (binSummaryBuilder_ == null) { - return java.util.Collections.unmodifiableList(binSummary_); - } else { - return binSummaryBuilder_.getMessageList(); - } - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public int getBinSummaryCount() { - if (binSummaryBuilder_ == null) { - return binSummary_.size(); - } else { - return binSummaryBuilder_.getCount(); - } - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public org.tensorflow.proto.BfcMemoryMap.BinSummary getBinSummary(int index) { - if (binSummaryBuilder_ == null) { - return binSummary_.get(index); - } else { - return binSummaryBuilder_.getMessage(index); - } - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public Builder setBinSummary( - int index, org.tensorflow.proto.BfcMemoryMap.BinSummary value) { - if (binSummaryBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureBinSummaryIsMutable(); - binSummary_.set(index, value); - onChanged(); - } else { - binSummaryBuilder_.setMessage(index, value); - } - return this; - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public Builder setBinSummary( - int index, org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder builderForValue) { - if (binSummaryBuilder_ == null) { - ensureBinSummaryIsMutable(); - binSummary_.set(index, builderForValue.build()); - onChanged(); - } else { - binSummaryBuilder_.setMessage(index, builderForValue.build()); - } - return this; - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public Builder addBinSummary(org.tensorflow.proto.BfcMemoryMap.BinSummary value) { - if (binSummaryBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureBinSummaryIsMutable(); - binSummary_.add(value); - onChanged(); - } else { - binSummaryBuilder_.addMessage(value); - } - return this; - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public Builder addBinSummary( - int index, org.tensorflow.proto.BfcMemoryMap.BinSummary value) { - if (binSummaryBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureBinSummaryIsMutable(); - binSummary_.add(index, value); - onChanged(); - } else { - binSummaryBuilder_.addMessage(index, value); - } - return this; - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public Builder addBinSummary( - org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder builderForValue) { - if (binSummaryBuilder_ == null) { - ensureBinSummaryIsMutable(); - binSummary_.add(builderForValue.build()); - onChanged(); - } else { - binSummaryBuilder_.addMessage(builderForValue.build()); - } - return this; - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public Builder addBinSummary( - int index, org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder builderForValue) { - if (binSummaryBuilder_ == null) { - ensureBinSummaryIsMutable(); - binSummary_.add(index, builderForValue.build()); - onChanged(); - } else { - binSummaryBuilder_.addMessage(index, builderForValue.build()); - } - return this; - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public Builder addAllBinSummary( - java.lang.Iterable values) { - if (binSummaryBuilder_ == null) { - ensureBinSummaryIsMutable(); - com.google.protobuf.AbstractMessageLite.Builder.addAll( - values, binSummary_); - onChanged(); - } else { - binSummaryBuilder_.addAllMessages(values); - } - return this; - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public Builder clearBinSummary() { - if (binSummaryBuilder_ == null) { - binSummary_ = java.util.Collections.emptyList(); - bitField0_ = (bitField0_ & ~0x00000001); - onChanged(); - } else { - binSummaryBuilder_.clear(); - } - return this; - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public Builder removeBinSummary(int index) { - if (binSummaryBuilder_ == null) { - ensureBinSummaryIsMutable(); - binSummary_.remove(index); - onChanged(); - } else { - binSummaryBuilder_.remove(index); - } - return this; - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder getBinSummaryBuilder( - int index) { - return getBinSummaryFieldBuilder().getBuilder(index); - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public org.tensorflow.proto.BfcMemoryMap.BinSummaryOrBuilder getBinSummaryOrBuilder( - int index) { - if (binSummaryBuilder_ == null) { - return binSummary_.get(index); } else { - return binSummaryBuilder_.getMessageOrBuilder(index); - } - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public java.util.List - getBinSummaryOrBuilderList() { - if (binSummaryBuilder_ != null) { - return binSummaryBuilder_.getMessageOrBuilderList(); - } else { - return java.util.Collections.unmodifiableList(binSummary_); - } - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder addBinSummaryBuilder() { - return getBinSummaryFieldBuilder().addBuilder( - org.tensorflow.proto.BfcMemoryMap.BinSummary.getDefaultInstance()); - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder addBinSummaryBuilder( - int index) { - return getBinSummaryFieldBuilder().addBuilder( - index, org.tensorflow.proto.BfcMemoryMap.BinSummary.getDefaultInstance()); - } - /** - * repeated .tensorflow.BinSummary bin_summary = 2; - */ - public java.util.List - getBinSummaryBuilderList() { - return getBinSummaryFieldBuilder().getBuilderList(); - } - private com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.BfcMemoryMap.BinSummary, org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder, org.tensorflow.proto.BfcMemoryMap.BinSummaryOrBuilder> - getBinSummaryFieldBuilder() { - if (binSummaryBuilder_ == null) { - binSummaryBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.BfcMemoryMap.BinSummary, org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder, org.tensorflow.proto.BfcMemoryMap.BinSummaryOrBuilder>( - binSummary_, - ((bitField0_ & 0x00000001) != 0), - getParentForChildren(), - isClean()); - binSummary_ = null; - } - return binSummaryBuilder_; - } - - private java.util.List chunk_ = - java.util.Collections.emptyList(); - private void ensureChunkIsMutable() { - if (!((bitField0_ & 0x00000002) != 0)) { - chunk_ = new java.util.ArrayList(chunk_); - bitField0_ |= 0x00000002; - } - } - - private com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.BfcMemoryMap.MemChunk, org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder, org.tensorflow.proto.BfcMemoryMap.MemChunkOrBuilder> chunkBuilder_; - - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public java.util.List getChunkList() { - if (chunkBuilder_ == null) { - return java.util.Collections.unmodifiableList(chunk_); - } else { - return chunkBuilder_.getMessageList(); - } - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public int getChunkCount() { - if (chunkBuilder_ == null) { - return chunk_.size(); - } else { - return chunkBuilder_.getCount(); - } - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public org.tensorflow.proto.BfcMemoryMap.MemChunk getChunk(int index) { - if (chunkBuilder_ == null) { - return chunk_.get(index); - } else { - return chunkBuilder_.getMessage(index); - } - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public Builder setChunk( - int index, org.tensorflow.proto.BfcMemoryMap.MemChunk value) { - if (chunkBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureChunkIsMutable(); - chunk_.set(index, value); - onChanged(); - } else { - chunkBuilder_.setMessage(index, value); - } - return this; - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public Builder setChunk( - int index, org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder builderForValue) { - if (chunkBuilder_ == null) { - ensureChunkIsMutable(); - chunk_.set(index, builderForValue.build()); - onChanged(); - } else { - chunkBuilder_.setMessage(index, builderForValue.build()); - } - return this; - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public Builder addChunk(org.tensorflow.proto.BfcMemoryMap.MemChunk value) { - if (chunkBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureChunkIsMutable(); - chunk_.add(value); - onChanged(); - } else { - chunkBuilder_.addMessage(value); - } - return this; - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public Builder addChunk( - int index, org.tensorflow.proto.BfcMemoryMap.MemChunk value) { - if (chunkBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureChunkIsMutable(); - chunk_.add(index, value); - onChanged(); - } else { - chunkBuilder_.addMessage(index, value); - } - return this; - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public Builder addChunk( - org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder builderForValue) { - if (chunkBuilder_ == null) { - ensureChunkIsMutable(); - chunk_.add(builderForValue.build()); - onChanged(); - } else { - chunkBuilder_.addMessage(builderForValue.build()); - } - return this; - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public Builder addChunk( - int index, org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder builderForValue) { - if (chunkBuilder_ == null) { - ensureChunkIsMutable(); - chunk_.add(index, builderForValue.build()); - onChanged(); - } else { - chunkBuilder_.addMessage(index, builderForValue.build()); - } - return this; - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public Builder addAllChunk( - java.lang.Iterable values) { - if (chunkBuilder_ == null) { - ensureChunkIsMutable(); - com.google.protobuf.AbstractMessageLite.Builder.addAll( - values, chunk_); - onChanged(); - } else { - chunkBuilder_.addAllMessages(values); - } - return this; - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public Builder clearChunk() { - if (chunkBuilder_ == null) { - chunk_ = java.util.Collections.emptyList(); - bitField0_ = (bitField0_ & ~0x00000002); - onChanged(); - } else { - chunkBuilder_.clear(); - } - return this; - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public Builder removeChunk(int index) { - if (chunkBuilder_ == null) { - ensureChunkIsMutable(); - chunk_.remove(index); - onChanged(); - } else { - chunkBuilder_.remove(index); - } - return this; - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder getChunkBuilder( - int index) { - return getChunkFieldBuilder().getBuilder(index); - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public org.tensorflow.proto.BfcMemoryMap.MemChunkOrBuilder getChunkOrBuilder( - int index) { - if (chunkBuilder_ == null) { - return chunk_.get(index); } else { - return chunkBuilder_.getMessageOrBuilder(index); - } - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public java.util.List - getChunkOrBuilderList() { - if (chunkBuilder_ != null) { - return chunkBuilder_.getMessageOrBuilderList(); - } else { - return java.util.Collections.unmodifiableList(chunk_); - } - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder addChunkBuilder() { - return getChunkFieldBuilder().addBuilder( - org.tensorflow.proto.BfcMemoryMap.MemChunk.getDefaultInstance()); - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder addChunkBuilder( - int index) { - return getChunkFieldBuilder().addBuilder( - index, org.tensorflow.proto.BfcMemoryMap.MemChunk.getDefaultInstance()); - } - /** - * repeated .tensorflow.MemChunk chunk = 3; - */ - public java.util.List - getChunkBuilderList() { - return getChunkFieldBuilder().getBuilderList(); - } - private com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.BfcMemoryMap.MemChunk, org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder, org.tensorflow.proto.BfcMemoryMap.MemChunkOrBuilder> - getChunkFieldBuilder() { - if (chunkBuilder_ == null) { - chunkBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.BfcMemoryMap.MemChunk, org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder, org.tensorflow.proto.BfcMemoryMap.MemChunkOrBuilder>( - chunk_, - ((bitField0_ & 0x00000002) != 0), - getParentForChildren(), - isClean()); - chunk_ = null; - } - return chunkBuilder_; - } - - private java.util.List snapShot_ = - java.util.Collections.emptyList(); - private void ensureSnapShotIsMutable() { - if (!((bitField0_ & 0x00000004) != 0)) { - snapShot_ = new java.util.ArrayList(snapShot_); - bitField0_ |= 0x00000004; - } - } - - private com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.BfcMemoryMap.SnapShot, org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder, org.tensorflow.proto.BfcMemoryMap.SnapShotOrBuilder> snapShotBuilder_; - - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public java.util.List getSnapShotList() { - if (snapShotBuilder_ == null) { - return java.util.Collections.unmodifiableList(snapShot_); - } else { - return snapShotBuilder_.getMessageList(); - } - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public int getSnapShotCount() { - if (snapShotBuilder_ == null) { - return snapShot_.size(); - } else { - return snapShotBuilder_.getCount(); - } - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public org.tensorflow.proto.BfcMemoryMap.SnapShot getSnapShot(int index) { - if (snapShotBuilder_ == null) { - return snapShot_.get(index); - } else { - return snapShotBuilder_.getMessage(index); - } - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public Builder setSnapShot( - int index, org.tensorflow.proto.BfcMemoryMap.SnapShot value) { - if (snapShotBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureSnapShotIsMutable(); - snapShot_.set(index, value); - onChanged(); - } else { - snapShotBuilder_.setMessage(index, value); - } - return this; - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public Builder setSnapShot( - int index, org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder builderForValue) { - if (snapShotBuilder_ == null) { - ensureSnapShotIsMutable(); - snapShot_.set(index, builderForValue.build()); - onChanged(); - } else { - snapShotBuilder_.setMessage(index, builderForValue.build()); - } - return this; - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public Builder addSnapShot(org.tensorflow.proto.BfcMemoryMap.SnapShot value) { - if (snapShotBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureSnapShotIsMutable(); - snapShot_.add(value); - onChanged(); - } else { - snapShotBuilder_.addMessage(value); - } - return this; - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public Builder addSnapShot( - int index, org.tensorflow.proto.BfcMemoryMap.SnapShot value) { - if (snapShotBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - ensureSnapShotIsMutable(); - snapShot_.add(index, value); - onChanged(); - } else { - snapShotBuilder_.addMessage(index, value); - } - return this; - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public Builder addSnapShot( - org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder builderForValue) { - if (snapShotBuilder_ == null) { - ensureSnapShotIsMutable(); - snapShot_.add(builderForValue.build()); - onChanged(); - } else { - snapShotBuilder_.addMessage(builderForValue.build()); - } - return this; - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public Builder addSnapShot( - int index, org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder builderForValue) { - if (snapShotBuilder_ == null) { - ensureSnapShotIsMutable(); - snapShot_.add(index, builderForValue.build()); - onChanged(); - } else { - snapShotBuilder_.addMessage(index, builderForValue.build()); - } - return this; - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public Builder addAllSnapShot( - java.lang.Iterable values) { - if (snapShotBuilder_ == null) { - ensureSnapShotIsMutable(); - com.google.protobuf.AbstractMessageLite.Builder.addAll( - values, snapShot_); - onChanged(); - } else { - snapShotBuilder_.addAllMessages(values); - } - return this; - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public Builder clearSnapShot() { - if (snapShotBuilder_ == null) { - snapShot_ = java.util.Collections.emptyList(); - bitField0_ = (bitField0_ & ~0x00000004); - onChanged(); - } else { - snapShotBuilder_.clear(); - } - return this; - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public Builder removeSnapShot(int index) { - if (snapShotBuilder_ == null) { - ensureSnapShotIsMutable(); - snapShot_.remove(index); - onChanged(); - } else { - snapShotBuilder_.remove(index); - } - return this; - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder getSnapShotBuilder( - int index) { - return getSnapShotFieldBuilder().getBuilder(index); - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public org.tensorflow.proto.BfcMemoryMap.SnapShotOrBuilder getSnapShotOrBuilder( - int index) { - if (snapShotBuilder_ == null) { - return snapShot_.get(index); } else { - return snapShotBuilder_.getMessageOrBuilder(index); - } - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public java.util.List - getSnapShotOrBuilderList() { - if (snapShotBuilder_ != null) { - return snapShotBuilder_.getMessageOrBuilderList(); - } else { - return java.util.Collections.unmodifiableList(snapShot_); - } - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder addSnapShotBuilder() { - return getSnapShotFieldBuilder().addBuilder( - org.tensorflow.proto.BfcMemoryMap.SnapShot.getDefaultInstance()); - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder addSnapShotBuilder( - int index) { - return getSnapShotFieldBuilder().addBuilder( - index, org.tensorflow.proto.BfcMemoryMap.SnapShot.getDefaultInstance()); - } - /** - * repeated .tensorflow.SnapShot snap_shot = 4; - */ - public java.util.List - getSnapShotBuilderList() { - return getSnapShotFieldBuilder().getBuilderList(); - } - private com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.BfcMemoryMap.SnapShot, org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder, org.tensorflow.proto.BfcMemoryMap.SnapShotOrBuilder> - getSnapShotFieldBuilder() { - if (snapShotBuilder_ == null) { - snapShotBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3< - org.tensorflow.proto.BfcMemoryMap.SnapShot, org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder, org.tensorflow.proto.BfcMemoryMap.SnapShotOrBuilder>( - snapShot_, - ((bitField0_ & 0x00000004) != 0), - getParentForChildren(), - isClean()); - snapShot_ = null; - } - return snapShotBuilder_; - } - - private org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats stats_; - private com.google.protobuf.SingleFieldBuilderV3< - org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.Builder, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStatsOrBuilder> statsBuilder_; - /** - * .tensorflow.MemAllocatorStats stats = 5; - * @return Whether the stats field is set. - */ - public boolean hasStats() { - return statsBuilder_ != null || stats_ != null; - } - /** - * .tensorflow.MemAllocatorStats stats = 5; - * @return The stats. - */ - public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats getStats() { - if (statsBuilder_ == null) { - return stats_ == null ? org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.getDefaultInstance() : stats_; - } else { - return statsBuilder_.getMessage(); - } - } - /** - * .tensorflow.MemAllocatorStats stats = 5; - */ - public Builder setStats(org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats value) { - if (statsBuilder_ == null) { - if (value == null) { - throw new NullPointerException(); - } - stats_ = value; - onChanged(); - } else { - statsBuilder_.setMessage(value); - } - - return this; - } - /** - * .tensorflow.MemAllocatorStats stats = 5; - */ - public Builder setStats( - org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.Builder builderForValue) { - if (statsBuilder_ == null) { - stats_ = builderForValue.build(); - onChanged(); - } else { - statsBuilder_.setMessage(builderForValue.build()); - } - - return this; - } - /** - * .tensorflow.MemAllocatorStats stats = 5; - */ - public Builder mergeStats(org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats value) { - if (statsBuilder_ == null) { - if (stats_ != null) { - stats_ = - org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.newBuilder(stats_).mergeFrom(value).buildPartial(); - } else { - stats_ = value; - } - onChanged(); - } else { - statsBuilder_.mergeFrom(value); - } - - return this; - } - /** - * .tensorflow.MemAllocatorStats stats = 5; - */ - public Builder clearStats() { - if (statsBuilder_ == null) { - stats_ = null; - onChanged(); - } else { - stats_ = null; - statsBuilder_ = null; - } - - return this; - } - /** - * .tensorflow.MemAllocatorStats stats = 5; - */ - public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.Builder getStatsBuilder() { - - onChanged(); - return getStatsFieldBuilder().getBuilder(); - } - /** - * .tensorflow.MemAllocatorStats stats = 5; - */ - public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStatsOrBuilder getStatsOrBuilder() { - if (statsBuilder_ != null) { - return statsBuilder_.getMessageOrBuilder(); - } else { - return stats_ == null ? - org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.getDefaultInstance() : stats_; - } - } - /** - * .tensorflow.MemAllocatorStats stats = 5; - */ - private com.google.protobuf.SingleFieldBuilderV3< - org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.Builder, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStatsOrBuilder> - getStatsFieldBuilder() { - if (statsBuilder_ == null) { - statsBuilder_ = new com.google.protobuf.SingleFieldBuilderV3< - org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.Builder, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStatsOrBuilder>( - getStats(), - getParentForChildren(), - isClean()); - stats_ = null; - } - return statsBuilder_; - } - @java.lang.Override - public final Builder setUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.setUnknownFields(unknownFields); - } - - @java.lang.Override - public final Builder mergeUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.mergeUnknownFields(unknownFields); - } - - - // @@protoc_insertion_point(builder_scope:tensorflow.MemoryDump) - } - - // @@protoc_insertion_point(class_scope:tensorflow.MemoryDump) - private static final org.tensorflow.proto.BfcMemoryMap.MemoryDump DEFAULT_INSTANCE; - static { - DEFAULT_INSTANCE = new org.tensorflow.proto.BfcMemoryMap.MemoryDump(); - } - - public static org.tensorflow.proto.BfcMemoryMap.MemoryDump getDefaultInstance() { - return DEFAULT_INSTANCE; - } - - private static final com.google.protobuf.Parser - PARSER = new com.google.protobuf.AbstractParser() { - @java.lang.Override - public MemoryDump parsePartialFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - Builder builder = newBuilder(); - try { - builder.mergeFrom(input, extensionRegistry); - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.setUnfinishedMessage(builder.buildPartial()); - } catch (com.google.protobuf.UninitializedMessageException e) { - throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); - } catch (java.io.IOException e) { - throw new com.google.protobuf.InvalidProtocolBufferException(e) - .setUnfinishedMessage(builder.buildPartial()); - } - return builder.buildPartial(); - } - }; - - public static com.google.protobuf.Parser parser() { - return PARSER; - } - - @java.lang.Override - public com.google.protobuf.Parser getParserForType() { - return PARSER; - } - - @java.lang.Override - public org.tensorflow.proto.BfcMemoryMap.MemoryDump getDefaultInstanceForType() { - return DEFAULT_INSTANCE; - } - - } - - private static final com.google.protobuf.Descriptors.Descriptor - internal_static_tensorflow_MemAllocatorStats_descriptor; - private static final - com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internal_static_tensorflow_MemAllocatorStats_fieldAccessorTable; - private static final com.google.protobuf.Descriptors.Descriptor - internal_static_tensorflow_MemChunk_descriptor; - private static final - com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internal_static_tensorflow_MemChunk_fieldAccessorTable; - private static final com.google.protobuf.Descriptors.Descriptor - internal_static_tensorflow_BinSummary_descriptor; - private static final - com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internal_static_tensorflow_BinSummary_fieldAccessorTable; - private static final com.google.protobuf.Descriptors.Descriptor - internal_static_tensorflow_SnapShot_descriptor; - private static final - com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internal_static_tensorflow_SnapShot_fieldAccessorTable; - private static final com.google.protobuf.Descriptors.Descriptor - internal_static_tensorflow_MemoryDump_descriptor; - private static final - com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internal_static_tensorflow_MemoryDump_fieldAccessorTable; - - public static com.google.protobuf.Descriptors.FileDescriptor - getDescriptor() { - return descriptor; - } - private static com.google.protobuf.Descriptors.FileDescriptor - descriptor; - static { - java.lang.String[] descriptorData = { - "\n!tsl/protobuf/bfc_memory_map.proto\022\nten" + - "sorflow\"\222\001\n\021MemAllocatorStats\022\022\n\nnum_all" + - "ocs\030\001 \001(\003\022\024\n\014bytes_in_use\030\002 \001(\003\022\031\n\021peak_" + - "bytes_in_use\030\003 \001(\003\022\032\n\022largest_alloc_size" + - "\030\004 \001(\003\022\034\n\024fragmentation_metric\030\005 \001(\002\"\256\001\n" + - "\010MemChunk\022\017\n\007address\030\001 \001(\004\022\014\n\004size\030\002 \001(\003" + - "\022\026\n\016requested_size\030\003 \001(\003\022\013\n\003bin\030\004 \001(\005\022\017\n" + - "\007op_name\030\005 \001(\t\022\026\n\016freed_at_count\030\006 \001(\004\022\024" + - "\n\014action_count\030\007 \001(\004\022\016\n\006in_use\030\010 \001(\010\022\017\n\007" + - "step_id\030\t \001(\004\"\213\001\n\nBinSummary\022\013\n\003bin\030\001 \001(" + - "\005\022\032\n\022total_bytes_in_use\030\002 \001(\003\022\032\n\022total_b" + - "ytes_in_bin\030\003 \001(\003\022\033\n\023total_chunks_in_use" + - "\030\004 \001(\003\022\033\n\023total_chunks_in_bin\030\005 \001(\003\".\n\010S" + - "napShot\022\024\n\014action_count\030\001 \001(\004\022\014\n\004size\030\002 " + - "\001(\003\"\315\001\n\nMemoryDump\022\026\n\016allocator_name\030\001 \001" + - "(\t\022+\n\013bin_summary\030\002 \003(\0132\026.tensorflow.Bin" + - "Summary\022#\n\005chunk\030\003 \003(\0132\024.tensorflow.MemC" + - "hunk\022\'\n\tsnap_shot\030\004 \003(\0132\024.tensorflow.Sna" + - "pShot\022,\n\005stats\030\005 \001(\0132\035.tensorflow.MemAll" + - "ocatorStatsBV\n\024org.tensorflow.protoZ>git" + - "hub.com/google/tsl/tsl/go/protobuf/for_c" + - "ore_protos_go_protob\006proto3" - }; - descriptor = com.google.protobuf.Descriptors.FileDescriptor - .internalBuildGeneratedFileFrom(descriptorData, - new com.google.protobuf.Descriptors.FileDescriptor[] { - }); - internal_static_tensorflow_MemAllocatorStats_descriptor = - getDescriptor().getMessageTypes().get(0); - internal_static_tensorflow_MemAllocatorStats_fieldAccessorTable = new - com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( - internal_static_tensorflow_MemAllocatorStats_descriptor, - new java.lang.String[] { "NumAllocs", "BytesInUse", "PeakBytesInUse", "LargestAllocSize", "FragmentationMetric", }); - internal_static_tensorflow_MemChunk_descriptor = - getDescriptor().getMessageTypes().get(1); - internal_static_tensorflow_MemChunk_fieldAccessorTable = new - com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( - internal_static_tensorflow_MemChunk_descriptor, - new java.lang.String[] { "Address", "Size", "RequestedSize", "Bin", "OpName", "FreedAtCount", "ActionCount", "InUse", "StepId", }); - internal_static_tensorflow_BinSummary_descriptor = - getDescriptor().getMessageTypes().get(2); - internal_static_tensorflow_BinSummary_fieldAccessorTable = new - com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( - internal_static_tensorflow_BinSummary_descriptor, - new java.lang.String[] { "Bin", "TotalBytesInUse", "TotalBytesInBin", "TotalChunksInUse", "TotalChunksInBin", }); - internal_static_tensorflow_SnapShot_descriptor = - getDescriptor().getMessageTypes().get(3); - internal_static_tensorflow_SnapShot_fieldAccessorTable = new - com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( - internal_static_tensorflow_SnapShot_descriptor, - new java.lang.String[] { "ActionCount", "Size", }); - internal_static_tensorflow_MemoryDump_descriptor = - getDescriptor().getMessageTypes().get(4); - internal_static_tensorflow_MemoryDump_fieldAccessorTable = new - com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( - internal_static_tensorflow_MemoryDump_descriptor, - new java.lang.String[] { "AllocatorName", "BinSummary", "Chunk", "SnapShot", "Stats", }); - } - - // @@protoc_insertion_point(outer_class_scope) -} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BuildConfiguration.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BuildConfiguration.java deleted file mode 100644 index 8e3f0c9e7b5..00000000000 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BuildConfiguration.java +++ /dev/null @@ -1,1044 +0,0 @@ -// Generated by the protocol buffer compiler. DO NOT EDIT! -// source: tsl/protobuf/test_log.proto - -package org.tensorflow.proto; - -/** - * Protobuf type {@code tensorflow.BuildConfiguration} - */ -public final class BuildConfiguration extends - com.google.protobuf.GeneratedMessageV3 implements - // @@protoc_insertion_point(message_implements:tensorflow.BuildConfiguration) - BuildConfigurationOrBuilder { -private static final long serialVersionUID = 0L; - // Use BuildConfiguration.newBuilder() to construct. - private BuildConfiguration(com.google.protobuf.GeneratedMessageV3.Builder builder) { - super(builder); - } - private BuildConfiguration() { - mode_ = ""; - ccFlags_ = com.google.protobuf.LazyStringArrayList.EMPTY; - opts_ = com.google.protobuf.LazyStringArrayList.EMPTY; - } - - @java.lang.Override - @SuppressWarnings({"unused"}) - protected java.lang.Object newInstance( - UnusedPrivateParameter unused) { - return new BuildConfiguration(); - } - - @java.lang.Override - public final com.google.protobuf.UnknownFieldSet - getUnknownFields() { - return this.unknownFields; - } - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BuildConfiguration_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BuildConfiguration_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BuildConfiguration.class, org.tensorflow.proto.BuildConfiguration.Builder.class); - } - - public static final int MODE_FIELD_NUMBER = 1; - private volatile java.lang.Object mode_; - /** - * 
-   * opt, dbg, etc
-   *
- * - * string mode = 1; - * @return The mode. - */ - @java.lang.Override - public java.lang.String getMode() { - java.lang.Object ref = mode_; - if (ref instanceof java.lang.String) { - return (java.lang.String) ref; - } else { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - mode_ = s; - return s; - } - } - /** - * 
-   * opt, dbg, etc
-   *
- * - * string mode = 1; - * @return The bytes for mode. - */ - @java.lang.Override - public com.google.protobuf.ByteString - getModeBytes() { - java.lang.Object ref = mode_; - if (ref instanceof java.lang.String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - mode_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - - public static final int CC_FLAGS_FIELD_NUMBER = 2; - private com.google.protobuf.LazyStringList ccFlags_; - /** - * 
-   * CC compiler flags, if known
-   *
- * - * repeated string cc_flags = 2; - * @return A list containing the ccFlags. - */ - public com.google.protobuf.ProtocolStringList - getCcFlagsList() { - return ccFlags_; - } - /** - * 
-   * CC compiler flags, if known
-   *
- * - * repeated string cc_flags = 2; - * @return The count of ccFlags. - */ - public int getCcFlagsCount() { - return ccFlags_.size(); - } - /** - * 
-   * CC compiler flags, if known
-   *
- * - * repeated string cc_flags = 2; - * @param index The index of the element to return. - * @return The ccFlags at the given index. - */ - public java.lang.String getCcFlags(int index) { - return ccFlags_.get(index); - } - /** - * 
-   * CC compiler flags, if known
-   *
- * - * repeated string cc_flags = 2; - * @param index The index of the value to return. - * @return The bytes of the ccFlags at the given index. - */ - public com.google.protobuf.ByteString - getCcFlagsBytes(int index) { - return ccFlags_.getByteString(index); - } - - public static final int OPTS_FIELD_NUMBER = 3; - private com.google.protobuf.LazyStringList opts_; - /** - * 
-   * Bazel compilation options, if known
-   *
- * - * repeated string opts = 3; - * @return A list containing the opts. - */ - public com.google.protobuf.ProtocolStringList - getOptsList() { - return opts_; - } - /** - * 
-   * Bazel compilation options, if known
-   *
- * - * repeated string opts = 3; - * @return The count of opts. - */ - public int getOptsCount() { - return opts_.size(); - } - /** - * 
-   * Bazel compilation options, if known
-   *
- * - * repeated string opts = 3; - * @param index The index of the element to return. - * @return The opts at the given index. - */ - public java.lang.String getOpts(int index) { - return opts_.get(index); - } - /** - * 
-   * Bazel compilation options, if known
-   *
- * - * repeated string opts = 3; - * @param index The index of the value to return. - * @return The bytes of the opts at the given index. - */ - public com.google.protobuf.ByteString - getOptsBytes(int index) { - return opts_.getByteString(index); - } - - private byte memoizedIsInitialized = -1; - @java.lang.Override - public final boolean isInitialized() { - byte isInitialized = memoizedIsInitialized; - if (isInitialized == 1) return true; - if (isInitialized == 0) return false; - - memoizedIsInitialized = 1; - return true; - } - - @java.lang.Override - public void writeTo(com.google.protobuf.CodedOutputStream output) - throws java.io.IOException { - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(mode_)) { - com.google.protobuf.GeneratedMessageV3.writeString(output, 1, mode_); - } - for (int i = 0; i < ccFlags_.size(); i++) { - com.google.protobuf.GeneratedMessageV3.writeString(output, 2, ccFlags_.getRaw(i)); - } - for (int i = 0; i < opts_.size(); i++) { - com.google.protobuf.GeneratedMessageV3.writeString(output, 3, opts_.getRaw(i)); - } - getUnknownFields().writeTo(output); - } - - @java.lang.Override - public int getSerializedSize() { - int size = memoizedSize; - if (size != -1) return size; - - size = 0; - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(mode_)) { - size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, mode_); - } - { - int dataSize = 0; - for (int i = 0; i < ccFlags_.size(); i++) { - dataSize += computeStringSizeNoTag(ccFlags_.getRaw(i)); - } - size += dataSize; - size += 1 * getCcFlagsList().size(); - } - { - int dataSize = 0; - for (int i = 0; i < opts_.size(); i++) { - dataSize += computeStringSizeNoTag(opts_.getRaw(i)); - } - size += dataSize; - size += 1 * getOptsList().size(); - } - size += getUnknownFields().getSerializedSize(); - memoizedSize = size; - return size; - } - - @java.lang.Override - public boolean equals(final java.lang.Object obj) { - if (obj == this) { - return true; - } - if (!(obj instanceof org.tensorflow.proto.BuildConfiguration)) { - return super.equals(obj); - } - org.tensorflow.proto.BuildConfiguration other = (org.tensorflow.proto.BuildConfiguration) obj; - - if (!getMode() - .equals(other.getMode())) return false; - if (!getCcFlagsList() - .equals(other.getCcFlagsList())) return false; - if (!getOptsList() - .equals(other.getOptsList())) return false; - if (!getUnknownFields().equals(other.getUnknownFields())) return false; - return true; - } - - @java.lang.Override - public int hashCode() { - if (memoizedHashCode != 0) { - return memoizedHashCode; - } - int hash = 41; - hash = (19 * hash) + getDescriptor().hashCode(); - hash = (37 * hash) + MODE_FIELD_NUMBER; - hash = (53 * hash) + getMode().hashCode(); - if (getCcFlagsCount() > 0) { - hash = (37 * hash) + CC_FLAGS_FIELD_NUMBER; - hash = (53 * hash) + getCcFlagsList().hashCode(); - } - if (getOptsCount() > 0) { - hash = (37 * hash) + OPTS_FIELD_NUMBER; - hash = (53 * hash) + getOptsList().hashCode(); - } - hash = (29 * hash) + getUnknownFields().hashCode(); - memoizedHashCode = hash; - return hash; - } - - public static org.tensorflow.proto.BuildConfiguration parseFrom( - java.nio.ByteBuffer data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BuildConfiguration parseFrom( - java.nio.ByteBuffer data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BuildConfiguration parseFrom( - com.google.protobuf.ByteString data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BuildConfiguration parseFrom( - com.google.protobuf.ByteString data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BuildConfiguration parseFrom(byte[] data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.BuildConfiguration parseFrom( - byte[] data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.BuildConfiguration parseFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BuildConfiguration parseFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BuildConfiguration parseDelimitedFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BuildConfiguration parseDelimitedFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.BuildConfiguration parseFrom( - com.google.protobuf.CodedInputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.BuildConfiguration parseFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - - @java.lang.Override - public Builder newBuilderForType() { return newBuilder(); } - public static Builder newBuilder() { - return DEFAULT_INSTANCE.toBuilder(); - } - public static Builder newBuilder(org.tensorflow.proto.BuildConfiguration prototype) { - return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); - } - @java.lang.Override - public Builder toBuilder() { - return this == DEFAULT_INSTANCE - ? new Builder() : new Builder().mergeFrom(this); - } - - @java.lang.Override - protected Builder newBuilderForType( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - Builder builder = new Builder(parent); - return builder; - } - /** - * Protobuf type {@code tensorflow.BuildConfiguration} - */ - public static final class Builder extends - com.google.protobuf.GeneratedMessageV3.Builder implements - // @@protoc_insertion_point(builder_implements:tensorflow.BuildConfiguration) - org.tensorflow.proto.BuildConfigurationOrBuilder { - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BuildConfiguration_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BuildConfiguration_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.BuildConfiguration.class, org.tensorflow.proto.BuildConfiguration.Builder.class); - } - - // Construct using org.tensorflow.proto.BuildConfiguration.newBuilder() - private Builder() { - - } - - private Builder( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - super(parent); - - } - @java.lang.Override - public Builder clear() { - super.clear(); - mode_ = ""; - - ccFlags_ = com.google.protobuf.LazyStringArrayList.EMPTY; - bitField0_ = (bitField0_ & ~0x00000001); - opts_ = com.google.protobuf.LazyStringArrayList.EMPTY; - bitField0_ = (bitField0_ & ~0x00000002); - return this; - } - - @java.lang.Override - public com.google.protobuf.Descriptors.Descriptor - getDescriptorForType() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BuildConfiguration_descriptor; - } - - @java.lang.Override - public org.tensorflow.proto.BuildConfiguration getDefaultInstanceForType() { - return org.tensorflow.proto.BuildConfiguration.getDefaultInstance(); - } - - @java.lang.Override - public org.tensorflow.proto.BuildConfiguration build() { - org.tensorflow.proto.BuildConfiguration result = buildPartial(); - if (!result.isInitialized()) { - throw newUninitializedMessageException(result); - } - return result; - } - - @java.lang.Override - public org.tensorflow.proto.BuildConfiguration buildPartial() { - org.tensorflow.proto.BuildConfiguration result = new org.tensorflow.proto.BuildConfiguration(this); - int from_bitField0_ = bitField0_; - result.mode_ = mode_; - if (((bitField0_ & 0x00000001) != 0)) { - ccFlags_ = ccFlags_.getUnmodifiableView(); - bitField0_ = (bitField0_ & ~0x00000001); - } - result.ccFlags_ = ccFlags_; - if (((bitField0_ & 0x00000002) != 0)) { - opts_ = opts_.getUnmodifiableView(); - bitField0_ = (bitField0_ & ~0x00000002); - } - result.opts_ = opts_; - onBuilt(); - return result; - } - - @java.lang.Override - public Builder clone() { - return super.clone(); - } - @java.lang.Override - public Builder setField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.setField(field, value); - } - @java.lang.Override - public Builder clearField( - com.google.protobuf.Descriptors.FieldDescriptor field) { - return super.clearField(field); - } - @java.lang.Override - public Builder clearOneof( - com.google.protobuf.Descriptors.OneofDescriptor oneof) { - return super.clearOneof(oneof); - } - @java.lang.Override - public Builder setRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - int index, java.lang.Object value) { - return super.setRepeatedField(field, index, value); - } - @java.lang.Override - public Builder addRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.addRepeatedField(field, value); - } - @java.lang.Override - public Builder mergeFrom(com.google.protobuf.Message other) { - if (other instanceof org.tensorflow.proto.BuildConfiguration) { - return mergeFrom((org.tensorflow.proto.BuildConfiguration)other); - } else { - super.mergeFrom(other); - return this; - } - } - - public Builder mergeFrom(org.tensorflow.proto.BuildConfiguration other) { - if (other == org.tensorflow.proto.BuildConfiguration.getDefaultInstance()) return this; - if (!other.getMode().isEmpty()) { - mode_ = other.mode_; - onChanged(); - } - if (!other.ccFlags_.isEmpty()) { - if (ccFlags_.isEmpty()) { - ccFlags_ = other.ccFlags_; - bitField0_ = (bitField0_ & ~0x00000001); - } else { - ensureCcFlagsIsMutable(); - ccFlags_.addAll(other.ccFlags_); - } - onChanged(); - } - if (!other.opts_.isEmpty()) { - if (opts_.isEmpty()) { - opts_ = other.opts_; - bitField0_ = (bitField0_ & ~0x00000002); - } else { - ensureOptsIsMutable(); - opts_.addAll(other.opts_); - } - onChanged(); - } - this.mergeUnknownFields(other.getUnknownFields()); - onChanged(); - return this; - } - - @java.lang.Override - public final boolean isInitialized() { - return true; - } - - @java.lang.Override - public Builder mergeFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - if (extensionRegistry == null) { - throw new java.lang.NullPointerException(); - } - try { - boolean done = false; - while (!done) { - int tag = input.readTag(); - switch (tag) { - case 0: - done = true; - break; - case 10: { - mode_ = input.readStringRequireUtf8(); - - break; - } // case 10 - case 18: { - java.lang.String s = input.readStringRequireUtf8(); - ensureCcFlagsIsMutable(); - ccFlags_.add(s); - break; - } // case 18 - case 26: { - java.lang.String s = input.readStringRequireUtf8(); - ensureOptsIsMutable(); - opts_.add(s); - break; - } // case 26 - default: { - if (!super.parseUnknownField(input, extensionRegistry, tag)) { - done = true; // was an endgroup tag - } - break; - } // default: - } // switch (tag) - } // while (!done) - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.unwrapIOException(); - } finally { - onChanged(); - } // finally - return this; - } - private int bitField0_; - - private java.lang.Object mode_ = ""; - /** - * 
-     * opt, dbg, etc
-     *
- * - * string mode = 1; - * @return The mode. - */ - public java.lang.String getMode() { - java.lang.Object ref = mode_; - if (!(ref instanceof java.lang.String)) { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - mode_ = s; - return s; - } else { - return (java.lang.String) ref; - } - } - /** - * 
-     * opt, dbg, etc
-     *
- * - * string mode = 1; - * @return The bytes for mode. - */ - public com.google.protobuf.ByteString - getModeBytes() { - java.lang.Object ref = mode_; - if (ref instanceof String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - mode_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - /** - * 
-     * opt, dbg, etc
-     *
- * - * string mode = 1; - * @param value The mode to set. - * @return This builder for chaining. - */ - public Builder setMode( - java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - - mode_ = value; - onChanged(); - return this; - } - /** - * 
-     * opt, dbg, etc
-     *
- * - * string mode = 1; - * @return This builder for chaining. - */ - public Builder clearMode() { - - mode_ = getDefaultInstance().getMode(); - onChanged(); - return this; - } - /** - * 
-     * opt, dbg, etc
-     *
- * - * string mode = 1; - * @param value The bytes for mode to set. - * @return This builder for chaining. - */ - public Builder setModeBytes( - com.google.protobuf.ByteString value) { - if (value == null) { - throw new NullPointerException(); - } - checkByteStringIsUtf8(value); - - mode_ = value; - onChanged(); - return this; - } - - private com.google.protobuf.LazyStringList ccFlags_ = com.google.protobuf.LazyStringArrayList.EMPTY; - private void ensureCcFlagsIsMutable() { - if (!((bitField0_ & 0x00000001) != 0)) { - ccFlags_ = new com.google.protobuf.LazyStringArrayList(ccFlags_); - bitField0_ |= 0x00000001; - } - } - /** - * 
-     * CC compiler flags, if known
-     *
- * - * repeated string cc_flags = 2; - * @return A list containing the ccFlags. - */ - public com.google.protobuf.ProtocolStringList - getCcFlagsList() { - return ccFlags_.getUnmodifiableView(); - } - /** - * 
-     * CC compiler flags, if known
-     *
- * - * repeated string cc_flags = 2; - * @return The count of ccFlags. - */ - public int getCcFlagsCount() { - return ccFlags_.size(); - } - /** - * 
-     * CC compiler flags, if known
-     *
- * - * repeated string cc_flags = 2; - * @param index The index of the element to return. - * @return The ccFlags at the given index. - */ - public java.lang.String getCcFlags(int index) { - return ccFlags_.get(index); - } - /** - * 
-     * CC compiler flags, if known
-     *
- * - * repeated string cc_flags = 2; - * @param index The index of the value to return. - * @return The bytes of the ccFlags at the given index. - */ - public com.google.protobuf.ByteString - getCcFlagsBytes(int index) { - return ccFlags_.getByteString(index); - } - /** - * 
-     * CC compiler flags, if known
-     *
- * - * repeated string cc_flags = 2; - * @param index The index to set the value at. - * @param value The ccFlags to set. - * @return This builder for chaining. - */ - public Builder setCcFlags( - int index, java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - ensureCcFlagsIsMutable(); - ccFlags_.set(index, value); - onChanged(); - return this; - } - /** - * 
-     * CC compiler flags, if known
-     *
- * - * repeated string cc_flags = 2; - * @param value The ccFlags to add. - * @return This builder for chaining. - */ - public Builder addCcFlags( - java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - ensureCcFlagsIsMutable(); - ccFlags_.add(value); - onChanged(); - return this; - } - /** - * 
-     * CC compiler flags, if known
-     *
- * - * repeated string cc_flags = 2; - * @param values The ccFlags to add. - * @return This builder for chaining. - */ - public Builder addAllCcFlags( - java.lang.Iterable values) { - ensureCcFlagsIsMutable(); - com.google.protobuf.AbstractMessageLite.Builder.addAll( - values, ccFlags_); - onChanged(); - return this; - } - /** - * 
-     * CC compiler flags, if known
-     *
- * - * repeated string cc_flags = 2; - * @return This builder for chaining. - */ - public Builder clearCcFlags() { - ccFlags_ = com.google.protobuf.LazyStringArrayList.EMPTY; - bitField0_ = (bitField0_ & ~0x00000001); - onChanged(); - return this; - } - /** - * 
-     * CC compiler flags, if known
-     *
- * - * repeated string cc_flags = 2; - * @param value The bytes of the ccFlags to add. - * @return This builder for chaining. - */ - public Builder addCcFlagsBytes( - com.google.protobuf.ByteString value) { - if (value == null) { - throw new NullPointerException(); - } - checkByteStringIsUtf8(value); - ensureCcFlagsIsMutable(); - ccFlags_.add(value); - onChanged(); - return this; - } - - private com.google.protobuf.LazyStringList opts_ = com.google.protobuf.LazyStringArrayList.EMPTY; - private void ensureOptsIsMutable() { - if (!((bitField0_ & 0x00000002) != 0)) { - opts_ = new com.google.protobuf.LazyStringArrayList(opts_); - bitField0_ |= 0x00000002; - } - } - /** - * 
-     * Bazel compilation options, if known
-     *
- * - * repeated string opts = 3; - * @return A list containing the opts. - */ - public com.google.protobuf.ProtocolStringList - getOptsList() { - return opts_.getUnmodifiableView(); - } - /** - * 
-     * Bazel compilation options, if known
-     *
- * - * repeated string opts = 3; - * @return The count of opts. - */ - public int getOptsCount() { - return opts_.size(); - } - /** - * 
-     * Bazel compilation options, if known
-     *
- * - * repeated string opts = 3; - * @param index The index of the element to return. - * @return The opts at the given index. - */ - public java.lang.String getOpts(int index) { - return opts_.get(index); - } - /** - * 
-     * Bazel compilation options, if known
-     *
- * - * repeated string opts = 3; - * @param index The index of the value to return. - * @return The bytes of the opts at the given index. - */ - public com.google.protobuf.ByteString - getOptsBytes(int index) { - return opts_.getByteString(index); - } - /** - * 
-     * Bazel compilation options, if known
-     *
- * - * repeated string opts = 3; - * @param index The index to set the value at. - * @param value The opts to set. - * @return This builder for chaining. - */ - public Builder setOpts( - int index, java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - ensureOptsIsMutable(); - opts_.set(index, value); - onChanged(); - return this; - } - /** - * 
-     * Bazel compilation options, if known
-     *
- * - * repeated string opts = 3; - * @param value The opts to add. - * @return This builder for chaining. - */ - public Builder addOpts( - java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - ensureOptsIsMutable(); - opts_.add(value); - onChanged(); - return this; - } - /** - * 
-     * Bazel compilation options, if known
-     *
- * - * repeated string opts = 3; - * @param values The opts to add. - * @return This builder for chaining. - */ - public Builder addAllOpts( - java.lang.Iterable values) { - ensureOptsIsMutable(); - com.google.protobuf.AbstractMessageLite.Builder.addAll( - values, opts_); - onChanged(); - return this; - } - /** - * 
-     * Bazel compilation options, if known
-     *
- * - * repeated string opts = 3; - * @return This builder for chaining. - */ - public Builder clearOpts() { - opts_ = com.google.protobuf.LazyStringArrayList.EMPTY; - bitField0_ = (bitField0_ & ~0x00000002); - onChanged(); - return this; - } - /** - * 
-     * Bazel compilation options, if known
-     *
- * - * repeated string opts = 3; - * @param value The bytes of the opts to add. - * @return This builder for chaining. - */ - public Builder addOptsBytes( - com.google.protobuf.ByteString value) { - if (value == null) { - throw new NullPointerException(); - } - checkByteStringIsUtf8(value); - ensureOptsIsMutable(); - opts_.add(value); - onChanged(); - return this; - } - @java.lang.Override - public final Builder setUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.setUnknownFields(unknownFields); - } - - @java.lang.Override - public final Builder mergeUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.mergeUnknownFields(unknownFields); - } - - - // @@protoc_insertion_point(builder_scope:tensorflow.BuildConfiguration) - } - - // @@protoc_insertion_point(class_scope:tensorflow.BuildConfiguration) - private static final org.tensorflow.proto.BuildConfiguration DEFAULT_INSTANCE; - static { - DEFAULT_INSTANCE = new org.tensorflow.proto.BuildConfiguration(); - } - - public static org.tensorflow.proto.BuildConfiguration getDefaultInstance() { - return DEFAULT_INSTANCE; - } - - private static final com.google.protobuf.Parser - PARSER = new com.google.protobuf.AbstractParser() { - @java.lang.Override - public BuildConfiguration parsePartialFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - Builder builder = newBuilder(); - try { - builder.mergeFrom(input, extensionRegistry); - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.setUnfinishedMessage(builder.buildPartial()); - } catch (com.google.protobuf.UninitializedMessageException e) { - throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); - } catch (java.io.IOException e) { - throw new com.google.protobuf.InvalidProtocolBufferException(e) - .setUnfinishedMessage(builder.buildPartial()); - } - return builder.buildPartial(); - } - }; - - public static com.google.protobuf.Parser parser() { - return PARSER; - } - - @java.lang.Override - public com.google.protobuf.Parser getParserForType() { - return PARSER; - } - - @java.lang.Override - public org.tensorflow.proto.BuildConfiguration getDefaultInstanceForType() { - return DEFAULT_INSTANCE; - } - -} - diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BuildConfigurationOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BuildConfigurationOrBuilder.java deleted file mode 100644 index 0f4bc0c0740..00000000000 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BuildConfigurationOrBuilder.java +++ /dev/null @@ -1,111 +0,0 @@ -// Generated by the protocol buffer compiler. DO NOT EDIT! -// source: tsl/protobuf/test_log.proto - -package org.tensorflow.proto; - -public interface BuildConfigurationOrBuilder extends - // @@protoc_insertion_point(interface_extends:tensorflow.BuildConfiguration) - com.google.protobuf.MessageOrBuilder { - - /** - * 
-   * opt, dbg, etc
-   *
- * - * string mode = 1; - * @return The mode. - */ - java.lang.String getMode(); - /** - * 
-   * opt, dbg, etc
-   *
- * - * string mode = 1; - * @return The bytes for mode. - */ - com.google.protobuf.ByteString - getModeBytes(); - - /** - * 
-   * CC compiler flags, if known
-   *
- * - * repeated string cc_flags = 2; - * @return A list containing the ccFlags. - */ - java.util.List - getCcFlagsList(); - /** - * 
-   * CC compiler flags, if known
-   *
- * - * repeated string cc_flags = 2; - * @return The count of ccFlags. - */ - int getCcFlagsCount(); - /** - * 
-   * CC compiler flags, if known
-   *
- * - * repeated string cc_flags = 2; - * @param index The index of the element to return. - * @return The ccFlags at the given index. - */ - java.lang.String getCcFlags(int index); - /** - * 
-   * CC compiler flags, if known
-   *
- * - * repeated string cc_flags = 2; - * @param index The index of the value to return. - * @return The bytes of the ccFlags at the given index. - */ - com.google.protobuf.ByteString - getCcFlagsBytes(int index); - - /** - * 
-   * Bazel compilation options, if known
-   *
- * - * repeated string opts = 3; - * @return A list containing the opts. - */ - java.util.List - getOptsList(); - /** - * 
-   * Bazel compilation options, if known
-   *
- * - * repeated string opts = 3; - * @return The count of opts. - */ - int getOptsCount(); - /** - * 
-   * Bazel compilation options, if known
-   *
- * - * repeated string opts = 3; - * @param index The index of the element to return. - * @return The opts at the given index. - */ - java.lang.String getOpts(int index); - /** - * 
-   * Bazel compilation options, if known
-   *
- * - * repeated string opts = 3; - * @param index The index of the value to return. - * @return The bytes of the opts at the given index. - */ - com.google.protobuf.ByteString - getOptsBytes(int index); -} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CPUInfo.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CPUInfo.java deleted file mode 100644 index 906c5e01a83..00000000000 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CPUInfo.java +++ /dev/null @@ -1,1281 +0,0 @@ -// Generated by the protocol buffer compiler. DO NOT EDIT! -// source: tsl/protobuf/test_log.proto - -package org.tensorflow.proto; - -/** - * Protobuf type {@code tensorflow.CPUInfo} - */ -public final class CPUInfo extends - com.google.protobuf.GeneratedMessageV3 implements - // @@protoc_insertion_point(message_implements:tensorflow.CPUInfo) - CPUInfoOrBuilder { -private static final long serialVersionUID = 0L; - // Use CPUInfo.newBuilder() to construct. - private CPUInfo(com.google.protobuf.GeneratedMessageV3.Builder builder) { - super(builder); - } - private CPUInfo() { - cpuInfo_ = ""; - cpuGovernor_ = ""; - } - - @java.lang.Override - @SuppressWarnings({"unused"}) - protected java.lang.Object newInstance( - UnusedPrivateParameter unused) { - return new CPUInfo(); - } - - @java.lang.Override - public final com.google.protobuf.UnknownFieldSet - getUnknownFields() { - return this.unknownFields; - } - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CPUInfo_descriptor; - } - - @SuppressWarnings({"rawtypes"}) - @java.lang.Override - protected com.google.protobuf.MapField internalGetMapField( - int number) { - switch (number) { - case 6: - return internalGetCacheSize(); - default: - throw new RuntimeException( - "Invalid map field number: " + number); - } - } - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CPUInfo_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.CPUInfo.class, org.tensorflow.proto.CPUInfo.Builder.class); - } - - public static final int NUM_CORES_FIELD_NUMBER = 1; - private long numCores_; - /** - * int64 num_cores = 1; - * @return The numCores. - */ - @java.lang.Override - public long getNumCores() { - return numCores_; - } - - public static final int NUM_CORES_ALLOWED_FIELD_NUMBER = 2; - private long numCoresAllowed_; - /** - * int64 num_cores_allowed = 2; - * @return The numCoresAllowed. - */ - @java.lang.Override - public long getNumCoresAllowed() { - return numCoresAllowed_; - } - - public static final int MHZ_PER_CPU_FIELD_NUMBER = 3; - private double mhzPerCpu_; - /** - * 
-   * How fast are these cpus?
-   *
- * - * double mhz_per_cpu = 3; - * @return The mhzPerCpu. - */ - @java.lang.Override - public double getMhzPerCpu() { - return mhzPerCpu_; - } - - public static final int CPU_INFO_FIELD_NUMBER = 4; - private volatile java.lang.Object cpuInfo_; - /** - * 
-   * Additional cpu information. For example,
-   * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
-   *
- * - * string cpu_info = 4; - * @return The cpuInfo. - */ - @java.lang.Override - public java.lang.String getCpuInfo() { - java.lang.Object ref = cpuInfo_; - if (ref instanceof java.lang.String) { - return (java.lang.String) ref; - } else { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - cpuInfo_ = s; - return s; - } - } - /** - * 
-   * Additional cpu information. For example,
-   * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
-   *
- * - * string cpu_info = 4; - * @return The bytes for cpuInfo. - */ - @java.lang.Override - public com.google.protobuf.ByteString - getCpuInfoBytes() { - java.lang.Object ref = cpuInfo_; - if (ref instanceof java.lang.String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - cpuInfo_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - - public static final int CPU_GOVERNOR_FIELD_NUMBER = 5; - private volatile java.lang.Object cpuGovernor_; - /** - * 
-   * What kind of cpu scaling is enabled on the host.
-   * Examples include "performance", "ondemand", "conservative", "mixed".
-   *
- * - * string cpu_governor = 5; - * @return The cpuGovernor. - */ - @java.lang.Override - public java.lang.String getCpuGovernor() { - java.lang.Object ref = cpuGovernor_; - if (ref instanceof java.lang.String) { - return (java.lang.String) ref; - } else { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - cpuGovernor_ = s; - return s; - } - } - /** - * 
-   * What kind of cpu scaling is enabled on the host.
-   * Examples include "performance", "ondemand", "conservative", "mixed".
-   *
- * - * string cpu_governor = 5; - * @return The bytes for cpuGovernor. - */ - @java.lang.Override - public com.google.protobuf.ByteString - getCpuGovernorBytes() { - java.lang.Object ref = cpuGovernor_; - if (ref instanceof java.lang.String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - cpuGovernor_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - - public static final int CACHE_SIZE_FIELD_NUMBER = 6; - private static final class CacheSizeDefaultEntryHolder { - static final com.google.protobuf.MapEntry< - java.lang.String, java.lang.Long> defaultEntry = - com.google.protobuf.MapEntry - .newDefaultInstance( - org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CPUInfo_CacheSizeEntry_descriptor, - com.google.protobuf.WireFormat.FieldType.STRING, - "", - com.google.protobuf.WireFormat.FieldType.INT64, - 0L); - } - private com.google.protobuf.MapField< - java.lang.String, java.lang.Long> cacheSize_; - private com.google.protobuf.MapField - internalGetCacheSize() { - if (cacheSize_ == null) { - return com.google.protobuf.MapField.emptyMapField( - CacheSizeDefaultEntryHolder.defaultEntry); - } - return cacheSize_; - } - - public int getCacheSizeCount() { - return internalGetCacheSize().getMap().size(); - } - /** - * 
-   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-   *
- * - * map<string, int64> cache_size = 6; - */ - - @java.lang.Override - public boolean containsCacheSize( - java.lang.String key) { - if (key == null) { throw new NullPointerException("map key"); } - return internalGetCacheSize().getMap().containsKey(key); - } - /** - * Use {@link #getCacheSizeMap()} instead. - */ - @java.lang.Override - @java.lang.Deprecated - public java.util.Map getCacheSize() { - return getCacheSizeMap(); - } - /** - * 
-   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-   *
- * - * map<string, int64> cache_size = 6; - */ - @java.lang.Override - - public java.util.Map getCacheSizeMap() { - return internalGetCacheSize().getMap(); - } - /** - * 
-   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-   *
- * - * map<string, int64> cache_size = 6; - */ - @java.lang.Override - - public long getCacheSizeOrDefault( - java.lang.String key, - long defaultValue) { - if (key == null) { throw new NullPointerException("map key"); } - java.util.Map map = - internalGetCacheSize().getMap(); - return map.containsKey(key) ? map.get(key) : defaultValue; - } - /** - * 
-   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-   *
- * - * map<string, int64> cache_size = 6; - */ - @java.lang.Override - - public long getCacheSizeOrThrow( - java.lang.String key) { - if (key == null) { throw new NullPointerException("map key"); } - java.util.Map map = - internalGetCacheSize().getMap(); - if (!map.containsKey(key)) { - throw new java.lang.IllegalArgumentException(); - } - return map.get(key); - } - - private byte memoizedIsInitialized = -1; - @java.lang.Override - public final boolean isInitialized() { - byte isInitialized = memoizedIsInitialized; - if (isInitialized == 1) return true; - if (isInitialized == 0) return false; - - memoizedIsInitialized = 1; - return true; - } - - @java.lang.Override - public void writeTo(com.google.protobuf.CodedOutputStream output) - throws java.io.IOException { - if (numCores_ != 0L) { - output.writeInt64(1, numCores_); - } - if (numCoresAllowed_ != 0L) { - output.writeInt64(2, numCoresAllowed_); - } - if (java.lang.Double.doubleToRawLongBits(mhzPerCpu_) != 0) { - output.writeDouble(3, mhzPerCpu_); - } - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(cpuInfo_)) { - com.google.protobuf.GeneratedMessageV3.writeString(output, 4, cpuInfo_); - } - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(cpuGovernor_)) { - com.google.protobuf.GeneratedMessageV3.writeString(output, 5, cpuGovernor_); - } - com.google.protobuf.GeneratedMessageV3 - .serializeStringMapTo( - output, - internalGetCacheSize(), - CacheSizeDefaultEntryHolder.defaultEntry, - 6); - getUnknownFields().writeTo(output); - } - - @java.lang.Override - public int getSerializedSize() { - int size = memoizedSize; - if (size != -1) return size; - - size = 0; - if (numCores_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(1, numCores_); - } - if (numCoresAllowed_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(2, numCoresAllowed_); - } - if (java.lang.Double.doubleToRawLongBits(mhzPerCpu_) != 0) { - size += com.google.protobuf.CodedOutputStream - .computeDoubleSize(3, mhzPerCpu_); - } - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(cpuInfo_)) { - size += com.google.protobuf.GeneratedMessageV3.computeStringSize(4, cpuInfo_); - } - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(cpuGovernor_)) { - size += com.google.protobuf.GeneratedMessageV3.computeStringSize(5, cpuGovernor_); - } - for (java.util.Map.Entry entry - : internalGetCacheSize().getMap().entrySet()) { - com.google.protobuf.MapEntry - cacheSize__ = CacheSizeDefaultEntryHolder.defaultEntry.newBuilderForType() - .setKey(entry.getKey()) - .setValue(entry.getValue()) - .build(); - size += com.google.protobuf.CodedOutputStream - .computeMessageSize(6, cacheSize__); - } - size += getUnknownFields().getSerializedSize(); - memoizedSize = size; - return size; - } - - @java.lang.Override - public boolean equals(final java.lang.Object obj) { - if (obj == this) { - return true; - } - if (!(obj instanceof org.tensorflow.proto.CPUInfo)) { - return super.equals(obj); - } - org.tensorflow.proto.CPUInfo other = (org.tensorflow.proto.CPUInfo) obj; - - if (getNumCores() - != other.getNumCores()) return false; - if (getNumCoresAllowed() - != other.getNumCoresAllowed()) return false; - if (java.lang.Double.doubleToLongBits(getMhzPerCpu()) - != java.lang.Double.doubleToLongBits( - other.getMhzPerCpu())) return false; - if (!getCpuInfo() - .equals(other.getCpuInfo())) return false; - if (!getCpuGovernor() - .equals(other.getCpuGovernor())) return false; - if (!internalGetCacheSize().equals( - other.internalGetCacheSize())) return false; - if (!getUnknownFields().equals(other.getUnknownFields())) return false; - return true; - } - - @java.lang.Override - public int hashCode() { - if (memoizedHashCode != 0) { - return memoizedHashCode; - } - int hash = 41; - hash = (19 * hash) + getDescriptor().hashCode(); - hash = (37 * hash) + NUM_CORES_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getNumCores()); - hash = (37 * hash) + NUM_CORES_ALLOWED_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getNumCoresAllowed()); - hash = (37 * hash) + MHZ_PER_CPU_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - java.lang.Double.doubleToLongBits(getMhzPerCpu())); - hash = (37 * hash) + CPU_INFO_FIELD_NUMBER; - hash = (53 * hash) + getCpuInfo().hashCode(); - hash = (37 * hash) + CPU_GOVERNOR_FIELD_NUMBER; - hash = (53 * hash) + getCpuGovernor().hashCode(); - if (!internalGetCacheSize().getMap().isEmpty()) { - hash = (37 * hash) + CACHE_SIZE_FIELD_NUMBER; - hash = (53 * hash) + internalGetCacheSize().hashCode(); - } - hash = (29 * hash) + getUnknownFields().hashCode(); - memoizedHashCode = hash; - return hash; - } - - public static org.tensorflow.proto.CPUInfo parseFrom( - java.nio.ByteBuffer data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.CPUInfo parseFrom( - java.nio.ByteBuffer data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.CPUInfo parseFrom( - com.google.protobuf.ByteString data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.CPUInfo parseFrom( - com.google.protobuf.ByteString data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.CPUInfo parseFrom(byte[] data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.CPUInfo parseFrom( - byte[] data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.CPUInfo parseFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.CPUInfo parseFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.CPUInfo parseDelimitedFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input); - } - public static org.tensorflow.proto.CPUInfo parseDelimitedFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.CPUInfo parseFrom( - com.google.protobuf.CodedInputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.CPUInfo parseFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - - @java.lang.Override - public Builder newBuilderForType() { return newBuilder(); } - public static Builder newBuilder() { - return DEFAULT_INSTANCE.toBuilder(); - } - public static Builder newBuilder(org.tensorflow.proto.CPUInfo prototype) { - return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); - } - @java.lang.Override - public Builder toBuilder() { - return this == DEFAULT_INSTANCE - ? new Builder() : new Builder().mergeFrom(this); - } - - @java.lang.Override - protected Builder newBuilderForType( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - Builder builder = new Builder(parent); - return builder; - } - /** - * Protobuf type {@code tensorflow.CPUInfo} - */ - public static final class Builder extends - com.google.protobuf.GeneratedMessageV3.Builder implements - // @@protoc_insertion_point(builder_implements:tensorflow.CPUInfo) - org.tensorflow.proto.CPUInfoOrBuilder { - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CPUInfo_descriptor; - } - - @SuppressWarnings({"rawtypes"}) - protected com.google.protobuf.MapField internalGetMapField( - int number) { - switch (number) { - case 6: - return internalGetCacheSize(); - default: - throw new RuntimeException( - "Invalid map field number: " + number); - } - } - @SuppressWarnings({"rawtypes"}) - protected com.google.protobuf.MapField internalGetMutableMapField( - int number) { - switch (number) { - case 6: - return internalGetMutableCacheSize(); - default: - throw new RuntimeException( - "Invalid map field number: " + number); - } - } - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CPUInfo_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.CPUInfo.class, org.tensorflow.proto.CPUInfo.Builder.class); - } - - // Construct using org.tensorflow.proto.CPUInfo.newBuilder() - private Builder() { - - } - - private Builder( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - super(parent); - - } - @java.lang.Override - public Builder clear() { - super.clear(); - numCores_ = 0L; - - numCoresAllowed_ = 0L; - - mhzPerCpu_ = 0D; - - cpuInfo_ = ""; - - cpuGovernor_ = ""; - - internalGetMutableCacheSize().clear(); - return this; - } - - @java.lang.Override - public com.google.protobuf.Descriptors.Descriptor - getDescriptorForType() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CPUInfo_descriptor; - } - - @java.lang.Override - public org.tensorflow.proto.CPUInfo getDefaultInstanceForType() { - return org.tensorflow.proto.CPUInfo.getDefaultInstance(); - } - - @java.lang.Override - public org.tensorflow.proto.CPUInfo build() { - org.tensorflow.proto.CPUInfo result = buildPartial(); - if (!result.isInitialized()) { - throw newUninitializedMessageException(result); - } - return result; - } - - @java.lang.Override - public org.tensorflow.proto.CPUInfo buildPartial() { - org.tensorflow.proto.CPUInfo result = new org.tensorflow.proto.CPUInfo(this); - int from_bitField0_ = bitField0_; - result.numCores_ = numCores_; - result.numCoresAllowed_ = numCoresAllowed_; - result.mhzPerCpu_ = mhzPerCpu_; - result.cpuInfo_ = cpuInfo_; - result.cpuGovernor_ = cpuGovernor_; - result.cacheSize_ = internalGetCacheSize(); - result.cacheSize_.makeImmutable(); - onBuilt(); - return result; - } - - @java.lang.Override - public Builder clone() { - return super.clone(); - } - @java.lang.Override - public Builder setField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.setField(field, value); - } - @java.lang.Override - public Builder clearField( - com.google.protobuf.Descriptors.FieldDescriptor field) { - return super.clearField(field); - } - @java.lang.Override - public Builder clearOneof( - com.google.protobuf.Descriptors.OneofDescriptor oneof) { - return super.clearOneof(oneof); - } - @java.lang.Override - public Builder setRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - int index, java.lang.Object value) { - return super.setRepeatedField(field, index, value); - } - @java.lang.Override - public Builder addRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.addRepeatedField(field, value); - } - @java.lang.Override - public Builder mergeFrom(com.google.protobuf.Message other) { - if (other instanceof org.tensorflow.proto.CPUInfo) { - return mergeFrom((org.tensorflow.proto.CPUInfo)other); - } else { - super.mergeFrom(other); - return this; - } - } - - public Builder mergeFrom(org.tensorflow.proto.CPUInfo other) { - if (other == org.tensorflow.proto.CPUInfo.getDefaultInstance()) return this; - if (other.getNumCores() != 0L) { - setNumCores(other.getNumCores()); - } - if (other.getNumCoresAllowed() != 0L) { - setNumCoresAllowed(other.getNumCoresAllowed()); - } - if (other.getMhzPerCpu() != 0D) { - setMhzPerCpu(other.getMhzPerCpu()); - } - if (!other.getCpuInfo().isEmpty()) { - cpuInfo_ = other.cpuInfo_; - onChanged(); - } - if (!other.getCpuGovernor().isEmpty()) { - cpuGovernor_ = other.cpuGovernor_; - onChanged(); - } - internalGetMutableCacheSize().mergeFrom( - other.internalGetCacheSize()); - this.mergeUnknownFields(other.getUnknownFields()); - onChanged(); - return this; - } - - @java.lang.Override - public final boolean isInitialized() { - return true; - } - - @java.lang.Override - public Builder mergeFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - if (extensionRegistry == null) { - throw new java.lang.NullPointerException(); - } - try { - boolean done = false; - while (!done) { - int tag = input.readTag(); - switch (tag) { - case 0: - done = true; - break; - case 8: { - numCores_ = input.readInt64(); - - break; - } // case 8 - case 16: { - numCoresAllowed_ = input.readInt64(); - - break; - } // case 16 - case 25: { - mhzPerCpu_ = input.readDouble(); - - break; - } // case 25 - case 34: { - cpuInfo_ = input.readStringRequireUtf8(); - - break; - } // case 34 - case 42: { - cpuGovernor_ = input.readStringRequireUtf8(); - - break; - } // case 42 - case 50: { - com.google.protobuf.MapEntry - cacheSize__ = input.readMessage( - CacheSizeDefaultEntryHolder.defaultEntry.getParserForType(), extensionRegistry); - internalGetMutableCacheSize().getMutableMap().put( - cacheSize__.getKey(), cacheSize__.getValue()); - break; - } // case 50 - default: { - if (!super.parseUnknownField(input, extensionRegistry, tag)) { - done = true; // was an endgroup tag - } - break; - } // default: - } // switch (tag) - } // while (!done) - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.unwrapIOException(); - } finally { - onChanged(); - } // finally - return this; - } - private int bitField0_; - - private long numCores_ ; - /** - * int64 num_cores = 1; - * @return The numCores. - */ - @java.lang.Override - public long getNumCores() { - return numCores_; - } - /** - * int64 num_cores = 1; - * @param value The numCores to set. - * @return This builder for chaining. - */ - public Builder setNumCores(long value) { - - numCores_ = value; - onChanged(); - return this; - } - /** - * int64 num_cores = 1; - * @return This builder for chaining. - */ - public Builder clearNumCores() { - - numCores_ = 0L; - onChanged(); - return this; - } - - private long numCoresAllowed_ ; - /** - * int64 num_cores_allowed = 2; - * @return The numCoresAllowed. - */ - @java.lang.Override - public long getNumCoresAllowed() { - return numCoresAllowed_; - } - /** - * int64 num_cores_allowed = 2; - * @param value The numCoresAllowed to set. - * @return This builder for chaining. - */ - public Builder setNumCoresAllowed(long value) { - - numCoresAllowed_ = value; - onChanged(); - return this; - } - /** - * int64 num_cores_allowed = 2; - * @return This builder for chaining. - */ - public Builder clearNumCoresAllowed() { - - numCoresAllowed_ = 0L; - onChanged(); - return this; - } - - private double mhzPerCpu_ ; - /** - * 
-     * How fast are these cpus?
-     *
- * - * double mhz_per_cpu = 3; - * @return The mhzPerCpu. - */ - @java.lang.Override - public double getMhzPerCpu() { - return mhzPerCpu_; - } - /** - * 
-     * How fast are these cpus?
-     *
- * - * double mhz_per_cpu = 3; - * @param value The mhzPerCpu to set. - * @return This builder for chaining. - */ - public Builder setMhzPerCpu(double value) { - - mhzPerCpu_ = value; - onChanged(); - return this; - } - /** - * 
-     * How fast are these cpus?
-     *
- * - * double mhz_per_cpu = 3; - * @return This builder for chaining. - */ - public Builder clearMhzPerCpu() { - - mhzPerCpu_ = 0D; - onChanged(); - return this; - } - - private java.lang.Object cpuInfo_ = ""; - /** - * 
-     * Additional cpu information. For example,
-     * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
-     *
- * - * string cpu_info = 4; - * @return The cpuInfo. - */ - public java.lang.String getCpuInfo() { - java.lang.Object ref = cpuInfo_; - if (!(ref instanceof java.lang.String)) { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - cpuInfo_ = s; - return s; - } else { - return (java.lang.String) ref; - } - } - /** - * 
-     * Additional cpu information. For example,
-     * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
-     *
- * - * string cpu_info = 4; - * @return The bytes for cpuInfo. - */ - public com.google.protobuf.ByteString - getCpuInfoBytes() { - java.lang.Object ref = cpuInfo_; - if (ref instanceof String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - cpuInfo_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - /** - * 
-     * Additional cpu information. For example,
-     * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
-     *
- * - * string cpu_info = 4; - * @param value The cpuInfo to set. - * @return This builder for chaining. - */ - public Builder setCpuInfo( - java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - - cpuInfo_ = value; - onChanged(); - return this; - } - /** - * 
-     * Additional cpu information. For example,
-     * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
-     *
- * - * string cpu_info = 4; - * @return This builder for chaining. - */ - public Builder clearCpuInfo() { - - cpuInfo_ = getDefaultInstance().getCpuInfo(); - onChanged(); - return this; - } - /** - * 
-     * Additional cpu information. For example,
-     * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
-     *
- * - * string cpu_info = 4; - * @param value The bytes for cpuInfo to set. - * @return This builder for chaining. - */ - public Builder setCpuInfoBytes( - com.google.protobuf.ByteString value) { - if (value == null) { - throw new NullPointerException(); - } - checkByteStringIsUtf8(value); - - cpuInfo_ = value; - onChanged(); - return this; - } - - private java.lang.Object cpuGovernor_ = ""; - /** - * 
-     * What kind of cpu scaling is enabled on the host.
-     * Examples include "performance", "ondemand", "conservative", "mixed".
-     *
- * - * string cpu_governor = 5; - * @return The cpuGovernor. - */ - public java.lang.String getCpuGovernor() { - java.lang.Object ref = cpuGovernor_; - if (!(ref instanceof java.lang.String)) { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - cpuGovernor_ = s; - return s; - } else { - return (java.lang.String) ref; - } - } - /** - * 
-     * What kind of cpu scaling is enabled on the host.
-     * Examples include "performance", "ondemand", "conservative", "mixed".
-     *
- * - * string cpu_governor = 5; - * @return The bytes for cpuGovernor. - */ - public com.google.protobuf.ByteString - getCpuGovernorBytes() { - java.lang.Object ref = cpuGovernor_; - if (ref instanceof String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - cpuGovernor_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - /** - * 
-     * What kind of cpu scaling is enabled on the host.
-     * Examples include "performance", "ondemand", "conservative", "mixed".
-     *
- * - * string cpu_governor = 5; - * @param value The cpuGovernor to set. - * @return This builder for chaining. - */ - public Builder setCpuGovernor( - java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - - cpuGovernor_ = value; - onChanged(); - return this; - } - /** - * 
-     * What kind of cpu scaling is enabled on the host.
-     * Examples include "performance", "ondemand", "conservative", "mixed".
-     *
- * - * string cpu_governor = 5; - * @return This builder for chaining. - */ - public Builder clearCpuGovernor() { - - cpuGovernor_ = getDefaultInstance().getCpuGovernor(); - onChanged(); - return this; - } - /** - * 
-     * What kind of cpu scaling is enabled on the host.
-     * Examples include "performance", "ondemand", "conservative", "mixed".
-     *
- * - * string cpu_governor = 5; - * @param value The bytes for cpuGovernor to set. - * @return This builder for chaining. - */ - public Builder setCpuGovernorBytes( - com.google.protobuf.ByteString value) { - if (value == null) { - throw new NullPointerException(); - } - checkByteStringIsUtf8(value); - - cpuGovernor_ = value; - onChanged(); - return this; - } - - private com.google.protobuf.MapField< - java.lang.String, java.lang.Long> cacheSize_; - private com.google.protobuf.MapField - internalGetCacheSize() { - if (cacheSize_ == null) { - return com.google.protobuf.MapField.emptyMapField( - CacheSizeDefaultEntryHolder.defaultEntry); - } - return cacheSize_; - } - private com.google.protobuf.MapField - internalGetMutableCacheSize() { - onChanged();; - if (cacheSize_ == null) { - cacheSize_ = com.google.protobuf.MapField.newMapField( - CacheSizeDefaultEntryHolder.defaultEntry); - } - if (!cacheSize_.isMutable()) { - cacheSize_ = cacheSize_.copy(); - } - return cacheSize_; - } - - public int getCacheSizeCount() { - return internalGetCacheSize().getMap().size(); - } - /** - * 
-     * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-     *
- * - * map<string, int64> cache_size = 6; - */ - - @java.lang.Override - public boolean containsCacheSize( - java.lang.String key) { - if (key == null) { throw new NullPointerException("map key"); } - return internalGetCacheSize().getMap().containsKey(key); - } - /** - * Use {@link #getCacheSizeMap()} instead. - */ - @java.lang.Override - @java.lang.Deprecated - public java.util.Map getCacheSize() { - return getCacheSizeMap(); - } - /** - * 
-     * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-     *
- * - * map<string, int64> cache_size = 6; - */ - @java.lang.Override - - public java.util.Map getCacheSizeMap() { - return internalGetCacheSize().getMap(); - } - /** - * 
-     * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-     *
- * - * map<string, int64> cache_size = 6; - */ - @java.lang.Override - - public long getCacheSizeOrDefault( - java.lang.String key, - long defaultValue) { - if (key == null) { throw new NullPointerException("map key"); } - java.util.Map map = - internalGetCacheSize().getMap(); - return map.containsKey(key) ? map.get(key) : defaultValue; - } - /** - * 
-     * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-     *
- * - * map<string, int64> cache_size = 6; - */ - @java.lang.Override - - public long getCacheSizeOrThrow( - java.lang.String key) { - if (key == null) { throw new NullPointerException("map key"); } - java.util.Map map = - internalGetCacheSize().getMap(); - if (!map.containsKey(key)) { - throw new java.lang.IllegalArgumentException(); - } - return map.get(key); - } - - public Builder clearCacheSize() { - internalGetMutableCacheSize().getMutableMap() - .clear(); - return this; - } - /** - * 
-     * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-     *
- * - * map<string, int64> cache_size = 6; - */ - - public Builder removeCacheSize( - java.lang.String key) { - if (key == null) { throw new NullPointerException("map key"); } - internalGetMutableCacheSize().getMutableMap() - .remove(key); - return this; - } - /** - * Use alternate mutation accessors instead. - */ - @java.lang.Deprecated - public java.util.Map - getMutableCacheSize() { - return internalGetMutableCacheSize().getMutableMap(); - } - /** - * 
-     * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-     *
- * - * map<string, int64> cache_size = 6; - */ - public Builder putCacheSize( - java.lang.String key, - long value) { - if (key == null) { throw new NullPointerException("map key"); } - - internalGetMutableCacheSize().getMutableMap() - .put(key, value); - return this; - } - /** - * 
-     * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-     *
- * - * map<string, int64> cache_size = 6; - */ - - public Builder putAllCacheSize( - java.util.Map values) { - internalGetMutableCacheSize().getMutableMap() - .putAll(values); - return this; - } - @java.lang.Override - public final Builder setUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.setUnknownFields(unknownFields); - } - - @java.lang.Override - public final Builder mergeUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.mergeUnknownFields(unknownFields); - } - - - // @@protoc_insertion_point(builder_scope:tensorflow.CPUInfo) - } - - // @@protoc_insertion_point(class_scope:tensorflow.CPUInfo) - private static final org.tensorflow.proto.CPUInfo DEFAULT_INSTANCE; - static { - DEFAULT_INSTANCE = new org.tensorflow.proto.CPUInfo(); - } - - public static org.tensorflow.proto.CPUInfo getDefaultInstance() { - return DEFAULT_INSTANCE; - } - - private static final com.google.protobuf.Parser - PARSER = new com.google.protobuf.AbstractParser() { - @java.lang.Override - public CPUInfo parsePartialFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - Builder builder = newBuilder(); - try { - builder.mergeFrom(input, extensionRegistry); - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.setUnfinishedMessage(builder.buildPartial()); - } catch (com.google.protobuf.UninitializedMessageException e) { - throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); - } catch (java.io.IOException e) { - throw new com.google.protobuf.InvalidProtocolBufferException(e) - .setUnfinishedMessage(builder.buildPartial()); - } - return builder.buildPartial(); - } - }; - - public static com.google.protobuf.Parser parser() { - return PARSER; - } - - @java.lang.Override - public com.google.protobuf.Parser getParserForType() { - return PARSER; - } - - @java.lang.Override - public org.tensorflow.proto.CPUInfo getDefaultInstanceForType() { - return DEFAULT_INSTANCE; - } - -} - diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CPUInfoOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CPUInfoOrBuilder.java deleted file mode 100644 index de66bb23d57..00000000000 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CPUInfoOrBuilder.java +++ /dev/null @@ -1,129 +0,0 @@ -// Generated by the protocol buffer compiler. DO NOT EDIT! -// source: tsl/protobuf/test_log.proto - -package org.tensorflow.proto; - -public interface CPUInfoOrBuilder extends - // @@protoc_insertion_point(interface_extends:tensorflow.CPUInfo) - com.google.protobuf.MessageOrBuilder { - - /** - * int64 num_cores = 1; - * @return The numCores. - */ - long getNumCores(); - - /** - * int64 num_cores_allowed = 2; - * @return The numCoresAllowed. - */ - long getNumCoresAllowed(); - - /** - * 
-   * How fast are these cpus?
-   *
- * - * double mhz_per_cpu = 3; - * @return The mhzPerCpu. - */ - double getMhzPerCpu(); - - /** - * 
-   * Additional cpu information. For example,
-   * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
-   *
- * - * string cpu_info = 4; - * @return The cpuInfo. - */ - java.lang.String getCpuInfo(); - /** - * 
-   * Additional cpu information. For example,
-   * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
-   *
- * - * string cpu_info = 4; - * @return The bytes for cpuInfo. - */ - com.google.protobuf.ByteString - getCpuInfoBytes(); - - /** - * 
-   * What kind of cpu scaling is enabled on the host.
-   * Examples include "performance", "ondemand", "conservative", "mixed".
-   *
- * - * string cpu_governor = 5; - * @return The cpuGovernor. - */ - java.lang.String getCpuGovernor(); - /** - * 
-   * What kind of cpu scaling is enabled on the host.
-   * Examples include "performance", "ondemand", "conservative", "mixed".
-   *
- * - * string cpu_governor = 5; - * @return The bytes for cpuGovernor. - */ - com.google.protobuf.ByteString - getCpuGovernorBytes(); - - /** - * 
-   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-   *
- * - * map<string, int64> cache_size = 6; - */ - int getCacheSizeCount(); - /** - * 
-   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-   *
- * - * map<string, int64> cache_size = 6; - */ - boolean containsCacheSize( - java.lang.String key); - /** - * Use {@link #getCacheSizeMap()} instead. - */ - @java.lang.Deprecated - java.util.Map - getCacheSize(); - /** - * 
-   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-   *
- * - * map<string, int64> cache_size = 6; - */ - java.util.Map - getCacheSizeMap(); - /** - * 
-   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-   *
- * - * map<string, int64> cache_size = 6; - */ - - long getCacheSizeOrDefault( - java.lang.String key, - long defaultValue); - /** - * 
-   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
-   *
- * - * map<string, int64> cache_size = 6; - */ - - long getCacheSizeOrThrow( - java.lang.String key); -} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CommitId.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CommitId.java deleted file mode 100644 index 3fdd1c804b6..00000000000 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CommitId.java +++ /dev/null @@ -1,1021 +0,0 @@ -// Generated by the protocol buffer compiler. DO NOT EDIT! -// source: tsl/protobuf/test_log.proto - -package org.tensorflow.proto; - -/** - * Protobuf type {@code tensorflow.CommitId} - */ -public final class CommitId extends - com.google.protobuf.GeneratedMessageV3 implements - // @@protoc_insertion_point(message_implements:tensorflow.CommitId) - CommitIdOrBuilder { -private static final long serialVersionUID = 0L; - // Use CommitId.newBuilder() to construct. - private CommitId(com.google.protobuf.GeneratedMessageV3.Builder builder) { - super(builder); - } - private CommitId() { - snapshot_ = ""; - } - - @java.lang.Override - @SuppressWarnings({"unused"}) - protected java.lang.Object newInstance( - UnusedPrivateParameter unused) { - return new CommitId(); - } - - @java.lang.Override - public final com.google.protobuf.UnknownFieldSet - getUnknownFields() { - return this.unknownFields; - } - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CommitId_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CommitId_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.CommitId.class, org.tensorflow.proto.CommitId.Builder.class); - } - - private int kindCase_ = 0; - private java.lang.Object kind_; - public enum KindCase - implements com.google.protobuf.Internal.EnumLite, - com.google.protobuf.AbstractMessage.InternalOneOfEnum { - CHANGELIST(1), - HASH(2), - KIND_NOT_SET(0); - private final int value; - private KindCase(int value) { - this.value = value; - } - /** - * @param value The number of the enum to look for. - * @return The enum associated with the given number. - * @deprecated Use {@link #forNumber(int)} instead. - */ - @java.lang.Deprecated - public static KindCase valueOf(int value) { - return forNumber(value); - } - - public static KindCase forNumber(int value) { - switch (value) { - case 1: return CHANGELIST; - case 2: return HASH; - case 0: return KIND_NOT_SET; - default: return null; - } - } - public int getNumber() { - return this.value; - } - }; - - public KindCase - getKindCase() { - return KindCase.forNumber( - kindCase_); - } - - public static final int CHANGELIST_FIELD_NUMBER = 1; - /** - * 
-   * Submitted changelist.
-   *
- * - * int64 changelist = 1; - * @return Whether the changelist field is set. - */ - @java.lang.Override - public boolean hasChangelist() { - return kindCase_ == 1; - } - /** - * 
-   * Submitted changelist.
-   *
- * - * int64 changelist = 1; - * @return The changelist. - */ - @java.lang.Override - public long getChangelist() { - if (kindCase_ == 1) { - return (java.lang.Long) kind_; - } - return 0L; - } - - public static final int HASH_FIELD_NUMBER = 2; - /** - * string hash = 2; - * @return Whether the hash field is set. - */ - public boolean hasHash() { - return kindCase_ == 2; - } - /** - * string hash = 2; - * @return The hash. - */ - public java.lang.String getHash() { - java.lang.Object ref = ""; - if (kindCase_ == 2) { - ref = kind_; - } - if (ref instanceof java.lang.String) { - return (java.lang.String) ref; - } else { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - if (kindCase_ == 2) { - kind_ = s; - } - return s; - } - } - /** - * string hash = 2; - * @return The bytes for hash. - */ - public com.google.protobuf.ByteString - getHashBytes() { - java.lang.Object ref = ""; - if (kindCase_ == 2) { - ref = kind_; - } - if (ref instanceof java.lang.String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - if (kindCase_ == 2) { - kind_ = b; - } - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - - public static final int SNAPSHOT_FIELD_NUMBER = 3; - private volatile java.lang.Object snapshot_; - /** - * 
-   * Hash of intermediate change between hash/changelist and what was tested.
-   * Not used if the build is from a commit without modifications.
-   *
- * - * string snapshot = 3; - * @return The snapshot. - */ - @java.lang.Override - public java.lang.String getSnapshot() { - java.lang.Object ref = snapshot_; - if (ref instanceof java.lang.String) { - return (java.lang.String) ref; - } else { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - snapshot_ = s; - return s; - } - } - /** - * 
-   * Hash of intermediate change between hash/changelist and what was tested.
-   * Not used if the build is from a commit without modifications.
-   *
- * - * string snapshot = 3; - * @return The bytes for snapshot. - */ - @java.lang.Override - public com.google.protobuf.ByteString - getSnapshotBytes() { - java.lang.Object ref = snapshot_; - if (ref instanceof java.lang.String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - snapshot_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - - public static final int PENDING_CHANGELIST_FIELD_NUMBER = 4; - private long pendingChangelist_; - /** - * 
-   * Changelist tested if the change list is not already submitted.
-   *
- * - * int64 pending_changelist = 4; - * @return The pendingChangelist. - */ - @java.lang.Override - public long getPendingChangelist() { - return pendingChangelist_; - } - - private byte memoizedIsInitialized = -1; - @java.lang.Override - public final boolean isInitialized() { - byte isInitialized = memoizedIsInitialized; - if (isInitialized == 1) return true; - if (isInitialized == 0) return false; - - memoizedIsInitialized = 1; - return true; - } - - @java.lang.Override - public void writeTo(com.google.protobuf.CodedOutputStream output) - throws java.io.IOException { - if (kindCase_ == 1) { - output.writeInt64( - 1, (long)((java.lang.Long) kind_)); - } - if (kindCase_ == 2) { - com.google.protobuf.GeneratedMessageV3.writeString(output, 2, kind_); - } - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(snapshot_)) { - com.google.protobuf.GeneratedMessageV3.writeString(output, 3, snapshot_); - } - if (pendingChangelist_ != 0L) { - output.writeInt64(4, pendingChangelist_); - } - getUnknownFields().writeTo(output); - } - - @java.lang.Override - public int getSerializedSize() { - int size = memoizedSize; - if (size != -1) return size; - - size = 0; - if (kindCase_ == 1) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size( - 1, (long)((java.lang.Long) kind_)); - } - if (kindCase_ == 2) { - size += com.google.protobuf.GeneratedMessageV3.computeStringSize(2, kind_); - } - if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(snapshot_)) { - size += com.google.protobuf.GeneratedMessageV3.computeStringSize(3, snapshot_); - } - if (pendingChangelist_ != 0L) { - size += com.google.protobuf.CodedOutputStream - .computeInt64Size(4, pendingChangelist_); - } - size += getUnknownFields().getSerializedSize(); - memoizedSize = size; - return size; - } - - @java.lang.Override - public boolean equals(final java.lang.Object obj) { - if (obj == this) { - return true; - } - if (!(obj instanceof org.tensorflow.proto.CommitId)) { - return super.equals(obj); - } - org.tensorflow.proto.CommitId other = (org.tensorflow.proto.CommitId) obj; - - if (!getSnapshot() - .equals(other.getSnapshot())) return false; - if (getPendingChangelist() - != other.getPendingChangelist()) return false; - if (!getKindCase().equals(other.getKindCase())) return false; - switch (kindCase_) { - case 1: - if (getChangelist() - != other.getChangelist()) return false; - break; - case 2: - if (!getHash() - .equals(other.getHash())) return false; - break; - case 0: - default: - } - if (!getUnknownFields().equals(other.getUnknownFields())) return false; - return true; - } - - @java.lang.Override - public int hashCode() { - if (memoizedHashCode != 0) { - return memoizedHashCode; - } - int hash = 41; - hash = (19 * hash) + getDescriptor().hashCode(); - hash = (37 * hash) + SNAPSHOT_FIELD_NUMBER; - hash = (53 * hash) + getSnapshot().hashCode(); - hash = (37 * hash) + PENDING_CHANGELIST_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getPendingChangelist()); - switch (kindCase_) { - case 1: - hash = (37 * hash) + CHANGELIST_FIELD_NUMBER; - hash = (53 * hash) + com.google.protobuf.Internal.hashLong( - getChangelist()); - break; - case 2: - hash = (37 * hash) + HASH_FIELD_NUMBER; - hash = (53 * hash) + getHash().hashCode(); - break; - case 0: - default: - } - hash = (29 * hash) + getUnknownFields().hashCode(); - memoizedHashCode = hash; - return hash; - } - - public static org.tensorflow.proto.CommitId parseFrom( - java.nio.ByteBuffer data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.CommitId parseFrom( - java.nio.ByteBuffer data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.CommitId parseFrom( - com.google.protobuf.ByteString data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.CommitId parseFrom( - com.google.protobuf.ByteString data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.CommitId parseFrom(byte[] data) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data); - } - public static org.tensorflow.proto.CommitId parseFrom( - byte[] data, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - return PARSER.parseFrom(data, extensionRegistry); - } - public static org.tensorflow.proto.CommitId parseFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.CommitId parseFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.CommitId parseDelimitedFrom(java.io.InputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input); - } - public static org.tensorflow.proto.CommitId parseDelimitedFrom( - java.io.InputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseDelimitedWithIOException(PARSER, input, extensionRegistry); - } - public static org.tensorflow.proto.CommitId parseFrom( - com.google.protobuf.CodedInputStream input) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input); - } - public static org.tensorflow.proto.CommitId parseFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - return com.google.protobuf.GeneratedMessageV3 - .parseWithIOException(PARSER, input, extensionRegistry); - } - - @java.lang.Override - public Builder newBuilderForType() { return newBuilder(); } - public static Builder newBuilder() { - return DEFAULT_INSTANCE.toBuilder(); - } - public static Builder newBuilder(org.tensorflow.proto.CommitId prototype) { - return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); - } - @java.lang.Override - public Builder toBuilder() { - return this == DEFAULT_INSTANCE - ? new Builder() : new Builder().mergeFrom(this); - } - - @java.lang.Override - protected Builder newBuilderForType( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - Builder builder = new Builder(parent); - return builder; - } - /** - * Protobuf type {@code tensorflow.CommitId} - */ - public static final class Builder extends - com.google.protobuf.GeneratedMessageV3.Builder implements - // @@protoc_insertion_point(builder_implements:tensorflow.CommitId) - org.tensorflow.proto.CommitIdOrBuilder { - public static final com.google.protobuf.Descriptors.Descriptor - getDescriptor() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CommitId_descriptor; - } - - @java.lang.Override - protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable - internalGetFieldAccessorTable() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CommitId_fieldAccessorTable - .ensureFieldAccessorsInitialized( - org.tensorflow.proto.CommitId.class, org.tensorflow.proto.CommitId.Builder.class); - } - - // Construct using org.tensorflow.proto.CommitId.newBuilder() - private Builder() { - - } - - private Builder( - com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { - super(parent); - - } - @java.lang.Override - public Builder clear() { - super.clear(); - snapshot_ = ""; - - pendingChangelist_ = 0L; - - kindCase_ = 0; - kind_ = null; - return this; - } - - @java.lang.Override - public com.google.protobuf.Descriptors.Descriptor - getDescriptorForType() { - return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CommitId_descriptor; - } - - @java.lang.Override - public org.tensorflow.proto.CommitId getDefaultInstanceForType() { - return org.tensorflow.proto.CommitId.getDefaultInstance(); - } - - @java.lang.Override - public org.tensorflow.proto.CommitId build() { - org.tensorflow.proto.CommitId result = buildPartial(); - if (!result.isInitialized()) { - throw newUninitializedMessageException(result); - } - return result; - } - - @java.lang.Override - public org.tensorflow.proto.CommitId buildPartial() { - org.tensorflow.proto.CommitId result = new org.tensorflow.proto.CommitId(this); - if (kindCase_ == 1) { - result.kind_ = kind_; - } - if (kindCase_ == 2) { - result.kind_ = kind_; - } - result.snapshot_ = snapshot_; - result.pendingChangelist_ = pendingChangelist_; - result.kindCase_ = kindCase_; - onBuilt(); - return result; - } - - @java.lang.Override - public Builder clone() { - return super.clone(); - } - @java.lang.Override - public Builder setField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.setField(field, value); - } - @java.lang.Override - public Builder clearField( - com.google.protobuf.Descriptors.FieldDescriptor field) { - return super.clearField(field); - } - @java.lang.Override - public Builder clearOneof( - com.google.protobuf.Descriptors.OneofDescriptor oneof) { - return super.clearOneof(oneof); - } - @java.lang.Override - public Builder setRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - int index, java.lang.Object value) { - return super.setRepeatedField(field, index, value); - } - @java.lang.Override - public Builder addRepeatedField( - com.google.protobuf.Descriptors.FieldDescriptor field, - java.lang.Object value) { - return super.addRepeatedField(field, value); - } - @java.lang.Override - public Builder mergeFrom(com.google.protobuf.Message other) { - if (other instanceof org.tensorflow.proto.CommitId) { - return mergeFrom((org.tensorflow.proto.CommitId)other); - } else { - super.mergeFrom(other); - return this; - } - } - - public Builder mergeFrom(org.tensorflow.proto.CommitId other) { - if (other == org.tensorflow.proto.CommitId.getDefaultInstance()) return this; - if (!other.getSnapshot().isEmpty()) { - snapshot_ = other.snapshot_; - onChanged(); - } - if (other.getPendingChangelist() != 0L) { - setPendingChangelist(other.getPendingChangelist()); - } - switch (other.getKindCase()) { - case CHANGELIST: { - setChangelist(other.getChangelist()); - break; - } - case HASH: { - kindCase_ = 2; - kind_ = other.kind_; - onChanged(); - break; - } - case KIND_NOT_SET: { - break; - } - } - this.mergeUnknownFields(other.getUnknownFields()); - onChanged(); - return this; - } - - @java.lang.Override - public final boolean isInitialized() { - return true; - } - - @java.lang.Override - public Builder mergeFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws java.io.IOException { - if (extensionRegistry == null) { - throw new java.lang.NullPointerException(); - } - try { - boolean done = false; - while (!done) { - int tag = input.readTag(); - switch (tag) { - case 0: - done = true; - break; - case 8: { - kind_ = input.readInt64(); - kindCase_ = 1; - break; - } // case 8 - case 18: { - java.lang.String s = input.readStringRequireUtf8(); - kindCase_ = 2; - kind_ = s; - break; - } // case 18 - case 26: { - snapshot_ = input.readStringRequireUtf8(); - - break; - } // case 26 - case 32: { - pendingChangelist_ = input.readInt64(); - - break; - } // case 32 - default: { - if (!super.parseUnknownField(input, extensionRegistry, tag)) { - done = true; // was an endgroup tag - } - break; - } // default: - } // switch (tag) - } // while (!done) - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.unwrapIOException(); - } finally { - onChanged(); - } // finally - return this; - } - private int kindCase_ = 0; - private java.lang.Object kind_; - public KindCase - getKindCase() { - return KindCase.forNumber( - kindCase_); - } - - public Builder clearKind() { - kindCase_ = 0; - kind_ = null; - onChanged(); - return this; - } - - - /** - * 
-     * Submitted changelist.
-     *
- * - * int64 changelist = 1; - * @return Whether the changelist field is set. - */ - public boolean hasChangelist() { - return kindCase_ == 1; - } - /** - * 
-     * Submitted changelist.
-     *
- * - * int64 changelist = 1; - * @return The changelist. - */ - public long getChangelist() { - if (kindCase_ == 1) { - return (java.lang.Long) kind_; - } - return 0L; - } - /** - * 
-     * Submitted changelist.
-     *
- * - * int64 changelist = 1; - * @param value The changelist to set. - * @return This builder for chaining. - */ - public Builder setChangelist(long value) { - kindCase_ = 1; - kind_ = value; - onChanged(); - return this; - } - /** - * 
-     * Submitted changelist.
-     *
- * - * int64 changelist = 1; - * @return This builder for chaining. - */ - public Builder clearChangelist() { - if (kindCase_ == 1) { - kindCase_ = 0; - kind_ = null; - onChanged(); - } - return this; - } - - /** - * string hash = 2; - * @return Whether the hash field is set. - */ - @java.lang.Override - public boolean hasHash() { - return kindCase_ == 2; - } - /** - * string hash = 2; - * @return The hash. - */ - @java.lang.Override - public java.lang.String getHash() { - java.lang.Object ref = ""; - if (kindCase_ == 2) { - ref = kind_; - } - if (!(ref instanceof java.lang.String)) { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - if (kindCase_ == 2) { - kind_ = s; - } - return s; - } else { - return (java.lang.String) ref; - } - } - /** - * string hash = 2; - * @return The bytes for hash. - */ - @java.lang.Override - public com.google.protobuf.ByteString - getHashBytes() { - java.lang.Object ref = ""; - if (kindCase_ == 2) { - ref = kind_; - } - if (ref instanceof String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - if (kindCase_ == 2) { - kind_ = b; - } - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - /** - * string hash = 2; - * @param value The hash to set. - * @return This builder for chaining. - */ - public Builder setHash( - java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - kindCase_ = 2; - kind_ = value; - onChanged(); - return this; - } - /** - * string hash = 2; - * @return This builder for chaining. - */ - public Builder clearHash() { - if (kindCase_ == 2) { - kindCase_ = 0; - kind_ = null; - onChanged(); - } - return this; - } - /** - * string hash = 2; - * @param value The bytes for hash to set. - * @return This builder for chaining. - */ - public Builder setHashBytes( - com.google.protobuf.ByteString value) { - if (value == null) { - throw new NullPointerException(); - } - checkByteStringIsUtf8(value); - kindCase_ = 2; - kind_ = value; - onChanged(); - return this; - } - - private java.lang.Object snapshot_ = ""; - /** - * 
-     * Hash of intermediate change between hash/changelist and what was tested.
-     * Not used if the build is from a commit without modifications.
-     *
- * - * string snapshot = 3; - * @return The snapshot. - */ - public java.lang.String getSnapshot() { - java.lang.Object ref = snapshot_; - if (!(ref instanceof java.lang.String)) { - com.google.protobuf.ByteString bs = - (com.google.protobuf.ByteString) ref; - java.lang.String s = bs.toStringUtf8(); - snapshot_ = s; - return s; - } else { - return (java.lang.String) ref; - } - } - /** - * 
-     * Hash of intermediate change between hash/changelist and what was tested.
-     * Not used if the build is from a commit without modifications.
-     *
- * - * string snapshot = 3; - * @return The bytes for snapshot. - */ - public com.google.protobuf.ByteString - getSnapshotBytes() { - java.lang.Object ref = snapshot_; - if (ref instanceof String) { - com.google.protobuf.ByteString b = - com.google.protobuf.ByteString.copyFromUtf8( - (java.lang.String) ref); - snapshot_ = b; - return b; - } else { - return (com.google.protobuf.ByteString) ref; - } - } - /** - * 
-     * Hash of intermediate change between hash/changelist and what was tested.
-     * Not used if the build is from a commit without modifications.
-     *
- * - * string snapshot = 3; - * @param value The snapshot to set. - * @return This builder for chaining. - */ - public Builder setSnapshot( - java.lang.String value) { - if (value == null) { - throw new NullPointerException(); - } - - snapshot_ = value; - onChanged(); - return this; - } - /** - * 
-     * Hash of intermediate change between hash/changelist and what was tested.
-     * Not used if the build is from a commit without modifications.
-     *
- * - * string snapshot = 3; - * @return This builder for chaining. - */ - public Builder clearSnapshot() { - - snapshot_ = getDefaultInstance().getSnapshot(); - onChanged(); - return this; - } - /** - * 
-     * Hash of intermediate change between hash/changelist and what was tested.
-     * Not used if the build is from a commit without modifications.
-     *
- * - * string snapshot = 3; - * @param value The bytes for snapshot to set. - * @return This builder for chaining. - */ - public Builder setSnapshotBytes( - com.google.protobuf.ByteString value) { - if (value == null) { - throw new NullPointerException(); - } - checkByteStringIsUtf8(value); - - snapshot_ = value; - onChanged(); - return this; - } - - private long pendingChangelist_ ; - /** - * 
-     * Changelist tested if the change list is not already submitted.
-     *
- * - * int64 pending_changelist = 4; - * @return The pendingChangelist. - */ - @java.lang.Override - public long getPendingChangelist() { - return pendingChangelist_; - } - /** - * 
-     * Changelist tested if the change list is not already submitted.
-     *
- * - * int64 pending_changelist = 4; - * @param value The pendingChangelist to set. - * @return This builder for chaining. - */ - public Builder setPendingChangelist(long value) { - - pendingChangelist_ = value; - onChanged(); - return this; - } - /** - * 
-     * Changelist tested if the change list is not already submitted.
-     *
- * - * int64 pending_changelist = 4; - * @return This builder for chaining. - */ - public Builder clearPendingChangelist() { - - pendingChangelist_ = 0L; - onChanged(); - return this; - } - @java.lang.Override - public final Builder setUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.setUnknownFields(unknownFields); - } - - @java.lang.Override - public final Builder mergeUnknownFields( - final com.google.protobuf.UnknownFieldSet unknownFields) { - return super.mergeUnknownFields(unknownFields); - } - - - // @@protoc_insertion_point(builder_scope:tensorflow.CommitId) - } - - // @@protoc_insertion_point(class_scope:tensorflow.CommitId) - private static final org.tensorflow.proto.CommitId DEFAULT_INSTANCE; - static { - DEFAULT_INSTANCE = new org.tensorflow.proto.CommitId(); - } - - public static org.tensorflow.proto.CommitId getDefaultInstance() { - return DEFAULT_INSTANCE; - } - - private static final com.google.protobuf.Parser - PARSER = new com.google.protobuf.AbstractParser() { - @java.lang.Override - public CommitId parsePartialFrom( - com.google.protobuf.CodedInputStream input, - com.google.protobuf.ExtensionRegistryLite extensionRegistry) - throws com.google.protobuf.InvalidProtocolBufferException { - Builder builder = newBuilder(); - try { - builder.mergeFrom(input, extensionRegistry); - } catch (com.google.protobuf.InvalidProtocolBufferException e) { - throw e.setUnfinishedMessage(builder.buildPartial()); - } catch (com.google.protobuf.UninitializedMessageException e) { - throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); - } catch (java.io.IOException e) { - throw new com.google.protobuf.InvalidProtocolBufferException(e) - .setUnfinishedMessage(builder.buildPartial()); - } - return builder.buildPartial(); - } - }; - - public static com.google.protobuf.Parser parser() { - return PARSER; - } - - @java.lang.Override - public com.google.protobuf.Parser getParserForType() { - return PARSER; - } - - @java.lang.Override - public org.tensorflow.proto.CommitId getDefaultInstanceForType() { - return DEFAULT_INSTANCE; - } - -} - diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CommitIdOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CommitIdOrBuilder.java deleted file mode 100644 index 1b124825e66..00000000000 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CommitIdOrBuilder.java +++ /dev/null @@ -1,79 +0,0 @@ -// Generated by the protocol buffer compiler. DO NOT EDIT! -// source: tsl/protobuf/test_log.proto - -package org.tensorflow.proto; - -public interface CommitIdOrBuilder extends - // @@protoc_insertion_point(interface_extends:tensorflow.CommitId) - com.google.protobuf.MessageOrBuilder { - - /** - * 
-   * Submitted changelist.
-   *
- * - * int64 changelist = 1; - * @return Whether the changelist field is set. - */ - boolean hasChangelist(); - /** - * 
-   * Submitted changelist.
-   *
- * - * int64 changelist = 1; - * @return The changelist. - */ - long getChangelist(); - - /** - * string hash = 2; - * @return Whether the hash field is set. - */ - boolean hasHash(); - /** - * string hash = 2; - * @return The hash. - */ - java.lang.String getHash(); - /** - * string hash = 2; - * @return The bytes for hash. - */ - com.google.protobuf.ByteString - getHashBytes(); - - /** - * 
-   * Hash of intermediate change between hash/changelist and what was tested.
-   * Not used if the build is from a commit without modifications.
-   *
- * - * string snapshot = 3; - * @return The snapshot. - */ - java.lang.String getSnapshot(); - /** - * 
-   * Hash of intermediate change between hash/changelist and what was tested.
-   * Not used if the build is from a commit without modifications.
-   *
- * - * string snapshot = 3; - * @return The bytes for snapshot. - */ - com.google.protobuf.ByteString - getSnapshotBytes(); - - /** - * 
-   * Changelist tested if the change list is not already submitted.
-   *
- * - * int64 pending_changelist = 4; - * @return The pendingChangelist. - */ - long getPendingChangelist(); - - public org.tensorflow.proto.CommitId.KindCase getKindCase(); -} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ConfigProto.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ConfigProto.java index 04d15e4a308..5dcca1ed5f7 100644 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ConfigProto.java +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ConfigProto.java @@ -354,6 +354,17 @@ public interface ExperimentalOrBuilder extends */ boolean getEnableMultiHost(); + /** + * 
+     * If true, use ifrt as the backend for TFRT. This is only used when
+     * `use_tfrt` is true.
+     *
+ * + * bool tfrt_use_ifrt = 32; + * @return The tfrtUseIfrt. + */ + boolean getTfrtUseIfrt(); + /** * 
      * Port for the Pathways server. Ignored if enable_multi_host=false.
@@ -1101,6 +1112,22 @@ public boolean getEnableMultiHost() {
       return enableMultiHost_;
     }
 
+    public static final int TFRT_USE_IFRT_FIELD_NUMBER = 32;
+    private boolean tfrtUseIfrt_;
+    /**
+     * 
+     * If true, use ifrt as the backend for TFRT. This is only used when
+     * `use_tfrt` is true.
+     * 

+     *
+     * bool tfrt_use_ifrt = 32;
+     * @return The tfrtUseIfrt.
+     */
+    @java.lang.Override
+    public boolean getTfrtUseIfrt() {
+      return tfrtUseIfrt_;
+    }
+
     public static final int BACKEND_SERVER_PORT_FIELD_NUMBER = 28;
     private int backendServerPort_;
     /**
@@ -1369,6 +1396,9 @@ public void writeTo(com.google.protobuf.CodedOutputStream output)
       if (streamMergeThreshold_ != 0) {
         output.writeInt32(31, streamMergeThreshold_);
       }
+      if (tfrtUseIfrt_ != false) {
+        output.writeBool(32, tfrtUseIfrt_);
+      }
       getUnknownFields().writeTo(output);
     }
 
@@ -1484,6 +1514,10 @@ public int getSerializedSize() {
         size += com.google.protobuf.CodedOutputStream
           .computeInt32Size(31, streamMergeThreshold_);
       }
+      if (tfrtUseIfrt_ != false) {
+        size += com.google.protobuf.CodedOutputStream
+          .computeBoolSize(32, tfrtUseIfrt_);
+      }
       size += getUnknownFields().getSerializedSize();
       memoizedSize = size;
       return size;
@@ -1537,6 +1571,8 @@ public boolean equals(final java.lang.Object obj) {
           != other.getUseTfrt()) return false;
       if (getEnableMultiHost()
           != other.getEnableMultiHost()) return false;
+      if (getTfrtUseIfrt()
+          != other.getTfrtUseIfrt()) return false;
       if (getBackendServerPort()
           != other.getBackendServerPort()) return false;
       if (getTargetTpu()
@@ -1620,6 +1656,9 @@ public int hashCode() {
       hash = (37 * hash) + ENABLE_MULTI_HOST_FIELD_NUMBER;
       hash = (53 * hash) + com.google.protobuf.Internal.hashBoolean(
           getEnableMultiHost());
+      hash = (37 * hash) + TFRT_USE_IFRT_FIELD_NUMBER;
+      hash = (53 * hash) + com.google.protobuf.Internal.hashBoolean(
+          getTfrtUseIfrt());
       hash = (37 * hash) + BACKEND_SERVER_PORT_FIELD_NUMBER;
       hash = (53 * hash) + getBackendServerPort();
       hash = (37 * hash) + TARGET_TPU_FIELD_NUMBER;
@@ -1820,6 +1859,8 @@ public Builder clear() {
 
         enableMultiHost_ = false;
 
+        tfrtUseIfrt_ = false;
+
         backendServerPort_ = 0;
 
         targetTpu_ = false;
@@ -1890,6 +1931,7 @@ public org.tensorflow.proto.ConfigProto.Experimental buildPartial() {
         result.xlaFusionAutotunerThresh_ = xlaFusionAutotunerThresh_;
         result.useTfrt_ = useTfrt_;
         result.enableMultiHost_ = enableMultiHost_;
+        result.tfrtUseIfrt_ = tfrtUseIfrt_;
         result.backendServerPort_ = backendServerPort_;
         result.targetTpu_ = targetTpu_;
         result.targetGpu_ = targetGpu_;
@@ -2007,6 +2049,9 @@ public Builder mergeFrom(org.tensorflow.proto.ConfigProto.Experimental other) {
         if (other.getEnableMultiHost() != false) {
           setEnableMultiHost(other.getEnableMultiHost());
         }
+        if (other.getTfrtUseIfrt() != false) {
+          setTfrtUseIfrt(other.getTfrtUseIfrt());
+        }
         if (other.getBackendServerPort() != 0) {
           setBackendServerPort(other.getBackendServerPort());
         }
@@ -2199,6 +2244,11 @@ public Builder mergeFrom(
 
                 break;
               } // case 248
+              case 256: {
+                tfrtUseIfrt_ = input.readBool();
+
+                break;
+              } // case 256
               default: {
                 if (!super.parseUnknownField(input, extensionRegistry, tag)) {
                   done = true; // was an endgroup tag
@@ -3423,6 +3473,52 @@ public Builder clearEnableMultiHost() {
         return this;
       }
 
+      private boolean tfrtUseIfrt_ ;
+      /**
+       * 
+       * If true, use ifrt as the backend for TFRT. This is only used when
+       * `use_tfrt` is true.
+       * 

+       *
+       * bool tfrt_use_ifrt = 32;
+       * @return The tfrtUseIfrt.
+       */
+      @java.lang.Override
+      public boolean getTfrtUseIfrt() {
+        return tfrtUseIfrt_;
+      }
+      /**
+       * 
+       * If true, use ifrt as the backend for TFRT. This is only used when
+       * `use_tfrt` is true.
+       * 

+       *
+       * bool tfrt_use_ifrt = 32;
+       * @param value The tfrtUseIfrt to set.
+       * @return This builder for chaining.
+       */
+      public Builder setTfrtUseIfrt(boolean value) {
+        
+        tfrtUseIfrt_ = value;
+        onChanged();
+        return this;
+      }
+      /**
+       * 
+       * If true, use ifrt as the backend for TFRT. This is only used when
+       * `use_tfrt` is true.
+       * 

+       *
+       * bool tfrt_use_ifrt = 32;
+       * @return This builder for chaining.
+       */
+      public Builder clearTfrtUseIfrt() {
+        
+        tfrtUseIfrt_ = false;
+        onChanged();
+        return this;
+      }
+
       private int backendServerPort_ ;
       /**
        * 
@@ -4461,6 +4557,44 @@ public org.tensorflow.proto.GPUOptionsOrBuilder getGpuOptionsOrBuilder() {
     return getGpuOptions();
   }
 
+  public static final int PLUGGABLE_DEVICE_OPTIONS_FIELD_NUMBER = 18;
+  private org.tensorflow.proto.GPUOptions pluggableDeviceOptions_;
+  /**
+   * 
+   * Options that apply to pluggable devices.
+   * 

+   *
+   * .tensorflow.GPUOptions pluggable_device_options = 18;
+   * @return Whether the pluggableDeviceOptions field is set.
+   */
+  @java.lang.Override
+  public boolean hasPluggableDeviceOptions() {
+    return pluggableDeviceOptions_ != null;
+  }
+  /**
+   * 
+   * Options that apply to pluggable devices.
+   * 

+   *
+   * .tensorflow.GPUOptions pluggable_device_options = 18;
+   * @return The pluggableDeviceOptions.
+   */
+  @java.lang.Override
+  public org.tensorflow.proto.GPUOptions getPluggableDeviceOptions() {
+    return pluggableDeviceOptions_ == null ? org.tensorflow.proto.GPUOptions.getDefaultInstance() : pluggableDeviceOptions_;
+  }
+  /**
+   * 
+   * Options that apply to pluggable devices.
+   * 

+   *
+   * .tensorflow.GPUOptions pluggable_device_options = 18;
+   */
+  @java.lang.Override
+  public org.tensorflow.proto.GPUOptionsOrBuilder getPluggableDeviceOptionsOrBuilder() {
+    return getPluggableDeviceOptions();
+  }
+
   public static final int ALLOW_SOFT_PLACEMENT_FIELD_NUMBER = 7;
   private boolean allowSoftPlacement_;
   /**
@@ -4757,6 +4891,9 @@ public void writeTo(com.google.protobuf.CodedOutputStream output)
     if (shareClusterDevicesInSession_ != false) {
       output.writeBool(17, shareClusterDevicesInSession_);
     }
+    if (pluggableDeviceOptions_ != null) {
+      output.writeMessage(18, getPluggableDeviceOptions());
+    }
     getUnknownFields().writeTo(output);
   }
 
@@ -4844,6 +4981,10 @@ public int getSerializedSize() {
       size += com.google.protobuf.CodedOutputStream
         .computeBoolSize(17, shareClusterDevicesInSession_);
     }
+    if (pluggableDeviceOptions_ != null) {
+      size += com.google.protobuf.CodedOutputStream
+        .computeMessageSize(18, getPluggableDeviceOptions());
+    }
     size += getUnknownFields().getSerializedSize();
     memoizedSize = size;
     return size;
@@ -4878,6 +5019,11 @@ public boolean equals(final java.lang.Object obj) {
       if (!getGpuOptions()
           .equals(other.getGpuOptions())) return false;
     }
+    if (hasPluggableDeviceOptions() != other.hasPluggableDeviceOptions()) return false;
+    if (hasPluggableDeviceOptions()) {
+      if (!getPluggableDeviceOptions()
+          .equals(other.getPluggableDeviceOptions())) return false;
+    }
     if (getAllowSoftPlacement()
         != other.getAllowSoftPlacement()) return false;
     if (getLogDevicePlacement()
@@ -4944,6 +5090,10 @@ public int hashCode() {
       hash = (37 * hash) + GPU_OPTIONS_FIELD_NUMBER;
       hash = (53 * hash) + getGpuOptions().hashCode();
     }
+    if (hasPluggableDeviceOptions()) {
+      hash = (37 * hash) + PLUGGABLE_DEVICE_OPTIONS_FIELD_NUMBER;
+      hash = (53 * hash) + getPluggableDeviceOptions().hashCode();
+    }
     hash = (37 * hash) + ALLOW_SOFT_PLACEMENT_FIELD_NUMBER;
     hash = (53 * hash) + com.google.protobuf.Internal.hashBoolean(
         getAllowSoftPlacement());
@@ -5154,6 +5304,12 @@ public Builder clear() {
         gpuOptions_ = null;
         gpuOptionsBuilder_ = null;
       }
+      if (pluggableDeviceOptionsBuilder_ == null) {
+        pluggableDeviceOptions_ = null;
+      } else {
+        pluggableDeviceOptions_ = null;
+        pluggableDeviceOptionsBuilder_ = null;
+      }
       allowSoftPlacement_ = false;
 
       logDevicePlacement_ = false;
@@ -5240,6 +5396,11 @@ public org.tensorflow.proto.ConfigProto buildPartial() {
       } else {
         result.gpuOptions_ = gpuOptionsBuilder_.build();
       }
+      if (pluggableDeviceOptionsBuilder_ == null) {
+        result.pluggableDeviceOptions_ = pluggableDeviceOptions_;
+      } else {
+        result.pluggableDeviceOptions_ = pluggableDeviceOptionsBuilder_.build();
+      }
       result.allowSoftPlacement_ = allowSoftPlacement_;
       result.logDevicePlacement_ = logDevicePlacement_;
       if (graphOptionsBuilder_ == null) {
@@ -5366,6 +5527,9 @@ public Builder mergeFrom(org.tensorflow.proto.ConfigProto other) {
       if (other.hasGpuOptions()) {
         mergeGpuOptions(other.getGpuOptions());
       }
+      if (other.hasPluggableDeviceOptions()) {
+        mergePluggableDeviceOptions(other.getPluggableDeviceOptions());
+      }
       if (other.getAllowSoftPlacement() != false) {
         setAllowSoftPlacement(other.getAllowSoftPlacement());
       }
@@ -5526,6 +5690,13 @@ public Builder mergeFrom(
 
               break;
             } // case 136
+            case 146: {
+              input.readMessage(
+                  getPluggableDeviceOptionsFieldBuilder().getBuilder(),
+                  extensionRegistry);
+
+              break;
+            } // case 146
             default: {
               if (!super.parseUnknownField(input, extensionRegistry, tag)) {
                 done = true; // was an endgroup tag
@@ -6886,6 +7057,161 @@ public org.tensorflow.proto.GPUOptionsOrBuilder getGpuOptionsOrBuilder() {
       return gpuOptionsBuilder_;
     }
 
+    private org.tensorflow.proto.GPUOptions pluggableDeviceOptions_;
+    private com.google.protobuf.SingleFieldBuilderV3<
+        org.tensorflow.proto.GPUOptions, org.tensorflow.proto.GPUOptions.Builder, org.tensorflow.proto.GPUOptionsOrBuilder> pluggableDeviceOptionsBuilder_;
+    /**
+     * 
+     * Options that apply to pluggable devices.
+     * 

+     *
+     * .tensorflow.GPUOptions pluggable_device_options = 18;
+     * @return Whether the pluggableDeviceOptions field is set.
+     */
+    public boolean hasPluggableDeviceOptions() {
+      return pluggableDeviceOptionsBuilder_ != null || pluggableDeviceOptions_ != null;
+    }
+    /**
+     * 
+     * Options that apply to pluggable devices.
+     * 

+     *
+     * .tensorflow.GPUOptions pluggable_device_options = 18;
+     * @return The pluggableDeviceOptions.
+     */
+    public org.tensorflow.proto.GPUOptions getPluggableDeviceOptions() {
+      if (pluggableDeviceOptionsBuilder_ == null) {
+        return pluggableDeviceOptions_ == null ? org.tensorflow.proto.GPUOptions.getDefaultInstance() : pluggableDeviceOptions_;
+      } else {
+        return pluggableDeviceOptionsBuilder_.getMessage();
+      }
+    }
+    /**
+     * 
+     * Options that apply to pluggable devices.
+     * 

+     *
+     * .tensorflow.GPUOptions pluggable_device_options = 18;
+     */
+    public Builder setPluggableDeviceOptions(org.tensorflow.proto.GPUOptions value) {
+      if (pluggableDeviceOptionsBuilder_ == null) {
+        if (value == null) {
+          throw new NullPointerException();
+        }
+        pluggableDeviceOptions_ = value;
+        onChanged();
+      } else {
+        pluggableDeviceOptionsBuilder_.setMessage(value);
+      }
+
+      return this;
+    }
+    /**
+     * 
+     * Options that apply to pluggable devices.
+     * 

+     *
+     * .tensorflow.GPUOptions pluggable_device_options = 18;
+     */
+    public Builder setPluggableDeviceOptions(
+        org.tensorflow.proto.GPUOptions.Builder builderForValue) {
+      if (pluggableDeviceOptionsBuilder_ == null) {
+        pluggableDeviceOptions_ = builderForValue.build();
+        onChanged();
+      } else {
+        pluggableDeviceOptionsBuilder_.setMessage(builderForValue.build());
+      }
+
+      return this;
+    }
+    /**
+     * 
+     * Options that apply to pluggable devices.
+     * 

+     *
+     * .tensorflow.GPUOptions pluggable_device_options = 18;
+     */
+    public Builder mergePluggableDeviceOptions(org.tensorflow.proto.GPUOptions value) {
+      if (pluggableDeviceOptionsBuilder_ == null) {
+        if (pluggableDeviceOptions_ != null) {
+          pluggableDeviceOptions_ =
+            org.tensorflow.proto.GPUOptions.newBuilder(pluggableDeviceOptions_).mergeFrom(value).buildPartial();
+        } else {
+          pluggableDeviceOptions_ = value;
+        }
+        onChanged();
+      } else {
+        pluggableDeviceOptionsBuilder_.mergeFrom(value);
+      }
+
+      return this;
+    }
+    /**
+     * 
+     * Options that apply to pluggable devices.
+     * 

+     *
+     * .tensorflow.GPUOptions pluggable_device_options = 18;
+     */
+    public Builder clearPluggableDeviceOptions() {
+      if (pluggableDeviceOptionsBuilder_ == null) {
+        pluggableDeviceOptions_ = null;
+        onChanged();
+      } else {
+        pluggableDeviceOptions_ = null;
+        pluggableDeviceOptionsBuilder_ = null;
+      }
+
+      return this;
+    }
+    /**
+     * 
+     * Options that apply to pluggable devices.
+     * 

+     *
+     * .tensorflow.GPUOptions pluggable_device_options = 18;
+     */
+    public org.tensorflow.proto.GPUOptions.Builder getPluggableDeviceOptionsBuilder() {
+      
+      onChanged();
+      return getPluggableDeviceOptionsFieldBuilder().getBuilder();
+    }
+    /**
+     * 
+     * Options that apply to pluggable devices.
+     * 

+     *
+     * .tensorflow.GPUOptions pluggable_device_options = 18;
+     */
+    public org.tensorflow.proto.GPUOptionsOrBuilder getPluggableDeviceOptionsOrBuilder() {
+      if (pluggableDeviceOptionsBuilder_ != null) {
+        return pluggableDeviceOptionsBuilder_.getMessageOrBuilder();
+      } else {
+        return pluggableDeviceOptions_ == null ?
+            org.tensorflow.proto.GPUOptions.getDefaultInstance() : pluggableDeviceOptions_;
+      }
+    }
+    /**
+     * 
+     * Options that apply to pluggable devices.
+     * 

+     *
+     * .tensorflow.GPUOptions pluggable_device_options = 18;
+     */
+    private com.google.protobuf.SingleFieldBuilderV3<
+        org.tensorflow.proto.GPUOptions, org.tensorflow.proto.GPUOptions.Builder, org.tensorflow.proto.GPUOptionsOrBuilder> 
+        getPluggableDeviceOptionsFieldBuilder() {
+      if (pluggableDeviceOptionsBuilder_ == null) {
+        pluggableDeviceOptionsBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
+            org.tensorflow.proto.GPUOptions, org.tensorflow.proto.GPUOptions.Builder, org.tensorflow.proto.GPUOptionsOrBuilder>(
+                getPluggableDeviceOptions(),
+                getParentForChildren(),
+                isClean());
+        pluggableDeviceOptions_ = null;
+      }
+      return pluggableDeviceOptionsBuilder_;
+    }
+
     private boolean allowSoftPlacement_ ;
     /**
      * 
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ConfigProtoOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ConfigProtoOrBuilder.java
index d158b44e08f..29a052555c6 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ConfigProtoOrBuilder.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ConfigProtoOrBuilder.java
@@ -341,6 +341,33 @@ org.tensorflow.proto.ThreadPoolOptionProtoOrBuilder getSessionInterOpThreadPoolO
    */
   org.tensorflow.proto.GPUOptionsOrBuilder getGpuOptionsOrBuilder();
 
+  /**
+   * 
+   * Options that apply to pluggable devices.
+   * 

+   *
+   * .tensorflow.GPUOptions pluggable_device_options = 18;
+   * @return Whether the pluggableDeviceOptions field is set.
+   */
+  boolean hasPluggableDeviceOptions();
+  /**
+   * 
+   * Options that apply to pluggable devices.
+   * 

+   *
+   * .tensorflow.GPUOptions pluggable_device_options = 18;
+   * @return The pluggableDeviceOptions.
+   */
+  org.tensorflow.proto.GPUOptions getPluggableDeviceOptions();
+  /**
+   * 
+   * Options that apply to pluggable devices.
+   * 

+   *
+   * .tensorflow.GPUOptions pluggable_device_options = 18;
+   */
+  org.tensorflow.proto.GPUOptionsOrBuilder getPluggableDeviceOptionsOrBuilder();
+
   /**
    * 
    * Whether soft placement is allowed. If allow_soft_placement is true,
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ConfigProtos.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ConfigProtos.java
index bca6f96f8b0..ee8eb70f710 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ConfigProtos.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ConfigProtos.java
@@ -29,6 +29,11 @@ public static void registerAllExtensions(
   static final 
     com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
       internal_static_tensorflow_GPUOptions_Experimental_VirtualDevices_fieldAccessorTable;
+  static final com.google.protobuf.Descriptors.Descriptor
+    internal_static_tensorflow_GPUOptions_Experimental_StreamMergeOptions_descriptor;
+  static final 
+    com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
+      internal_static_tensorflow_GPUOptions_Experimental_StreamMergeOptions_fieldAccessorTable;
   static final com.google.protobuf.Descriptors.Descriptor
     internal_static_tensorflow_OptimizerOptions_descriptor;
   static final 
@@ -127,7 +132,7 @@ public static void registerAllExtensions(
       "obuf/debug.proto\032.tensorflow/core/protob" +
       "uf/rewriter_config.proto\032*tensorflow/cor" +
       "e/protobuf/rpc_options.proto\032&tsl/protob" +
-      "uf/coordination_config.proto\"\352\007\n\nGPUOpti" +
+      "uf/coordination_config.proto\"\211\n\n\nGPUOpti" +
       "ons\022\'\n\037per_process_gpu_memory_fraction\030\001" +
       " \001(\001\022\024\n\014allow_growth\030\004 \001(\010\022\026\n\016allocator_" +
       "type\030\002 \001(\t\022\037\n\027deferred_deletion_bytes\030\003 " +
@@ -135,7 +140,7 @@ public static void registerAllExtensions(
       "ing_active_delay_usecs\030\006 \001(\005\022$\n\034polling_" +
       "inactive_delay_msecs\030\007 \001(\005\022\034\n\024force_gpu_" +
       "compatible\030\010 \001(\010\0229\n\014experimental\030\t \001(\0132#" +
-      ".tensorflow.GPUOptions.Experimental\032\243\005\n\014" +
+      ".tensorflow.GPUOptions.Experimental\032\302\007\n\014" +
       "Experimental\022K\n\017virtual_devices\030\001 \003(\01322." +
       "tensorflow.GPUOptions.Experimental.Virtu" +
       "alDevices\022#\n\033num_virtual_devices_per_gpu" +
@@ -150,126 +155,135 @@ public static void registerAllExtensions(
       "llow_retry_on_allocation_failure\030\014 \001(\010\022 " +
       "\n\030gpu_host_mem_limit_in_mb\030\r \001(\002\022$\n\034gpu_" +
       "host_mem_disallow_growth\030\016 \001(\010\022$\n\034gpu_sy" +
-      "stem_memory_size_in_mb\030\020 \001(\005\032S\n\016VirtualD" +
-      "evices\022\027\n\017memory_limit_mb\030\001 \003(\002\022\020\n\010prior" +
-      "ity\030\002 \003(\005\022\026\n\016device_ordinal\030\003 \003(\005\"\235\003\n\020Op" +
-      "timizerOptions\022+\n#do_common_subexpressio" +
-      "n_elimination\030\001 \001(\010\022\033\n\023do_constant_foldi" +
-      "ng\030\002 \001(\010\022$\n\034max_folded_constant_in_bytes" +
-      "\030\006 \001(\003\022\034\n\024do_function_inlining\030\004 \001(\010\0225\n\t" +
-      "opt_level\030\003 \001(\0162\".tensorflow.OptimizerOp" +
-      "tions.Level\022E\n\020global_jit_level\030\005 \001(\0162+." +
-      "tensorflow.OptimizerOptions.GlobalJitLev" +
-      "el\022\026\n\016cpu_global_jit\030\007 \001(\010\" \n\005Level\022\006\n\002L" +
-      "1\020\000\022\017\n\002L0\020\377\377\377\377\377\377\377\377\377\001\"C\n\016GlobalJitLevel\022\013" +
-      "\n\007DEFAULT\020\000\022\020\n\003OFF\020\377\377\377\377\377\377\377\377\377\001\022\010\n\004ON_1\020\001\022" +
-      "\010\n\004ON_2\020\002\"\356\002\n\014GraphOptions\022\036\n\026enable_rec" +
-      "v_scheduling\030\002 \001(\010\0227\n\021optimizer_options\030" +
-      "\003 \001(\0132\034.tensorflow.OptimizerOptions\022\030\n\020b" +
-      "uild_cost_model\030\004 \001(\003\022\036\n\026build_cost_mode" +
-      "l_after\030\t \001(\003\022\024\n\014infer_shapes\030\005 \001(\010\022\032\n\022p" +
-      "lace_pruned_graph\030\006 \001(\010\022 \n\030enable_bfloat" +
-      "16_sendrecv\030\007 \001(\010\022\025\n\rtimeline_step\030\010 \001(\005" +
-      "\0223\n\017rewrite_options\030\n \001(\0132\032.tensorflow.R" +
-      "ewriterConfigJ\004\010\001\020\002R%skip_common_subexpr" +
-      "ession_elimination\"A\n\025ThreadPoolOptionPr" +
-      "oto\022\023\n\013num_threads\030\001 \001(\005\022\023\n\013global_name\030" +
-      "\002 \001(\t\"0\n\017SessionMetadata\022\014\n\004name\030\001 \001(\t\022\017" +
-      "\n\007version\030\002 \001(\003\"\225\020\n\013ConfigProto\022>\n\014devic" +
-      "e_count\030\001 \003(\0132(.tensorflow.ConfigProto.D" +
-      "eviceCountEntry\022$\n\034intra_op_parallelism_" +
-      "threads\030\002 \001(\005\022$\n\034inter_op_parallelism_th" +
-      "reads\030\005 \001(\005\022\037\n\027use_per_session_threads\030\t" +
-      " \001(\010\022G\n\034session_inter_op_thread_pool\030\014 \003" +
-      "(\0132!.tensorflow.ThreadPoolOptionProto\022\030\n" +
-      "\020placement_period\030\003 \001(\005\022\026\n\016device_filter" +
-      "s\030\004 \003(\t\022+\n\013gpu_options\030\006 \001(\0132\026.tensorflo" +
-      "w.GPUOptions\022\034\n\024allow_soft_placement\030\007 \001" +
-      "(\010\022\034\n\024log_device_placement\030\010 \001(\010\022/\n\rgrap" +
-      "h_options\030\n \001(\0132\030.tensorflow.GraphOption" +
-      "s\022\037\n\027operation_timeout_in_ms\030\013 \001(\003\022+\n\013rp" +
-      "c_options\030\r \001(\0132\026.tensorflow.RPCOptions\022" +
-      "+\n\013cluster_def\030\016 \001(\0132\026.tensorflow.Cluste" +
-      "rDef\022\035\n\025isolate_session_state\030\017 \001(\010\022(\n s" +
-      "hare_cluster_devices_in_session\030\021 \001(\010\022:\n" +
-      "\014experimental\030\020 \001(\0132$.tensorflow.ConfigP" +
-      "roto.Experimental\0322\n\020DeviceCountEntry\022\013\n" +
-      "\003key\030\001 \001(\t\022\r\n\005value\030\002 \001(\005:\0028\001\032\217\n\n\014Experi" +
-      "mental\022\037\n\027collective_group_leader\030\001 \001(\t\022" +
-      "\025\n\rexecutor_type\030\003 \001(\t\022\032\n\022recv_buf_max_c" +
-      "hunk\030\004 \001(\005\022\031\n\021use_numa_affinity\030\005 \001(\010\0225\n" +
-      "-collective_deterministic_sequential_exe" +
-      "cution\030\006 \001(\010\022\027\n\017collective_nccl\030\007 \001(\010\0226\n" +
-      ".share_session_state_in_clusterspec_prop" +
-      "agation\030\010 \001(\010\022\037\n\027disable_thread_spinning" +
-      "\030\t \001(\010\022(\n share_cluster_devices_in_sessi" +
-      "on\030\n \001(\010\0225\n\020session_metadata\030\013 \001(\0132\033.ten" +
-      "sorflow.SessionMetadata\022!\n\031optimize_for_" +
-      "static_graph\030\014 \001(\010\022\032\n\022enable_mlir_bridge" +
-      "\030\r \001(\010\022S\n\023mlir_bridge_rollout\030\021 \001(\01626.te" +
-      "nsorflow.ConfigProto.Experimental.MlirBr" +
-      "idgeRollout\022&\n\036enable_mlir_graph_optimiz" +
-      "ation\030\020 \001(\010\022\'\n\037disable_output_partition_" +
-      "graphs\030\016 \001(\010\022#\n\033xla_fusion_autotuner_thr" +
-      "esh\030\017 \001(\003\022\020\n\010use_tfrt\030\022 \001(\010\022\031\n\021enable_mu" +
-      "lti_host\030\033 \001(\010\022\033\n\023backend_server_port\030\034 " +
-      "\001(\005\022\022\n\ntarget_tpu\030\035 \001(\010\022\022\n\ntarget_gpu\030\036 " +
-      "\001(\010\022\036\n\026stream_merge_threshold\030\037 \001(\005\022\'\n\037d" +
-      "isable_functional_ops_lowering\030\025 \001(\010\022\'\n\037" +
-      "xla_prefer_single_graph_cluster\030\026 \001(\010\022B\n" +
-      "\023coordination_config\030\027 \001(\0132%.tensorflow." +
-      "CoordinationServiceConfig\022)\n!disable_opt" +
-      "imize_for_static_graph\030\030 \001(\010\0220\n(disable_" +
-      "eager_executor_streaming_enqueue\030\032 \001(\010\"\336" +
-      "\001\n\021MlirBridgeRollout\022#\n\037MLIR_BRIDGE_ROLL" +
-      "OUT_UNSPECIFIED\020\000\022\037\n\033MLIR_BRIDGE_ROLLOUT" +
-      "_ENABLED\020\001\022 \n\034MLIR_BRIDGE_ROLLOUT_DISABL" +
-      "ED\020\002\"\004\010\003\020\003\"\004\010\004\020\004*%MLIR_BRIDGE_ROLLOUT_SA" +
-      "FE_MODE_ENABLED*.MLIR_BRIDGE_ROLLOUT_SAF" +
-      "E_MODE_FALLBACK_ENABLEDJ\004\010\002\020\003J\004\010\023\020\024J\004\010\024\020" +
-      "\025J\004\010\031\020\032\"\341\004\n\nRunOptions\0226\n\013trace_level\030\001 " +
-      "\001(\0162!.tensorflow.RunOptions.TraceLevel\022\025" +
-      "\n\rtimeout_in_ms\030\002 \001(\003\022\034\n\024inter_op_thread" +
-      "_pool\030\003 \001(\005\022\037\n\027output_partition_graphs\030\005" +
-      " \001(\010\022/\n\rdebug_options\030\006 \001(\0132\030.tensorflow" +
-      ".DebugOptions\022*\n\"report_tensor_allocatio" +
-      "ns_upon_oom\030\007 \001(\010\0229\n\014experimental\030\010 \001(\0132" +
-      "#.tensorflow.RunOptions.Experimental\032\322\001\n" +
-      "\014Experimental\022\034\n\024collective_graph_key\030\001 " +
-      "\001(\003\022\034\n\024use_run_handler_pool\030\002 \001(\010\022[\n\030run" +
-      "_handler_pool_options\030\003 \001(\01329.tensorflow" +
-      ".RunOptions.Experimental.RunHandlerPoolO" +
-      "ptions\032)\n\025RunHandlerPoolOptions\022\020\n\010prior" +
-      "ity\030\001 \001(\003\"R\n\nTraceLevel\022\014\n\010NO_TRACE\020\000\022\022\n" +
-      "\016SOFTWARE_TRACE\020\001\022\022\n\016HARDWARE_TRACE\020\002\022\016\n" +
-      "\nFULL_TRACE\020\003J\004\010\004\020\005\"\276\003\n\013RunMetadata\022)\n\ns" +
-      "tep_stats\030\001 \001(\0132\025.tensorflow.StepStats\022," +
-      "\n\ncost_graph\030\002 \001(\0132\030.tensorflow.CostGrap" +
-      "hDef\022.\n\020partition_graphs\030\003 \003(\0132\024.tensorf" +
-      "low.GraphDef\022?\n\017function_graphs\030\004 \003(\0132&." +
-      "tensorflow.RunMetadata.FunctionGraphs\0225\n" +
-      "\020session_metadata\030\005 \001(\0132\033.tensorflow.Ses" +
-      "sionMetadata\032\255\001\n\016FunctionGraphs\022.\n\020parti" +
-      "tion_graphs\030\001 \003(\0132\024.tensorflow.GraphDef\022" +
-      "4\n\026pre_optimization_graph\030\002 \001(\0132\024.tensor" +
-      "flow.GraphDef\0225\n\027post_optimization_graph" +
-      "\030\003 \001(\0132\024.tensorflow.GraphDef\":\n\020TensorCo" +
-      "nnection\022\023\n\013from_tensor\030\001 \001(\t\022\021\n\tto_tens" +
-      "or\030\002 \001(\t\"\260\003\n\017CallableOptions\022\014\n\004feed\030\001 \003" +
-      "(\t\022\r\n\005fetch\030\002 \003(\t\022\016\n\006target\030\003 \003(\t\022+\n\013run" +
-      "_options\030\004 \001(\0132\026.tensorflow.RunOptions\0227" +
-      "\n\021tensor_connection\030\005 \003(\0132\034.tensorflow.T" +
-      "ensorConnection\022B\n\014feed_devices\030\006 \003(\0132,." +
-      "tensorflow.CallableOptions.FeedDevicesEn" +
-      "try\022D\n\rfetch_devices\030\007 \003(\0132-.tensorflow." +
-      "CallableOptions.FetchDevicesEntry\022\027\n\017fet" +
-      "ch_skip_sync\030\010 \001(\010\0322\n\020FeedDevicesEntry\022\013" +
-      "\n\003key\030\001 \001(\t\022\r\n\005value\030\002 \001(\t:\0028\001\0323\n\021FetchD" +
-      "evicesEntry\022\013\n\003key\030\001 \001(\t\022\r\n\005value\030\002 \001(\t:" +
-      "\0028\001B\200\001\n\024org.tensorflow.protoB\014ConfigProt" +
-      "osP\001ZUgithub.com/tensorflow/tensorflow/t" +
-      "ensorflow/go/core/protobuf/for_core_prot" +
-      "os_go_proto\370\001\001b\006proto3"
+      "stem_memory_size_in_mb\030\020 \001(\005\022.\n&populate" +
+      "_pjrt_gpu_client_creation_info\030\021 \001(\010\022\017\n\007" +
+      "node_id\030\022 \001(\005\022T\n\024stream_merge_options\030\023 " +
+      "\001(\01326.tensorflow.GPUOptions.Experimental" +
+      ".StreamMergeOptions\032S\n\016VirtualDevices\022\027\n" +
+      "\017memory_limit_mb\030\001 \003(\002\022\020\n\010priority\030\002 \003(\005" +
+      "\022\026\n\016device_ordinal\030\003 \003(\005\032\205\001\n\022StreamMerge" +
+      "Options\022#\n\033merge_host_to_device_stream\030\001" +
+      " \001(\010\022#\n\033merge_device_to_host_stream\030\002 \001(" +
+      "\010\022%\n\035merge_device_to_device_stream\030\003 \001(\010" +
+      "\"\235\003\n\020OptimizerOptions\022+\n#do_common_subex" +
+      "pression_elimination\030\001 \001(\010\022\033\n\023do_constan" +
+      "t_folding\030\002 \001(\010\022$\n\034max_folded_constant_i" +
+      "n_bytes\030\006 \001(\003\022\034\n\024do_function_inlining\030\004 " +
+      "\001(\010\0225\n\topt_level\030\003 \001(\0162\".tensorflow.Opti" +
+      "mizerOptions.Level\022E\n\020global_jit_level\030\005" +
+      " \001(\0162+.tensorflow.OptimizerOptions.Globa" +
+      "lJitLevel\022\026\n\016cpu_global_jit\030\007 \001(\010\" \n\005Lev" +
+      "el\022\006\n\002L1\020\000\022\017\n\002L0\020\377\377\377\377\377\377\377\377\377\001\"C\n\016GlobalJit" +
+      "Level\022\013\n\007DEFAULT\020\000\022\020\n\003OFF\020\377\377\377\377\377\377\377\377\377\001\022\010\n\004" +
+      "ON_1\020\001\022\010\n\004ON_2\020\002\"\356\002\n\014GraphOptions\022\036\n\026ena" +
+      "ble_recv_scheduling\030\002 \001(\010\0227\n\021optimizer_o" +
+      "ptions\030\003 \001(\0132\034.tensorflow.OptimizerOptio" +
+      "ns\022\030\n\020build_cost_model\030\004 \001(\003\022\036\n\026build_co" +
+      "st_model_after\030\t \001(\003\022\024\n\014infer_shapes\030\005 \001" +
+      "(\010\022\032\n\022place_pruned_graph\030\006 \001(\010\022 \n\030enable" +
+      "_bfloat16_sendrecv\030\007 \001(\010\022\025\n\rtimeline_ste" +
+      "p\030\010 \001(\005\0223\n\017rewrite_options\030\n \001(\0132\032.tenso" +
+      "rflow.RewriterConfigJ\004\010\001\020\002R%skip_common_" +
+      "subexpression_elimination\"A\n\025ThreadPoolO" +
+      "ptionProto\022\023\n\013num_threads\030\001 \001(\005\022\023\n\013globa" +
+      "l_name\030\002 \001(\t\"0\n\017SessionMetadata\022\014\n\004name\030" +
+      "\001 \001(\t\022\017\n\007version\030\002 \001(\003\"\346\020\n\013ConfigProto\022>" +
+      "\n\014device_count\030\001 \003(\0132(.tensorflow.Config" +
+      "Proto.DeviceCountEntry\022$\n\034intra_op_paral" +
+      "lelism_threads\030\002 \001(\005\022$\n\034inter_op_paralle" +
+      "lism_threads\030\005 \001(\005\022\037\n\027use_per_session_th" +
+      "reads\030\t \001(\010\022G\n\034session_inter_op_thread_p" +
+      "ool\030\014 \003(\0132!.tensorflow.ThreadPoolOptionP" +
+      "roto\022\030\n\020placement_period\030\003 \001(\005\022\026\n\016device" +
+      "_filters\030\004 \003(\t\022+\n\013gpu_options\030\006 \001(\0132\026.te" +
+      "nsorflow.GPUOptions\0228\n\030pluggable_device_" +
+      "options\030\022 \001(\0132\026.tensorflow.GPUOptions\022\034\n" +
+      "\024allow_soft_placement\030\007 \001(\010\022\034\n\024log_devic" +
+      "e_placement\030\010 \001(\010\022/\n\rgraph_options\030\n \001(\013" +
+      "2\030.tensorflow.GraphOptions\022\037\n\027operation_" +
+      "timeout_in_ms\030\013 \001(\003\022+\n\013rpc_options\030\r \001(\013" +
+      "2\026.tensorflow.RPCOptions\022+\n\013cluster_def\030" +
+      "\016 \001(\0132\026.tensorflow.ClusterDef\022\035\n\025isolate" +
+      "_session_state\030\017 \001(\010\022(\n share_cluster_de" +
+      "vices_in_session\030\021 \001(\010\022:\n\014experimental\030\020" +
+      " \001(\0132$.tensorflow.ConfigProto.Experiment" +
+      "al\0322\n\020DeviceCountEntry\022\013\n\003key\030\001 \001(\t\022\r\n\005v" +
+      "alue\030\002 \001(\005:\0028\001\032\246\n\n\014Experimental\022\037\n\027colle" +
+      "ctive_group_leader\030\001 \001(\t\022\025\n\rexecutor_typ" +
+      "e\030\003 \001(\t\022\032\n\022recv_buf_max_chunk\030\004 \001(\005\022\031\n\021u" +
+      "se_numa_affinity\030\005 \001(\010\0225\n-collective_det" +
+      "erministic_sequential_execution\030\006 \001(\010\022\027\n" +
+      "\017collective_nccl\030\007 \001(\010\0226\n.share_session_" +
+      "state_in_clusterspec_propagation\030\010 \001(\010\022\037" +
+      "\n\027disable_thread_spinning\030\t \001(\010\022(\n share" +
+      "_cluster_devices_in_session\030\n \001(\010\0225\n\020ses" +
+      "sion_metadata\030\013 \001(\0132\033.tensorflow.Session" +
+      "Metadata\022!\n\031optimize_for_static_graph\030\014 " +
+      "\001(\010\022\032\n\022enable_mlir_bridge\030\r \001(\010\022S\n\023mlir_" +
+      "bridge_rollout\030\021 \001(\01626.tensorflow.Config" +
+      "Proto.Experimental.MlirBridgeRollout\022&\n\036" +
+      "enable_mlir_graph_optimization\030\020 \001(\010\022\'\n\037" +
+      "disable_output_partition_graphs\030\016 \001(\010\022#\n" +
+      "\033xla_fusion_autotuner_thresh\030\017 \001(\003\022\020\n\010us" +
+      "e_tfrt\030\022 \001(\010\022\031\n\021enable_multi_host\030\033 \001(\010\022" +
+      "\025\n\rtfrt_use_ifrt\030  \001(\010\022\033\n\023backend_server" +
+      "_port\030\034 \001(\005\022\022\n\ntarget_tpu\030\035 \001(\010\022\022\n\ntarge" +
+      "t_gpu\030\036 \001(\010\022\036\n\026stream_merge_threshold\030\037 " +
+      "\001(\005\022\'\n\037disable_functional_ops_lowering\030\025" +
+      " \001(\010\022\'\n\037xla_prefer_single_graph_cluster\030" +
+      "\026 \001(\010\022B\n\023coordination_config\030\027 \001(\0132%.ten" +
+      "sorflow.CoordinationServiceConfig\022)\n!dis" +
+      "able_optimize_for_static_graph\030\030 \001(\010\0220\n(" +
+      "disable_eager_executor_streaming_enqueue" +
+      "\030\032 \001(\010\"\336\001\n\021MlirBridgeRollout\022#\n\037MLIR_BRI" +
+      "DGE_ROLLOUT_UNSPECIFIED\020\000\022\037\n\033MLIR_BRIDGE" +
+      "_ROLLOUT_ENABLED\020\001\022 \n\034MLIR_BRIDGE_ROLLOU" +
+      "T_DISABLED\020\002\"\004\010\003\020\003\"\004\010\004\020\004*%MLIR_BRIDGE_RO" +
+      "LLOUT_SAFE_MODE_ENABLED*.MLIR_BRIDGE_ROL" +
+      "LOUT_SAFE_MODE_FALLBACK_ENABLEDJ\004\010\002\020\003J\004\010" +
+      "\023\020\024J\004\010\024\020\025J\004\010\031\020\032\"\341\004\n\nRunOptions\0226\n\013trace_" +
+      "level\030\001 \001(\0162!.tensorflow.RunOptions.Trac" +
+      "eLevel\022\025\n\rtimeout_in_ms\030\002 \001(\003\022\034\n\024inter_o" +
+      "p_thread_pool\030\003 \001(\005\022\037\n\027output_partition_" +
+      "graphs\030\005 \001(\010\022/\n\rdebug_options\030\006 \001(\0132\030.te" +
+      "nsorflow.DebugOptions\022*\n\"report_tensor_a" +
+      "llocations_upon_oom\030\007 \001(\010\0229\n\014experimenta" +
+      "l\030\010 \001(\0132#.tensorflow.RunOptions.Experime" +
+      "ntal\032\322\001\n\014Experimental\022\034\n\024collective_grap" +
+      "h_key\030\001 \001(\003\022\034\n\024use_run_handler_pool\030\002 \001(" +
+      "\010\022[\n\030run_handler_pool_options\030\003 \001(\01329.te" +
+      "nsorflow.RunOptions.Experimental.RunHand" +
+      "lerPoolOptions\032)\n\025RunHandlerPoolOptions\022" +
+      "\020\n\010priority\030\001 \001(\003\"R\n\nTraceLevel\022\014\n\010NO_TR" +
+      "ACE\020\000\022\022\n\016SOFTWARE_TRACE\020\001\022\022\n\016HARDWARE_TR" +
+      "ACE\020\002\022\016\n\nFULL_TRACE\020\003J\004\010\004\020\005\"\276\003\n\013RunMetad" +
+      "ata\022)\n\nstep_stats\030\001 \001(\0132\025.tensorflow.Ste" +
+      "pStats\022,\n\ncost_graph\030\002 \001(\0132\030.tensorflow." +
+      "CostGraphDef\022.\n\020partition_graphs\030\003 \003(\0132\024" +
+      ".tensorflow.GraphDef\022?\n\017function_graphs\030" +
+      "\004 \003(\0132&.tensorflow.RunMetadata.FunctionG" +
+      "raphs\0225\n\020session_metadata\030\005 \001(\0132\033.tensor" +
+      "flow.SessionMetadata\032\255\001\n\016FunctionGraphs\022" +
+      ".\n\020partition_graphs\030\001 \003(\0132\024.tensorflow.G" +
+      "raphDef\0224\n\026pre_optimization_graph\030\002 \001(\0132" +
+      "\024.tensorflow.GraphDef\0225\n\027post_optimizati" +
+      "on_graph\030\003 \001(\0132\024.tensorflow.GraphDef\":\n\020" +
+      "TensorConnection\022\023\n\013from_tensor\030\001 \001(\t\022\021\n" +
+      "\tto_tensor\030\002 \001(\t\"\260\003\n\017CallableOptions\022\014\n\004" +
+      "feed\030\001 \003(\t\022\r\n\005fetch\030\002 \003(\t\022\016\n\006target\030\003 \003(" +
+      "\t\022+\n\013run_options\030\004 \001(\0132\026.tensorflow.RunO" +
+      "ptions\0227\n\021tensor_connection\030\005 \003(\0132\034.tens" +
+      "orflow.TensorConnection\022B\n\014feed_devices\030" +
+      "\006 \003(\0132,.tensorflow.CallableOptions.FeedD" +
+      "evicesEntry\022D\n\rfetch_devices\030\007 \003(\0132-.ten" +
+      "sorflow.CallableOptions.FetchDevicesEntr" +
+      "y\022\027\n\017fetch_skip_sync\030\010 \001(\010\0322\n\020FeedDevice" +
+      "sEntry\022\013\n\003key\030\001 \001(\t\022\r\n\005value\030\002 \001(\t:\0028\001\0323" +
+      "\n\021FetchDevicesEntry\022\013\n\003key\030\001 \001(\t\022\r\n\005valu" +
+      "e\030\002 \001(\t:\0028\001B\200\001\n\024org.tensorflow.protoB\014Co" +
+      "nfigProtosP\001ZUgithub.com/tensorflow/tens" +
+      "orflow/tensorflow/go/core/protobuf/for_c" +
+      "ore_protos_go_proto\370\001\001b\006proto3"
     };
     descriptor = com.google.protobuf.Descriptors.FileDescriptor
       .internalBuildGeneratedFileFrom(descriptorData,
@@ -294,13 +308,19 @@ public static void registerAllExtensions(
     internal_static_tensorflow_GPUOptions_Experimental_fieldAccessorTable = new
       com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
         internal_static_tensorflow_GPUOptions_Experimental_descriptor,
-        new java.lang.String[] { "VirtualDevices", "NumVirtualDevicesPerGpu", "UseUnifiedMemory", "NumDevToDevCopyStreams", "CollectiveRingOrder", "TimestampedAllocator", "KernelTrackerMaxInterval", "KernelTrackerMaxBytes", "KernelTrackerMaxPending", "InternalFragmentationFraction", "UseCudaMallocAsync", "DisallowRetryOnAllocationFailure", "GpuHostMemLimitInMb", "GpuHostMemDisallowGrowth", "GpuSystemMemorySizeInMb", });
+        new java.lang.String[] { "VirtualDevices", "NumVirtualDevicesPerGpu", "UseUnifiedMemory", "NumDevToDevCopyStreams", "CollectiveRingOrder", "TimestampedAllocator", "KernelTrackerMaxInterval", "KernelTrackerMaxBytes", "KernelTrackerMaxPending", "InternalFragmentationFraction", "UseCudaMallocAsync", "DisallowRetryOnAllocationFailure", "GpuHostMemLimitInMb", "GpuHostMemDisallowGrowth", "GpuSystemMemorySizeInMb", "PopulatePjrtGpuClientCreationInfo", "NodeId", "StreamMergeOptions", });
     internal_static_tensorflow_GPUOptions_Experimental_VirtualDevices_descriptor =
       internal_static_tensorflow_GPUOptions_Experimental_descriptor.getNestedTypes().get(0);
     internal_static_tensorflow_GPUOptions_Experimental_VirtualDevices_fieldAccessorTable = new
       com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
         internal_static_tensorflow_GPUOptions_Experimental_VirtualDevices_descriptor,
         new java.lang.String[] { "MemoryLimitMb", "Priority", "DeviceOrdinal", });
+    internal_static_tensorflow_GPUOptions_Experimental_StreamMergeOptions_descriptor =
+      internal_static_tensorflow_GPUOptions_Experimental_descriptor.getNestedTypes().get(1);
+    internal_static_tensorflow_GPUOptions_Experimental_StreamMergeOptions_fieldAccessorTable = new
+      com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
+        internal_static_tensorflow_GPUOptions_Experimental_StreamMergeOptions_descriptor,
+        new java.lang.String[] { "MergeHostToDeviceStream", "MergeDeviceToHostStream", "MergeDeviceToDeviceStream", });
     internal_static_tensorflow_OptimizerOptions_descriptor =
       getDescriptor().getMessageTypes().get(1);
     internal_static_tensorflow_OptimizerOptions_fieldAccessorTable = new
@@ -330,7 +350,7 @@ public static void registerAllExtensions(
     internal_static_tensorflow_ConfigProto_fieldAccessorTable = new
       com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
         internal_static_tensorflow_ConfigProto_descriptor,
-        new java.lang.String[] { "DeviceCount", "IntraOpParallelismThreads", "InterOpParallelismThreads", "UsePerSessionThreads", "SessionInterOpThreadPool", "PlacementPeriod", "DeviceFilters", "GpuOptions", "AllowSoftPlacement", "LogDevicePlacement", "GraphOptions", "OperationTimeoutInMs", "RpcOptions", "ClusterDef", "IsolateSessionState", "ShareClusterDevicesInSession", "Experimental", });
+        new java.lang.String[] { "DeviceCount", "IntraOpParallelismThreads", "InterOpParallelismThreads", "UsePerSessionThreads", "SessionInterOpThreadPool", "PlacementPeriod", "DeviceFilters", "GpuOptions", "PluggableDeviceOptions", "AllowSoftPlacement", "LogDevicePlacement", "GraphOptions", "OperationTimeoutInMs", "RpcOptions", "ClusterDef", "IsolateSessionState", "ShareClusterDevicesInSession", "Experimental", });
     internal_static_tensorflow_ConfigProto_DeviceCountEntry_descriptor =
       internal_static_tensorflow_ConfigProto_descriptor.getNestedTypes().get(0);
     internal_static_tensorflow_ConfigProto_DeviceCountEntry_fieldAccessorTable = new
@@ -342,7 +362,7 @@ public static void registerAllExtensions(
     internal_static_tensorflow_ConfigProto_Experimental_fieldAccessorTable = new
       com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
         internal_static_tensorflow_ConfigProto_Experimental_descriptor,
-        new java.lang.String[] { "CollectiveGroupLeader", "ExecutorType", "RecvBufMaxChunk", "UseNumaAffinity", "CollectiveDeterministicSequentialExecution", "CollectiveNccl", "ShareSessionStateInClusterspecPropagation", "DisableThreadSpinning", "ShareClusterDevicesInSession", "SessionMetadata", "OptimizeForStaticGraph", "EnableMlirBridge", "MlirBridgeRollout", "EnableMlirGraphOptimization", "DisableOutputPartitionGraphs", "XlaFusionAutotunerThresh", "UseTfrt", "EnableMultiHost", "BackendServerPort", "TargetTpu", "TargetGpu", "StreamMergeThreshold", "DisableFunctionalOpsLowering", "XlaPreferSingleGraphCluster", "CoordinationConfig", "DisableOptimizeForStaticGraph", "DisableEagerExecutorStreamingEnqueue", });
+        new java.lang.String[] { "CollectiveGroupLeader", "ExecutorType", "RecvBufMaxChunk", "UseNumaAffinity", "CollectiveDeterministicSequentialExecution", "CollectiveNccl", "ShareSessionStateInClusterspecPropagation", "DisableThreadSpinning", "ShareClusterDevicesInSession", "SessionMetadata", "OptimizeForStaticGraph", "EnableMlirBridge", "MlirBridgeRollout", "EnableMlirGraphOptimization", "DisableOutputPartitionGraphs", "XlaFusionAutotunerThresh", "UseTfrt", "EnableMultiHost", "TfrtUseIfrt", "BackendServerPort", "TargetTpu", "TargetGpu", "StreamMergeThreshold", "DisableFunctionalOpsLowering", "XlaPreferSingleGraphCluster", "CoordinationConfig", "DisableOptimizeForStaticGraph", "DisableEagerExecutorStreamingEnqueue", });
     internal_static_tensorflow_RunOptions_descriptor =
       getDescriptor().getMessageTypes().get(6);
     internal_static_tensorflow_RunOptions_fieldAccessorTable = new
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CoordinationConfig.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CoordinationConfig.java
index 6c1f875d2f6..5dfed710211 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CoordinationConfig.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CoordinationConfig.java
@@ -853,6 +853,17 @@ org.tensorflow.proto.CoordinationConfig.CoordinatedJobOrBuilder getCoordinatedJo
      * @return The forceDisable.
      */
     boolean getForceDisable();
+
+    /**
+     * 
+     * Use long polling to get error from coordination service as the error
+     * propagation mechanism.
+     * 

+     *
+     * bool poll_for_error_from_service_at_startup = 13;
+     * @return The pollForErrorFromServiceAtStartup.
+     */
+    boolean getPollForErrorFromServiceAtStartup();
   }
   /**
    * 
@@ -1223,6 +1234,22 @@ public boolean getForceDisable() {
       return forceDisable_;
     }
 
+    public static final int POLL_FOR_ERROR_FROM_SERVICE_AT_STARTUP_FIELD_NUMBER = 13;
+    private boolean pollForErrorFromServiceAtStartup_;
+    /**
+     * 
+     * Use long polling to get error from coordination service as the error
+     * propagation mechanism.
+     * 

+     *
+     * bool poll_for_error_from_service_at_startup = 13;
+     * @return The pollForErrorFromServiceAtStartup.
+     */
+    @java.lang.Override
+    public boolean getPollForErrorFromServiceAtStartup() {
+      return pollForErrorFromServiceAtStartup_;
+    }
+
     private byte memoizedIsInitialized = -1;
     @java.lang.Override
     public final boolean isInitialized() {
@@ -1270,6 +1297,9 @@ public void writeTo(com.google.protobuf.CodedOutputStream output)
       if (forceDisable_ != false) {
         output.writeBool(12, forceDisable_);
       }
+      if (pollForErrorFromServiceAtStartup_ != false) {
+        output.writeBool(13, pollForErrorFromServiceAtStartup_);
+      }
       getUnknownFields().writeTo(output);
     }
 
@@ -1325,6 +1355,10 @@ public int getSerializedSize() {
         size += com.google.protobuf.CodedOutputStream
           .computeBoolSize(12, forceDisable_);
       }
+      if (pollForErrorFromServiceAtStartup_ != false) {
+        size += com.google.protobuf.CodedOutputStream
+          .computeBoolSize(13, pollForErrorFromServiceAtStartup_);
+      }
       size += getUnknownFields().getSerializedSize();
       memoizedSize = size;
       return size;
@@ -1362,6 +1396,8 @@ public boolean equals(final java.lang.Object obj) {
           != other.getAllowNewIncarnationToReconnect()) return false;
       if (getForceDisable()
           != other.getForceDisable()) return false;
+      if (getPollForErrorFromServiceAtStartup()
+          != other.getPollForErrorFromServiceAtStartup()) return false;
       if (!getUnknownFields().equals(other.getUnknownFields())) return false;
       return true;
     }
@@ -1406,6 +1442,9 @@ public int hashCode() {
       hash = (37 * hash) + FORCE_DISABLE_FIELD_NUMBER;
       hash = (53 * hash) + com.google.protobuf.Internal.hashBoolean(
           getForceDisable());
+      hash = (37 * hash) + POLL_FOR_ERROR_FROM_SERVICE_AT_STARTUP_FIELD_NUMBER;
+      hash = (53 * hash) + com.google.protobuf.Internal.hashBoolean(
+          getPollForErrorFromServiceAtStartup());
       hash = (29 * hash) + getUnknownFields().hashCode();
       memoizedHashCode = hash;
       return hash;
@@ -1566,6 +1605,8 @@ public Builder clear() {
 
         forceDisable_ = false;
 
+        pollForErrorFromServiceAtStartup_ = false;
+
         return this;
       }
 
@@ -1616,6 +1657,7 @@ public org.tensorflow.proto.CoordinationConfig.CoordinationServiceConfig buildPa
         result.recoverableJobs_ = recoverableJobs_;
         result.allowNewIncarnationToReconnect_ = allowNewIncarnationToReconnect_;
         result.forceDisable_ = forceDisable_;
+        result.pollForErrorFromServiceAtStartup_ = pollForErrorFromServiceAtStartup_;
         onBuilt();
         return result;
       }
@@ -1729,6 +1771,9 @@ public Builder mergeFrom(org.tensorflow.proto.CoordinationConfig.CoordinationSer
         if (other.getForceDisable() != false) {
           setForceDisable(other.getForceDisable());
         }
+        if (other.getPollForErrorFromServiceAtStartup() != false) {
+          setPollForErrorFromServiceAtStartup(other.getPollForErrorFromServiceAtStartup());
+        }
         this.mergeUnknownFields(other.getUnknownFields());
         onChanged();
         return this;
@@ -1819,6 +1864,11 @@ public Builder mergeFrom(
 
                 break;
               } // case 96
+              case 104: {
+                pollForErrorFromServiceAtStartup_ = input.readBool();
+
+                break;
+              } // case 104
               default: {
                 if (!super.parseUnknownField(input, extensionRegistry, tag)) {
                   done = true; // was an endgroup tag
@@ -2798,6 +2848,52 @@ public Builder clearForceDisable() {
         onChanged();
         return this;
       }
+
+      private boolean pollForErrorFromServiceAtStartup_ ;
+      /**
+       * 
+       * Use long polling to get error from coordination service as the error
+       * propagation mechanism.
+       * 

+       *
+       * bool poll_for_error_from_service_at_startup = 13;
+       * @return The pollForErrorFromServiceAtStartup.
+       */
+      @java.lang.Override
+      public boolean getPollForErrorFromServiceAtStartup() {
+        return pollForErrorFromServiceAtStartup_;
+      }
+      /**
+       * 
+       * Use long polling to get error from coordination service as the error
+       * propagation mechanism.
+       * 

+       *
+       * bool poll_for_error_from_service_at_startup = 13;
+       * @param value The pollForErrorFromServiceAtStartup to set.
+       * @return This builder for chaining.
+       */
+      public Builder setPollForErrorFromServiceAtStartup(boolean value) {
+        
+        pollForErrorFromServiceAtStartup_ = value;
+        onChanged();
+        return this;
+      }
+      /**
+       * 
+       * Use long polling to get error from coordination service as the error
+       * propagation mechanism.
+       * 

+       *
+       * bool poll_for_error_from_service_at_startup = 13;
+       * @return This builder for chaining.
+       */
+      public Builder clearPollForErrorFromServiceAtStartup() {
+        
+        pollForErrorFromServiceAtStartup_ = false;
+        onChanged();
+        return this;
+      }
       @java.lang.Override
       public final Builder setUnknownFields(
           final com.google.protobuf.UnknownFieldSet unknownFields) {
@@ -2883,7 +2979,7 @@ public org.tensorflow.proto.CoordinationConfig.CoordinationServiceConfig getDefa
     java.lang.String[] descriptorData = {
       "\n&tsl/protobuf/coordination_config.proto" +
       "\022\ntensorflow\"1\n\016CoordinatedJob\022\014\n\004name\030\001" +
-      " \001(\t\022\021\n\tnum_tasks\030\002 \001(\005\"\240\003\n\031Coordination" +
+      " \001(\t\022\021\n\tnum_tasks\030\002 \001(\005\"\320\003\n\031Coordination" +
       "ServiceConfig\022\024\n\014service_type\030\001 \001(\t\022\026\n\016s" +
       "ervice_leader\030\002 \001(\t\022\033\n\023enable_health_che" +
       "ck\030\003 \001(\010\022&\n\036cluster_register_timeout_in_" +
@@ -2893,11 +2989,12 @@ public org.tensorflow.proto.CoordinationConfig.CoordinationServiceConfig getDefa
       "timeout_in_ms\030\007 \001(\003\022*\n\"agent_destruction" +
       "_without_shutdown\030\010 \001(\010\022\030\n\020recoverable_j" +
       "obs\030\t \003(\t\022*\n\"allow_new_incarnation_to_re" +
-      "connect\030\013 \001(\010\022\025\n\rforce_disable\030\014 \001(\010J\004\010\006" +
-      "\020\007Bm\n\024org.tensorflow.protoZUgithub.com/t" +
-      "ensorflow/tensorflow/tensorflow/go/core/" +
-      "protobuf/for_core_protos_go_protob\006proto" +
-      "3"
+      "connect\030\013 \001(\010\022\025\n\rforce_disable\030\014 \001(\010\022.\n&" +
+      "poll_for_error_from_service_at_startup\030\r" +
+      " \001(\010J\004\010\006\020\007Bm\n\024org.tensorflow.protoZUgith" +
+      "ub.com/tensorflow/tensorflow/tensorflow/" +
+      "go/core/protobuf/for_core_protos_go_prot" +
+      "ob\006proto3"
     };
     descriptor = com.google.protobuf.Descriptors.FileDescriptor
       .internalBuildGeneratedFileFrom(descriptorData,
@@ -2914,7 +3011,7 @@ public org.tensorflow.proto.CoordinationConfig.CoordinationServiceConfig getDefa
     internal_static_tensorflow_CoordinationServiceConfig_fieldAccessorTable = new
       com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
         internal_static_tensorflow_CoordinationServiceConfig_descriptor,
-        new java.lang.String[] { "ServiceType", "ServiceLeader", "EnableHealthCheck", "ClusterRegisterTimeoutInMs", "HeartbeatTimeoutInMs", "CoordinatedJobList", "ShutdownBarrierTimeoutInMs", "AgentDestructionWithoutShutdown", "RecoverableJobs", "AllowNewIncarnationToReconnect", "ForceDisable", });
+        new java.lang.String[] { "ServiceType", "ServiceLeader", "EnableHealthCheck", "ClusterRegisterTimeoutInMs", "HeartbeatTimeoutInMs", "CoordinatedJobList", "ShutdownBarrierTimeoutInMs", "AgentDestructionWithoutShutdown", "RecoverableJobs", "AllowNewIncarnationToReconnect", "ForceDisable", "PollForErrorFromServiceAtStartup", });
   }
 
   // @@protoc_insertion_point(outer_class_scope)
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/EntryValue.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/EntryValue.java
deleted file mode 100644
index 44deff4cb4d..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/EntryValue.java
+++ /dev/null
@@ -1,745 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-/**
- * Protobuf type {@code tensorflow.EntryValue}
- */
-public final class EntryValue extends
-    com.google.protobuf.GeneratedMessageV3 implements
-    // @@protoc_insertion_point(message_implements:tensorflow.EntryValue)
-    EntryValueOrBuilder {
-private static final long serialVersionUID = 0L;
-  // Use EntryValue.newBuilder() to construct.
-  private EntryValue(com.google.protobuf.GeneratedMessageV3.Builder builder) {
-    super(builder);
-  }
-  private EntryValue() {
-  }
-
-  @java.lang.Override
-  @SuppressWarnings({"unused"})
-  protected java.lang.Object newInstance(
-      UnusedPrivateParameter unused) {
-    return new EntryValue();
-  }
-
-  @java.lang.Override
-  public final com.google.protobuf.UnknownFieldSet
-  getUnknownFields() {
-    return this.unknownFields;
-  }
-  public static final com.google.protobuf.Descriptors.Descriptor
-      getDescriptor() {
-    return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_EntryValue_descriptor;
-  }
-
-  @java.lang.Override
-  protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
-      internalGetFieldAccessorTable() {
-    return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_EntryValue_fieldAccessorTable
-        .ensureFieldAccessorsInitialized(
-            org.tensorflow.proto.EntryValue.class, org.tensorflow.proto.EntryValue.Builder.class);
-  }
-
-  private int kindCase_ = 0;
-  private java.lang.Object kind_;
-  public enum KindCase
-      implements com.google.protobuf.Internal.EnumLite,
-          com.google.protobuf.AbstractMessage.InternalOneOfEnum {
-    DOUBLE_VALUE(1),
-    STRING_VALUE(2),
-    KIND_NOT_SET(0);
-    private final int value;
-    private KindCase(int value) {
-      this.value = value;
-    }
-    /**
-     * @param value The number of the enum to look for.
-     * @return The enum associated with the given number.
-     * @deprecated Use {@link #forNumber(int)} instead.
-     */
-    @java.lang.Deprecated
-    public static KindCase valueOf(int value) {
-      return forNumber(value);
-    }
-
-    public static KindCase forNumber(int value) {
-      switch (value) {
-        case 1: return DOUBLE_VALUE;
-        case 2: return STRING_VALUE;
-        case 0: return KIND_NOT_SET;
-        default: return null;
-      }
-    }
-    public int getNumber() {
-      return this.value;
-    }
-  };
-
-  public KindCase
-  getKindCase() {
-    return KindCase.forNumber(
-        kindCase_);
-  }
-
-  public static final int DOUBLE_VALUE_FIELD_NUMBER = 1;
-  /**
-   * double double_value = 1;
-   * @return Whether the doubleValue field is set.
-   */
-  @java.lang.Override
-  public boolean hasDoubleValue() {
-    return kindCase_ == 1;
-  }
-  /**
-   * double double_value = 1;
-   * @return The doubleValue.
-   */
-  @java.lang.Override
-  public double getDoubleValue() {
-    if (kindCase_ == 1) {
-      return (java.lang.Double) kind_;
-    }
-    return 0D;
-  }
-
-  public static final int STRING_VALUE_FIELD_NUMBER = 2;
-  /**
-   * string string_value = 2;
-   * @return Whether the stringValue field is set.
-   */
-  public boolean hasStringValue() {
-    return kindCase_ == 2;
-  }
-  /**
-   * string string_value = 2;
-   * @return The stringValue.
-   */
-  public java.lang.String getStringValue() {
-    java.lang.Object ref = "";
-    if (kindCase_ == 2) {
-      ref = kind_;
-    }
-    if (ref instanceof java.lang.String) {
-      return (java.lang.String) ref;
-    } else {
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deleted file mode 100644
index 525dfd70275..00000000000
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@@ -1,39 +0,0 @@
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deleted file mode 100644
index f07305dc1aa..00000000000
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-    public GPUInfo parsePartialFrom(
-        com.google.protobuf.CodedInputStream input,
-        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-        throws com.google.protobuf.InvalidProtocolBufferException {
-      Builder builder = newBuilder();
-      try {
-        builder.mergeFrom(input, extensionRegistry);
-      } catch (com.google.protobuf.InvalidProtocolBufferException e) {
-        throw e.setUnfinishedMessage(builder.buildPartial());
-      } catch (com.google.protobuf.UninitializedMessageException e) {
-        throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial());
-      } catch (java.io.IOException e) {
-        throw new com.google.protobuf.InvalidProtocolBufferException(e)
-            .setUnfinishedMessage(builder.buildPartial());
-      }
-      return builder.buildPartial();
-    }
-  };
-
-  public static com.google.protobuf.Parser parser() {
-    return PARSER;
-  }
-
-  @java.lang.Override
-  public com.google.protobuf.Parser getParserForType() {
-    return PARSER;
-  }
-
-  @java.lang.Override
-  public org.tensorflow.proto.GPUInfo getDefaultInstanceForType() {
-    return DEFAULT_INSTANCE;
-  }
-
-}
-
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/GPUInfoOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/GPUInfoOrBuilder.java
deleted file mode 100644
index 6aefc92ee8c..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/GPUInfoOrBuilder.java
+++ /dev/null
@@ -1,69 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-public interface GPUInfoOrBuilder extends
-    // @@protoc_insertion_point(interface_extends:tensorflow.GPUInfo)
-    com.google.protobuf.MessageOrBuilder {
-
-  /**
-   * 
-   * e.g. "Tesla K40c"
-   * 

-   *
-   * string model = 1;
-   * @return The model.
-   */
-  java.lang.String getModel();
-  /**
-   * 
-   * e.g. "Tesla K40c"
-   * 

-   *
-   * string model = 1;
-   * @return The bytes for model.
-   */
-  com.google.protobuf.ByteString
-      getModelBytes();
-
-  /**
-   * 
-   * Final entry in output of "nvidia-smi -L"
-   * 

-   *
-   * string uuid = 2;
-   * @return The uuid.
-   */
-  java.lang.String getUuid();
-  /**
-   * 
-   * Final entry in output of "nvidia-smi -L"
-   * 

-   *
-   * string uuid = 2;
-   * @return The bytes for uuid.
-   */
-  com.google.protobuf.ByteString
-      getUuidBytes();
-
-  /**
-   * 
-   * e.g. "0000:04:00.0"
-   * 

-   *
-   * string bus_id = 3;
-   * @return The busId.
-   */
-  java.lang.String getBusId();
-  /**
-   * 
-   * e.g. "0000:04:00.0"
-   * 

-   *
-   * string bus_id = 3;
-   * @return The bytes for busId.
-   */
-  com.google.protobuf.ByteString
-      getBusIdBytes();
-}
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/GPUOptions.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/GPUOptions.java
index 8eac8bc4ef1..d9db2330adb 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/GPUOptions.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/GPUOptions.java
@@ -467,6 +467,43 @@ org.tensorflow.proto.GPUOptions.Experimental.VirtualDevicesOrBuilder getVirtualD
      * @return The gpuSystemMemorySizeInMb.
      */
     int getGpuSystemMemorySizeInMb();
+
+    /**
+     * 
+     * If true, save information needed for created a PjRt GPU client for
+     * creating a client with remote devices.
+     * 

+     *
+     * bool populate_pjrt_gpu_client_creation_info = 17;
+     * @return The populatePjrtGpuClientCreationInfo.
+     */
+    boolean getPopulatePjrtGpuClientCreationInfo();
+
+    /**
+     * 
+     * node_id for use when creating a PjRt GPU client with remote devices,
+     * which enumerates jobs*tasks from a ServerDef.
+     * 

+     *
+     * int32 node_id = 18;
+     * @return The nodeId.
+     */
+    int getNodeId();
+
+    /**
+     * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+     * @return Whether the streamMergeOptions field is set.
+     */
+    boolean hasStreamMergeOptions();
+    /**
+     * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+     * @return The streamMergeOptions.
+     */
+    org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions getStreamMergeOptions();
+    /**
+     * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+     */
+    org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptionsOrBuilder getStreamMergeOptionsOrBuilder();
   }
   /**
    * Protobuf type {@code tensorflow.GPUOptions.Experimental}
@@ -1673,105 +1710,846 @@ private void ensureDeviceOrdinalIsMutable() {
         }
         /**
          * 
-         * Virtual Device ordinal number determines the device ID of the device.
-         * A Virtual device with a lower ordinal number always receives the a
-         * smaller device id. The phyiscal device id and location in the
-         * virtual device list is used to break ties.
+         * Virtual Device ordinal number determines the device ID of the device.
+         * A Virtual device with a lower ordinal number always receives the a
+         * smaller device id. The phyiscal device id and location in the
+         * virtual device list is used to break ties.
+         * 

+         *
+         * repeated int32 device_ordinal = 3;
+         * @return The count of deviceOrdinal.
+         */
+        public int getDeviceOrdinalCount() {
+          return deviceOrdinal_.size();
+        }
+        /**
+         * 
+         * Virtual Device ordinal number determines the device ID of the device.
+         * A Virtual device with a lower ordinal number always receives the a
+         * smaller device id. The phyiscal device id and location in the
+         * virtual device list is used to break ties.
+         * 

+         *
+         * repeated int32 device_ordinal = 3;
+         * @param index The index of the element to return.
+         * @return The deviceOrdinal at the given index.
+         */
+        public int getDeviceOrdinal(int index) {
+          return deviceOrdinal_.getInt(index);
+        }
+        /**
+         * 
+         * Virtual Device ordinal number determines the device ID of the device.
+         * A Virtual device with a lower ordinal number always receives the a
+         * smaller device id. The phyiscal device id and location in the
+         * virtual device list is used to break ties.
+         * 

+         *
+         * repeated int32 device_ordinal = 3;
+         * @param index The index to set the value at.
+         * @param value The deviceOrdinal to set.
+         * @return This builder for chaining.
+         */
+        public Builder setDeviceOrdinal(
+            int index, int value) {
+          ensureDeviceOrdinalIsMutable();
+          deviceOrdinal_.setInt(index, value);
+          onChanged();
+          return this;
+        }
+        /**
+         * 
+         * Virtual Device ordinal number determines the device ID of the device.
+         * A Virtual device with a lower ordinal number always receives the a
+         * smaller device id. The phyiscal device id and location in the
+         * virtual device list is used to break ties.
+         * 

+         *
+         * repeated int32 device_ordinal = 3;
+         * @param value The deviceOrdinal to add.
+         * @return This builder for chaining.
+         */
+        public Builder addDeviceOrdinal(int value) {
+          ensureDeviceOrdinalIsMutable();
+          deviceOrdinal_.addInt(value);
+          onChanged();
+          return this;
+        }
+        /**
+         * 
+         * Virtual Device ordinal number determines the device ID of the device.
+         * A Virtual device with a lower ordinal number always receives the a
+         * smaller device id. The phyiscal device id and location in the
+         * virtual device list is used to break ties.
+         * 

+         *
+         * repeated int32 device_ordinal = 3;
+         * @param values The deviceOrdinal to add.
+         * @return This builder for chaining.
+         */
+        public Builder addAllDeviceOrdinal(
+            java.lang.Iterable values) {
+          ensureDeviceOrdinalIsMutable();
+          com.google.protobuf.AbstractMessageLite.Builder.addAll(
+              values, deviceOrdinal_);
+          onChanged();
+          return this;
+        }
+        /**
+         * 
+         * Virtual Device ordinal number determines the device ID of the device.
+         * A Virtual device with a lower ordinal number always receives the a
+         * smaller device id. The phyiscal device id and location in the
+         * virtual device list is used to break ties.
+         * 

+         *
+         * repeated int32 device_ordinal = 3;
+         * @return This builder for chaining.
+         */
+        public Builder clearDeviceOrdinal() {
+          deviceOrdinal_ = emptyIntList();
+          bitField0_ = (bitField0_ & ~0x00000004);
+          onChanged();
+          return this;
+        }
+        @java.lang.Override
+        public final Builder setUnknownFields(
+            final com.google.protobuf.UnknownFieldSet unknownFields) {
+          return super.setUnknownFields(unknownFields);
+        }
+
+        @java.lang.Override
+        public final Builder mergeUnknownFields(
+            final com.google.protobuf.UnknownFieldSet unknownFields) {
+          return super.mergeUnknownFields(unknownFields);
+        }
+
+
+        // @@protoc_insertion_point(builder_scope:tensorflow.GPUOptions.Experimental.VirtualDevices)
+      }
+
+      // @@protoc_insertion_point(class_scope:tensorflow.GPUOptions.Experimental.VirtualDevices)
+      private static final org.tensorflow.proto.GPUOptions.Experimental.VirtualDevices DEFAULT_INSTANCE;
+      static {
+        DEFAULT_INSTANCE = new org.tensorflow.proto.GPUOptions.Experimental.VirtualDevices();
+      }
+
+      public static org.tensorflow.proto.GPUOptions.Experimental.VirtualDevices getDefaultInstance() {
+        return DEFAULT_INSTANCE;
+      }
+
+      private static final com.google.protobuf.Parser
+          PARSER = new com.google.protobuf.AbstractParser() {
+        @java.lang.Override
+        public VirtualDevices parsePartialFrom(
+            com.google.protobuf.CodedInputStream input,
+            com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+            throws com.google.protobuf.InvalidProtocolBufferException {
+          Builder builder = newBuilder();
+          try {
+            builder.mergeFrom(input, extensionRegistry);
+          } catch (com.google.protobuf.InvalidProtocolBufferException e) {
+            throw e.setUnfinishedMessage(builder.buildPartial());
+          } catch (com.google.protobuf.UninitializedMessageException e) {
+            throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial());
+          } catch (java.io.IOException e) {
+            throw new com.google.protobuf.InvalidProtocolBufferException(e)
+                .setUnfinishedMessage(builder.buildPartial());
+          }
+          return builder.buildPartial();
+        }
+      };
+
+      public static com.google.protobuf.Parser parser() {
+        return PARSER;
+      }
+
+      @java.lang.Override
+      public com.google.protobuf.Parser getParserForType() {
+        return PARSER;
+      }
+
+      @java.lang.Override
+      public org.tensorflow.proto.GPUOptions.Experimental.VirtualDevices getDefaultInstanceForType() {
+        return DEFAULT_INSTANCE;
+      }
+
+    }
+
+    public interface StreamMergeOptionsOrBuilder extends
+        // @@protoc_insertion_point(interface_extends:tensorflow.GPUOptions.Experimental.StreamMergeOptions)
+        com.google.protobuf.MessageOrBuilder {
+
+      /**
+       * 
+       * If true, the compute stream will be used for host_to_device copy as
+       * well. It's no longer necessary to record an event before the copy to
+       * let the copy stream wait for the compute stream to finish. There is
+       * also no need to wait for the copy to complete before executing the
+       * callback function.
+       * 

+       *
+       * bool merge_host_to_device_stream = 1;
+       * @return The mergeHostToDeviceStream.
+       */
+      boolean getMergeHostToDeviceStream();
+
+      /**
+       * 
+       * If true, the compute stream will be used for device_to_host copy as
+       * well. It's no longer necessary to record an event before the copy to
+       * let the copy stream wait for the compute stream to finish.
+       * 

+       *
+       * bool merge_device_to_host_stream = 2;
+       * @return The mergeDeviceToHostStream.
+       */
+      boolean getMergeDeviceToHostStream();
+
+      /**
+       * 
+       * If true, the compute stream will be used for device_to_device copy as
+       * well. It's no longer necessary to record an event before the copy to
+       * let the copy stream wait for the compute stream of the sending device
+       * to finish. There is also no need to wait for the compute stream of the
+       * receiving device to finish if the copy is within the same device.
+       * 

+       *
+       * bool merge_device_to_device_stream = 3;
+       * @return The mergeDeviceToDeviceStream.
+       */
+      boolean getMergeDeviceToDeviceStream();
+    }
+    /**
+     * 
+     * Whether to merge data transfer streams into the compute stream in the
+     * same stream group. Stream merging helps reduce the overhead caused by
+     * stream synchronization, especially when data transfers are frequent. For
+     * example, setting "merge_host_to_device_stream = true" will make the
+     * compute stream responsible for both computation and host to device memory
+     * copy.
+     * 

+     *
+     * Protobuf type {@code tensorflow.GPUOptions.Experimental.StreamMergeOptions}
+     */
+    public static final class StreamMergeOptions extends
+        com.google.protobuf.GeneratedMessageV3 implements
+        // @@protoc_insertion_point(message_implements:tensorflow.GPUOptions.Experimental.StreamMergeOptions)
+        StreamMergeOptionsOrBuilder {
+    private static final long serialVersionUID = 0L;
+      // Use StreamMergeOptions.newBuilder() to construct.
+      private StreamMergeOptions(com.google.protobuf.GeneratedMessageV3.Builder builder) {
+        super(builder);
+      }
+      private StreamMergeOptions() {
+      }
+
+      @java.lang.Override
+      @SuppressWarnings({"unused"})
+      protected java.lang.Object newInstance(
+          UnusedPrivateParameter unused) {
+        return new StreamMergeOptions();
+      }
+
+      @java.lang.Override
+      public final com.google.protobuf.UnknownFieldSet
+      getUnknownFields() {
+        return this.unknownFields;
+      }
+      public static final com.google.protobuf.Descriptors.Descriptor
+          getDescriptor() {
+        return org.tensorflow.proto.ConfigProtos.internal_static_tensorflow_GPUOptions_Experimental_StreamMergeOptions_descriptor;
+      }
+
+      @java.lang.Override
+      protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
+          internalGetFieldAccessorTable() {
+        return org.tensorflow.proto.ConfigProtos.internal_static_tensorflow_GPUOptions_Experimental_StreamMergeOptions_fieldAccessorTable
+            .ensureFieldAccessorsInitialized(
+                org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.class, org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.Builder.class);
+      }
+
+      public static final int MERGE_HOST_TO_DEVICE_STREAM_FIELD_NUMBER = 1;
+      private boolean mergeHostToDeviceStream_;
+      /**
+       * 
+       * If true, the compute stream will be used for host_to_device copy as
+       * well. It's no longer necessary to record an event before the copy to
+       * let the copy stream wait for the compute stream to finish. There is
+       * also no need to wait for the copy to complete before executing the
+       * callback function.
+       * 

+       *
+       * bool merge_host_to_device_stream = 1;
+       * @return The mergeHostToDeviceStream.
+       */
+      @java.lang.Override
+      public boolean getMergeHostToDeviceStream() {
+        return mergeHostToDeviceStream_;
+      }
+
+      public static final int MERGE_DEVICE_TO_HOST_STREAM_FIELD_NUMBER = 2;
+      private boolean mergeDeviceToHostStream_;
+      /**
+       * 
+       * If true, the compute stream will be used for device_to_host copy as
+       * well. It's no longer necessary to record an event before the copy to
+       * let the copy stream wait for the compute stream to finish.
+       * 

+       *
+       * bool merge_device_to_host_stream = 2;
+       * @return The mergeDeviceToHostStream.
+       */
+      @java.lang.Override
+      public boolean getMergeDeviceToHostStream() {
+        return mergeDeviceToHostStream_;
+      }
+
+      public static final int MERGE_DEVICE_TO_DEVICE_STREAM_FIELD_NUMBER = 3;
+      private boolean mergeDeviceToDeviceStream_;
+      /**
+       * 
+       * If true, the compute stream will be used for device_to_device copy as
+       * well. It's no longer necessary to record an event before the copy to
+       * let the copy stream wait for the compute stream of the sending device
+       * to finish. There is also no need to wait for the compute stream of the
+       * receiving device to finish if the copy is within the same device.
+       * 

+       *
+       * bool merge_device_to_device_stream = 3;
+       * @return The mergeDeviceToDeviceStream.
+       */
+      @java.lang.Override
+      public boolean getMergeDeviceToDeviceStream() {
+        return mergeDeviceToDeviceStream_;
+      }
+
+      private byte memoizedIsInitialized = -1;
+      @java.lang.Override
+      public final boolean isInitialized() {
+        byte isInitialized = memoizedIsInitialized;
+        if (isInitialized == 1) return true;
+        if (isInitialized == 0) return false;
+
+        memoizedIsInitialized = 1;
+        return true;
+      }
+
+      @java.lang.Override
+      public void writeTo(com.google.protobuf.CodedOutputStream output)
+                          throws java.io.IOException {
+        if (mergeHostToDeviceStream_ != false) {
+          output.writeBool(1, mergeHostToDeviceStream_);
+        }
+        if (mergeDeviceToHostStream_ != false) {
+          output.writeBool(2, mergeDeviceToHostStream_);
+        }
+        if (mergeDeviceToDeviceStream_ != false) {
+          output.writeBool(3, mergeDeviceToDeviceStream_);
+        }
+        getUnknownFields().writeTo(output);
+      }
+
+      @java.lang.Override
+      public int getSerializedSize() {
+        int size = memoizedSize;
+        if (size != -1) return size;
+
+        size = 0;
+        if (mergeHostToDeviceStream_ != false) {
+          size += com.google.protobuf.CodedOutputStream
+            .computeBoolSize(1, mergeHostToDeviceStream_);
+        }
+        if (mergeDeviceToHostStream_ != false) {
+          size += com.google.protobuf.CodedOutputStream
+            .computeBoolSize(2, mergeDeviceToHostStream_);
+        }
+        if (mergeDeviceToDeviceStream_ != false) {
+          size += com.google.protobuf.CodedOutputStream
+            .computeBoolSize(3, mergeDeviceToDeviceStream_);
+        }
+        size += getUnknownFields().getSerializedSize();
+        memoizedSize = size;
+        return size;
+      }
+
+      @java.lang.Override
+      public boolean equals(final java.lang.Object obj) {
+        if (obj == this) {
+         return true;
+        }
+        if (!(obj instanceof org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions)) {
+          return super.equals(obj);
+        }
+        org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions other = (org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions) obj;
+
+        if (getMergeHostToDeviceStream()
+            != other.getMergeHostToDeviceStream()) return false;
+        if (getMergeDeviceToHostStream()
+            != other.getMergeDeviceToHostStream()) return false;
+        if (getMergeDeviceToDeviceStream()
+            != other.getMergeDeviceToDeviceStream()) return false;
+        if (!getUnknownFields().equals(other.getUnknownFields())) return false;
+        return true;
+      }
+
+      @java.lang.Override
+      public int hashCode() {
+        if (memoizedHashCode != 0) {
+          return memoizedHashCode;
+        }
+        int hash = 41;
+        hash = (19 * hash) + getDescriptor().hashCode();
+        hash = (37 * hash) + MERGE_HOST_TO_DEVICE_STREAM_FIELD_NUMBER;
+        hash = (53 * hash) + com.google.protobuf.Internal.hashBoolean(
+            getMergeHostToDeviceStream());
+        hash = (37 * hash) + MERGE_DEVICE_TO_HOST_STREAM_FIELD_NUMBER;
+        hash = (53 * hash) + com.google.protobuf.Internal.hashBoolean(
+            getMergeDeviceToHostStream());
+        hash = (37 * hash) + MERGE_DEVICE_TO_DEVICE_STREAM_FIELD_NUMBER;
+        hash = (53 * hash) + com.google.protobuf.Internal.hashBoolean(
+            getMergeDeviceToDeviceStream());
+        hash = (29 * hash) + getUnknownFields().hashCode();
+        memoizedHashCode = hash;
+        return hash;
+      }
+
+      public static org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions parseFrom(
+          java.nio.ByteBuffer data)
+          throws com.google.protobuf.InvalidProtocolBufferException {
+        return PARSER.parseFrom(data);
+      }
+      public static org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions parseFrom(
+          java.nio.ByteBuffer data,
+          com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+          throws com.google.protobuf.InvalidProtocolBufferException {
+        return PARSER.parseFrom(data, extensionRegistry);
+      }
+      public static org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions parseFrom(
+          com.google.protobuf.ByteString data)
+          throws com.google.protobuf.InvalidProtocolBufferException {
+        return PARSER.parseFrom(data);
+      }
+      public static org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions parseFrom(
+          com.google.protobuf.ByteString data,
+          com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+          throws com.google.protobuf.InvalidProtocolBufferException {
+        return PARSER.parseFrom(data, extensionRegistry);
+      }
+      public static org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions parseFrom(byte[] data)
+          throws com.google.protobuf.InvalidProtocolBufferException {
+        return PARSER.parseFrom(data);
+      }
+      public static org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions parseFrom(
+          byte[] data,
+          com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+          throws com.google.protobuf.InvalidProtocolBufferException {
+        return PARSER.parseFrom(data, extensionRegistry);
+      }
+      public static org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions parseFrom(java.io.InputStream input)
+          throws java.io.IOException {
+        return com.google.protobuf.GeneratedMessageV3
+            .parseWithIOException(PARSER, input);
+      }
+      public static org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions parseFrom(
+          java.io.InputStream input,
+          com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+          throws java.io.IOException {
+        return com.google.protobuf.GeneratedMessageV3
+            .parseWithIOException(PARSER, input, extensionRegistry);
+      }
+      public static org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions parseDelimitedFrom(java.io.InputStream input)
+          throws java.io.IOException {
+        return com.google.protobuf.GeneratedMessageV3
+            .parseDelimitedWithIOException(PARSER, input);
+      }
+      public static org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions parseDelimitedFrom(
+          java.io.InputStream input,
+          com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+          throws java.io.IOException {
+        return com.google.protobuf.GeneratedMessageV3
+            .parseDelimitedWithIOException(PARSER, input, extensionRegistry);
+      }
+      public static org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions parseFrom(
+          com.google.protobuf.CodedInputStream input)
+          throws java.io.IOException {
+        return com.google.protobuf.GeneratedMessageV3
+            .parseWithIOException(PARSER, input);
+      }
+      public static org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions parseFrom(
+          com.google.protobuf.CodedInputStream input,
+          com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+          throws java.io.IOException {
+        return com.google.protobuf.GeneratedMessageV3
+            .parseWithIOException(PARSER, input, extensionRegistry);
+      }
+
+      @java.lang.Override
+      public Builder newBuilderForType() { return newBuilder(); }
+      public static Builder newBuilder() {
+        return DEFAULT_INSTANCE.toBuilder();
+      }
+      public static Builder newBuilder(org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions prototype) {
+        return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype);
+      }
+      @java.lang.Override
+      public Builder toBuilder() {
+        return this == DEFAULT_INSTANCE
+            ? new Builder() : new Builder().mergeFrom(this);
+      }
+
+      @java.lang.Override
+      protected Builder newBuilderForType(
+          com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
+        Builder builder = new Builder(parent);
+        return builder;
+      }
+      /**
+       * 
+       * Whether to merge data transfer streams into the compute stream in the
+       * same stream group. Stream merging helps reduce the overhead caused by
+       * stream synchronization, especially when data transfers are frequent. For
+       * example, setting "merge_host_to_device_stream = true" will make the
+       * compute stream responsible for both computation and host to device memory
+       * copy.
+       * 

+       *
+       * Protobuf type {@code tensorflow.GPUOptions.Experimental.StreamMergeOptions}
+       */
+      public static final class Builder extends
+          com.google.protobuf.GeneratedMessageV3.Builder implements
+          // @@protoc_insertion_point(builder_implements:tensorflow.GPUOptions.Experimental.StreamMergeOptions)
+          org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptionsOrBuilder {
+        public static final com.google.protobuf.Descriptors.Descriptor
+            getDescriptor() {
+          return org.tensorflow.proto.ConfigProtos.internal_static_tensorflow_GPUOptions_Experimental_StreamMergeOptions_descriptor;
+        }
+
+        @java.lang.Override
+        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
+            internalGetFieldAccessorTable() {
+          return org.tensorflow.proto.ConfigProtos.internal_static_tensorflow_GPUOptions_Experimental_StreamMergeOptions_fieldAccessorTable
+              .ensureFieldAccessorsInitialized(
+                  org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.class, org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.Builder.class);
+        }
+
+        // Construct using org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.newBuilder()
+        private Builder() {
+
+        }
+
+        private Builder(
+            com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
+          super(parent);
+
+        }
+        @java.lang.Override
+        public Builder clear() {
+          super.clear();
+          mergeHostToDeviceStream_ = false;
+
+          mergeDeviceToHostStream_ = false;
+
+          mergeDeviceToDeviceStream_ = false;
+
+          return this;
+        }
+
+        @java.lang.Override
+        public com.google.protobuf.Descriptors.Descriptor
+            getDescriptorForType() {
+          return org.tensorflow.proto.ConfigProtos.internal_static_tensorflow_GPUOptions_Experimental_StreamMergeOptions_descriptor;
+        }
+
+        @java.lang.Override
+        public org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions getDefaultInstanceForType() {
+          return org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.getDefaultInstance();
+        }
+
+        @java.lang.Override
+        public org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions build() {
+          org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions result = buildPartial();
+          if (!result.isInitialized()) {
+            throw newUninitializedMessageException(result);
+          }
+          return result;
+        }
+
+        @java.lang.Override
+        public org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions buildPartial() {
+          org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions result = new org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions(this);
+          result.mergeHostToDeviceStream_ = mergeHostToDeviceStream_;
+          result.mergeDeviceToHostStream_ = mergeDeviceToHostStream_;
+          result.mergeDeviceToDeviceStream_ = mergeDeviceToDeviceStream_;
+          onBuilt();
+          return result;
+        }
+
+        @java.lang.Override
+        public Builder clone() {
+          return super.clone();
+        }
+        @java.lang.Override
+        public Builder setField(
+            com.google.protobuf.Descriptors.FieldDescriptor field,
+            java.lang.Object value) {
+          return super.setField(field, value);
+        }
+        @java.lang.Override
+        public Builder clearField(
+            com.google.protobuf.Descriptors.FieldDescriptor field) {
+          return super.clearField(field);
+        }
+        @java.lang.Override
+        public Builder clearOneof(
+            com.google.protobuf.Descriptors.OneofDescriptor oneof) {
+          return super.clearOneof(oneof);
+        }
+        @java.lang.Override
+        public Builder setRepeatedField(
+            com.google.protobuf.Descriptors.FieldDescriptor field,
+            int index, java.lang.Object value) {
+          return super.setRepeatedField(field, index, value);
+        }
+        @java.lang.Override
+        public Builder addRepeatedField(
+            com.google.protobuf.Descriptors.FieldDescriptor field,
+            java.lang.Object value) {
+          return super.addRepeatedField(field, value);
+        }
+        @java.lang.Override
+        public Builder mergeFrom(com.google.protobuf.Message other) {
+          if (other instanceof org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions) {
+            return mergeFrom((org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions)other);
+          } else {
+            super.mergeFrom(other);
+            return this;
+          }
+        }
+
+        public Builder mergeFrom(org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions other) {
+          if (other == org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.getDefaultInstance()) return this;
+          if (other.getMergeHostToDeviceStream() != false) {
+            setMergeHostToDeviceStream(other.getMergeHostToDeviceStream());
+          }
+          if (other.getMergeDeviceToHostStream() != false) {
+            setMergeDeviceToHostStream(other.getMergeDeviceToHostStream());
+          }
+          if (other.getMergeDeviceToDeviceStream() != false) {
+            setMergeDeviceToDeviceStream(other.getMergeDeviceToDeviceStream());
+          }
+          this.mergeUnknownFields(other.getUnknownFields());
+          onChanged();
+          return this;
+        }
+
+        @java.lang.Override
+        public final boolean isInitialized() {
+          return true;
+        }
+
+        @java.lang.Override
+        public Builder mergeFrom(
+            com.google.protobuf.CodedInputStream input,
+            com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+            throws java.io.IOException {
+          if (extensionRegistry == null) {
+            throw new java.lang.NullPointerException();
+          }
+          try {
+            boolean done = false;
+            while (!done) {
+              int tag = input.readTag();
+              switch (tag) {
+                case 0:
+                  done = true;
+                  break;
+                case 8: {
+                  mergeHostToDeviceStream_ = input.readBool();
+
+                  break;
+                } // case 8
+                case 16: {
+                  mergeDeviceToHostStream_ = input.readBool();
+
+                  break;
+                } // case 16
+                case 24: {
+                  mergeDeviceToDeviceStream_ = input.readBool();
+
+                  break;
+                } // case 24
+                default: {
+                  if (!super.parseUnknownField(input, extensionRegistry, tag)) {
+                    done = true; // was an endgroup tag
+                  }
+                  break;
+                } // default:
+              } // switch (tag)
+            } // while (!done)
+          } catch (com.google.protobuf.InvalidProtocolBufferException e) {
+            throw e.unwrapIOException();
+          } finally {
+            onChanged();
+          } // finally
+          return this;
+        }
+
+        private boolean mergeHostToDeviceStream_ ;
+        /**
+         * 
+         * If true, the compute stream will be used for host_to_device copy as
+         * well. It's no longer necessary to record an event before the copy to
+         * let the copy stream wait for the compute stream to finish. There is
+         * also no need to wait for the copy to complete before executing the
+         * callback function.
+         * 

+         *
+         * bool merge_host_to_device_stream = 1;
+         * @return The mergeHostToDeviceStream.
+         */
+        @java.lang.Override
+        public boolean getMergeHostToDeviceStream() {
+          return mergeHostToDeviceStream_;
+        }
+        /**
+         * 
+         * If true, the compute stream will be used for host_to_device copy as
+         * well. It's no longer necessary to record an event before the copy to
+         * let the copy stream wait for the compute stream to finish. There is
+         * also no need to wait for the copy to complete before executing the
+         * callback function.
+         * 

+         *
+         * bool merge_host_to_device_stream = 1;
+         * @param value The mergeHostToDeviceStream to set.
+         * @return This builder for chaining.
+         */
+        public Builder setMergeHostToDeviceStream(boolean value) {
+          
+          mergeHostToDeviceStream_ = value;
+          onChanged();
+          return this;
+        }
+        /**
+         * 
+         * If true, the compute stream will be used for host_to_device copy as
+         * well. It's no longer necessary to record an event before the copy to
+         * let the copy stream wait for the compute stream to finish. There is
+         * also no need to wait for the copy to complete before executing the
+         * callback function.
          * 

          *
-         * repeated int32 device_ordinal = 3;
-         * @return The count of deviceOrdinal.
+         * bool merge_host_to_device_stream = 1;
+         * @return This builder for chaining.
          */
-        public int getDeviceOrdinalCount() {
-          return deviceOrdinal_.size();
+        public Builder clearMergeHostToDeviceStream() {
+          
+          mergeHostToDeviceStream_ = false;
+          onChanged();
+          return this;
         }
+
+        private boolean mergeDeviceToHostStream_ ;
         /**
          * 
-         * Virtual Device ordinal number determines the device ID of the device.
-         * A Virtual device with a lower ordinal number always receives the a
-         * smaller device id. The phyiscal device id and location in the
-         * virtual device list is used to break ties.
+         * If true, the compute stream will be used for device_to_host copy as
+         * well. It's no longer necessary to record an event before the copy to
+         * let the copy stream wait for the compute stream to finish.
          * 

          *
-         * repeated int32 device_ordinal = 3;
-         * @param index The index of the element to return.
-         * @return The deviceOrdinal at the given index.
+         * bool merge_device_to_host_stream = 2;
+         * @return The mergeDeviceToHostStream.
          */
-        public int getDeviceOrdinal(int index) {
-          return deviceOrdinal_.getInt(index);
+        @java.lang.Override
+        public boolean getMergeDeviceToHostStream() {
+          return mergeDeviceToHostStream_;
         }
         /**
          * 
-         * Virtual Device ordinal number determines the device ID of the device.
-         * A Virtual device with a lower ordinal number always receives the a
-         * smaller device id. The phyiscal device id and location in the
-         * virtual device list is used to break ties.
+         * If true, the compute stream will be used for device_to_host copy as
+         * well. It's no longer necessary to record an event before the copy to
+         * let the copy stream wait for the compute stream to finish.
          * 

          *
-         * repeated int32 device_ordinal = 3;
-         * @param index The index to set the value at.
-         * @param value The deviceOrdinal to set.
+         * bool merge_device_to_host_stream = 2;
+         * @param value The mergeDeviceToHostStream to set.
          * @return This builder for chaining.
          */
-        public Builder setDeviceOrdinal(
-            int index, int value) {
-          ensureDeviceOrdinalIsMutable();
-          deviceOrdinal_.setInt(index, value);
+        public Builder setMergeDeviceToHostStream(boolean value) {
+          
+          mergeDeviceToHostStream_ = value;
           onChanged();
           return this;
         }
         /**
          * 
-         * Virtual Device ordinal number determines the device ID of the device.
-         * A Virtual device with a lower ordinal number always receives the a
-         * smaller device id. The phyiscal device id and location in the
-         * virtual device list is used to break ties.
+         * If true, the compute stream will be used for device_to_host copy as
+         * well. It's no longer necessary to record an event before the copy to
+         * let the copy stream wait for the compute stream to finish.
          * 

          *
-         * repeated int32 device_ordinal = 3;
-         * @param value The deviceOrdinal to add.
+         * bool merge_device_to_host_stream = 2;
          * @return This builder for chaining.
          */
-        public Builder addDeviceOrdinal(int value) {
-          ensureDeviceOrdinalIsMutable();
-          deviceOrdinal_.addInt(value);
+        public Builder clearMergeDeviceToHostStream() {
+          
+          mergeDeviceToHostStream_ = false;
           onChanged();
           return this;
         }
+
+        private boolean mergeDeviceToDeviceStream_ ;
         /**
          * 
-         * Virtual Device ordinal number determines the device ID of the device.
-         * A Virtual device with a lower ordinal number always receives the a
-         * smaller device id. The phyiscal device id and location in the
-         * virtual device list is used to break ties.
+         * If true, the compute stream will be used for device_to_device copy as
+         * well. It's no longer necessary to record an event before the copy to
+         * let the copy stream wait for the compute stream of the sending device
+         * to finish. There is also no need to wait for the compute stream of the
+         * receiving device to finish if the copy is within the same device.
          * 

          *
-         * repeated int32 device_ordinal = 3;
-         * @param values The deviceOrdinal to add.
+         * bool merge_device_to_device_stream = 3;
+         * @return The mergeDeviceToDeviceStream.
+         */
+        @java.lang.Override
+        public boolean getMergeDeviceToDeviceStream() {
+          return mergeDeviceToDeviceStream_;
+        }
+        /**
+         * 
+         * If true, the compute stream will be used for device_to_device copy as
+         * well. It's no longer necessary to record an event before the copy to
+         * let the copy stream wait for the compute stream of the sending device
+         * to finish. There is also no need to wait for the compute stream of the
+         * receiving device to finish if the copy is within the same device.
+         * 

+         *
+         * bool merge_device_to_device_stream = 3;
+         * @param value The mergeDeviceToDeviceStream to set.
          * @return This builder for chaining.
          */
-        public Builder addAllDeviceOrdinal(
-            java.lang.Iterable values) {
-          ensureDeviceOrdinalIsMutable();
-          com.google.protobuf.AbstractMessageLite.Builder.addAll(
-              values, deviceOrdinal_);
+        public Builder setMergeDeviceToDeviceStream(boolean value) {
+          
+          mergeDeviceToDeviceStream_ = value;
           onChanged();
           return this;
         }
         /**
          * 
-         * Virtual Device ordinal number determines the device ID of the device.
-         * A Virtual device with a lower ordinal number always receives the a
-         * smaller device id. The phyiscal device id and location in the
-         * virtual device list is used to break ties.
+         * If true, the compute stream will be used for device_to_device copy as
+         * well. It's no longer necessary to record an event before the copy to
+         * let the copy stream wait for the compute stream of the sending device
+         * to finish. There is also no need to wait for the compute stream of the
+         * receiving device to finish if the copy is within the same device.
          * 

          *
-         * repeated int32 device_ordinal = 3;
+         * bool merge_device_to_device_stream = 3;
          * @return This builder for chaining.
          */
-        public Builder clearDeviceOrdinal() {
-          deviceOrdinal_ = emptyIntList();
-          bitField0_ = (bitField0_ & ~0x00000004);
+        public Builder clearMergeDeviceToDeviceStream() {
+          
+          mergeDeviceToDeviceStream_ = false;
           onChanged();
           return this;
         }
@@ -1788,23 +2566,23 @@ public final Builder mergeUnknownFields(
         }
 
 
-        // @@protoc_insertion_point(builder_scope:tensorflow.GPUOptions.Experimental.VirtualDevices)
+        // @@protoc_insertion_point(builder_scope:tensorflow.GPUOptions.Experimental.StreamMergeOptions)
       }
 
-      // @@protoc_insertion_point(class_scope:tensorflow.GPUOptions.Experimental.VirtualDevices)
-      private static final org.tensorflow.proto.GPUOptions.Experimental.VirtualDevices DEFAULT_INSTANCE;
+      // @@protoc_insertion_point(class_scope:tensorflow.GPUOptions.Experimental.StreamMergeOptions)
+      private static final org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions DEFAULT_INSTANCE;
       static {
-        DEFAULT_INSTANCE = new org.tensorflow.proto.GPUOptions.Experimental.VirtualDevices();
+        DEFAULT_INSTANCE = new org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions();
       }
 
-      public static org.tensorflow.proto.GPUOptions.Experimental.VirtualDevices getDefaultInstance() {
+      public static org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions getDefaultInstance() {
         return DEFAULT_INSTANCE;
       }
 
-      private static final com.google.protobuf.Parser
-          PARSER = new com.google.protobuf.AbstractParser() {
+      private static final com.google.protobuf.Parser
+          PARSER = new com.google.protobuf.AbstractParser() {
         @java.lang.Override
-        public VirtualDevices parsePartialFrom(
+        public StreamMergeOptions parsePartialFrom(
             com.google.protobuf.CodedInputStream input,
             com.google.protobuf.ExtensionRegistryLite extensionRegistry)
             throws com.google.protobuf.InvalidProtocolBufferException {
@@ -1823,17 +2601,17 @@ public VirtualDevices parsePartialFrom(
         }
       };
 
-      public static com.google.protobuf.Parser parser() {
+      public static com.google.protobuf.Parser parser() {
         return PARSER;
       }
 
       @java.lang.Override
-      public com.google.protobuf.Parser getParserForType() {
+      public com.google.protobuf.Parser getParserForType() {
         return PARSER;
       }
 
       @java.lang.Override
-      public org.tensorflow.proto.GPUOptions.Experimental.VirtualDevices getDefaultInstanceForType() {
+      public org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions getDefaultInstanceForType() {
         return DEFAULT_INSTANCE;
       }
 
@@ -2365,6 +3143,64 @@ public int getGpuSystemMemorySizeInMb() {
       return gpuSystemMemorySizeInMb_;
     }
 
+    public static final int POPULATE_PJRT_GPU_CLIENT_CREATION_INFO_FIELD_NUMBER = 17;
+    private boolean populatePjrtGpuClientCreationInfo_;
+    /**
+     * 
+     * If true, save information needed for created a PjRt GPU client for
+     * creating a client with remote devices.
+     * 

+     *
+     * bool populate_pjrt_gpu_client_creation_info = 17;
+     * @return The populatePjrtGpuClientCreationInfo.
+     */
+    @java.lang.Override
+    public boolean getPopulatePjrtGpuClientCreationInfo() {
+      return populatePjrtGpuClientCreationInfo_;
+    }
+
+    public static final int NODE_ID_FIELD_NUMBER = 18;
+    private int nodeId_;
+    /**
+     * 
+     * node_id for use when creating a PjRt GPU client with remote devices,
+     * which enumerates jobs*tasks from a ServerDef.
+     * 

+     *
+     * int32 node_id = 18;
+     * @return The nodeId.
+     */
+    @java.lang.Override
+    public int getNodeId() {
+      return nodeId_;
+    }
+
+    public static final int STREAM_MERGE_OPTIONS_FIELD_NUMBER = 19;
+    private org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions streamMergeOptions_;
+    /**
+     * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+     * @return Whether the streamMergeOptions field is set.
+     */
+    @java.lang.Override
+    public boolean hasStreamMergeOptions() {
+      return streamMergeOptions_ != null;
+    }
+    /**
+     * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+     * @return The streamMergeOptions.
+     */
+    @java.lang.Override
+    public org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions getStreamMergeOptions() {
+      return streamMergeOptions_ == null ? org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.getDefaultInstance() : streamMergeOptions_;
+    }
+    /**
+     * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+     */
+    @java.lang.Override
+    public org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptionsOrBuilder getStreamMergeOptionsOrBuilder() {
+      return getStreamMergeOptions();
+    }
+
     private byte memoizedIsInitialized = -1;
     @java.lang.Override
     public final boolean isInitialized() {
@@ -2424,6 +3260,15 @@ public void writeTo(com.google.protobuf.CodedOutputStream output)
       if (gpuSystemMemorySizeInMb_ != 0) {
         output.writeInt32(16, gpuSystemMemorySizeInMb_);
       }
+      if (populatePjrtGpuClientCreationInfo_ != false) {
+        output.writeBool(17, populatePjrtGpuClientCreationInfo_);
+      }
+      if (nodeId_ != 0) {
+        output.writeInt32(18, nodeId_);
+      }
+      if (streamMergeOptions_ != null) {
+        output.writeMessage(19, getStreamMergeOptions());
+      }
       getUnknownFields().writeTo(output);
     }
 
@@ -2492,6 +3337,18 @@ public int getSerializedSize() {
         size += com.google.protobuf.CodedOutputStream
           .computeInt32Size(16, gpuSystemMemorySizeInMb_);
       }
+      if (populatePjrtGpuClientCreationInfo_ != false) {
+        size += com.google.protobuf.CodedOutputStream
+          .computeBoolSize(17, populatePjrtGpuClientCreationInfo_);
+      }
+      if (nodeId_ != 0) {
+        size += com.google.protobuf.CodedOutputStream
+          .computeInt32Size(18, nodeId_);
+      }
+      if (streamMergeOptions_ != null) {
+        size += com.google.protobuf.CodedOutputStream
+          .computeMessageSize(19, getStreamMergeOptions());
+      }
       size += getUnknownFields().getSerializedSize();
       memoizedSize = size;
       return size;
@@ -2539,6 +3396,15 @@ public boolean equals(final java.lang.Object obj) {
           != other.getGpuHostMemDisallowGrowth()) return false;
       if (getGpuSystemMemorySizeInMb()
           != other.getGpuSystemMemorySizeInMb()) return false;
+      if (getPopulatePjrtGpuClientCreationInfo()
+          != other.getPopulatePjrtGpuClientCreationInfo()) return false;
+      if (getNodeId()
+          != other.getNodeId()) return false;
+      if (hasStreamMergeOptions() != other.hasStreamMergeOptions()) return false;
+      if (hasStreamMergeOptions()) {
+        if (!getStreamMergeOptions()
+            .equals(other.getStreamMergeOptions())) return false;
+      }
       if (!getUnknownFields().equals(other.getUnknownFields())) return false;
       return true;
     }
@@ -2589,6 +3455,15 @@ public int hashCode() {
           getGpuHostMemDisallowGrowth());
       hash = (37 * hash) + GPU_SYSTEM_MEMORY_SIZE_IN_MB_FIELD_NUMBER;
       hash = (53 * hash) + getGpuSystemMemorySizeInMb();
+      hash = (37 * hash) + POPULATE_PJRT_GPU_CLIENT_CREATION_INFO_FIELD_NUMBER;
+      hash = (53 * hash) + com.google.protobuf.Internal.hashBoolean(
+          getPopulatePjrtGpuClientCreationInfo());
+      hash = (37 * hash) + NODE_ID_FIELD_NUMBER;
+      hash = (53 * hash) + getNodeId();
+      if (hasStreamMergeOptions()) {
+        hash = (37 * hash) + STREAM_MERGE_OPTIONS_FIELD_NUMBER;
+        hash = (53 * hash) + getStreamMergeOptions().hashCode();
+      }
       hash = (29 * hash) + getUnknownFields().hashCode();
       memoizedHashCode = hash;
       return hash;
@@ -2752,6 +3627,16 @@ public Builder clear() {
 
         gpuSystemMemorySizeInMb_ = 0;
 
+        populatePjrtGpuClientCreationInfo_ = false;
+
+        nodeId_ = 0;
+
+        if (streamMergeOptionsBuilder_ == null) {
+          streamMergeOptions_ = null;
+        } else {
+          streamMergeOptions_ = null;
+          streamMergeOptionsBuilder_ = null;
+        }
         return this;
       }
 
@@ -2802,6 +3687,13 @@ public org.tensorflow.proto.GPUOptions.Experimental buildPartial() {
         result.gpuHostMemLimitInMb_ = gpuHostMemLimitInMb_;
         result.gpuHostMemDisallowGrowth_ = gpuHostMemDisallowGrowth_;
         result.gpuSystemMemorySizeInMb_ = gpuSystemMemorySizeInMb_;
+        result.populatePjrtGpuClientCreationInfo_ = populatePjrtGpuClientCreationInfo_;
+        result.nodeId_ = nodeId_;
+        if (streamMergeOptionsBuilder_ == null) {
+          result.streamMergeOptions_ = streamMergeOptions_;
+        } else {
+          result.streamMergeOptions_ = streamMergeOptionsBuilder_.build();
+        }
         onBuilt();
         return result;
       }
@@ -2919,6 +3811,15 @@ public Builder mergeFrom(org.tensorflow.proto.GPUOptions.Experimental other) {
         if (other.getGpuSystemMemorySizeInMb() != 0) {
           setGpuSystemMemorySizeInMb(other.getGpuSystemMemorySizeInMb());
         }
+        if (other.getPopulatePjrtGpuClientCreationInfo() != false) {
+          setPopulatePjrtGpuClientCreationInfo(other.getPopulatePjrtGpuClientCreationInfo());
+        }
+        if (other.getNodeId() != 0) {
+          setNodeId(other.getNodeId());
+        }
+        if (other.hasStreamMergeOptions()) {
+          mergeStreamMergeOptions(other.getStreamMergeOptions());
+        }
         this.mergeUnknownFields(other.getUnknownFields());
         onChanged();
         return this;
@@ -3028,6 +3929,23 @@ public Builder mergeFrom(
 
                 break;
               } // case 128
+              case 136: {
+                populatePjrtGpuClientCreationInfo_ = input.readBool();
+
+                break;
+              } // case 136
+              case 144: {
+                nodeId_ = input.readInt32();
+
+                break;
+              } // case 144
+              case 154: {
+                input.readMessage(
+                    getStreamMergeOptionsFieldBuilder().getBuilder(),
+                    extensionRegistry);
+
+                break;
+              } // case 154
               default: {
                 if (!super.parseUnknownField(input, extensionRegistry, tag)) {
                   done = true; // was an endgroup tag
@@ -4783,6 +5701,217 @@ public Builder clearGpuSystemMemorySizeInMb() {
         onChanged();
         return this;
       }
+
+      private boolean populatePjrtGpuClientCreationInfo_ ;
+      /**
+       * 
+       * If true, save information needed for created a PjRt GPU client for
+       * creating a client with remote devices.
+       * 

+       *
+       * bool populate_pjrt_gpu_client_creation_info = 17;
+       * @return The populatePjrtGpuClientCreationInfo.
+       */
+      @java.lang.Override
+      public boolean getPopulatePjrtGpuClientCreationInfo() {
+        return populatePjrtGpuClientCreationInfo_;
+      }
+      /**
+       * 
+       * If true, save information needed for created a PjRt GPU client for
+       * creating a client with remote devices.
+       * 

+       *
+       * bool populate_pjrt_gpu_client_creation_info = 17;
+       * @param value The populatePjrtGpuClientCreationInfo to set.
+       * @return This builder for chaining.
+       */
+      public Builder setPopulatePjrtGpuClientCreationInfo(boolean value) {
+        
+        populatePjrtGpuClientCreationInfo_ = value;
+        onChanged();
+        return this;
+      }
+      /**
+       * 
+       * If true, save information needed for created a PjRt GPU client for
+       * creating a client with remote devices.
+       * 

+       *
+       * bool populate_pjrt_gpu_client_creation_info = 17;
+       * @return This builder for chaining.
+       */
+      public Builder clearPopulatePjrtGpuClientCreationInfo() {
+        
+        populatePjrtGpuClientCreationInfo_ = false;
+        onChanged();
+        return this;
+      }
+
+      private int nodeId_ ;
+      /**
+       * 
+       * node_id for use when creating a PjRt GPU client with remote devices,
+       * which enumerates jobs*tasks from a ServerDef.
+       * 

+       *
+       * int32 node_id = 18;
+       * @return The nodeId.
+       */
+      @java.lang.Override
+      public int getNodeId() {
+        return nodeId_;
+      }
+      /**
+       * 
+       * node_id for use when creating a PjRt GPU client with remote devices,
+       * which enumerates jobs*tasks from a ServerDef.
+       * 

+       *
+       * int32 node_id = 18;
+       * @param value The nodeId to set.
+       * @return This builder for chaining.
+       */
+      public Builder setNodeId(int value) {
+        
+        nodeId_ = value;
+        onChanged();
+        return this;
+      }
+      /**
+       * 
+       * node_id for use when creating a PjRt GPU client with remote devices,
+       * which enumerates jobs*tasks from a ServerDef.
+       * 

+       *
+       * int32 node_id = 18;
+       * @return This builder for chaining.
+       */
+      public Builder clearNodeId() {
+        
+        nodeId_ = 0;
+        onChanged();
+        return this;
+      }
+
+      private org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions streamMergeOptions_;
+      private com.google.protobuf.SingleFieldBuilderV3<
+          org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions, org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.Builder, org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptionsOrBuilder> streamMergeOptionsBuilder_;
+      /**
+       * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+       * @return Whether the streamMergeOptions field is set.
+       */
+      public boolean hasStreamMergeOptions() {
+        return streamMergeOptionsBuilder_ != null || streamMergeOptions_ != null;
+      }
+      /**
+       * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+       * @return The streamMergeOptions.
+       */
+      public org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions getStreamMergeOptions() {
+        if (streamMergeOptionsBuilder_ == null) {
+          return streamMergeOptions_ == null ? org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.getDefaultInstance() : streamMergeOptions_;
+        } else {
+          return streamMergeOptionsBuilder_.getMessage();
+        }
+      }
+      /**
+       * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+       */
+      public Builder setStreamMergeOptions(org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions value) {
+        if (streamMergeOptionsBuilder_ == null) {
+          if (value == null) {
+            throw new NullPointerException();
+          }
+          streamMergeOptions_ = value;
+          onChanged();
+        } else {
+          streamMergeOptionsBuilder_.setMessage(value);
+        }
+
+        return this;
+      }
+      /**
+       * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+       */
+      public Builder setStreamMergeOptions(
+          org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.Builder builderForValue) {
+        if (streamMergeOptionsBuilder_ == null) {
+          streamMergeOptions_ = builderForValue.build();
+          onChanged();
+        } else {
+          streamMergeOptionsBuilder_.setMessage(builderForValue.build());
+        }
+
+        return this;
+      }
+      /**
+       * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+       */
+      public Builder mergeStreamMergeOptions(org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions value) {
+        if (streamMergeOptionsBuilder_ == null) {
+          if (streamMergeOptions_ != null) {
+            streamMergeOptions_ =
+              org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.newBuilder(streamMergeOptions_).mergeFrom(value).buildPartial();
+          } else {
+            streamMergeOptions_ = value;
+          }
+          onChanged();
+        } else {
+          streamMergeOptionsBuilder_.mergeFrom(value);
+        }
+
+        return this;
+      }
+      /**
+       * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+       */
+      public Builder clearStreamMergeOptions() {
+        if (streamMergeOptionsBuilder_ == null) {
+          streamMergeOptions_ = null;
+          onChanged();
+        } else {
+          streamMergeOptions_ = null;
+          streamMergeOptionsBuilder_ = null;
+        }
+
+        return this;
+      }
+      /**
+       * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+       */
+      public org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.Builder getStreamMergeOptionsBuilder() {
+        
+        onChanged();
+        return getStreamMergeOptionsFieldBuilder().getBuilder();
+      }
+      /**
+       * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+       */
+      public org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptionsOrBuilder getStreamMergeOptionsOrBuilder() {
+        if (streamMergeOptionsBuilder_ != null) {
+          return streamMergeOptionsBuilder_.getMessageOrBuilder();
+        } else {
+          return streamMergeOptions_ == null ?
+              org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.getDefaultInstance() : streamMergeOptions_;
+        }
+      }
+      /**
+       * .tensorflow.GPUOptions.Experimental.StreamMergeOptions stream_merge_options = 19;
+       */
+      private com.google.protobuf.SingleFieldBuilderV3<
+          org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions, org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.Builder, org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptionsOrBuilder> 
+          getStreamMergeOptionsFieldBuilder() {
+        if (streamMergeOptionsBuilder_ == null) {
+          streamMergeOptionsBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
+              org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions, org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptions.Builder, org.tensorflow.proto.GPUOptions.Experimental.StreamMergeOptionsOrBuilder>(
+                  getStreamMergeOptions(),
+                  getParentForChildren(),
+                  isClean());
+          streamMergeOptions_ = null;
+        }
+        return streamMergeOptionsBuilder_;
+      }
       @java.lang.Override
       public final Builder setUnknownFields(
           final com.google.protobuf.UnknownFieldSet unknownFields) {
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MachineConfiguration.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MachineConfiguration.java
deleted file mode 100644
index 56ab6b425d1..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MachineConfiguration.java
+++ /dev/null
@@ -1,2257 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-/**
- * Protobuf type {@code tensorflow.MachineConfiguration}
- */
-public final class MachineConfiguration extends
-    com.google.protobuf.GeneratedMessageV3 implements
-    // @@protoc_insertion_point(message_implements:tensorflow.MachineConfiguration)
-    MachineConfigurationOrBuilder {
-private static final long serialVersionUID = 0L;
-  // Use MachineConfiguration.newBuilder() to construct.
-  private MachineConfiguration(com.google.protobuf.GeneratedMessageV3.Builder builder) {
-    super(builder);
-  }
-  private MachineConfiguration() {
-    hostname_ = "";
-    serialIdentifier_ = "";
-    deviceInfo_ = java.util.Collections.emptyList();
-    availableDeviceInfo_ = java.util.Collections.emptyList();
-  }
-
-  @java.lang.Override
-  @SuppressWarnings({"unused"})
-  protected java.lang.Object newInstance(
-      UnusedPrivateParameter unused) {
-    return new MachineConfiguration();
-  }
-
-  @java.lang.Override
-  public final com.google.protobuf.UnknownFieldSet
-  getUnknownFields() {
-    return this.unknownFields;
-  }
-  public static final com.google.protobuf.Descriptors.Descriptor
-      getDescriptor() {
-    return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MachineConfiguration_descriptor;
-  }
-
-  @java.lang.Override
-  protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
-      internalGetFieldAccessorTable() {
-    return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MachineConfiguration_fieldAccessorTable
-        .ensureFieldAccessorsInitialized(
-            org.tensorflow.proto.MachineConfiguration.class, org.tensorflow.proto.MachineConfiguration.Builder.class);
-  }
-
-  public static final int HOSTNAME_FIELD_NUMBER = 1;
-  private volatile java.lang.Object hostname_;
-  /**
-   * 
-   * Host name of machine that ran the benchmark.
-   * 

-   *
-   * string hostname = 1;
-   * @return The hostname.
-   */
-  @java.lang.Override
-  public java.lang.String getHostname() {
-    java.lang.Object ref = hostname_;
-    if (ref instanceof java.lang.String) {
-      return (java.lang.String) ref;
-    } else {
-      com.google.protobuf.ByteString bs = 
-          (com.google.protobuf.ByteString) ref;
-      java.lang.String s = bs.toStringUtf8();
-      hostname_ = s;
-      return s;
-    }
-  }
-  /**
-   * 
-   * Host name of machine that ran the benchmark.
-   * 

-   *
-   * string hostname = 1;
-   * @return The bytes for hostname.
-   */
-  @java.lang.Override
-  public com.google.protobuf.ByteString
-      getHostnameBytes() {
-    java.lang.Object ref = hostname_;
-    if (ref instanceof java.lang.String) {
-      com.google.protobuf.ByteString b = 
-          com.google.protobuf.ByteString.copyFromUtf8(
-              (java.lang.String) ref);
-      hostname_ = b;
-      return b;
-    } else {
-      return (com.google.protobuf.ByteString) ref;
-    }
-  }
-
-  public static final int SERIAL_IDENTIFIER_FIELD_NUMBER = 7;
-  private volatile java.lang.Object serialIdentifier_;
-  /**
-   * 
-   * Unique serial number of the machine.
-   * 

-   *
-   * string serial_identifier = 7;
-   * @return The serialIdentifier.
-   */
-  @java.lang.Override
-  public java.lang.String getSerialIdentifier() {
-    java.lang.Object ref = serialIdentifier_;
-    if (ref instanceof java.lang.String) {
-      return (java.lang.String) ref;
-    } else {
-      com.google.protobuf.ByteString bs = 
-          (com.google.protobuf.ByteString) ref;
-      java.lang.String s = bs.toStringUtf8();
-      serialIdentifier_ = s;
-      return s;
-    }
-  }
-  /**
-   * 
-   * Unique serial number of the machine.
-   * 

-   *
-   * string serial_identifier = 7;
-   * @return The bytes for serialIdentifier.
-   */
-  @java.lang.Override
-  public com.google.protobuf.ByteString
-      getSerialIdentifierBytes() {
-    java.lang.Object ref = serialIdentifier_;
-    if (ref instanceof java.lang.String) {
-      com.google.protobuf.ByteString b = 
-          com.google.protobuf.ByteString.copyFromUtf8(
-              (java.lang.String) ref);
-      serialIdentifier_ = b;
-      return b;
-    } else {
-      return (com.google.protobuf.ByteString) ref;
-    }
-  }
-
-  public static final int PLATFORM_INFO_FIELD_NUMBER = 2;
-  private org.tensorflow.proto.PlatformInfo platformInfo_;
-  /**
-   * 
-   * Additional platform information.
-   * 

-   *
-   * .tensorflow.PlatformInfo platform_info = 2;
-   * @return Whether the platformInfo field is set.
-   */
-  @java.lang.Override
-  public boolean hasPlatformInfo() {
-    return platformInfo_ != null;
-  }
-  /**
-   * 
-   * Additional platform information.
-   * 

-   *
-   * .tensorflow.PlatformInfo platform_info = 2;
-   * @return The platformInfo.
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.PlatformInfo getPlatformInfo() {
-    return platformInfo_ == null ? org.tensorflow.proto.PlatformInfo.getDefaultInstance() : platformInfo_;
-  }
-  /**
-   * 
-   * Additional platform information.
-   * 

-   *
-   * .tensorflow.PlatformInfo platform_info = 2;
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.PlatformInfoOrBuilder getPlatformInfoOrBuilder() {
-    return getPlatformInfo();
-  }
-
-  public static final int CPU_INFO_FIELD_NUMBER = 3;
-  private org.tensorflow.proto.CPUInfo cpuInfo_;
-  /**
-   * 
-   * CPU Information.
-   * 

-   *
-   * .tensorflow.CPUInfo cpu_info = 3;
-   * @return Whether the cpuInfo field is set.
-   */
-  @java.lang.Override
-  public boolean hasCpuInfo() {
-    return cpuInfo_ != null;
-  }
-  /**
-   * 
-   * CPU Information.
-   * 

-   *
-   * .tensorflow.CPUInfo cpu_info = 3;
-   * @return The cpuInfo.
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.CPUInfo getCpuInfo() {
-    return cpuInfo_ == null ? org.tensorflow.proto.CPUInfo.getDefaultInstance() : cpuInfo_;
-  }
-  /**
-   * 
-   * CPU Information.
-   * 

-   *
-   * .tensorflow.CPUInfo cpu_info = 3;
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.CPUInfoOrBuilder getCpuInfoOrBuilder() {
-    return getCpuInfo();
-  }
-
-  public static final int DEVICE_INFO_FIELD_NUMBER = 4;
-  private java.util.List deviceInfo_;
-  /**
-   * 
-   * Other devices that are attached and relevant (e.g. GPUInfo).
-   * 

-   *
-   * repeated .google.protobuf.Any device_info = 4;
-   */
-  @java.lang.Override
-  public java.util.List getDeviceInfoList() {
-    return deviceInfo_;
-  }
-  /**
-   * 
-   * Other devices that are attached and relevant (e.g. GPUInfo).
-   * 

-   *
-   * repeated .google.protobuf.Any device_info = 4;
-   */
-  @java.lang.Override
-  public java.util.List 
-      getDeviceInfoOrBuilderList() {
-    return deviceInfo_;
-  }
-  /**
-   * 
-   * Other devices that are attached and relevant (e.g. GPUInfo).
-   * 

-   *
-   * repeated .google.protobuf.Any device_info = 4;
-   */
-  @java.lang.Override
-  public int getDeviceInfoCount() {
-    return deviceInfo_.size();
-  }
-  /**
-   * 
-   * Other devices that are attached and relevant (e.g. GPUInfo).
-   * 

-   *
-   * repeated .google.protobuf.Any device_info = 4;
-   */
-  @java.lang.Override
-  public com.google.protobuf.Any getDeviceInfo(int index) {
-    return deviceInfo_.get(index);
-  }
-  /**
-   * 
-   * Other devices that are attached and relevant (e.g. GPUInfo).
-   * 

-   *
-   * repeated .google.protobuf.Any device_info = 4;
-   */
-  @java.lang.Override
-  public com.google.protobuf.AnyOrBuilder getDeviceInfoOrBuilder(
-      int index) {
-    return deviceInfo_.get(index);
-  }
-
-  public static final int AVAILABLE_DEVICE_INFO_FIELD_NUMBER = 5;
-  private java.util.List availableDeviceInfo_;
-  /**
-   * 
-   * Devices accessible to the test (e.g. as given by list_local_devices).
-   * 

-   *
-   * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-   */
-  @java.lang.Override
-  public java.util.List getAvailableDeviceInfoList() {
-    return availableDeviceInfo_;
-  }
-  /**
-   * 
-   * Devices accessible to the test (e.g. as given by list_local_devices).
-   * 

-   *
-   * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-   */
-  @java.lang.Override
-  public java.util.List 
-      getAvailableDeviceInfoOrBuilderList() {
-    return availableDeviceInfo_;
-  }
-  /**
-   * 
-   * Devices accessible to the test (e.g. as given by list_local_devices).
-   * 

-   *
-   * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-   */
-  @java.lang.Override
-  public int getAvailableDeviceInfoCount() {
-    return availableDeviceInfo_.size();
-  }
-  /**
-   * 
-   * Devices accessible to the test (e.g. as given by list_local_devices).
-   * 

-   *
-   * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.AvailableDeviceInfo getAvailableDeviceInfo(int index) {
-    return availableDeviceInfo_.get(index);
-  }
-  /**
-   * 
-   * Devices accessible to the test (e.g. as given by list_local_devices).
-   * 

-   *
-   * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.AvailableDeviceInfoOrBuilder getAvailableDeviceInfoOrBuilder(
-      int index) {
-    return availableDeviceInfo_.get(index);
-  }
-
-  public static final int MEMORY_INFO_FIELD_NUMBER = 6;
-  private org.tensorflow.proto.MemoryInfo memoryInfo_;
-  /**
-   * .tensorflow.MemoryInfo memory_info = 6;
-   * @return Whether the memoryInfo field is set.
-   */
-  @java.lang.Override
-  public boolean hasMemoryInfo() {
-    return memoryInfo_ != null;
-  }
-  /**
-   * .tensorflow.MemoryInfo memory_info = 6;
-   * @return The memoryInfo.
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.MemoryInfo getMemoryInfo() {
-    return memoryInfo_ == null ? org.tensorflow.proto.MemoryInfo.getDefaultInstance() : memoryInfo_;
-  }
-  /**
-   * .tensorflow.MemoryInfo memory_info = 6;
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.MemoryInfoOrBuilder getMemoryInfoOrBuilder() {
-    return getMemoryInfo();
-  }
-
-  private byte memoizedIsInitialized = -1;
-  @java.lang.Override
-  public final boolean isInitialized() {
-    byte isInitialized = memoizedIsInitialized;
-    if (isInitialized == 1) return true;
-    if (isInitialized == 0) return false;
-
-    memoizedIsInitialized = 1;
-    return true;
-  }
-
-  @java.lang.Override
-  public void writeTo(com.google.protobuf.CodedOutputStream output)
-                      throws java.io.IOException {
-    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(hostname_)) {
-      com.google.protobuf.GeneratedMessageV3.writeString(output, 1, hostname_);
-    }
-    if (platformInfo_ != null) {
-      output.writeMessage(2, getPlatformInfo());
-    }
-    if (cpuInfo_ != null) {
-      output.writeMessage(3, getCpuInfo());
-    }
-    for (int i = 0; i < deviceInfo_.size(); i++) {
-      output.writeMessage(4, deviceInfo_.get(i));
-    }
-    for (int i = 0; i < availableDeviceInfo_.size(); i++) {
-      output.writeMessage(5, availableDeviceInfo_.get(i));
-    }
-    if (memoryInfo_ != null) {
-      output.writeMessage(6, getMemoryInfo());
-    }
-    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(serialIdentifier_)) {
-      com.google.protobuf.GeneratedMessageV3.writeString(output, 7, serialIdentifier_);
-    }
-    getUnknownFields().writeTo(output);
-  }
-
-  @java.lang.Override
-  public int getSerializedSize() {
-    int size = memoizedSize;
-    if (size != -1) return size;
-
-    size = 0;
-    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(hostname_)) {
-      size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, hostname_);
-    }
-    if (platformInfo_ != null) {
-      size += com.google.protobuf.CodedOutputStream
-        .computeMessageSize(2, getPlatformInfo());
-    }
-    if (cpuInfo_ != null) {
-      size += com.google.protobuf.CodedOutputStream
-        .computeMessageSize(3, getCpuInfo());
-    }
-    for (int i = 0; i < deviceInfo_.size(); i++) {
-      size += com.google.protobuf.CodedOutputStream
-        .computeMessageSize(4, deviceInfo_.get(i));
-    }
-    for (int i = 0; i < availableDeviceInfo_.size(); i++) {
-      size += com.google.protobuf.CodedOutputStream
-        .computeMessageSize(5, availableDeviceInfo_.get(i));
-    }
-    if (memoryInfo_ != null) {
-      size += com.google.protobuf.CodedOutputStream
-        .computeMessageSize(6, getMemoryInfo());
-    }
-    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(serialIdentifier_)) {
-      size += com.google.protobuf.GeneratedMessageV3.computeStringSize(7, serialIdentifier_);
-    }
-    size += getUnknownFields().getSerializedSize();
-    memoizedSize = size;
-    return size;
-  }
-
-  @java.lang.Override
-  public boolean equals(final java.lang.Object obj) {
-    if (obj == this) {
-     return true;
-    }
-    if (!(obj instanceof org.tensorflow.proto.MachineConfiguration)) {
-      return super.equals(obj);
-    }
-    org.tensorflow.proto.MachineConfiguration other = (org.tensorflow.proto.MachineConfiguration) obj;
-
-    if (!getHostname()
-        .equals(other.getHostname())) return false;
-    if (!getSerialIdentifier()
-        .equals(other.getSerialIdentifier())) return false;
-    if (hasPlatformInfo() != other.hasPlatformInfo()) return false;
-    if (hasPlatformInfo()) {
-      if (!getPlatformInfo()
-          .equals(other.getPlatformInfo())) return false;
-    }
-    if (hasCpuInfo() != other.hasCpuInfo()) return false;
-    if (hasCpuInfo()) {
-      if (!getCpuInfo()
-          .equals(other.getCpuInfo())) return false;
-    }
-    if (!getDeviceInfoList()
-        .equals(other.getDeviceInfoList())) return false;
-    if (!getAvailableDeviceInfoList()
-        .equals(other.getAvailableDeviceInfoList())) return false;
-    if (hasMemoryInfo() != other.hasMemoryInfo()) return false;
-    if (hasMemoryInfo()) {
-      if (!getMemoryInfo()
-          .equals(other.getMemoryInfo())) return false;
-    }
-    if (!getUnknownFields().equals(other.getUnknownFields())) return false;
-    return true;
-  }
-
-  @java.lang.Override
-  public int hashCode() {
-    if (memoizedHashCode != 0) {
-      return memoizedHashCode;
-    }
-    int hash = 41;
-    hash = (19 * hash) + getDescriptor().hashCode();
-    hash = (37 * hash) + HOSTNAME_FIELD_NUMBER;
-    hash = (53 * hash) + getHostname().hashCode();
-    hash = (37 * hash) + SERIAL_IDENTIFIER_FIELD_NUMBER;
-    hash = (53 * hash) + getSerialIdentifier().hashCode();
-    if (hasPlatformInfo()) {
-      hash = (37 * hash) + PLATFORM_INFO_FIELD_NUMBER;
-      hash = (53 * hash) + getPlatformInfo().hashCode();
-    }
-    if (hasCpuInfo()) {
-      hash = (37 * hash) + CPU_INFO_FIELD_NUMBER;
-      hash = (53 * hash) + getCpuInfo().hashCode();
-    }
-    if (getDeviceInfoCount() > 0) {
-      hash = (37 * hash) + DEVICE_INFO_FIELD_NUMBER;
-      hash = (53 * hash) + getDeviceInfoList().hashCode();
-    }
-    if (getAvailableDeviceInfoCount() > 0) {
-      hash = (37 * hash) + AVAILABLE_DEVICE_INFO_FIELD_NUMBER;
-      hash = (53 * hash) + getAvailableDeviceInfoList().hashCode();
-    }
-    if (hasMemoryInfo()) {
-      hash = (37 * hash) + MEMORY_INFO_FIELD_NUMBER;
-      hash = (53 * hash) + getMemoryInfo().hashCode();
-    }
-    hash = (29 * hash) + getUnknownFields().hashCode();
-    memoizedHashCode = hash;
-    return hash;
-  }
-
-  public static org.tensorflow.proto.MachineConfiguration parseFrom(
-      java.nio.ByteBuffer data)
-      throws com.google.protobuf.InvalidProtocolBufferException {
-    return PARSER.parseFrom(data);
-  }
-  public static org.tensorflow.proto.MachineConfiguration parseFrom(
-      java.nio.ByteBuffer data,
-      com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-      throws com.google.protobuf.InvalidProtocolBufferException {
-    return PARSER.parseFrom(data, extensionRegistry);
-  }
-  public static org.tensorflow.proto.MachineConfiguration parseFrom(
-      com.google.protobuf.ByteString data)
-      throws com.google.protobuf.InvalidProtocolBufferException {
-    return PARSER.parseFrom(data);
-  }
-  public static org.tensorflow.proto.MachineConfiguration parseFrom(
-      com.google.protobuf.ByteString data,
-      com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-      throws com.google.protobuf.InvalidProtocolBufferException {
-    return PARSER.parseFrom(data, extensionRegistry);
-  }
-  public static org.tensorflow.proto.MachineConfiguration parseFrom(byte[] data)
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-  public static Builder newBuilder() {
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-    return this == DEFAULT_INSTANCE
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-  @java.lang.Override
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-  /**
-   * Protobuf type {@code tensorflow.MachineConfiguration}
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-  public static final class Builder extends
-      com.google.protobuf.GeneratedMessageV3.Builder implements
-      // @@protoc_insertion_point(builder_implements:tensorflow.MachineConfiguration)
-      org.tensorflow.proto.MachineConfigurationOrBuilder {
-    public static final com.google.protobuf.Descriptors.Descriptor
-        getDescriptor() {
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-    private Builder() {
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-    }
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-      serialIdentifier_ = "";
-
-      if (platformInfoBuilder_ == null) {
-        platformInfo_ = null;
-      } else {
-        platformInfo_ = null;
-        platformInfoBuilder_ = null;
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-      return this;
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-    @java.lang.Override
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-      return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MachineConfiguration_descriptor;
-    }
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-    @java.lang.Override
-    public org.tensorflow.proto.MachineConfiguration getDefaultInstanceForType() {
-      return org.tensorflow.proto.MachineConfiguration.getDefaultInstance();
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-    @java.lang.Override
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-      org.tensorflow.proto.MachineConfiguration result = buildPartial();
-      if (!result.isInitialized()) {
-        throw newUninitializedMessageException(result);
-      }
-      return result;
-    }
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-    @java.lang.Override
-    public org.tensorflow.proto.MachineConfiguration buildPartial() {
-      org.tensorflow.proto.MachineConfiguration result = new org.tensorflow.proto.MachineConfiguration(this);
-      int from_bitField0_ = bitField0_;
-      result.hostname_ = hostname_;
-      result.serialIdentifier_ = serialIdentifier_;
-      if (platformInfoBuilder_ == null) {
-        result.platformInfo_ = platformInfo_;
-      } else {
-        result.platformInfo_ = platformInfoBuilder_.build();
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-    @java.lang.Override
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-    @java.lang.Override
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-      return super.setField(field, value);
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-      return super.clearField(field);
-    }
-    @java.lang.Override
-    public Builder clearOneof(
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-      return super.clearOneof(oneof);
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-        int index, java.lang.Object value) {
-      return super.setRepeatedField(field, index, value);
-    }
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-    public Builder addRepeatedField(
-        com.google.protobuf.Descriptors.FieldDescriptor field,
-        java.lang.Object value) {
-      return super.addRepeatedField(field, value);
-    }
-    @java.lang.Override
-    public Builder mergeFrom(com.google.protobuf.Message other) {
-      if (other instanceof org.tensorflow.proto.MachineConfiguration) {
-        return mergeFrom((org.tensorflow.proto.MachineConfiguration)other);
-      } else {
-        super.mergeFrom(other);
-        return this;
-      }
-    }
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-    public Builder mergeFrom(org.tensorflow.proto.MachineConfiguration other) {
-      if (other == org.tensorflow.proto.MachineConfiguration.getDefaultInstance()) return this;
-      if (!other.getHostname().isEmpty()) {
-        hostname_ = other.hostname_;
-        onChanged();
-      }
-      if (!other.getSerialIdentifier().isEmpty()) {
-        serialIdentifier_ = other.serialIdentifier_;
-        onChanged();
-      }
-      if (other.hasPlatformInfo()) {
-        mergePlatformInfo(other.getPlatformInfo());
-      }
-      if (other.hasCpuInfo()) {
-        mergeCpuInfo(other.getCpuInfo());
-      }
-      if (deviceInfoBuilder_ == null) {
-        if (!other.deviceInfo_.isEmpty()) {
-          if (deviceInfo_.isEmpty()) {
-            deviceInfo_ = other.deviceInfo_;
-            bitField0_ = (bitField0_ & ~0x00000001);
-          } else {
-            ensureDeviceInfoIsMutable();
-            deviceInfo_.addAll(other.deviceInfo_);
-          }
-          onChanged();
-        }
-      } else {
-        if (!other.deviceInfo_.isEmpty()) {
-          if (deviceInfoBuilder_.isEmpty()) {
-            deviceInfoBuilder_.dispose();
-            deviceInfoBuilder_ = null;
-            deviceInfo_ = other.deviceInfo_;
-            bitField0_ = (bitField0_ & ~0x00000001);
-            deviceInfoBuilder_ = 
-              com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ?
-                 getDeviceInfoFieldBuilder() : null;
-          } else {
-            deviceInfoBuilder_.addAllMessages(other.deviceInfo_);
-          }
-        }
-      }
-      if (availableDeviceInfoBuilder_ == null) {
-        if (!other.availableDeviceInfo_.isEmpty()) {
-          if (availableDeviceInfo_.isEmpty()) {
-            availableDeviceInfo_ = other.availableDeviceInfo_;
-            bitField0_ = (bitField0_ & ~0x00000002);
-          } else {
-            ensureAvailableDeviceInfoIsMutable();
-            availableDeviceInfo_.addAll(other.availableDeviceInfo_);
-          }
-          onChanged();
-        }
-      } else {
-        if (!other.availableDeviceInfo_.isEmpty()) {
-          if (availableDeviceInfoBuilder_.isEmpty()) {
-            availableDeviceInfoBuilder_.dispose();
-            availableDeviceInfoBuilder_ = null;
-            availableDeviceInfo_ = other.availableDeviceInfo_;
-            bitField0_ = (bitField0_ & ~0x00000002);
-            availableDeviceInfoBuilder_ = 
-              com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ?
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-          } else {
-            availableDeviceInfoBuilder_.addAllMessages(other.availableDeviceInfo_);
-          }
-        }
-      }
-      if (other.hasMemoryInfo()) {
-        mergeMemoryInfo(other.getMemoryInfo());
-      }
-      this.mergeUnknownFields(other.getUnknownFields());
-      onChanged();
-      return this;
-    }
-
-    @java.lang.Override
-    public final boolean isInitialized() {
-      return true;
-    }
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-    @java.lang.Override
-    public Builder mergeFrom(
-        com.google.protobuf.CodedInputStream input,
-        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-        throws java.io.IOException {
-      if (extensionRegistry == null) {
-        throw new java.lang.NullPointerException();
-      }
-      try {
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-        while (!done) {
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-          switch (tag) {
-            case 0:
-              done = true;
-              break;
-            case 10: {
-              hostname_ = input.readStringRequireUtf8();
-
-              break;
-            } // case 10
-            case 18: {
-              input.readMessage(
-                  getPlatformInfoFieldBuilder().getBuilder(),
-                  extensionRegistry);
-
-              break;
-            } // case 18
-            case 26: {
-              input.readMessage(
-                  getCpuInfoFieldBuilder().getBuilder(),
-                  extensionRegistry);
-
-              break;
-            } // case 26
-            case 34: {
-              com.google.protobuf.Any m =
-                  input.readMessage(
-                      com.google.protobuf.Any.parser(),
-                      extensionRegistry);
-              if (deviceInfoBuilder_ == null) {
-                ensureDeviceInfoIsMutable();
-                deviceInfo_.add(m);
-              } else {
-                deviceInfoBuilder_.addMessage(m);
-              }
-              break;
-            } // case 34
-            case 42: {
-              org.tensorflow.proto.AvailableDeviceInfo m =
-                  input.readMessage(
-                      org.tensorflow.proto.AvailableDeviceInfo.parser(),
-                      extensionRegistry);
-              if (availableDeviceInfoBuilder_ == null) {
-                ensureAvailableDeviceInfoIsMutable();
-                availableDeviceInfo_.add(m);
-              } else {
-                availableDeviceInfoBuilder_.addMessage(m);
-              }
-              break;
-            } // case 42
-            case 50: {
-              input.readMessage(
-                  getMemoryInfoFieldBuilder().getBuilder(),
-                  extensionRegistry);
-
-              break;
-            } // case 50
-            case 58: {
-              serialIdentifier_ = input.readStringRequireUtf8();
-
-              break;
-            } // case 58
-            default: {
-              if (!super.parseUnknownField(input, extensionRegistry, tag)) {
-                done = true; // was an endgroup tag
-              }
-              break;
-            } // default:
-          } // switch (tag)
-        } // while (!done)
-      } catch (com.google.protobuf.InvalidProtocolBufferException e) {
-        throw e.unwrapIOException();
-      } finally {
-        onChanged();
-      } // finally
-      return this;
-    }
-    private int bitField0_;
-
-    private java.lang.Object hostname_ = "";
-    /**
-     * 
-     * Host name of machine that ran the benchmark.
-     * 

-     *
-     * string hostname = 1;
-     * @return The hostname.
-     */
-    public java.lang.String getHostname() {
-      java.lang.Object ref = hostname_;
-      if (!(ref instanceof java.lang.String)) {
-        com.google.protobuf.ByteString bs =
-            (com.google.protobuf.ByteString) ref;
-        java.lang.String s = bs.toStringUtf8();
-        hostname_ = s;
-        return s;
-      } else {
-        return (java.lang.String) ref;
-      }
-    }
-    /**
-     * 
-     * Host name of machine that ran the benchmark.
-     * 

-     *
-     * string hostname = 1;
-     * @return The bytes for hostname.
-     */
-    public com.google.protobuf.ByteString
-        getHostnameBytes() {
-      java.lang.Object ref = hostname_;
-      if (ref instanceof String) {
-        com.google.protobuf.ByteString b = 
-            com.google.protobuf.ByteString.copyFromUtf8(
-                (java.lang.String) ref);
-        hostname_ = b;
-        return b;
-      } else {
-        return (com.google.protobuf.ByteString) ref;
-      }
-    }
-    /**
-     * 
-     * Host name of machine that ran the benchmark.
-     * 

-     *
-     * string hostname = 1;
-     * @param value The hostname to set.
-     * @return This builder for chaining.
-     */
-    public Builder setHostname(
-        java.lang.String value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  
-      hostname_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * Host name of machine that ran the benchmark.
-     * 

-     *
-     * string hostname = 1;
-     * @return This builder for chaining.
-     */
-    public Builder clearHostname() {
-      
-      hostname_ = getDefaultInstance().getHostname();
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * Host name of machine that ran the benchmark.
-     * 

-     *
-     * string hostname = 1;
-     * @param value The bytes for hostname to set.
-     * @return This builder for chaining.
-     */
-    public Builder setHostnameBytes(
-        com.google.protobuf.ByteString value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  checkByteStringIsUtf8(value);
-      
-      hostname_ = value;
-      onChanged();
-      return this;
-    }
-
-    private java.lang.Object serialIdentifier_ = "";
-    /**
-     * 
-     * Unique serial number of the machine.
-     * 

-     *
-     * string serial_identifier = 7;
-     * @return The serialIdentifier.
-     */
-    public java.lang.String getSerialIdentifier() {
-      java.lang.Object ref = serialIdentifier_;
-      if (!(ref instanceof java.lang.String)) {
-        com.google.protobuf.ByteString bs =
-            (com.google.protobuf.ByteString) ref;
-        java.lang.String s = bs.toStringUtf8();
-        serialIdentifier_ = s;
-        return s;
-      } else {
-        return (java.lang.String) ref;
-      }
-    }
-    /**
-     * 
-     * Unique serial number of the machine.
-     * 

-     *
-     * string serial_identifier = 7;
-     * @return The bytes for serialIdentifier.
-     */
-    public com.google.protobuf.ByteString
-        getSerialIdentifierBytes() {
-      java.lang.Object ref = serialIdentifier_;
-      if (ref instanceof String) {
-        com.google.protobuf.ByteString b = 
-            com.google.protobuf.ByteString.copyFromUtf8(
-                (java.lang.String) ref);
-        serialIdentifier_ = b;
-        return b;
-      } else {
-        return (com.google.protobuf.ByteString) ref;
-      }
-    }
-    /**
-     * 
-     * Unique serial number of the machine.
-     * 

-     *
-     * string serial_identifier = 7;
-     * @param value The serialIdentifier to set.
-     * @return This builder for chaining.
-     */
-    public Builder setSerialIdentifier(
-        java.lang.String value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  
-      serialIdentifier_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * Unique serial number of the machine.
-     * 

-     *
-     * string serial_identifier = 7;
-     * @return This builder for chaining.
-     */
-    public Builder clearSerialIdentifier() {
-      
-      serialIdentifier_ = getDefaultInstance().getSerialIdentifier();
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * Unique serial number of the machine.
-     * 

-     *
-     * string serial_identifier = 7;
-     * @param value The bytes for serialIdentifier to set.
-     * @return This builder for chaining.
-     */
-    public Builder setSerialIdentifierBytes(
-        com.google.protobuf.ByteString value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  checkByteStringIsUtf8(value);
-      
-      serialIdentifier_ = value;
-      onChanged();
-      return this;
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-
-    private org.tensorflow.proto.PlatformInfo platformInfo_;
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.PlatformInfo, org.tensorflow.proto.PlatformInfo.Builder, org.tensorflow.proto.PlatformInfoOrBuilder> platformInfoBuilder_;
-    /**
-     * 
-     * Additional platform information.
-     * 

-     *
-     * .tensorflow.PlatformInfo platform_info = 2;
-     * @return Whether the platformInfo field is set.
-     */
-    public boolean hasPlatformInfo() {
-      return platformInfoBuilder_ != null || platformInfo_ != null;
-    }
-    /**
-     * 
-     * Additional platform information.
-     * 

-     *
-     * .tensorflow.PlatformInfo platform_info = 2;
-     * @return The platformInfo.
-     */
-    public org.tensorflow.proto.PlatformInfo getPlatformInfo() {
-      if (platformInfoBuilder_ == null) {
-        return platformInfo_ == null ? org.tensorflow.proto.PlatformInfo.getDefaultInstance() : platformInfo_;
-      } else {
-        return platformInfoBuilder_.getMessage();
-      }
-    }
-    /**
-     * 
-     * Additional platform information.
-     * 

-     *
-     * .tensorflow.PlatformInfo platform_info = 2;
-     */
-    public Builder setPlatformInfo(org.tensorflow.proto.PlatformInfo value) {
-      if (platformInfoBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        platformInfo_ = value;
-        onChanged();
-      } else {
-        platformInfoBuilder_.setMessage(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * Additional platform information.
-     * 

-     *
-     * .tensorflow.PlatformInfo platform_info = 2;
-     */
-    public Builder setPlatformInfo(
-        org.tensorflow.proto.PlatformInfo.Builder builderForValue) {
-      if (platformInfoBuilder_ == null) {
-        platformInfo_ = builderForValue.build();
-        onChanged();
-      } else {
-        platformInfoBuilder_.setMessage(builderForValue.build());
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * Additional platform information.
-     * 

-     *
-     * .tensorflow.PlatformInfo platform_info = 2;
-     */
-    public Builder mergePlatformInfo(org.tensorflow.proto.PlatformInfo value) {
-      if (platformInfoBuilder_ == null) {
-        if (platformInfo_ != null) {
-          platformInfo_ =
-            org.tensorflow.proto.PlatformInfo.newBuilder(platformInfo_).mergeFrom(value).buildPartial();
-        } else {
-          platformInfo_ = value;
-        }
-        onChanged();
-      } else {
-        platformInfoBuilder_.mergeFrom(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * Additional platform information.
-     * 

-     *
-     * .tensorflow.PlatformInfo platform_info = 2;
-     */
-    public Builder clearPlatformInfo() {
-      if (platformInfoBuilder_ == null) {
-        platformInfo_ = null;
-        onChanged();
-      } else {
-        platformInfo_ = null;
-        platformInfoBuilder_ = null;
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * Additional platform information.
-     * 

-     *
-     * .tensorflow.PlatformInfo platform_info = 2;
-     */
-    public org.tensorflow.proto.PlatformInfo.Builder getPlatformInfoBuilder() {
-      
-      onChanged();
-      return getPlatformInfoFieldBuilder().getBuilder();
-    }
-    /**
-     * 
-     * Additional platform information.
-     * 

-     *
-     * .tensorflow.PlatformInfo platform_info = 2;
-     */
-    public org.tensorflow.proto.PlatformInfoOrBuilder getPlatformInfoOrBuilder() {
-      if (platformInfoBuilder_ != null) {
-        return platformInfoBuilder_.getMessageOrBuilder();
-      } else {
-        return platformInfo_ == null ?
-            org.tensorflow.proto.PlatformInfo.getDefaultInstance() : platformInfo_;
-      }
-    }
-    /**
-     * 
-     * Additional platform information.
-     * 

-     *
-     * .tensorflow.PlatformInfo platform_info = 2;
-     */
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.PlatformInfo, org.tensorflow.proto.PlatformInfo.Builder, org.tensorflow.proto.PlatformInfoOrBuilder> 
-        getPlatformInfoFieldBuilder() {
-      if (platformInfoBuilder_ == null) {
-        platformInfoBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
-            org.tensorflow.proto.PlatformInfo, org.tensorflow.proto.PlatformInfo.Builder, org.tensorflow.proto.PlatformInfoOrBuilder>(
-                getPlatformInfo(),
-                getParentForChildren(),
-                isClean());
-        platformInfo_ = null;
-      }
-      return platformInfoBuilder_;
-    }
-
-    private org.tensorflow.proto.CPUInfo cpuInfo_;
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.CPUInfo, org.tensorflow.proto.CPUInfo.Builder, org.tensorflow.proto.CPUInfoOrBuilder> cpuInfoBuilder_;
-    /**
-     * 
-     * CPU Information.
-     * 

-     *
-     * .tensorflow.CPUInfo cpu_info = 3;
-     * @return Whether the cpuInfo field is set.
-     */
-    public boolean hasCpuInfo() {
-      return cpuInfoBuilder_ != null || cpuInfo_ != null;
-    }
-    /**
-     * 
-     * CPU Information.
-     * 

-     *
-     * .tensorflow.CPUInfo cpu_info = 3;
-     * @return The cpuInfo.
-     */
-    public org.tensorflow.proto.CPUInfo getCpuInfo() {
-      if (cpuInfoBuilder_ == null) {
-        return cpuInfo_ == null ? org.tensorflow.proto.CPUInfo.getDefaultInstance() : cpuInfo_;
-      } else {
-        return cpuInfoBuilder_.getMessage();
-      }
-    }
-    /**
-     * 
-     * CPU Information.
-     * 

-     *
-     * .tensorflow.CPUInfo cpu_info = 3;
-     */
-    public Builder setCpuInfo(org.tensorflow.proto.CPUInfo value) {
-      if (cpuInfoBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        cpuInfo_ = value;
-        onChanged();
-      } else {
-        cpuInfoBuilder_.setMessage(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * CPU Information.
-     * 

-     *
-     * .tensorflow.CPUInfo cpu_info = 3;
-     */
-    public Builder setCpuInfo(
-        org.tensorflow.proto.CPUInfo.Builder builderForValue) {
-      if (cpuInfoBuilder_ == null) {
-        cpuInfo_ = builderForValue.build();
-        onChanged();
-      } else {
-        cpuInfoBuilder_.setMessage(builderForValue.build());
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * CPU Information.
-     * 

-     *
-     * .tensorflow.CPUInfo cpu_info = 3;
-     */
-    public Builder mergeCpuInfo(org.tensorflow.proto.CPUInfo value) {
-      if (cpuInfoBuilder_ == null) {
-        if (cpuInfo_ != null) {
-          cpuInfo_ =
-            org.tensorflow.proto.CPUInfo.newBuilder(cpuInfo_).mergeFrom(value).buildPartial();
-        } else {
-          cpuInfo_ = value;
-        }
-        onChanged();
-      } else {
-        cpuInfoBuilder_.mergeFrom(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * CPU Information.
-     * 

-     *
-     * .tensorflow.CPUInfo cpu_info = 3;
-     */
-    public Builder clearCpuInfo() {
-      if (cpuInfoBuilder_ == null) {
-        cpuInfo_ = null;
-        onChanged();
-      } else {
-        cpuInfo_ = null;
-        cpuInfoBuilder_ = null;
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * CPU Information.
-     * 

-     *
-     * .tensorflow.CPUInfo cpu_info = 3;
-     */
-    public org.tensorflow.proto.CPUInfo.Builder getCpuInfoBuilder() {
-      
-      onChanged();
-      return getCpuInfoFieldBuilder().getBuilder();
-    }
-    /**
-     * 
-     * CPU Information.
-     * 

-     *
-     * .tensorflow.CPUInfo cpu_info = 3;
-     */
-    public org.tensorflow.proto.CPUInfoOrBuilder getCpuInfoOrBuilder() {
-      if (cpuInfoBuilder_ != null) {
-        return cpuInfoBuilder_.getMessageOrBuilder();
-      } else {
-        return cpuInfo_ == null ?
-            org.tensorflow.proto.CPUInfo.getDefaultInstance() : cpuInfo_;
-      }
-    }
-    /**
-     * 
-     * CPU Information.
-     * 

-     *
-     * .tensorflow.CPUInfo cpu_info = 3;
-     */
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.CPUInfo, org.tensorflow.proto.CPUInfo.Builder, org.tensorflow.proto.CPUInfoOrBuilder> 
-        getCpuInfoFieldBuilder() {
-      if (cpuInfoBuilder_ == null) {
-        cpuInfoBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
-            org.tensorflow.proto.CPUInfo, org.tensorflow.proto.CPUInfo.Builder, org.tensorflow.proto.CPUInfoOrBuilder>(
-                getCpuInfo(),
-                getParentForChildren(),
-                isClean());
-        cpuInfo_ = null;
-      }
-      return cpuInfoBuilder_;
-    }
-
-    private java.util.List deviceInfo_ =
-      java.util.Collections.emptyList();
-    private void ensureDeviceInfoIsMutable() {
-      if (!((bitField0_ & 0x00000001) != 0)) {
-        deviceInfo_ = new java.util.ArrayList(deviceInfo_);
-        bitField0_ |= 0x00000001;
-       }
-    }
-
-    private com.google.protobuf.RepeatedFieldBuilderV3<
-        com.google.protobuf.Any, com.google.protobuf.Any.Builder, com.google.protobuf.AnyOrBuilder> deviceInfoBuilder_;
-
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public java.util.List getDeviceInfoList() {
-      if (deviceInfoBuilder_ == null) {
-        return java.util.Collections.unmodifiableList(deviceInfo_);
-      } else {
-        return deviceInfoBuilder_.getMessageList();
-      }
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public int getDeviceInfoCount() {
-      if (deviceInfoBuilder_ == null) {
-        return deviceInfo_.size();
-      } else {
-        return deviceInfoBuilder_.getCount();
-      }
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public com.google.protobuf.Any getDeviceInfo(int index) {
-      if (deviceInfoBuilder_ == null) {
-        return deviceInfo_.get(index);
-      } else {
-        return deviceInfoBuilder_.getMessage(index);
-      }
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public Builder setDeviceInfo(
-        int index, com.google.protobuf.Any value) {
-      if (deviceInfoBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        ensureDeviceInfoIsMutable();
-        deviceInfo_.set(index, value);
-        onChanged();
-      } else {
-        deviceInfoBuilder_.setMessage(index, value);
-      }
-      return this;
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public Builder setDeviceInfo(
-        int index, com.google.protobuf.Any.Builder builderForValue) {
-      if (deviceInfoBuilder_ == null) {
-        ensureDeviceInfoIsMutable();
-        deviceInfo_.set(index, builderForValue.build());
-        onChanged();
-      } else {
-        deviceInfoBuilder_.setMessage(index, builderForValue.build());
-      }
-      return this;
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public Builder addDeviceInfo(com.google.protobuf.Any value) {
-      if (deviceInfoBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        ensureDeviceInfoIsMutable();
-        deviceInfo_.add(value);
-        onChanged();
-      } else {
-        deviceInfoBuilder_.addMessage(value);
-      }
-      return this;
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public Builder addDeviceInfo(
-        int index, com.google.protobuf.Any value) {
-      if (deviceInfoBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        ensureDeviceInfoIsMutable();
-        deviceInfo_.add(index, value);
-        onChanged();
-      } else {
-        deviceInfoBuilder_.addMessage(index, value);
-      }
-      return this;
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public Builder addDeviceInfo(
-        com.google.protobuf.Any.Builder builderForValue) {
-      if (deviceInfoBuilder_ == null) {
-        ensureDeviceInfoIsMutable();
-        deviceInfo_.add(builderForValue.build());
-        onChanged();
-      } else {
-        deviceInfoBuilder_.addMessage(builderForValue.build());
-      }
-      return this;
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public Builder addDeviceInfo(
-        int index, com.google.protobuf.Any.Builder builderForValue) {
-      if (deviceInfoBuilder_ == null) {
-        ensureDeviceInfoIsMutable();
-        deviceInfo_.add(index, builderForValue.build());
-        onChanged();
-      } else {
-        deviceInfoBuilder_.addMessage(index, builderForValue.build());
-      }
-      return this;
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public Builder addAllDeviceInfo(
-        java.lang.Iterable values) {
-      if (deviceInfoBuilder_ == null) {
-        ensureDeviceInfoIsMutable();
-        com.google.protobuf.AbstractMessageLite.Builder.addAll(
-            values, deviceInfo_);
-        onChanged();
-      } else {
-        deviceInfoBuilder_.addAllMessages(values);
-      }
-      return this;
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public Builder clearDeviceInfo() {
-      if (deviceInfoBuilder_ == null) {
-        deviceInfo_ = java.util.Collections.emptyList();
-        bitField0_ = (bitField0_ & ~0x00000001);
-        onChanged();
-      } else {
-        deviceInfoBuilder_.clear();
-      }
-      return this;
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public Builder removeDeviceInfo(int index) {
-      if (deviceInfoBuilder_ == null) {
-        ensureDeviceInfoIsMutable();
-        deviceInfo_.remove(index);
-        onChanged();
-      } else {
-        deviceInfoBuilder_.remove(index);
-      }
-      return this;
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public com.google.protobuf.Any.Builder getDeviceInfoBuilder(
-        int index) {
-      return getDeviceInfoFieldBuilder().getBuilder(index);
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public com.google.protobuf.AnyOrBuilder getDeviceInfoOrBuilder(
-        int index) {
-      if (deviceInfoBuilder_ == null) {
-        return deviceInfo_.get(index);  } else {
-        return deviceInfoBuilder_.getMessageOrBuilder(index);
-      }
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public java.util.List 
-         getDeviceInfoOrBuilderList() {
-      if (deviceInfoBuilder_ != null) {
-        return deviceInfoBuilder_.getMessageOrBuilderList();
-      } else {
-        return java.util.Collections.unmodifiableList(deviceInfo_);
-      }
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public com.google.protobuf.Any.Builder addDeviceInfoBuilder() {
-      return getDeviceInfoFieldBuilder().addBuilder(
-          com.google.protobuf.Any.getDefaultInstance());
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public com.google.protobuf.Any.Builder addDeviceInfoBuilder(
-        int index) {
-      return getDeviceInfoFieldBuilder().addBuilder(
-          index, com.google.protobuf.Any.getDefaultInstance());
-    }
-    /**
-     * 
-     * Other devices that are attached and relevant (e.g. GPUInfo).
-     * 

-     *
-     * repeated .google.protobuf.Any device_info = 4;
-     */
-    public java.util.List 
-         getDeviceInfoBuilderList() {
-      return getDeviceInfoFieldBuilder().getBuilderList();
-    }
-    private com.google.protobuf.RepeatedFieldBuilderV3<
-        com.google.protobuf.Any, com.google.protobuf.Any.Builder, com.google.protobuf.AnyOrBuilder> 
-        getDeviceInfoFieldBuilder() {
-      if (deviceInfoBuilder_ == null) {
-        deviceInfoBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3<
-            com.google.protobuf.Any, com.google.protobuf.Any.Builder, com.google.protobuf.AnyOrBuilder>(
-                deviceInfo_,
-                ((bitField0_ & 0x00000001) != 0),
-                getParentForChildren(),
-                isClean());
-        deviceInfo_ = null;
-      }
-      return deviceInfoBuilder_;
-    }
-
-    private java.util.List availableDeviceInfo_ =
-      java.util.Collections.emptyList();
-    private void ensureAvailableDeviceInfoIsMutable() {
-      if (!((bitField0_ & 0x00000002) != 0)) {
-        availableDeviceInfo_ = new java.util.ArrayList(availableDeviceInfo_);
-        bitField0_ |= 0x00000002;
-       }
-    }
-
-    private com.google.protobuf.RepeatedFieldBuilderV3<
-        org.tensorflow.proto.AvailableDeviceInfo, org.tensorflow.proto.AvailableDeviceInfo.Builder, org.tensorflow.proto.AvailableDeviceInfoOrBuilder> availableDeviceInfoBuilder_;
-
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public java.util.List getAvailableDeviceInfoList() {
-      if (availableDeviceInfoBuilder_ == null) {
-        return java.util.Collections.unmodifiableList(availableDeviceInfo_);
-      } else {
-        return availableDeviceInfoBuilder_.getMessageList();
-      }
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public int getAvailableDeviceInfoCount() {
-      if (availableDeviceInfoBuilder_ == null) {
-        return availableDeviceInfo_.size();
-      } else {
-        return availableDeviceInfoBuilder_.getCount();
-      }
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public org.tensorflow.proto.AvailableDeviceInfo getAvailableDeviceInfo(int index) {
-      if (availableDeviceInfoBuilder_ == null) {
-        return availableDeviceInfo_.get(index);
-      } else {
-        return availableDeviceInfoBuilder_.getMessage(index);
-      }
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public Builder setAvailableDeviceInfo(
-        int index, org.tensorflow.proto.AvailableDeviceInfo value) {
-      if (availableDeviceInfoBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        ensureAvailableDeviceInfoIsMutable();
-        availableDeviceInfo_.set(index, value);
-        onChanged();
-      } else {
-        availableDeviceInfoBuilder_.setMessage(index, value);
-      }
-      return this;
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public Builder setAvailableDeviceInfo(
-        int index, org.tensorflow.proto.AvailableDeviceInfo.Builder builderForValue) {
-      if (availableDeviceInfoBuilder_ == null) {
-        ensureAvailableDeviceInfoIsMutable();
-        availableDeviceInfo_.set(index, builderForValue.build());
-        onChanged();
-      } else {
-        availableDeviceInfoBuilder_.setMessage(index, builderForValue.build());
-      }
-      return this;
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public Builder addAvailableDeviceInfo(org.tensorflow.proto.AvailableDeviceInfo value) {
-      if (availableDeviceInfoBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        ensureAvailableDeviceInfoIsMutable();
-        availableDeviceInfo_.add(value);
-        onChanged();
-      } else {
-        availableDeviceInfoBuilder_.addMessage(value);
-      }
-      return this;
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public Builder addAvailableDeviceInfo(
-        int index, org.tensorflow.proto.AvailableDeviceInfo value) {
-      if (availableDeviceInfoBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        ensureAvailableDeviceInfoIsMutable();
-        availableDeviceInfo_.add(index, value);
-        onChanged();
-      } else {
-        availableDeviceInfoBuilder_.addMessage(index, value);
-      }
-      return this;
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public Builder addAvailableDeviceInfo(
-        org.tensorflow.proto.AvailableDeviceInfo.Builder builderForValue) {
-      if (availableDeviceInfoBuilder_ == null) {
-        ensureAvailableDeviceInfoIsMutable();
-        availableDeviceInfo_.add(builderForValue.build());
-        onChanged();
-      } else {
-        availableDeviceInfoBuilder_.addMessage(builderForValue.build());
-      }
-      return this;
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public Builder addAvailableDeviceInfo(
-        int index, org.tensorflow.proto.AvailableDeviceInfo.Builder builderForValue) {
-      if (availableDeviceInfoBuilder_ == null) {
-        ensureAvailableDeviceInfoIsMutable();
-        availableDeviceInfo_.add(index, builderForValue.build());
-        onChanged();
-      } else {
-        availableDeviceInfoBuilder_.addMessage(index, builderForValue.build());
-      }
-      return this;
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public Builder addAllAvailableDeviceInfo(
-        java.lang.Iterable values) {
-      if (availableDeviceInfoBuilder_ == null) {
-        ensureAvailableDeviceInfoIsMutable();
-        com.google.protobuf.AbstractMessageLite.Builder.addAll(
-            values, availableDeviceInfo_);
-        onChanged();
-      } else {
-        availableDeviceInfoBuilder_.addAllMessages(values);
-      }
-      return this;
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public Builder clearAvailableDeviceInfo() {
-      if (availableDeviceInfoBuilder_ == null) {
-        availableDeviceInfo_ = java.util.Collections.emptyList();
-        bitField0_ = (bitField0_ & ~0x00000002);
-        onChanged();
-      } else {
-        availableDeviceInfoBuilder_.clear();
-      }
-      return this;
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public Builder removeAvailableDeviceInfo(int index) {
-      if (availableDeviceInfoBuilder_ == null) {
-        ensureAvailableDeviceInfoIsMutable();
-        availableDeviceInfo_.remove(index);
-        onChanged();
-      } else {
-        availableDeviceInfoBuilder_.remove(index);
-      }
-      return this;
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public org.tensorflow.proto.AvailableDeviceInfo.Builder getAvailableDeviceInfoBuilder(
-        int index) {
-      return getAvailableDeviceInfoFieldBuilder().getBuilder(index);
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public org.tensorflow.proto.AvailableDeviceInfoOrBuilder getAvailableDeviceInfoOrBuilder(
-        int index) {
-      if (availableDeviceInfoBuilder_ == null) {
-        return availableDeviceInfo_.get(index);  } else {
-        return availableDeviceInfoBuilder_.getMessageOrBuilder(index);
-      }
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public java.util.List 
-         getAvailableDeviceInfoOrBuilderList() {
-      if (availableDeviceInfoBuilder_ != null) {
-        return availableDeviceInfoBuilder_.getMessageOrBuilderList();
-      } else {
-        return java.util.Collections.unmodifiableList(availableDeviceInfo_);
-      }
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public org.tensorflow.proto.AvailableDeviceInfo.Builder addAvailableDeviceInfoBuilder() {
-      return getAvailableDeviceInfoFieldBuilder().addBuilder(
-          org.tensorflow.proto.AvailableDeviceInfo.getDefaultInstance());
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public org.tensorflow.proto.AvailableDeviceInfo.Builder addAvailableDeviceInfoBuilder(
-        int index) {
-      return getAvailableDeviceInfoFieldBuilder().addBuilder(
-          index, org.tensorflow.proto.AvailableDeviceInfo.getDefaultInstance());
-    }
-    /**
-     * 
-     * Devices accessible to the test (e.g. as given by list_local_devices).
-     * 

-     *
-     * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-     */
-    public java.util.List 
-         getAvailableDeviceInfoBuilderList() {
-      return getAvailableDeviceInfoFieldBuilder().getBuilderList();
-    }
-    private com.google.protobuf.RepeatedFieldBuilderV3<
-        org.tensorflow.proto.AvailableDeviceInfo, org.tensorflow.proto.AvailableDeviceInfo.Builder, org.tensorflow.proto.AvailableDeviceInfoOrBuilder> 
-        getAvailableDeviceInfoFieldBuilder() {
-      if (availableDeviceInfoBuilder_ == null) {
-        availableDeviceInfoBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3<
-            org.tensorflow.proto.AvailableDeviceInfo, org.tensorflow.proto.AvailableDeviceInfo.Builder, org.tensorflow.proto.AvailableDeviceInfoOrBuilder>(
-                availableDeviceInfo_,
-                ((bitField0_ & 0x00000002) != 0),
-                getParentForChildren(),
-                isClean());
-        availableDeviceInfo_ = null;
-      }
-      return availableDeviceInfoBuilder_;
-    }
-
-    private org.tensorflow.proto.MemoryInfo memoryInfo_;
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.MemoryInfo, org.tensorflow.proto.MemoryInfo.Builder, org.tensorflow.proto.MemoryInfoOrBuilder> memoryInfoBuilder_;
-    /**
-     * .tensorflow.MemoryInfo memory_info = 6;
-     * @return Whether the memoryInfo field is set.
-     */
-    public boolean hasMemoryInfo() {
-      return memoryInfoBuilder_ != null || memoryInfo_ != null;
-    }
-    /**
-     * .tensorflow.MemoryInfo memory_info = 6;
-     * @return The memoryInfo.
-     */
-    public org.tensorflow.proto.MemoryInfo getMemoryInfo() {
-      if (memoryInfoBuilder_ == null) {
-        return memoryInfo_ == null ? org.tensorflow.proto.MemoryInfo.getDefaultInstance() : memoryInfo_;
-      } else {
-        return memoryInfoBuilder_.getMessage();
-      }
-    }
-    /**
-     * .tensorflow.MemoryInfo memory_info = 6;
-     */
-    public Builder setMemoryInfo(org.tensorflow.proto.MemoryInfo value) {
-      if (memoryInfoBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        memoryInfo_ = value;
-        onChanged();
-      } else {
-        memoryInfoBuilder_.setMessage(value);
-      }
-
-      return this;
-    }
-    /**
-     * .tensorflow.MemoryInfo memory_info = 6;
-     */
-    public Builder setMemoryInfo(
-        org.tensorflow.proto.MemoryInfo.Builder builderForValue) {
-      if (memoryInfoBuilder_ == null) {
-        memoryInfo_ = builderForValue.build();
-        onChanged();
-      } else {
-        memoryInfoBuilder_.setMessage(builderForValue.build());
-      }
-
-      return this;
-    }
-    /**
-     * .tensorflow.MemoryInfo memory_info = 6;
-     */
-    public Builder mergeMemoryInfo(org.tensorflow.proto.MemoryInfo value) {
-      if (memoryInfoBuilder_ == null) {
-        if (memoryInfo_ != null) {
-          memoryInfo_ =
-            org.tensorflow.proto.MemoryInfo.newBuilder(memoryInfo_).mergeFrom(value).buildPartial();
-        } else {
-          memoryInfo_ = value;
-        }
-        onChanged();
-      } else {
-        memoryInfoBuilder_.mergeFrom(value);
-      }
-
-      return this;
-    }
-    /**
-     * .tensorflow.MemoryInfo memory_info = 6;
-     */
-    public Builder clearMemoryInfo() {
-      if (memoryInfoBuilder_ == null) {
-        memoryInfo_ = null;
-        onChanged();
-      } else {
-        memoryInfo_ = null;
-        memoryInfoBuilder_ = null;
-      }
-
-      return this;
-    }
-    /**
-     * .tensorflow.MemoryInfo memory_info = 6;
-     */
-    public org.tensorflow.proto.MemoryInfo.Builder getMemoryInfoBuilder() {
-      
-      onChanged();
-      return getMemoryInfoFieldBuilder().getBuilder();
-    }
-    /**
-     * .tensorflow.MemoryInfo memory_info = 6;
-     */
-    public org.tensorflow.proto.MemoryInfoOrBuilder getMemoryInfoOrBuilder() {
-      if (memoryInfoBuilder_ != null) {
-        return memoryInfoBuilder_.getMessageOrBuilder();
-      } else {
-        return memoryInfo_ == null ?
-            org.tensorflow.proto.MemoryInfo.getDefaultInstance() : memoryInfo_;
-      }
-    }
-    /**
-     * .tensorflow.MemoryInfo memory_info = 6;
-     */
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.MemoryInfo, org.tensorflow.proto.MemoryInfo.Builder, org.tensorflow.proto.MemoryInfoOrBuilder> 
-        getMemoryInfoFieldBuilder() {
-      if (memoryInfoBuilder_ == null) {
-        memoryInfoBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
-            org.tensorflow.proto.MemoryInfo, org.tensorflow.proto.MemoryInfo.Builder, org.tensorflow.proto.MemoryInfoOrBuilder>(
-                getMemoryInfo(),
-                getParentForChildren(),
-                isClean());
-        memoryInfo_ = null;
-      }
-      return memoryInfoBuilder_;
-    }
-    @java.lang.Override
-    public final Builder setUnknownFields(
-        final com.google.protobuf.UnknownFieldSet unknownFields) {
-      return super.setUnknownFields(unknownFields);
-    }
-
-    @java.lang.Override
-    public final Builder mergeUnknownFields(
-        final com.google.protobuf.UnknownFieldSet unknownFields) {
-      return super.mergeUnknownFields(unknownFields);
-    }
-
-
-    // @@protoc_insertion_point(builder_scope:tensorflow.MachineConfiguration)
-  }
-
-  // @@protoc_insertion_point(class_scope:tensorflow.MachineConfiguration)
-  private static final org.tensorflow.proto.MachineConfiguration DEFAULT_INSTANCE;
-  static {
-    DEFAULT_INSTANCE = new org.tensorflow.proto.MachineConfiguration();
-  }
-
-  public static org.tensorflow.proto.MachineConfiguration getDefaultInstance() {
-    return DEFAULT_INSTANCE;
-  }
-
-  private static final com.google.protobuf.Parser
-      PARSER = new com.google.protobuf.AbstractParser() {
-    @java.lang.Override
-    public MachineConfiguration parsePartialFrom(
-        com.google.protobuf.CodedInputStream input,
-        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-        throws com.google.protobuf.InvalidProtocolBufferException {
-      Builder builder = newBuilder();
-      try {
-        builder.mergeFrom(input, extensionRegistry);
-      } catch (com.google.protobuf.InvalidProtocolBufferException e) {
-        throw e.setUnfinishedMessage(builder.buildPartial());
-      } catch (com.google.protobuf.UninitializedMessageException e) {
-        throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial());
-      } catch (java.io.IOException e) {
-        throw new com.google.protobuf.InvalidProtocolBufferException(e)
-            .setUnfinishedMessage(builder.buildPartial());
-      }
-      return builder.buildPartial();
-    }
-  };
-
-  public static com.google.protobuf.Parser parser() {
-    return PARSER;
-  }
-
-  @java.lang.Override
-  public com.google.protobuf.Parser getParserForType() {
-    return PARSER;
-  }
-
-  @java.lang.Override
-  public org.tensorflow.proto.MachineConfiguration getDefaultInstanceForType() {
-    return DEFAULT_INSTANCE;
-  }
-
-}
-
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MachineConfigurationOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MachineConfigurationOrBuilder.java
deleted file mode 100644
index 5821218bf8f..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MachineConfigurationOrBuilder.java
+++ /dev/null
@@ -1,206 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-public interface MachineConfigurationOrBuilder extends
-    // @@protoc_insertion_point(interface_extends:tensorflow.MachineConfiguration)
-    com.google.protobuf.MessageOrBuilder {
-
-  /**
-   * 
-   * Host name of machine that ran the benchmark.
-   * 

-   *
-   * string hostname = 1;
-   * @return The hostname.
-   */
-  java.lang.String getHostname();
-  /**
-   * 
-   * Host name of machine that ran the benchmark.
-   * 

-   *
-   * string hostname = 1;
-   * @return The bytes for hostname.
-   */
-  com.google.protobuf.ByteString
-      getHostnameBytes();
-
-  /**
-   * 
-   * Unique serial number of the machine.
-   * 

-   *
-   * string serial_identifier = 7;
-   * @return The serialIdentifier.
-   */
-  java.lang.String getSerialIdentifier();
-  /**
-   * 
-   * Unique serial number of the machine.
-   * 

-   *
-   * string serial_identifier = 7;
-   * @return The bytes for serialIdentifier.
-   */
-  com.google.protobuf.ByteString
-      getSerialIdentifierBytes();
-
-  /**
-   * 
-   * Additional platform information.
-   * 

-   *
-   * .tensorflow.PlatformInfo platform_info = 2;
-   * @return Whether the platformInfo field is set.
-   */
-  boolean hasPlatformInfo();
-  /**
-   * 
-   * Additional platform information.
-   * 

-   *
-   * .tensorflow.PlatformInfo platform_info = 2;
-   * @return The platformInfo.
-   */
-  org.tensorflow.proto.PlatformInfo getPlatformInfo();
-  /**
-   * 
-   * Additional platform information.
-   * 

-   *
-   * .tensorflow.PlatformInfo platform_info = 2;
-   */
-  org.tensorflow.proto.PlatformInfoOrBuilder getPlatformInfoOrBuilder();
-
-  /**
-   * 
-   * CPU Information.
-   * 

-   *
-   * .tensorflow.CPUInfo cpu_info = 3;
-   * @return Whether the cpuInfo field is set.
-   */
-  boolean hasCpuInfo();
-  /**
-   * 
-   * CPU Information.
-   * 

-   *
-   * .tensorflow.CPUInfo cpu_info = 3;
-   * @return The cpuInfo.
-   */
-  org.tensorflow.proto.CPUInfo getCpuInfo();
-  /**
-   * 
-   * CPU Information.
-   * 

-   *
-   * .tensorflow.CPUInfo cpu_info = 3;
-   */
-  org.tensorflow.proto.CPUInfoOrBuilder getCpuInfoOrBuilder();
-
-  /**
-   * 
-   * Other devices that are attached and relevant (e.g. GPUInfo).
-   * 

-   *
-   * repeated .google.protobuf.Any device_info = 4;
-   */
-  java.util.List 
-      getDeviceInfoList();
-  /**
-   * 
-   * Other devices that are attached and relevant (e.g. GPUInfo).
-   * 

-   *
-   * repeated .google.protobuf.Any device_info = 4;
-   */
-  com.google.protobuf.Any getDeviceInfo(int index);
-  /**
-   * 
-   * Other devices that are attached and relevant (e.g. GPUInfo).
-   * 

-   *
-   * repeated .google.protobuf.Any device_info = 4;
-   */
-  int getDeviceInfoCount();
-  /**
-   * 
-   * Other devices that are attached and relevant (e.g. GPUInfo).
-   * 

-   *
-   * repeated .google.protobuf.Any device_info = 4;
-   */
-  java.util.List 
-      getDeviceInfoOrBuilderList();
-  /**
-   * 
-   * Other devices that are attached and relevant (e.g. GPUInfo).
-   * 

-   *
-   * repeated .google.protobuf.Any device_info = 4;
-   */
-  com.google.protobuf.AnyOrBuilder getDeviceInfoOrBuilder(
-      int index);
-
-  /**
-   * 
-   * Devices accessible to the test (e.g. as given by list_local_devices).
-   * 

-   *
-   * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-   */
-  java.util.List 
-      getAvailableDeviceInfoList();
-  /**
-   * 
-   * Devices accessible to the test (e.g. as given by list_local_devices).
-   * 

-   *
-   * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-   */
-  org.tensorflow.proto.AvailableDeviceInfo getAvailableDeviceInfo(int index);
-  /**
-   * 
-   * Devices accessible to the test (e.g. as given by list_local_devices).
-   * 

-   *
-   * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-   */
-  int getAvailableDeviceInfoCount();
-  /**
-   * 
-   * Devices accessible to the test (e.g. as given by list_local_devices).
-   * 

-   *
-   * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-   */
-  java.util.List 
-      getAvailableDeviceInfoOrBuilderList();
-  /**
-   * 
-   * Devices accessible to the test (e.g. as given by list_local_devices).
-   * 

-   *
-   * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5;
-   */
-  org.tensorflow.proto.AvailableDeviceInfoOrBuilder getAvailableDeviceInfoOrBuilder(
-      int index);
-
-  /**
-   * .tensorflow.MemoryInfo memory_info = 6;
-   * @return Whether the memoryInfo field is set.
-   */
-  boolean hasMemoryInfo();
-  /**
-   * .tensorflow.MemoryInfo memory_info = 6;
-   * @return The memoryInfo.
-   */
-  org.tensorflow.proto.MemoryInfo getMemoryInfo();
-  /**
-   * .tensorflow.MemoryInfo memory_info = 6;
-   */
-  org.tensorflow.proto.MemoryInfoOrBuilder getMemoryInfoOrBuilder();
-}
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MemoryInfo.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MemoryInfo.java
deleted file mode 100644
index 8c4b5b692a6..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MemoryInfo.java
+++ /dev/null
@@ -1,563 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-/**
- * Protobuf type {@code tensorflow.MemoryInfo}
- */
-public final class MemoryInfo extends
-    com.google.protobuf.GeneratedMessageV3 implements
-    // @@protoc_insertion_point(message_implements:tensorflow.MemoryInfo)
-    MemoryInfoOrBuilder {
-private static final long serialVersionUID = 0L;
-  // Use MemoryInfo.newBuilder() to construct.
-  private MemoryInfo(com.google.protobuf.GeneratedMessageV3.Builder builder) {
-    super(builder);
-  }
-  private MemoryInfo() {
-  }
-
-  @java.lang.Override
-  @SuppressWarnings({"unused"})
-  protected java.lang.Object newInstance(
-      UnusedPrivateParameter unused) {
-    return new MemoryInfo();
-  }
-
-  @java.lang.Override
-  public final com.google.protobuf.UnknownFieldSet
-  getUnknownFields() {
-    return this.unknownFields;
-  }
-  public static final com.google.protobuf.Descriptors.Descriptor
-      getDescriptor() {
-    return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MemoryInfo_descriptor;
-  }
-
-  @java.lang.Override
-  protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
-      internalGetFieldAccessorTable() {
-    return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MemoryInfo_fieldAccessorTable
-        .ensureFieldAccessorsInitialized(
-            org.tensorflow.proto.MemoryInfo.class, org.tensorflow.proto.MemoryInfo.Builder.class);
-  }
-
-  public static final int TOTAL_FIELD_NUMBER = 1;
-  private long total_;
-  /**
-   * 
-   * Total virtual memory in bytes
-   * 

-   *
-   * int64 total = 1;
-   * @return The total.
-   */
-  @java.lang.Override
-  public long getTotal() {
-    return total_;
-  }
-
-  public static final int AVAILABLE_FIELD_NUMBER = 2;
-  private long available_;
-  /**
-   * 
-   * Immediately available memory in bytes
-   * 

-   *
-   * int64 available = 2;
-   * @return The available.
-   */
-  @java.lang.Override
-  public long getAvailable() {
-    return available_;
-  }
-
-  private byte memoizedIsInitialized = -1;
-  @java.lang.Override
-  public final boolean isInitialized() {
-    byte isInitialized = memoizedIsInitialized;
-    if (isInitialized == 1) return true;
-    if (isInitialized == 0) return false;
-
-    memoizedIsInitialized = 1;
-    return true;
-  }
-
-  @java.lang.Override
-  public void writeTo(com.google.protobuf.CodedOutputStream output)
-                      throws java.io.IOException {
-    if (total_ != 0L) {
-      output.writeInt64(1, total_);
-    }
-    if (available_ != 0L) {
-      output.writeInt64(2, available_);
-    }
-    getUnknownFields().writeTo(output);
-  }
-
-  @java.lang.Override
-  public int getSerializedSize() {
-    int size = memoizedSize;
-    if (size != -1) return size;
-
-    size = 0;
-    if (total_ != 0L) {
-      size += com.google.protobuf.CodedOutputStream
-        .computeInt64Size(1, total_);
-    }
-    if (available_ != 0L) {
-      size += com.google.protobuf.CodedOutputStream
-        .computeInt64Size(2, available_);
-    }
-    size += getUnknownFields().getSerializedSize();
-    memoizedSize = size;
-    return size;
-  }
-
-  @java.lang.Override
-  public boolean equals(final java.lang.Object obj) {
-    if (obj == this) {
-     return true;
-    }
-    if (!(obj instanceof org.tensorflow.proto.MemoryInfo)) {
-      return super.equals(obj);
-    }
-    org.tensorflow.proto.MemoryInfo other = (org.tensorflow.proto.MemoryInfo) obj;
-
-    if (getTotal()
-        != other.getTotal()) return false;
-    if (getAvailable()
-        != other.getAvailable()) return false;
-    if (!getUnknownFields().equals(other.getUnknownFields())) return false;
-    return true;
-  }
-
-  @java.lang.Override
-  public int hashCode() {
-    if (memoizedHashCode != 0) {
-      return memoizedHashCode;
-    }
-    int hash = 41;
-    hash = (19 * hash) + getDescriptor().hashCode();
-    hash = (37 * hash) + TOTAL_FIELD_NUMBER;
-    hash = (53 * hash) + com.google.protobuf.Internal.hashLong(
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-    hash = (37 * hash) + AVAILABLE_FIELD_NUMBER;
-    hash = (53 * hash) + com.google.protobuf.Internal.hashLong(
-        getAvailable());
-    hash = (29 * hash) + getUnknownFields().hashCode();
-    memoizedHashCode = hash;
-    return hash;
-  }
-
-  public static org.tensorflow.proto.MemoryInfo parseFrom(
-      java.nio.ByteBuffer data)
-      throws com.google.protobuf.InvalidProtocolBufferException {
-    return PARSER.parseFrom(data);
-  }
-  public static org.tensorflow.proto.MemoryInfo parseFrom(
-      java.nio.ByteBuffer data,
-      com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-      throws com.google.protobuf.InvalidProtocolBufferException {
-    return PARSER.parseFrom(data, extensionRegistry);
-  }
-  public static org.tensorflow.proto.MemoryInfo parseFrom(
-      com.google.protobuf.ByteString data)
-      throws com.google.protobuf.InvalidProtocolBufferException {
-    return PARSER.parseFrom(data);
-  }
-  public static org.tensorflow.proto.MemoryInfo parseFrom(
-      com.google.protobuf.ByteString data,
-      com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-      throws com.google.protobuf.InvalidProtocolBufferException {
-    return PARSER.parseFrom(data, extensionRegistry);
-  }
-  public static org.tensorflow.proto.MemoryInfo parseFrom(byte[] data)
-      throws com.google.protobuf.InvalidProtocolBufferException {
-    return PARSER.parseFrom(data);
-  }
-  public static org.tensorflow.proto.MemoryInfo parseFrom(
-      byte[] data,
-      com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-      throws com.google.protobuf.InvalidProtocolBufferException {
-    return PARSER.parseFrom(data, extensionRegistry);
-  }
-  public static org.tensorflow.proto.MemoryInfo parseFrom(java.io.InputStream input)
-      throws java.io.IOException {
-    return com.google.protobuf.GeneratedMessageV3
-        .parseWithIOException(PARSER, input);
-  }
-  public static org.tensorflow.proto.MemoryInfo parseFrom(
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-      com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-      throws java.io.IOException {
-    return com.google.protobuf.GeneratedMessageV3
-        .parseWithIOException(PARSER, input, extensionRegistry);
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-  public static org.tensorflow.proto.MemoryInfo parseDelimitedFrom(java.io.InputStream input)
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-    return com.google.protobuf.GeneratedMessageV3
-        .parseDelimitedWithIOException(PARSER, input);
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-  public static org.tensorflow.proto.MemoryInfo parseDelimitedFrom(
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-      com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-      throws java.io.IOException {
-    return com.google.protobuf.GeneratedMessageV3
-        .parseDelimitedWithIOException(PARSER, input, extensionRegistry);
-  }
-  public static org.tensorflow.proto.MemoryInfo parseFrom(
-      com.google.protobuf.CodedInputStream input)
-      throws java.io.IOException {
-    return com.google.protobuf.GeneratedMessageV3
-        .parseWithIOException(PARSER, input);
-  }
-  public static org.tensorflow.proto.MemoryInfo parseFrom(
-      com.google.protobuf.CodedInputStream input,
-      com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-      throws java.io.IOException {
-    return com.google.protobuf.GeneratedMessageV3
-        .parseWithIOException(PARSER, input, extensionRegistry);
-  }
-
-  @java.lang.Override
-  public Builder newBuilderForType() { return newBuilder(); }
-  public static Builder newBuilder() {
-    return DEFAULT_INSTANCE.toBuilder();
-  }
-  public static Builder newBuilder(org.tensorflow.proto.MemoryInfo prototype) {
-    return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype);
-  }
-  @java.lang.Override
-  public Builder toBuilder() {
-    return this == DEFAULT_INSTANCE
-        ? new Builder() : new Builder().mergeFrom(this);
-  }
-
-  @java.lang.Override
-  protected Builder newBuilderForType(
-      com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
-    Builder builder = new Builder(parent);
-    return builder;
-  }
-  /**
-   * Protobuf type {@code tensorflow.MemoryInfo}
-   */
-  public static final class Builder extends
-      com.google.protobuf.GeneratedMessageV3.Builder implements
-      // @@protoc_insertion_point(builder_implements:tensorflow.MemoryInfo)
-      org.tensorflow.proto.MemoryInfoOrBuilder {
-    public static final com.google.protobuf.Descriptors.Descriptor
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-
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-
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-          switch (tag) {
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-              done = true;
-              break;
-            case 8: {
-              total_ = input.readInt64();
-
-              break;
-            } // case 8
-            case 16: {
-              available_ = input.readInt64();
-
-              break;
-            } // case 16
-            default: {
-              if (!super.parseUnknownField(input, extensionRegistry, tag)) {
-                done = true; // was an endgroup tag
-              }
-              break;
-            } // default:
-          } // switch (tag)
-        } // while (!done)
-      } catch (com.google.protobuf.InvalidProtocolBufferException e) {
-        throw e.unwrapIOException();
-      } finally {
-        onChanged();
-      } // finally
-      return this;
-    }
-
-    private long total_ ;
-    /**
-     * 
-     * Total virtual memory in bytes
-     * 

-     *
-     * int64 total = 1;
-     * @return The total.
-     */
-    @java.lang.Override
-    public long getTotal() {
-      return total_;
-    }
-    /**
-     * 
-     * Total virtual memory in bytes
-     * 

-     *
-     * int64 total = 1;
-     * @param value The total to set.
-     * @return This builder for chaining.
-     */
-    public Builder setTotal(long value) {
-      
-      total_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * Total virtual memory in bytes
-     * 

-     *
-     * int64 total = 1;
-     * @return This builder for chaining.
-     */
-    public Builder clearTotal() {
-      
-      total_ = 0L;
-      onChanged();
-      return this;
-    }
-
-    private long available_ ;
-    /**
-     * 
-     * Immediately available memory in bytes
-     * 

-     *
-     * int64 available = 2;
-     * @return The available.
-     */
-    @java.lang.Override
-    public long getAvailable() {
-      return available_;
-    }
-    /**
-     * 
-     * Immediately available memory in bytes
-     * 

-     *
-     * int64 available = 2;
-     * @param value The available to set.
-     * @return This builder for chaining.
-     */
-    public Builder setAvailable(long value) {
-      
-      available_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * Immediately available memory in bytes
-     * 

-     *
-     * int64 available = 2;
-     * @return This builder for chaining.
-     */
-    public Builder clearAvailable() {
-      
-      available_ = 0L;
-      onChanged();
-      return this;
-    }
-    @java.lang.Override
-    public final Builder setUnknownFields(
-        final com.google.protobuf.UnknownFieldSet unknownFields) {
-      return super.setUnknownFields(unknownFields);
-    }
-
-    @java.lang.Override
-    public final Builder mergeUnknownFields(
-        final com.google.protobuf.UnknownFieldSet unknownFields) {
-      return super.mergeUnknownFields(unknownFields);
-    }
-
-
-    // @@protoc_insertion_point(builder_scope:tensorflow.MemoryInfo)
-  }
-
-  // @@protoc_insertion_point(class_scope:tensorflow.MemoryInfo)
-  private static final org.tensorflow.proto.MemoryInfo DEFAULT_INSTANCE;
-  static {
-    DEFAULT_INSTANCE = new org.tensorflow.proto.MemoryInfo();
-  }
-
-  public static org.tensorflow.proto.MemoryInfo getDefaultInstance() {
-    return DEFAULT_INSTANCE;
-  }
-
-  private static final com.google.protobuf.Parser
-      PARSER = new com.google.protobuf.AbstractParser() {
-    @java.lang.Override
-    public MemoryInfo parsePartialFrom(
-        com.google.protobuf.CodedInputStream input,
-        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-        throws com.google.protobuf.InvalidProtocolBufferException {
-      Builder builder = newBuilder();
-      try {
-        builder.mergeFrom(input, extensionRegistry);
-      } catch (com.google.protobuf.InvalidProtocolBufferException e) {
-        throw e.setUnfinishedMessage(builder.buildPartial());
-      } catch (com.google.protobuf.UninitializedMessageException e) {
-        throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial());
-      } catch (java.io.IOException e) {
-        throw new com.google.protobuf.InvalidProtocolBufferException(e)
-            .setUnfinishedMessage(builder.buildPartial());
-      }
-      return builder.buildPartial();
-    }
-  };
-
-  public static com.google.protobuf.Parser parser() {
-    return PARSER;
-  }
-
-  @java.lang.Override
-  public com.google.protobuf.Parser getParserForType() {
-    return PARSER;
-  }
-
-  @java.lang.Override
-  public org.tensorflow.proto.MemoryInfo getDefaultInstanceForType() {
-    return DEFAULT_INSTANCE;
-  }
-
-}
-
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MemoryInfoOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MemoryInfoOrBuilder.java
deleted file mode 100644
index 265206a7c19..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MemoryInfoOrBuilder.java
+++ /dev/null
@@ -1,29 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-public interface MemoryInfoOrBuilder extends
-    // @@protoc_insertion_point(interface_extends:tensorflow.MemoryInfo)
-    com.google.protobuf.MessageOrBuilder {
-
-  /**
-   * 
-   * Total virtual memory in bytes
-   * 

-   *
-   * int64 total = 1;
-   * @return The total.
-   */
-  long getTotal();
-
-  /**
-   * 
-   * Immediately available memory in bytes
-   * 

-   *
-   * int64 available = 2;
-   * @return The available.
-   */
-  long getAvailable();
-}
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MetricEntry.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MetricEntry.java
deleted file mode 100644
index 70a5e1ba8bc..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MetricEntry.java
+++ /dev/null
@@ -1,1108 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-/**
- * Protobuf type {@code tensorflow.MetricEntry}
- */
-public final class MetricEntry extends
-    com.google.protobuf.GeneratedMessageV3 implements
-    // @@protoc_insertion_point(message_implements:tensorflow.MetricEntry)
-    MetricEntryOrBuilder {
-private static final long serialVersionUID = 0L;
-  // Use MetricEntry.newBuilder() to construct.
-  private MetricEntry(com.google.protobuf.GeneratedMessageV3.Builder builder) {
-    super(builder);
-  }
-  private MetricEntry() {
-    name_ = "";
-  }
-
-  @java.lang.Override
-  @SuppressWarnings({"unused"})
-  protected java.lang.Object newInstance(
-      UnusedPrivateParameter unused) {
-    return new MetricEntry();
-  }
-
-  @java.lang.Override
-  public final com.google.protobuf.UnknownFieldSet
-  getUnknownFields() {
-    return this.unknownFields;
-  }
-  public static final com.google.protobuf.Descriptors.Descriptor
-      getDescriptor() {
-    return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MetricEntry_descriptor;
-  }
-
-  @java.lang.Override
-  protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
-      internalGetFieldAccessorTable() {
-    return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MetricEntry_fieldAccessorTable
-        .ensureFieldAccessorsInitialized(
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-  }
-
-  public static final int NAME_FIELD_NUMBER = 1;
-  private volatile java.lang.Object name_;
-  /**
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-   * Metric name
-   * 

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-   * @return The name.
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-  @java.lang.Override
-  public java.lang.String getName() {
-    java.lang.Object ref = name_;
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-      com.google.protobuf.ByteString bs = 
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-      java.lang.String s = bs.toStringUtf8();
-      name_ = s;
-      return s;
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-  }
-  /**
-   * 
-   * Metric name
-   * 

-   *
-   * string name = 1;
-   * @return The bytes for name.
-   */
-  @java.lang.Override
-  public com.google.protobuf.ByteString
-      getNameBytes() {
-    java.lang.Object ref = name_;
-    if (ref instanceof java.lang.String) {
-      com.google.protobuf.ByteString b = 
-          com.google.protobuf.ByteString.copyFromUtf8(
-              (java.lang.String) ref);
-      name_ = b;
-      return b;
-    } else {
-      return (com.google.protobuf.ByteString) ref;
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-  }
-
-  public static final int VALUE_FIELD_NUMBER = 2;
-  private double value_;
-  /**
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-   * Metric value
-   * 

-   *
-   * double value = 2;
-   * @return The value.
-   */
-  @java.lang.Override
-  public double getValue() {
-    return value_;
-  }
-
-  public static final int MIN_VALUE_FIELD_NUMBER = 3;
-  private com.google.protobuf.DoubleValue minValue_;
-  /**
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-   * The minimum acceptable value for the metric if specified
-   * 

-   *
-   * .google.protobuf.DoubleValue min_value = 3;
-   * @return Whether the minValue field is set.
-   */
-  @java.lang.Override
-  public boolean hasMinValue() {
-    return minValue_ != null;
-  }
-  /**
-   * 
-   * The minimum acceptable value for the metric if specified
-   * 

-   *
-   * .google.protobuf.DoubleValue min_value = 3;
-   * @return The minValue.
-   */
-  @java.lang.Override
-  public com.google.protobuf.DoubleValue getMinValue() {
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-  @java.lang.Override
-  public com.google.protobuf.DoubleValueOrBuilder getMinValueOrBuilder() {
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-
-  public static final int MAX_VALUE_FIELD_NUMBER = 4;
-  private com.google.protobuf.DoubleValue maxValue_;
-  /**
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-   * The maximum acceptable value for the metric if specified
-   * 

-   *
-   * .google.protobuf.DoubleValue max_value = 4;
-   * @return Whether the maxValue field is set.
-   */
-  @java.lang.Override
-  public boolean hasMaxValue() {
-    return maxValue_ != null;
-  }
-  /**
-   * 
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-   * 

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-   * .google.protobuf.DoubleValue max_value = 4;
-   * @return The maxValue.
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-  @java.lang.Override
-  public com.google.protobuf.DoubleValue getMaxValue() {
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-  /**
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-   * 

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-  @java.lang.Override
-  public com.google.protobuf.DoubleValueOrBuilder getMaxValueOrBuilder() {
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-    if (java.lang.Double.doubleToRawLongBits(value_) != 0) {
-      output.writeDouble(2, value_);
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-      output.writeMessage(3, getMinValue());
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-    if (maxValue_ != null) {
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-    getUnknownFields().writeTo(output);
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-
-  @java.lang.Override
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-    int size = memoizedSize;
-    if (size != -1) return size;
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-    memoizedSize = size;
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-  public boolean equals(final java.lang.Object obj) {
-    if (obj == this) {
-     return true;
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-    if (!(obj instanceof org.tensorflow.proto.MetricEntry)) {
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-    }
-    org.tensorflow.proto.MetricEntry other = (org.tensorflow.proto.MetricEntry) obj;
-
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-    if (java.lang.Double.doubleToLongBits(getValue())
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-    if (hasMaxValue() != other.hasMaxValue()) return false;
-    if (hasMaxValue()) {
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-    return true;
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-  public int hashCode() {
-    if (memoizedHashCode != 0) {
-      return memoizedHashCode;
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-    int hash = 41;
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-  public static org.tensorflow.proto.MetricEntry parseFrom(
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-    return com.google.protobuf.GeneratedMessageV3
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-      com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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-
-  @java.lang.Override
-  public Builder newBuilderForType() { return newBuilder(); }
-  public static Builder newBuilder() {
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-  public static Builder newBuilder(org.tensorflow.proto.MetricEntry prototype) {
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-  @java.lang.Override
-  public Builder toBuilder() {
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-  /**
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-        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-        throws java.io.IOException {
-      if (extensionRegistry == null) {
-        throw new java.lang.NullPointerException();
-      }
-      try {
-        boolean done = false;
-        while (!done) {
-          int tag = input.readTag();
-          switch (tag) {
-            case 0:
-              done = true;
-              break;
-            case 10: {
-              name_ = input.readStringRequireUtf8();
-
-              break;
-            } // case 10
-            case 17: {
-              value_ = input.readDouble();
-
-              break;
-            } // case 17
-            case 26: {
-              input.readMessage(
-                  getMinValueFieldBuilder().getBuilder(),
-                  extensionRegistry);
-
-              break;
-            } // case 26
-            case 34: {
-              input.readMessage(
-                  getMaxValueFieldBuilder().getBuilder(),
-                  extensionRegistry);
-
-              break;
-            } // case 34
-            default: {
-              if (!super.parseUnknownField(input, extensionRegistry, tag)) {
-                done = true; // was an endgroup tag
-              }
-              break;
-            } // default:
-          } // switch (tag)
-        } // while (!done)
-      } catch (com.google.protobuf.InvalidProtocolBufferException e) {
-        throw e.unwrapIOException();
-      } finally {
-        onChanged();
-      } // finally
-      return this;
-    }
-
-    private java.lang.Object name_ = "";
-    /**
-     * 
-     * Metric name
-     * 

-     *
-     * string name = 1;
-     * @return The name.
-     */
-    public java.lang.String getName() {
-      java.lang.Object ref = name_;
-      if (!(ref instanceof java.lang.String)) {
-        com.google.protobuf.ByteString bs =
-            (com.google.protobuf.ByteString) ref;
-        java.lang.String s = bs.toStringUtf8();
-        name_ = s;
-        return s;
-      } else {
-        return (java.lang.String) ref;
-      }
-    }
-    /**
-     * 
-     * Metric name
-     * 

-     *
-     * string name = 1;
-     * @return The bytes for name.
-     */
-    public com.google.protobuf.ByteString
-        getNameBytes() {
-      java.lang.Object ref = name_;
-      if (ref instanceof String) {
-        com.google.protobuf.ByteString b = 
-            com.google.protobuf.ByteString.copyFromUtf8(
-                (java.lang.String) ref);
-        name_ = b;
-        return b;
-      } else {
-        return (com.google.protobuf.ByteString) ref;
-      }
-    }
-    /**
-     * 
-     * Metric name
-     * 

-     *
-     * string name = 1;
-     * @param value The name to set.
-     * @return This builder for chaining.
-     */
-    public Builder setName(
-        java.lang.String value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  
-      name_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * Metric name
-     * 

-     *
-     * string name = 1;
-     * @return This builder for chaining.
-     */
-    public Builder clearName() {
-      
-      name_ = getDefaultInstance().getName();
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * Metric name
-     * 

-     *
-     * string name = 1;
-     * @param value The bytes for name to set.
-     * @return This builder for chaining.
-     */
-    public Builder setNameBytes(
-        com.google.protobuf.ByteString value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  checkByteStringIsUtf8(value);
-      
-      name_ = value;
-      onChanged();
-      return this;
-    }
-
-    private double value_ ;
-    /**
-     * 
-     * Metric value
-     * 

-     *
-     * double value = 2;
-     * @return The value.
-     */
-    @java.lang.Override
-    public double getValue() {
-      return value_;
-    }
-    /**
-     * 
-     * Metric value
-     * 

-     *
-     * double value = 2;
-     * @param value The value to set.
-     * @return This builder for chaining.
-     */
-    public Builder setValue(double value) {
-      
-      value_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * Metric value
-     * 

-     *
-     * double value = 2;
-     * @return This builder for chaining.
-     */
-    public Builder clearValue() {
-      
-      value_ = 0D;
-      onChanged();
-      return this;
-    }
-
-    private com.google.protobuf.DoubleValue minValue_;
-    private com.google.protobuf.SingleFieldBuilderV3<
-        com.google.protobuf.DoubleValue, com.google.protobuf.DoubleValue.Builder, com.google.protobuf.DoubleValueOrBuilder> minValueBuilder_;
-    /**
-     * 
-     * The minimum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue min_value = 3;
-     * @return Whether the minValue field is set.
-     */
-    public boolean hasMinValue() {
-      return minValueBuilder_ != null || minValue_ != null;
-    }
-    /**
-     * 
-     * The minimum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue min_value = 3;
-     * @return The minValue.
-     */
-    public com.google.protobuf.DoubleValue getMinValue() {
-      if (minValueBuilder_ == null) {
-        return minValue_ == null ? com.google.protobuf.DoubleValue.getDefaultInstance() : minValue_;
-      } else {
-        return minValueBuilder_.getMessage();
-      }
-    }
-    /**
-     * 
-     * The minimum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue min_value = 3;
-     */
-    public Builder setMinValue(com.google.protobuf.DoubleValue value) {
-      if (minValueBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        minValue_ = value;
-        onChanged();
-      } else {
-        minValueBuilder_.setMessage(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The minimum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue min_value = 3;
-     */
-    public Builder setMinValue(
-        com.google.protobuf.DoubleValue.Builder builderForValue) {
-      if (minValueBuilder_ == null) {
-        minValue_ = builderForValue.build();
-        onChanged();
-      } else {
-        minValueBuilder_.setMessage(builderForValue.build());
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The minimum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue min_value = 3;
-     */
-    public Builder mergeMinValue(com.google.protobuf.DoubleValue value) {
-      if (minValueBuilder_ == null) {
-        if (minValue_ != null) {
-          minValue_ =
-            com.google.protobuf.DoubleValue.newBuilder(minValue_).mergeFrom(value).buildPartial();
-        } else {
-          minValue_ = value;
-        }
-        onChanged();
-      } else {
-        minValueBuilder_.mergeFrom(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The minimum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue min_value = 3;
-     */
-    public Builder clearMinValue() {
-      if (minValueBuilder_ == null) {
-        minValue_ = null;
-        onChanged();
-      } else {
-        minValue_ = null;
-        minValueBuilder_ = null;
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The minimum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue min_value = 3;
-     */
-    public com.google.protobuf.DoubleValue.Builder getMinValueBuilder() {
-      
-      onChanged();
-      return getMinValueFieldBuilder().getBuilder();
-    }
-    /**
-     * 
-     * The minimum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue min_value = 3;
-     */
-    public com.google.protobuf.DoubleValueOrBuilder getMinValueOrBuilder() {
-      if (minValueBuilder_ != null) {
-        return minValueBuilder_.getMessageOrBuilder();
-      } else {
-        return minValue_ == null ?
-            com.google.protobuf.DoubleValue.getDefaultInstance() : minValue_;
-      }
-    }
-    /**
-     * 
-     * The minimum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue min_value = 3;
-     */
-    private com.google.protobuf.SingleFieldBuilderV3<
-        com.google.protobuf.DoubleValue, com.google.protobuf.DoubleValue.Builder, com.google.protobuf.DoubleValueOrBuilder> 
-        getMinValueFieldBuilder() {
-      if (minValueBuilder_ == null) {
-        minValueBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
-            com.google.protobuf.DoubleValue, com.google.protobuf.DoubleValue.Builder, com.google.protobuf.DoubleValueOrBuilder>(
-                getMinValue(),
-                getParentForChildren(),
-                isClean());
-        minValue_ = null;
-      }
-      return minValueBuilder_;
-    }
-
-    private com.google.protobuf.DoubleValue maxValue_;
-    private com.google.protobuf.SingleFieldBuilderV3<
-        com.google.protobuf.DoubleValue, com.google.protobuf.DoubleValue.Builder, com.google.protobuf.DoubleValueOrBuilder> maxValueBuilder_;
-    /**
-     * 
-     * The maximum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue max_value = 4;
-     * @return Whether the maxValue field is set.
-     */
-    public boolean hasMaxValue() {
-      return maxValueBuilder_ != null || maxValue_ != null;
-    }
-    /**
-     * 
-     * The maximum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue max_value = 4;
-     * @return The maxValue.
-     */
-    public com.google.protobuf.DoubleValue getMaxValue() {
-      if (maxValueBuilder_ == null) {
-        return maxValue_ == null ? com.google.protobuf.DoubleValue.getDefaultInstance() : maxValue_;
-      } else {
-        return maxValueBuilder_.getMessage();
-      }
-    }
-    /**
-     * 
-     * The maximum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue max_value = 4;
-     */
-    public Builder setMaxValue(com.google.protobuf.DoubleValue value) {
-      if (maxValueBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        maxValue_ = value;
-        onChanged();
-      } else {
-        maxValueBuilder_.setMessage(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The maximum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue max_value = 4;
-     */
-    public Builder setMaxValue(
-        com.google.protobuf.DoubleValue.Builder builderForValue) {
-      if (maxValueBuilder_ == null) {
-        maxValue_ = builderForValue.build();
-        onChanged();
-      } else {
-        maxValueBuilder_.setMessage(builderForValue.build());
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The maximum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue max_value = 4;
-     */
-    public Builder mergeMaxValue(com.google.protobuf.DoubleValue value) {
-      if (maxValueBuilder_ == null) {
-        if (maxValue_ != null) {
-          maxValue_ =
-            com.google.protobuf.DoubleValue.newBuilder(maxValue_).mergeFrom(value).buildPartial();
-        } else {
-          maxValue_ = value;
-        }
-        onChanged();
-      } else {
-        maxValueBuilder_.mergeFrom(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The maximum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue max_value = 4;
-     */
-    public Builder clearMaxValue() {
-      if (maxValueBuilder_ == null) {
-        maxValue_ = null;
-        onChanged();
-      } else {
-        maxValue_ = null;
-        maxValueBuilder_ = null;
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The maximum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue max_value = 4;
-     */
-    public com.google.protobuf.DoubleValue.Builder getMaxValueBuilder() {
-      
-      onChanged();
-      return getMaxValueFieldBuilder().getBuilder();
-    }
-    /**
-     * 
-     * The maximum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue max_value = 4;
-     */
-    public com.google.protobuf.DoubleValueOrBuilder getMaxValueOrBuilder() {
-      if (maxValueBuilder_ != null) {
-        return maxValueBuilder_.getMessageOrBuilder();
-      } else {
-        return maxValue_ == null ?
-            com.google.protobuf.DoubleValue.getDefaultInstance() : maxValue_;
-      }
-    }
-    /**
-     * 
-     * The maximum acceptable value for the metric if specified
-     * 

-     *
-     * .google.protobuf.DoubleValue max_value = 4;
-     */
-    private com.google.protobuf.SingleFieldBuilderV3<
-        com.google.protobuf.DoubleValue, com.google.protobuf.DoubleValue.Builder, com.google.protobuf.DoubleValueOrBuilder> 
-        getMaxValueFieldBuilder() {
-      if (maxValueBuilder_ == null) {
-        maxValueBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
-            com.google.protobuf.DoubleValue, com.google.protobuf.DoubleValue.Builder, com.google.protobuf.DoubleValueOrBuilder>(
-                getMaxValue(),
-                getParentForChildren(),
-                isClean());
-        maxValue_ = null;
-      }
-      return maxValueBuilder_;
-    }
-    @java.lang.Override
-    public final Builder setUnknownFields(
-        final com.google.protobuf.UnknownFieldSet unknownFields) {
-      return super.setUnknownFields(unknownFields);
-    }
-
-    @java.lang.Override
-    public final Builder mergeUnknownFields(
-        final com.google.protobuf.UnknownFieldSet unknownFields) {
-      return super.mergeUnknownFields(unknownFields);
-    }
-
-
-    // @@protoc_insertion_point(builder_scope:tensorflow.MetricEntry)
-  }
-
-  // @@protoc_insertion_point(class_scope:tensorflow.MetricEntry)
-  private static final org.tensorflow.proto.MetricEntry DEFAULT_INSTANCE;
-  static {
-    DEFAULT_INSTANCE = new org.tensorflow.proto.MetricEntry();
-  }
-
-  public static org.tensorflow.proto.MetricEntry getDefaultInstance() {
-    return DEFAULT_INSTANCE;
-  }
-
-  private static final com.google.protobuf.Parser
-      PARSER = new com.google.protobuf.AbstractParser() {
-    @java.lang.Override
-    public MetricEntry parsePartialFrom(
-        com.google.protobuf.CodedInputStream input,
-        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-        throws com.google.protobuf.InvalidProtocolBufferException {
-      Builder builder = newBuilder();
-      try {
-        builder.mergeFrom(input, extensionRegistry);
-      } catch (com.google.protobuf.InvalidProtocolBufferException e) {
-        throw e.setUnfinishedMessage(builder.buildPartial());
-      } catch (com.google.protobuf.UninitializedMessageException e) {
-        throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial());
-      } catch (java.io.IOException e) {
-        throw new com.google.protobuf.InvalidProtocolBufferException(e)
-            .setUnfinishedMessage(builder.buildPartial());
-      }
-      return builder.buildPartial();
-    }
-  };
-
-  public static com.google.protobuf.Parser parser() {
-    return PARSER;
-  }
-
-  @java.lang.Override
-  public com.google.protobuf.Parser getParserForType() {
-    return PARSER;
-  }
-
-  @java.lang.Override
-  public org.tensorflow.proto.MetricEntry getDefaultInstanceForType() {
-    return DEFAULT_INSTANCE;
-  }
-
-}
-
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MetricEntryOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MetricEntryOrBuilder.java
deleted file mode 100644
index 9898de2810f..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MetricEntryOrBuilder.java
+++ /dev/null
@@ -1,93 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-public interface MetricEntryOrBuilder extends
-    // @@protoc_insertion_point(interface_extends:tensorflow.MetricEntry)
-    com.google.protobuf.MessageOrBuilder {
-
-  /**
-   * 
-   * Metric name
-   * 

-   *
-   * string name = 1;
-   * @return The name.
-   */
-  java.lang.String getName();
-  /**
-   * 
-   * Metric name
-   * 

-   *
-   * string name = 1;
-   * @return The bytes for name.
-   */
-  com.google.protobuf.ByteString
-      getNameBytes();
-
-  /**
-   * 
-   * Metric value
-   * 

-   *
-   * double value = 2;
-   * @return The value.
-   */
-  double getValue();
-
-  /**
-   * 
-   * The minimum acceptable value for the metric if specified
-   * 

-   *
-   * .google.protobuf.DoubleValue min_value = 3;
-   * @return Whether the minValue field is set.
-   */
-  boolean hasMinValue();
-  /**
-   * 
-   * The minimum acceptable value for the metric if specified
-   * 

-   *
-   * .google.protobuf.DoubleValue min_value = 3;
-   * @return The minValue.
-   */
-  com.google.protobuf.DoubleValue getMinValue();
-  /**
-   * 
-   * The minimum acceptable value for the metric if specified
-   * 

-   *
-   * .google.protobuf.DoubleValue min_value = 3;
-   */
-  com.google.protobuf.DoubleValueOrBuilder getMinValueOrBuilder();
-
-  /**
-   * 
-   * The maximum acceptable value for the metric if specified
-   * 

-   *
-   * .google.protobuf.DoubleValue max_value = 4;
-   * @return Whether the maxValue field is set.
-   */
-  boolean hasMaxValue();
-  /**
-   * 
-   * The maximum acceptable value for the metric if specified
-   * 

-   *
-   * .google.protobuf.DoubleValue max_value = 4;
-   * @return The maxValue.
-   */
-  com.google.protobuf.DoubleValue getMaxValue();
-  /**
-   * 
-   * The maximum acceptable value for the metric if specified
-   * 

-   *
-   * .google.protobuf.DoubleValue max_value = 4;
-   */
-  com.google.protobuf.DoubleValueOrBuilder getMaxValueOrBuilder();
-}
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/PlatformInfo.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/PlatformInfo.java
deleted file mode 100644
index 782524cf4d4..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/PlatformInfo.java
+++ /dev/null
@@ -1,1391 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-/**
- * Protobuf type {@code tensorflow.PlatformInfo}
- */
-public final class PlatformInfo extends
-    com.google.protobuf.GeneratedMessageV3 implements
-    // @@protoc_insertion_point(message_implements:tensorflow.PlatformInfo)
-    PlatformInfoOrBuilder {
-private static final long serialVersionUID = 0L;
-  // Use PlatformInfo.newBuilder() to construct.
-  private PlatformInfo(com.google.protobuf.GeneratedMessageV3.Builder builder) {
-    super(builder);
-  }
-  private PlatformInfo() {
-    bits_ = "";
-    linkage_ = "";
-    machine_ = "";
-    release_ = "";
-    system_ = "";
-    version_ = "";
-  }
-
-  @java.lang.Override
-  @SuppressWarnings({"unused"})
-  protected java.lang.Object newInstance(
-      UnusedPrivateParameter unused) {
-    return new PlatformInfo();
-  }
-
-  @java.lang.Override
-  public final com.google.protobuf.UnknownFieldSet
-  getUnknownFields() {
-    return this.unknownFields;
-  }
-  public static final com.google.protobuf.Descriptors.Descriptor
-      getDescriptor() {
-    return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_PlatformInfo_descriptor;
-  }
-
-  @java.lang.Override
-  protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
-      internalGetFieldAccessorTable() {
-    return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_PlatformInfo_fieldAccessorTable
-        .ensureFieldAccessorsInitialized(
-            org.tensorflow.proto.PlatformInfo.class, org.tensorflow.proto.PlatformInfo.Builder.class);
-  }
-
-  public static final int BITS_FIELD_NUMBER = 1;
-  private volatile java.lang.Object bits_;
-  /**
-   * 
-   * e.g. '64bit'
-   * 

-   *
-   * string bits = 1;
-   * @return The bits.
-   */
-  @java.lang.Override
-  public java.lang.String getBits() {
-    java.lang.Object ref = bits_;
-    if (ref instanceof java.lang.String) {
-      return (java.lang.String) ref;
-    } else {
-      com.google.protobuf.ByteString bs = 
-          (com.google.protobuf.ByteString) ref;
-      java.lang.String s = bs.toStringUtf8();
-      bits_ = s;
-      return s;
-    }
-  }
-  /**
-   * 
-   * e.g. '64bit'
-   * 

-   *
-   * string bits = 1;
-   * @return The bytes for bits.
-   */
-  @java.lang.Override
-  public com.google.protobuf.ByteString
-      getBitsBytes() {
-    java.lang.Object ref = bits_;
-    if (ref instanceof java.lang.String) {
-      com.google.protobuf.ByteString b = 
-          com.google.protobuf.ByteString.copyFromUtf8(
-              (java.lang.String) ref);
-      bits_ = b;
-      return b;
-    } else {
-      return (com.google.protobuf.ByteString) ref;
-    }
-  }
-
-  public static final int LINKAGE_FIELD_NUMBER = 2;
-  private volatile java.lang.Object linkage_;
-  /**
-   * 
-   * e.g. 'ELF'
-   * 

-   *
-   * string linkage = 2;
-   * @return The linkage.
-   */
-  @java.lang.Override
-  public java.lang.String getLinkage() {
-    java.lang.Object ref = linkage_;
-    if (ref instanceof java.lang.String) {
-      return (java.lang.String) ref;
-    } else {
-      com.google.protobuf.ByteString bs = 
-          (com.google.protobuf.ByteString) ref;
-      java.lang.String s = bs.toStringUtf8();
-      linkage_ = s;
-      return s;
-    }
-  }
-  /**
-   * 
-   * e.g. 'ELF'
-   * 

-   *
-   * string linkage = 2;
-   * @return The bytes for linkage.
-   */
-  @java.lang.Override
-  public com.google.protobuf.ByteString
-      getLinkageBytes() {
-    java.lang.Object ref = linkage_;
-    if (ref instanceof java.lang.String) {
-      com.google.protobuf.ByteString b = 
-          com.google.protobuf.ByteString.copyFromUtf8(
-              (java.lang.String) ref);
-      linkage_ = b;
-      return b;
-    } else {
-      return (com.google.protobuf.ByteString) ref;
-    }
-  }
-
-  public static final int MACHINE_FIELD_NUMBER = 3;
-  private volatile java.lang.Object machine_;
-  /**
-   * 
-   * e.g. 'i386'
-   * 

-   *
-   * string machine = 3;
-   * @return The machine.
-   */
-  @java.lang.Override
-  public java.lang.String getMachine() {
-    java.lang.Object ref = machine_;
-    if (ref instanceof java.lang.String) {
-      return (java.lang.String) ref;
-    } else {
-      com.google.protobuf.ByteString bs = 
-          (com.google.protobuf.ByteString) ref;
-      java.lang.String s = bs.toStringUtf8();
-      machine_ = s;
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-     *
-     * string linkage = 2;
-     * @param value The bytes for linkage to set.
-     * @return This builder for chaining.
-     */
-    public Builder setLinkageBytes(
-        com.google.protobuf.ByteString value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  checkByteStringIsUtf8(value);
-      
-      linkage_ = value;
-      onChanged();
-      return this;
-    }
-
-    private java.lang.Object machine_ = "";
-    /**
-     * 
-     * e.g. 'i386'
-     * 

-     *
-     * string machine = 3;
-     * @return The machine.
-     */
-    public java.lang.String getMachine() {
-      java.lang.Object ref = machine_;
-      if (!(ref instanceof java.lang.String)) {
-        com.google.protobuf.ByteString bs =
-            (com.google.protobuf.ByteString) ref;
-        java.lang.String s = bs.toStringUtf8();
-        machine_ = s;
-        return s;
-      } else {
-        return (java.lang.String) ref;
-      }
-    }
-    /**
-     * 
-     * e.g. 'i386'
-     * 

-     *
-     * string machine = 3;
-     * @return The bytes for machine.
-     */
-    public com.google.protobuf.ByteString
-        getMachineBytes() {
-      java.lang.Object ref = machine_;
-      if (ref instanceof String) {
-        com.google.protobuf.ByteString b = 
-            com.google.protobuf.ByteString.copyFromUtf8(
-                (java.lang.String) ref);
-        machine_ = b;
-        return b;
-      } else {
-        return (com.google.protobuf.ByteString) ref;
-      }
-    }
-    /**
-     * 
-     * e.g. 'i386'
-     * 

-     *
-     * string machine = 3;
-     * @param value The machine to set.
-     * @return This builder for chaining.
-     */
-    public Builder setMachine(
-        java.lang.String value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  
-      machine_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * e.g. 'i386'
-     * 

-     *
-     * string machine = 3;
-     * @return This builder for chaining.
-     */
-    public Builder clearMachine() {
-      
-      machine_ = getDefaultInstance().getMachine();
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * e.g. 'i386'
-     * 

-     *
-     * string machine = 3;
-     * @param value The bytes for machine to set.
-     * @return This builder for chaining.
-     */
-    public Builder setMachineBytes(
-        com.google.protobuf.ByteString value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  checkByteStringIsUtf8(value);
-      
-      machine_ = value;
-      onChanged();
-      return this;
-    }
-
-    private java.lang.Object release_ = "";
-    /**
-     * 
-     * e.g. '3.13.0-76-generic'
-     * 

-     *
-     * string release = 4;
-     * @return The release.
-     */
-    public java.lang.String getRelease() {
-      java.lang.Object ref = release_;
-      if (!(ref instanceof java.lang.String)) {
-        com.google.protobuf.ByteString bs =
-            (com.google.protobuf.ByteString) ref;
-        java.lang.String s = bs.toStringUtf8();
-        release_ = s;
-        return s;
-      } else {
-        return (java.lang.String) ref;
-      }
-    }
-    /**
-     * 
-     * e.g. '3.13.0-76-generic'
-     * 

-     *
-     * string release = 4;
-     * @return The bytes for release.
-     */
-    public com.google.protobuf.ByteString
-        getReleaseBytes() {
-      java.lang.Object ref = release_;
-      if (ref instanceof String) {
-        com.google.protobuf.ByteString b = 
-            com.google.protobuf.ByteString.copyFromUtf8(
-                (java.lang.String) ref);
-        release_ = b;
-        return b;
-      } else {
-        return (com.google.protobuf.ByteString) ref;
-      }
-    }
-    /**
-     * 
-     * e.g. '3.13.0-76-generic'
-     * 

-     *
-     * string release = 4;
-     * @param value The release to set.
-     * @return This builder for chaining.
-     */
-    public Builder setRelease(
-        java.lang.String value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  
-      release_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * e.g. '3.13.0-76-generic'
-     * 

-     *
-     * string release = 4;
-     * @return This builder for chaining.
-     */
-    public Builder clearRelease() {
-      
-      release_ = getDefaultInstance().getRelease();
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * e.g. '3.13.0-76-generic'
-     * 

-     *
-     * string release = 4;
-     * @param value The bytes for release to set.
-     * @return This builder for chaining.
-     */
-    public Builder setReleaseBytes(
-        com.google.protobuf.ByteString value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  checkByteStringIsUtf8(value);
-      
-      release_ = value;
-      onChanged();
-      return this;
-    }
-
-    private java.lang.Object system_ = "";
-    /**
-     * 
-     * e.g. 'Linux'
-     * 

-     *
-     * string system = 5;
-     * @return The system.
-     */
-    public java.lang.String getSystem() {
-      java.lang.Object ref = system_;
-      if (!(ref instanceof java.lang.String)) {
-        com.google.protobuf.ByteString bs =
-            (com.google.protobuf.ByteString) ref;
-        java.lang.String s = bs.toStringUtf8();
-        system_ = s;
-        return s;
-      } else {
-        return (java.lang.String) ref;
-      }
-    }
-    /**
-     * 
-     * e.g. 'Linux'
-     * 

-     *
-     * string system = 5;
-     * @return The bytes for system.
-     */
-    public com.google.protobuf.ByteString
-        getSystemBytes() {
-      java.lang.Object ref = system_;
-      if (ref instanceof String) {
-        com.google.protobuf.ByteString b = 
-            com.google.protobuf.ByteString.copyFromUtf8(
-                (java.lang.String) ref);
-        system_ = b;
-        return b;
-      } else {
-        return (com.google.protobuf.ByteString) ref;
-      }
-    }
-    /**
-     * 
-     * e.g. 'Linux'
-     * 

-     *
-     * string system = 5;
-     * @param value The system to set.
-     * @return This builder for chaining.
-     */
-    public Builder setSystem(
-        java.lang.String value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  
-      system_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * e.g. 'Linux'
-     * 

-     *
-     * string system = 5;
-     * @return This builder for chaining.
-     */
-    public Builder clearSystem() {
-      
-      system_ = getDefaultInstance().getSystem();
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * e.g. 'Linux'
-     * 

-     *
-     * string system = 5;
-     * @param value The bytes for system to set.
-     * @return This builder for chaining.
-     */
-    public Builder setSystemBytes(
-        com.google.protobuf.ByteString value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  checkByteStringIsUtf8(value);
-      
-      system_ = value;
-      onChanged();
-      return this;
-    }
-
-    private java.lang.Object version_ = "";
-    /**
-     * 
-     * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
-     * 

-     *
-     * string version = 6;
-     * @return The version.
-     */
-    public java.lang.String getVersion() {
-      java.lang.Object ref = version_;
-      if (!(ref instanceof java.lang.String)) {
-        com.google.protobuf.ByteString bs =
-            (com.google.protobuf.ByteString) ref;
-        java.lang.String s = bs.toStringUtf8();
-        version_ = s;
-        return s;
-      } else {
-        return (java.lang.String) ref;
-      }
-    }
-    /**
-     * 
-     * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
-     * 

-     *
-     * string version = 6;
-     * @return The bytes for version.
-     */
-    public com.google.protobuf.ByteString
-        getVersionBytes() {
-      java.lang.Object ref = version_;
-      if (ref instanceof String) {
-        com.google.protobuf.ByteString b = 
-            com.google.protobuf.ByteString.copyFromUtf8(
-                (java.lang.String) ref);
-        version_ = b;
-        return b;
-      } else {
-        return (com.google.protobuf.ByteString) ref;
-      }
-    }
-    /**
-     * 
-     * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
-     * 

-     *
-     * string version = 6;
-     * @param value The version to set.
-     * @return This builder for chaining.
-     */
-    public Builder setVersion(
-        java.lang.String value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  
-      version_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
-     * 

-     *
-     * string version = 6;
-     * @return This builder for chaining.
-     */
-    public Builder clearVersion() {
-      
-      version_ = getDefaultInstance().getVersion();
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
-     * 

-     *
-     * string version = 6;
-     * @param value The bytes for version to set.
-     * @return This builder for chaining.
-     */
-    public Builder setVersionBytes(
-        com.google.protobuf.ByteString value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  checkByteStringIsUtf8(value);
-      
-      version_ = value;
-      onChanged();
-      return this;
-    }
-    @java.lang.Override
-    public final Builder setUnknownFields(
-        final com.google.protobuf.UnknownFieldSet unknownFields) {
-      return super.setUnknownFields(unknownFields);
-    }
-
-    @java.lang.Override
-    public final Builder mergeUnknownFields(
-        final com.google.protobuf.UnknownFieldSet unknownFields) {
-      return super.mergeUnknownFields(unknownFields);
-    }
-
-
-    // @@protoc_insertion_point(builder_scope:tensorflow.PlatformInfo)
-  }
-
-  // @@protoc_insertion_point(class_scope:tensorflow.PlatformInfo)
-  private static final org.tensorflow.proto.PlatformInfo DEFAULT_INSTANCE;
-  static {
-    DEFAULT_INSTANCE = new org.tensorflow.proto.PlatformInfo();
-  }
-
-  public static org.tensorflow.proto.PlatformInfo getDefaultInstance() {
-    return DEFAULT_INSTANCE;
-  }
-
-  private static final com.google.protobuf.Parser
-      PARSER = new com.google.protobuf.AbstractParser() {
-    @java.lang.Override
-    public PlatformInfo parsePartialFrom(
-        com.google.protobuf.CodedInputStream input,
-        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-        throws com.google.protobuf.InvalidProtocolBufferException {
-      Builder builder = newBuilder();
-      try {
-        builder.mergeFrom(input, extensionRegistry);
-      } catch (com.google.protobuf.InvalidProtocolBufferException e) {
-        throw e.setUnfinishedMessage(builder.buildPartial());
-      } catch (com.google.protobuf.UninitializedMessageException e) {
-        throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial());
-      } catch (java.io.IOException e) {
-        throw new com.google.protobuf.InvalidProtocolBufferException(e)
-            .setUnfinishedMessage(builder.buildPartial());
-      }
-      return builder.buildPartial();
-    }
-  };
-
-  public static com.google.protobuf.Parser parser() {
-    return PARSER;
-  }
-
-  @java.lang.Override
-  public com.google.protobuf.Parser getParserForType() {
-    return PARSER;
-  }
-
-  @java.lang.Override
-  public org.tensorflow.proto.PlatformInfo getDefaultInstanceForType() {
-    return DEFAULT_INSTANCE;
-  }
-
-}
-
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/PlatformInfoOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/PlatformInfoOrBuilder.java
deleted file mode 100644
index fd9455571a2..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/PlatformInfoOrBuilder.java
+++ /dev/null
@@ -1,129 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-public interface PlatformInfoOrBuilder extends
-    // @@protoc_insertion_point(interface_extends:tensorflow.PlatformInfo)
-    com.google.protobuf.MessageOrBuilder {
-
-  /**
-   * 
-   * e.g. '64bit'
-   * 

-   *
-   * string bits = 1;
-   * @return The bits.
-   */
-  java.lang.String getBits();
-  /**
-   * 
-   * e.g. '64bit'
-   * 

-   *
-   * string bits = 1;
-   * @return The bytes for bits.
-   */
-  com.google.protobuf.ByteString
-      getBitsBytes();
-
-  /**
-   * 
-   * e.g. 'ELF'
-   * 

-   *
-   * string linkage = 2;
-   * @return The linkage.
-   */
-  java.lang.String getLinkage();
-  /**
-   * 
-   * e.g. 'ELF'
-   * 

-   *
-   * string linkage = 2;
-   * @return The bytes for linkage.
-   */
-  com.google.protobuf.ByteString
-      getLinkageBytes();
-
-  /**
-   * 
-   * e.g. 'i386'
-   * 

-   *
-   * string machine = 3;
-   * @return The machine.
-   */
-  java.lang.String getMachine();
-  /**
-   * 
-   * e.g. 'i386'
-   * 

-   *
-   * string machine = 3;
-   * @return The bytes for machine.
-   */
-  com.google.protobuf.ByteString
-      getMachineBytes();
-
-  /**
-   * 
-   * e.g. '3.13.0-76-generic'
-   * 

-   *
-   * string release = 4;
-   * @return The release.
-   */
-  java.lang.String getRelease();
-  /**
-   * 
-   * e.g. '3.13.0-76-generic'
-   * 

-   *
-   * string release = 4;
-   * @return The bytes for release.
-   */
-  com.google.protobuf.ByteString
-      getReleaseBytes();
-
-  /**
-   * 
-   * e.g. 'Linux'
-   * 

-   *
-   * string system = 5;
-   * @return The system.
-   */
-  java.lang.String getSystem();
-  /**
-   * 
-   * e.g. 'Linux'
-   * 

-   *
-   * string system = 5;
-   * @return The bytes for system.
-   */
-  com.google.protobuf.ByteString
-      getSystemBytes();
-
-  /**
-   * 
-   * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
-   * 

-   *
-   * string version = 6;
-   * @return The version.
-   */
-  java.lang.String getVersion();
-  /**
-   * 
-   * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
-   * 

-   *
-   * string version = 6;
-   * @return The bytes for version.
-   */
-  com.google.protobuf.ByteString
-      getVersionBytes();
-}
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ResourceHandleProto.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ResourceHandleProto.java
index 159c9574b47..df26d1e77cd 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ResourceHandleProto.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/ResourceHandleProto.java
@@ -59,27 +59,47 @@ public interface DtypeAndShapeOrBuilder extends
       com.google.protobuf.MessageOrBuilder {
 
     /**
+     * 
+     * Data type of the tensor.
+     * 

+     *
      * .tensorflow.DataType dtype = 1;
      * @return The enum numeric value on the wire for dtype.
      */
     int getDtypeValue();
     /**
+     * 
+     * Data type of the tensor.
+     * 

+     *
      * .tensorflow.DataType dtype = 1;
      * @return The dtype.
      */
     org.tensorflow.proto.DataType getDtype();
 
     /**
+     * 
+     * Shape of the tensor.
+     * 

+     *
      * .tensorflow.TensorShapeProto shape = 2;
      * @return Whether the shape field is set.
      */
     boolean hasShape();
     /**
+     * 
+     * Shape of the tensor.
+     * 

+     *
      * .tensorflow.TensorShapeProto shape = 2;
      * @return The shape.
      */
     org.tensorflow.proto.TensorShapeProto getShape();
     /**
+     * 
+     * Shape of the tensor.
+     * 

+     *
      * .tensorflow.TensorShapeProto shape = 2;
      */
     org.tensorflow.proto.TensorShapeProtoOrBuilder getShapeOrBuilder();
@@ -132,6 +152,10 @@ protected java.lang.Object newInstance(
     public static final int DTYPE_FIELD_NUMBER = 1;
     private int dtype_;
     /**
+     * 
+     * Data type of the tensor.
+     * 

+     *
      * .tensorflow.DataType dtype = 1;
      * @return The enum numeric value on the wire for dtype.
      */
@@ -139,6 +163,10 @@ protected java.lang.Object newInstance(
       return dtype_;
     }
     /**
+     * 
+     * Data type of the tensor.
+     * 

+     *
      * .tensorflow.DataType dtype = 1;
      * @return The dtype.
      */
@@ -151,6 +179,10 @@ protected java.lang.Object newInstance(
     public static final int SHAPE_FIELD_NUMBER = 2;
     private org.tensorflow.proto.TensorShapeProto shape_;
     /**
+     * 
+     * Shape of the tensor.
+     * 

+     *
      * .tensorflow.TensorShapeProto shape = 2;
      * @return Whether the shape field is set.
      */
@@ -159,6 +191,10 @@ public boolean hasShape() {
       return shape_ != null;
     }
     /**
+     * 
+     * Shape of the tensor.
+     * 

+     *
      * .tensorflow.TensorShapeProto shape = 2;
      * @return The shape.
      */
@@ -167,6 +203,10 @@ public org.tensorflow.proto.TensorShapeProto getShape() {
       return shape_ == null ? org.tensorflow.proto.TensorShapeProto.getDefaultInstance() : shape_;
     }
     /**
+     * 
+     * Shape of the tensor.
+     * 

+     *
      * .tensorflow.TensorShapeProto shape = 2;
      */
     @java.lang.Override
@@ -531,6 +571,10 @@ public Builder mergeFrom(
 
       private int dtype_ = 0;
       /**
+       * 
+       * Data type of the tensor.
+       * 

+       *
        * .tensorflow.DataType dtype = 1;
        * @return The enum numeric value on the wire for dtype.
        */
@@ -538,6 +582,10 @@ public Builder mergeFrom(
         return dtype_;
       }
       /**
+       * 
+       * Data type of the tensor.
+       * 

+       *
        * .tensorflow.DataType dtype = 1;
        * @param value The enum numeric value on the wire for dtype to set.
        * @return This builder for chaining.
@@ -549,6 +597,10 @@ public Builder setDtypeValue(int value) {
         return this;
       }
       /**
+       * 
+       * Data type of the tensor.
+       * 

+       *
        * .tensorflow.DataType dtype = 1;
        * @return The dtype.
        */
@@ -559,6 +611,10 @@ public org.tensorflow.proto.DataType getDtype() {
         return result == null ? org.tensorflow.proto.DataType.UNRECOGNIZED : result;
       }
       /**
+       * 
+       * Data type of the tensor.
+       * 

+       *
        * .tensorflow.DataType dtype = 1;
        * @param value The dtype to set.
        * @return This builder for chaining.
@@ -573,6 +629,10 @@ public Builder setDtype(org.tensorflow.proto.DataType value) {
         return this;
       }
       /**
+       * 
+       * Data type of the tensor.
+       * 

+       *
        * .tensorflow.DataType dtype = 1;
        * @return This builder for chaining.
        */
@@ -587,6 +647,10 @@ public Builder clearDtype() {
       private com.google.protobuf.SingleFieldBuilderV3<
           org.tensorflow.proto.TensorShapeProto, org.tensorflow.proto.TensorShapeProto.Builder, org.tensorflow.proto.TensorShapeProtoOrBuilder> shapeBuilder_;
       /**
+       * 
+       * Shape of the tensor.
+       * 

+       *
        * .tensorflow.TensorShapeProto shape = 2;
        * @return Whether the shape field is set.
        */
@@ -594,6 +658,10 @@ public boolean hasShape() {
         return shapeBuilder_ != null || shape_ != null;
       }
       /**
+       * 
+       * Shape of the tensor.
+       * 

+       *
        * .tensorflow.TensorShapeProto shape = 2;
        * @return The shape.
        */
@@ -605,6 +673,10 @@ public org.tensorflow.proto.TensorShapeProto getShape() {
         }
       }
       /**
+       * 
+       * Shape of the tensor.
+       * 

+       *
        * .tensorflow.TensorShapeProto shape = 2;
        */
       public Builder setShape(org.tensorflow.proto.TensorShapeProto value) {
@@ -621,6 +693,10 @@ public Builder setShape(org.tensorflow.proto.TensorShapeProto value) {
         return this;
       }
       /**
+       * 
+       * Shape of the tensor.
+       * 

+       *
        * .tensorflow.TensorShapeProto shape = 2;
        */
       public Builder setShape(
@@ -635,6 +711,10 @@ public Builder setShape(
         return this;
       }
       /**
+       * 
+       * Shape of the tensor.
+       * 

+       *
        * .tensorflow.TensorShapeProto shape = 2;
        */
       public Builder mergeShape(org.tensorflow.proto.TensorShapeProto value) {
@@ -653,6 +733,10 @@ public Builder mergeShape(org.tensorflow.proto.TensorShapeProto value) {
         return this;
       }
       /**
+       * 
+       * Shape of the tensor.
+       * 

+       *
        * .tensorflow.TensorShapeProto shape = 2;
        */
       public Builder clearShape() {
@@ -667,6 +751,10 @@ public Builder clearShape() {
         return this;
       }
       /**
+       * 
+       * Shape of the tensor.
+       * 

+       *
        * .tensorflow.TensorShapeProto shape = 2;
        */
       public org.tensorflow.proto.TensorShapeProto.Builder getShapeBuilder() {
@@ -675,6 +763,10 @@ public org.tensorflow.proto.TensorShapeProto.Builder getShapeBuilder() {
         return getShapeFieldBuilder().getBuilder();
       }
       /**
+       * 
+       * Shape of the tensor.
+       * 

+       *
        * .tensorflow.TensorShapeProto shape = 2;
        */
       public org.tensorflow.proto.TensorShapeProtoOrBuilder getShapeOrBuilder() {
@@ -686,6 +778,10 @@ public org.tensorflow.proto.TensorShapeProtoOrBuilder getShapeOrBuilder() {
         }
       }
       /**
+       * 
+       * Shape of the tensor.
+       * 

+       *
        * .tensorflow.TensorShapeProto shape = 2;
        */
       private com.google.protobuf.SingleFieldBuilderV3<
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RewriterConfig.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RewriterConfig.java
index ae97c9cc75f..c235fb30634 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RewriterConfig.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RewriterConfig.java
@@ -2002,8 +2002,8 @@ public boolean getDisableModelPruning() {
   private int autoMixedPrecision_;
   /**
    * 
-   * Optimize data types for CUDA (default is OFF).
-   * This will try to use float16 on GPU which is faster.
+   * Optimize data types for CUDA/oneDNN (default is OFF).
+   * This will try to use float16 on GPU/CPU which is faster.
    * Note that this can change the numerical stability of the graph and may
    * require the use of loss scaling to maintain model convergence.
    * 

@@ -2016,8 +2016,8 @@ public boolean getDisableModelPruning() {
   }
   /**
    * 
-   * Optimize data types for CUDA (default is OFF).
-   * This will try to use float16 on GPU which is faster.
+   * Optimize data types for CUDA/oneDNN (default is OFF).
+   * This will try to use float16 on GPU/CPU which is faster.
    * Note that this can change the numerical stability of the graph and may
    * require the use of loss scaling to maintain model convergence.
    * 

@@ -5074,8 +5074,8 @@ public Builder clearImplementationSelector() {
     private int autoMixedPrecision_ = 0;
     /**
      * 
-     * Optimize data types for CUDA (default is OFF).
-     * This will try to use float16 on GPU which is faster.
+     * Optimize data types for CUDA/oneDNN (default is OFF).
+     * This will try to use float16 on GPU/CPU which is faster.
      * Note that this can change the numerical stability of the graph and may
      * require the use of loss scaling to maintain model convergence.
      * 

@@ -5088,8 +5088,8 @@ public Builder clearImplementationSelector() {
     }
     /**
      * 
-     * Optimize data types for CUDA (default is OFF).
-     * This will try to use float16 on GPU which is faster.
+     * Optimize data types for CUDA/oneDNN (default is OFF).
+     * This will try to use float16 on GPU/CPU which is faster.
      * Note that this can change the numerical stability of the graph and may
      * require the use of loss scaling to maintain model convergence.
      * 

@@ -5106,8 +5106,8 @@ public Builder setAutoMixedPrecisionValue(int value) {
     }
     /**
      * 
-     * Optimize data types for CUDA (default is OFF).
-     * This will try to use float16 on GPU which is faster.
+     * Optimize data types for CUDA/oneDNN (default is OFF).
+     * This will try to use float16 on GPU/CPU which is faster.
      * Note that this can change the numerical stability of the graph and may
      * require the use of loss scaling to maintain model convergence.
      * 

@@ -5123,8 +5123,8 @@ public org.tensorflow.proto.RewriterConfig.Toggle getAutoMixedPrecision() {
     }
     /**
      * 
-     * Optimize data types for CUDA (default is OFF).
-     * This will try to use float16 on GPU which is faster.
+     * Optimize data types for CUDA/oneDNN (default is OFF).
+     * This will try to use float16 on GPU/CPU which is faster.
      * Note that this can change the numerical stability of the graph and may
      * require the use of loss scaling to maintain model convergence.
      * 

@@ -5144,8 +5144,8 @@ public Builder setAutoMixedPrecision(org.tensorflow.proto.RewriterConfig.Toggle
     }
     /**
      * 
-     * Optimize data types for CUDA (default is OFF).
-     * This will try to use float16 on GPU which is faster.
+     * Optimize data types for CUDA/oneDNN (default is OFF).
+     * This will try to use float16 on GPU/CPU which is faster.
      * Note that this can change the numerical stability of the graph and may
      * require the use of loss scaling to maintain model convergence.
      * 

diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RewriterConfigOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RewriterConfigOrBuilder.java
index 9ad4b3cf401..2676ca54911 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RewriterConfigOrBuilder.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RewriterConfigOrBuilder.java
@@ -305,8 +305,8 @@ public interface RewriterConfigOrBuilder extends
 
   /**
    * 
-   * Optimize data types for CUDA (default is OFF).
-   * This will try to use float16 on GPU which is faster.
+   * Optimize data types for CUDA/oneDNN (default is OFF).
+   * This will try to use float16 on GPU/CPU which is faster.
    * Note that this can change the numerical stability of the graph and may
    * require the use of loss scaling to maintain model convergence.
    * 

@@ -317,8 +317,8 @@ public interface RewriterConfigOrBuilder extends
   int getAutoMixedPrecisionValue();
   /**
    * 
-   * Optimize data types for CUDA (default is OFF).
-   * This will try to use float16 on GPU which is faster.
+   * Optimize data types for CUDA/oneDNN (default is OFF).
+   * This will try to use float16 on GPU/CPU which is faster.
    * Note that this can change the numerical stability of the graph and may
    * require the use of loss scaling to maintain model convergence.
    * 

diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RunConfiguration.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RunConfiguration.java
deleted file mode 100644
index 2a17bdafaf1..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RunConfiguration.java
+++ /dev/null
@@ -1,922 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-/**
- * 
- * Run-specific items such as arguments to the test / benchmark.
- * 

- *
- * Protobuf type {@code tensorflow.RunConfiguration}
- */
-public final class RunConfiguration extends
-    com.google.protobuf.GeneratedMessageV3 implements
-    // @@protoc_insertion_point(message_implements:tensorflow.RunConfiguration)
-    RunConfigurationOrBuilder {
-private static final long serialVersionUID = 0L;
-  // Use RunConfiguration.newBuilder() to construct.
-  private RunConfiguration(com.google.protobuf.GeneratedMessageV3.Builder builder) {
-    super(builder);
-  }
-  private RunConfiguration() {
-    argument_ = com.google.protobuf.LazyStringArrayList.EMPTY;
-  }
-
-  @java.lang.Override
-  @SuppressWarnings({"unused"})
-  protected java.lang.Object newInstance(
-      UnusedPrivateParameter unused) {
-    return new RunConfiguration();
-  }
-
-  @java.lang.Override
-  public final com.google.protobuf.UnknownFieldSet
-  getUnknownFields() {
-    return this.unknownFields;
-  }
-  public static final com.google.protobuf.Descriptors.Descriptor
-      getDescriptor() {
-    return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_RunConfiguration_descriptor;
-  }
-
-  @SuppressWarnings({"rawtypes"})
-  @java.lang.Override
-  protected com.google.protobuf.MapField internalGetMapField(
-      int number) {
-    switch (number) {
-      case 2:
-        return internalGetEnvVars();
-      default:
-        throw new RuntimeException(
-            "Invalid map field number: " + number);
-    }
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-  @java.lang.Override
-  protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
-      internalGetFieldAccessorTable() {
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-        .ensureFieldAccessorsInitialized(
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-
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-  /**
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-   * @return A list containing the argument.
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-    return argument_.getByteString(index);
-  }
-
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-        java.lang.String, java.lang.String> defaultEntry =
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-            .newDefaultInstance(
-                org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_RunConfiguration_EnvVarsEntry_descriptor, 
-                com.google.protobuf.WireFormat.FieldType.STRING,
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-                com.google.protobuf.WireFormat.FieldType.STRING,
-                "");
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-  private com.google.protobuf.MapField
-  internalGetEnvVars() {
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-    }
-    return envVars_;
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-
-  public int getEnvVarsCount() {
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-  /**
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-   * Environment variables used to run the test/benchmark.
-   * 

-   *
-   * map<string, string> env_vars = 2;
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-
-  @java.lang.Override
-  public boolean containsEnvVars(
-      java.lang.String key) {
-    if (key == null) { throw new NullPointerException("map key"); }
-    return internalGetEnvVars().getMap().containsKey(key);
-  }
-  /**
-   * Use {@link #getEnvVarsMap()} instead.
-   */
-  @java.lang.Override
-  @java.lang.Deprecated
-  public java.util.Map getEnvVars() {
-    return getEnvVarsMap();
-  }
-  /**
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-   * Environment variables used to run the test/benchmark.
-   * 

-   *
-   * map<string, string> env_vars = 2;
-   */
-  @java.lang.Override
-
-  public java.util.Map getEnvVarsMap() {
-    return internalGetEnvVars().getMap();
-  }
-  /**
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-   * Environment variables used to run the test/benchmark.
-   * 

-   *
-   * map<string, string> env_vars = 2;
-   */
-  @java.lang.Override
-
-  public java.lang.String getEnvVarsOrDefault(
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-    java.util.Map map =
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-    return map.containsKey(key) ? map.get(key) : defaultValue;
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-  @java.lang.Override
-
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-    java.util.Map map =
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-    com.google.protobuf.GeneratedMessageV3
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-
-  @java.lang.Override
-  public int getSerializedSize() {
-    int size = memoizedSize;
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-  @java.lang.Override
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-    if (obj == this) {
-     return true;
-    }
-    if (!(obj instanceof org.tensorflow.proto.RunConfiguration)) {
-      return super.equals(obj);
-    }
-    org.tensorflow.proto.RunConfiguration other = (org.tensorflow.proto.RunConfiguration) obj;
-
-    if (!getArgumentList()
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-    if (!internalGetEnvVars().equals(
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-    if (!getUnknownFields().equals(other.getUnknownFields())) return false;
-    return true;
-  }
-
-  @java.lang.Override
-  public int hashCode() {
-    if (memoizedHashCode != 0) {
-      return memoizedHashCode;
-    }
-    int hash = 41;
-    hash = (19 * hash) + getDescriptor().hashCode();
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-    return PARSER.parseFrom(data, extensionRegistry);
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-      com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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-    return PARSER.parseFrom(data, extensionRegistry);
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-  }
-  public static org.tensorflow.proto.RunConfiguration parseFrom(
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-    return com.google.protobuf.GeneratedMessageV3
-        .parseWithIOException(PARSER, input);
-  }
-  public static org.tensorflow.proto.RunConfiguration parseFrom(
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-        .parseWithIOException(PARSER, input);
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-  public static org.tensorflow.proto.RunConfiguration parseFrom(
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-      com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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-  public Builder newBuilderForType() { return newBuilder(); }
-  public static Builder newBuilder() {
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-  public static Builder newBuilder(org.tensorflow.proto.RunConfiguration prototype) {
-    return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype);
-  }
-  @java.lang.Override
-  public Builder toBuilder() {
-    return this == DEFAULT_INSTANCE
-        ? new Builder() : new Builder().mergeFrom(this);
-  }
-
-  @java.lang.Override
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-  /**
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-   * 

-   *
-   * Protobuf type {@code tensorflow.RunConfiguration}
-   */
-  public static final class Builder extends
-      com.google.protobuf.GeneratedMessageV3.Builder implements
-      // @@protoc_insertion_point(builder_implements:tensorflow.RunConfiguration)
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-              com.google.protobuf.MapEntry
-              envVars__ = input.readMessage(
-                  EnvVarsDefaultEntryHolder.defaultEntry.getParserForType(), extensionRegistry);
-              internalGetMutableEnvVars().getMutableMap().put(
-                  envVars__.getKey(), envVars__.getValue());
-              break;
-            } // case 18
-            default: {
-              if (!super.parseUnknownField(input, extensionRegistry, tag)) {
-                done = true; // was an endgroup tag
-              }
-              break;
-            } // default:
-          } // switch (tag)
-        } // while (!done)
-      } catch (com.google.protobuf.InvalidProtocolBufferException e) {
-        throw e.unwrapIOException();
-      } finally {
-        onChanged();
-      } // finally
-      return this;
-    }
-    private int bitField0_;
-
-    private com.google.protobuf.LazyStringList argument_ = com.google.protobuf.LazyStringArrayList.EMPTY;
-    private void ensureArgumentIsMutable() {
-      if (!((bitField0_ & 0x00000001) != 0)) {
-        argument_ = new com.google.protobuf.LazyStringArrayList(argument_);
-        bitField0_ |= 0x00000001;
-       }
-    }
-    /**
-     * repeated string argument = 1;
-     * @return A list containing the argument.
-     */
-    public com.google.protobuf.ProtocolStringList
-        getArgumentList() {
-      return argument_.getUnmodifiableView();
-    }
-    /**
-     * repeated string argument = 1;
-     * @return The count of argument.
-     */
-    public int getArgumentCount() {
-      return argument_.size();
-    }
-    /**
-     * repeated string argument = 1;
-     * @param index The index of the element to return.
-     * @return The argument at the given index.
-     */
-    public java.lang.String getArgument(int index) {
-      return argument_.get(index);
-    }
-    /**
-     * repeated string argument = 1;
-     * @param index The index of the value to return.
-     * @return The bytes of the argument at the given index.
-     */
-    public com.google.protobuf.ByteString
-        getArgumentBytes(int index) {
-      return argument_.getByteString(index);
-    }
-    /**
-     * repeated string argument = 1;
-     * @param index The index to set the value at.
-     * @param value The argument to set.
-     * @return This builder for chaining.
-     */
-    public Builder setArgument(
-        int index, java.lang.String value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  ensureArgumentIsMutable();
-      argument_.set(index, value);
-      onChanged();
-      return this;
-    }
-    /**
-     * repeated string argument = 1;
-     * @param value The argument to add.
-     * @return This builder for chaining.
-     */
-    public Builder addArgument(
-        java.lang.String value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  ensureArgumentIsMutable();
-      argument_.add(value);
-      onChanged();
-      return this;
-    }
-    /**
-     * repeated string argument = 1;
-     * @param values The argument to add.
-     * @return This builder for chaining.
-     */
-    public Builder addAllArgument(
-        java.lang.Iterable values) {
-      ensureArgumentIsMutable();
-      com.google.protobuf.AbstractMessageLite.Builder.addAll(
-          values, argument_);
-      onChanged();
-      return this;
-    }
-    /**
-     * repeated string argument = 1;
-     * @return This builder for chaining.
-     */
-    public Builder clearArgument() {
-      argument_ = com.google.protobuf.LazyStringArrayList.EMPTY;
-      bitField0_ = (bitField0_ & ~0x00000001);
-      onChanged();
-      return this;
-    }
-    /**
-     * repeated string argument = 1;
-     * @param value The bytes of the argument to add.
-     * @return This builder for chaining.
-     */
-    public Builder addArgumentBytes(
-        com.google.protobuf.ByteString value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  checkByteStringIsUtf8(value);
-      ensureArgumentIsMutable();
-      argument_.add(value);
-      onChanged();
-      return this;
-    }
-
-    private com.google.protobuf.MapField<
-        java.lang.String, java.lang.String> envVars_;
-    private com.google.protobuf.MapField
-    internalGetEnvVars() {
-      if (envVars_ == null) {
-        return com.google.protobuf.MapField.emptyMapField(
-            EnvVarsDefaultEntryHolder.defaultEntry);
-      }
-      return envVars_;
-    }
-    private com.google.protobuf.MapField
-    internalGetMutableEnvVars() {
-      onChanged();;
-      if (envVars_ == null) {
-        envVars_ = com.google.protobuf.MapField.newMapField(
-            EnvVarsDefaultEntryHolder.defaultEntry);
-      }
-      if (!envVars_.isMutable()) {
-        envVars_ = envVars_.copy();
-      }
-      return envVars_;
-    }
-
-    public int getEnvVarsCount() {
-      return internalGetEnvVars().getMap().size();
-    }
-    /**
-     * 
-     * Environment variables used to run the test/benchmark.
-     * 

-     *
-     * map<string, string> env_vars = 2;
-     */
-
-    @java.lang.Override
-    public boolean containsEnvVars(
-        java.lang.String key) {
-      if (key == null) { throw new NullPointerException("map key"); }
-      return internalGetEnvVars().getMap().containsKey(key);
-    }
-    /**
-     * Use {@link #getEnvVarsMap()} instead.
-     */
-    @java.lang.Override
-    @java.lang.Deprecated
-    public java.util.Map getEnvVars() {
-      return getEnvVarsMap();
-    }
-    /**
-     * 
-     * Environment variables used to run the test/benchmark.
-     * 

-     *
-     * map<string, string> env_vars = 2;
-     */
-    @java.lang.Override
-
-    public java.util.Map getEnvVarsMap() {
-      return internalGetEnvVars().getMap();
-    }
-    /**
-     * 
-     * Environment variables used to run the test/benchmark.
-     * 

-     *
-     * map<string, string> env_vars = 2;
-     */
-    @java.lang.Override
-
-    public java.lang.String getEnvVarsOrDefault(
-        java.lang.String key,
-        java.lang.String defaultValue) {
-      if (key == null) { throw new NullPointerException("map key"); }
-      java.util.Map map =
-          internalGetEnvVars().getMap();
-      return map.containsKey(key) ? map.get(key) : defaultValue;
-    }
-    /**
-     * 
-     * Environment variables used to run the test/benchmark.
-     * 

-     *
-     * map<string, string> env_vars = 2;
-     */
-    @java.lang.Override
-
-    public java.lang.String getEnvVarsOrThrow(
-        java.lang.String key) {
-      if (key == null) { throw new NullPointerException("map key"); }
-      java.util.Map map =
-          internalGetEnvVars().getMap();
-      if (!map.containsKey(key)) {
-        throw new java.lang.IllegalArgumentException();
-      }
-      return map.get(key);
-    }
-
-    public Builder clearEnvVars() {
-      internalGetMutableEnvVars().getMutableMap()
-          .clear();
-      return this;
-    }
-    /**
-     * 
-     * Environment variables used to run the test/benchmark.
-     * 

-     *
-     * map<string, string> env_vars = 2;
-     */
-
-    public Builder removeEnvVars(
-        java.lang.String key) {
-      if (key == null) { throw new NullPointerException("map key"); }
-      internalGetMutableEnvVars().getMutableMap()
-          .remove(key);
-      return this;
-    }
-    /**
-     * Use alternate mutation accessors instead.
-     */
-    @java.lang.Deprecated
-    public java.util.Map
-    getMutableEnvVars() {
-      return internalGetMutableEnvVars().getMutableMap();
-    }
-    /**
-     * 
-     * Environment variables used to run the test/benchmark.
-     * 

-     *
-     * map<string, string> env_vars = 2;
-     */
-    public Builder putEnvVars(
-        java.lang.String key,
-        java.lang.String value) {
-      if (key == null) { throw new NullPointerException("map key"); }
-      if (value == null) {
-  throw new NullPointerException("map value");
-}
-
-      internalGetMutableEnvVars().getMutableMap()
-          .put(key, value);
-      return this;
-    }
-    /**
-     * 
-     * Environment variables used to run the test/benchmark.
-     * 

-     *
-     * map<string, string> env_vars = 2;
-     */
-
-    public Builder putAllEnvVars(
-        java.util.Map values) {
-      internalGetMutableEnvVars().getMutableMap()
-          .putAll(values);
-      return this;
-    }
-    @java.lang.Override
-    public final Builder setUnknownFields(
-        final com.google.protobuf.UnknownFieldSet unknownFields) {
-      return super.setUnknownFields(unknownFields);
-    }
-
-    @java.lang.Override
-    public final Builder mergeUnknownFields(
-        final com.google.protobuf.UnknownFieldSet unknownFields) {
-      return super.mergeUnknownFields(unknownFields);
-    }
-
-
-    // @@protoc_insertion_point(builder_scope:tensorflow.RunConfiguration)
-  }
-
-  // @@protoc_insertion_point(class_scope:tensorflow.RunConfiguration)
-  private static final org.tensorflow.proto.RunConfiguration DEFAULT_INSTANCE;
-  static {
-    DEFAULT_INSTANCE = new org.tensorflow.proto.RunConfiguration();
-  }
-
-  public static org.tensorflow.proto.RunConfiguration getDefaultInstance() {
-    return DEFAULT_INSTANCE;
-  }
-
-  private static final com.google.protobuf.Parser
-      PARSER = new com.google.protobuf.AbstractParser() {
-    @java.lang.Override
-    public RunConfiguration parsePartialFrom(
-        com.google.protobuf.CodedInputStream input,
-        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-        throws com.google.protobuf.InvalidProtocolBufferException {
-      Builder builder = newBuilder();
-      try {
-        builder.mergeFrom(input, extensionRegistry);
-      } catch (com.google.protobuf.InvalidProtocolBufferException e) {
-        throw e.setUnfinishedMessage(builder.buildPartial());
-      } catch (com.google.protobuf.UninitializedMessageException e) {
-        throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial());
-      } catch (java.io.IOException e) {
-        throw new com.google.protobuf.InvalidProtocolBufferException(e)
-            .setUnfinishedMessage(builder.buildPartial());
-      }
-      return builder.buildPartial();
-    }
-  };
-
-  public static com.google.protobuf.Parser parser() {
-    return PARSER;
-  }
-
-  @java.lang.Override
-  public com.google.protobuf.Parser getParserForType() {
-    return PARSER;
-  }
-
-  @java.lang.Override
-  public org.tensorflow.proto.RunConfiguration getDefaultInstanceForType() {
-    return DEFAULT_INSTANCE;
-  }
-
-}
-
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RunConfigurationOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RunConfigurationOrBuilder.java
deleted file mode 100644
index a3b3ca982e8..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RunConfigurationOrBuilder.java
+++ /dev/null
@@ -1,90 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-public interface RunConfigurationOrBuilder extends
-    // @@protoc_insertion_point(interface_extends:tensorflow.RunConfiguration)
-    com.google.protobuf.MessageOrBuilder {
-
-  /**
-   * repeated string argument = 1;
-   * @return A list containing the argument.
-   */
-  java.util.List
-      getArgumentList();
-  /**
-   * repeated string argument = 1;
-   * @return The count of argument.
-   */
-  int getArgumentCount();
-  /**
-   * repeated string argument = 1;
-   * @param index The index of the element to return.
-   * @return The argument at the given index.
-   */
-  java.lang.String getArgument(int index);
-  /**
-   * repeated string argument = 1;
-   * @param index The index of the value to return.
-   * @return The bytes of the argument at the given index.
-   */
-  com.google.protobuf.ByteString
-      getArgumentBytes(int index);
-
-  /**
-   * 
-   * Environment variables used to run the test/benchmark.
-   * 

-   *
-   * map<string, string> env_vars = 2;
-   */
-  int getEnvVarsCount();
-  /**
-   * 
-   * Environment variables used to run the test/benchmark.
-   * 

-   *
-   * map<string, string> env_vars = 2;
-   */
-  boolean containsEnvVars(
-      java.lang.String key);
-  /**
-   * Use {@link #getEnvVarsMap()} instead.
-   */
-  @java.lang.Deprecated
-  java.util.Map
-  getEnvVars();
-  /**
-   * 
-   * Environment variables used to run the test/benchmark.
-   * 

-   *
-   * map<string, string> env_vars = 2;
-   */
-  java.util.Map
-  getEnvVarsMap();
-  /**
-   * 
-   * Environment variables used to run the test/benchmark.
-   * 

-   *
-   * map<string, string> env_vars = 2;
-   */
-
-  /* nullable */
-java.lang.String getEnvVarsOrDefault(
-      java.lang.String key,
-      /* nullable */
-java.lang.String defaultValue);
-  /**
-   * 
-   * Environment variables used to run the test/benchmark.
-   * 

-   *
-   * map<string, string> env_vars = 2;
-   */
-
-  java.lang.String getEnvVarsOrThrow(
-      java.lang.String key);
-}
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/SignatureDef.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/SignatureDef.java
index ecb73cc96e7..b701daabd03 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/SignatureDef.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/SignatureDef.java
@@ -7,58 +7,6 @@
  * 
  * SignatureDef defines the signature of a computation supported by a TensorFlow
  * graph.
- * For example, a model with two loss computations, sharing a single input,
- * might have the following signature_def map, in a MetaGraphDef message.
- * Note that across the two SignatureDefs "loss_A" and "loss_B", the input key,
- * output key, and method_name are identical, and will be used by system(s) that
- * implement or rely upon this particular loss method. The output tensor names
- * differ, demonstrating how different outputs can exist for the same method.
- * signature_def {
- *   key: "loss_A"
- *   value {
- *     inputs {
- *       key: "input"
- *       value {
- *         name: "input:0"
- *         dtype: DT_STRING
- *         tensor_shape: ...
- *       }
- *     }
- *     outputs {
- *       key: "loss_output"
- *       value {
- *         name: "loss_output_A:0"
- *         dtype: DT_FLOAT
- *         tensor_shape: ...
- *       }
- *     }
- *     method_name: "some/package/compute_loss"
- *   }
- *   ...
- * }
- * signature_def {
- *   key: "loss_B"
- *   value {
- *     inputs {
- *       key: "input"
- *       value {
- *         name: "input:0"
- *         dtype: DT_STRING
- *         tensor_shape: ...
- *       }
- *     }
- *     outputs {
- *       key: "loss_output"
- *       value {
- *         name: "loss_output_B:0"
- *         dtype: DT_FLOAT
- *         tensor_shape: ...
- *       }
- *     }
- *     method_name: "some/package/compute_loss"
- *   }
- *   ...
- * }
  * 

  *
  * Protobuf type {@code tensorflow.SignatureDef}
@@ -315,13 +263,12 @@ public org.tensorflow.proto.TensorInfo getOutputsOrThrow(
   private volatile java.lang.Object methodName_;
   /**
    * 
-   * Extensible method_name information enabling third-party users to mark a
-   * SignatureDef as supporting a particular method. This enables producers and
-   * consumers of SignatureDefs, e.g. a model definition library and a serving
-   * library to have a clear hand-off regarding the semantics of a computation.
-   * Note that multiple SignatureDefs in a single MetaGraphDef may have the same
-   * method_name. This is commonly used to support multi-headed computation,
-   * where a single graph computation may return multiple results.
+   * Deprecated: TensorFlow 2 always sets this to a fixed value;
+   * open-source TF Serving stopped checking by default since release 2.4.
+   * In TensorFlow 1, the method_name enabled users to mark a SignatureDef as
+   * supporting a particular method. Multiple SignatureDefs in a single
+   * MetaGraphDef could have the same method_name (e.g., to support multi-headed
+   * computation).
    * 

    *
    * string method_name = 3;
@@ -342,13 +289,12 @@ public java.lang.String getMethodName() {
   }
   /**
    * 
-   * Extensible method_name information enabling third-party users to mark a
-   * SignatureDef as supporting a particular method. This enables producers and
-   * consumers of SignatureDefs, e.g. a model definition library and a serving
-   * library to have a clear hand-off regarding the semantics of a computation.
-   * Note that multiple SignatureDefs in a single MetaGraphDef may have the same
-   * method_name. This is commonly used to support multi-headed computation,
-   * where a single graph computation may return multiple results.
+   * Deprecated: TensorFlow 2 always sets this to a fixed value;
+   * open-source TF Serving stopped checking by default since release 2.4.
+   * In TensorFlow 1, the method_name enabled users to mark a SignatureDef as
+   * supporting a particular method. Multiple SignatureDefs in a single
+   * MetaGraphDef could have the same method_name (e.g., to support multi-headed
+   * computation).
    * 

    *
    * string method_name = 3;
@@ -690,58 +636,6 @@ protected Builder newBuilderForType(
    * 
    * SignatureDef defines the signature of a computation supported by a TensorFlow
    * graph.
-   * For example, a model with two loss computations, sharing a single input,
-   * might have the following signature_def map, in a MetaGraphDef message.
-   * Note that across the two SignatureDefs "loss_A" and "loss_B", the input key,
-   * output key, and method_name are identical, and will be used by system(s) that
-   * implement or rely upon this particular loss method. The output tensor names
-   * differ, demonstrating how different outputs can exist for the same method.
-   * signature_def {
-   *   key: "loss_A"
-   *   value {
-   *     inputs {
-   *       key: "input"
-   *       value {
-   *         name: "input:0"
-   *         dtype: DT_STRING
-   *         tensor_shape: ...
-   *       }
-   *     }
-   *     outputs {
-   *       key: "loss_output"
-   *       value {
-   *         name: "loss_output_A:0"
-   *         dtype: DT_FLOAT
-   *         tensor_shape: ...
-   *       }
-   *     }
-   *     method_name: "some/package/compute_loss"
-   *   }
-   *   ...
-   * }
-   * signature_def {
-   *   key: "loss_B"
-   *   value {
-   *     inputs {
-   *       key: "input"
-   *       value {
-   *         name: "input:0"
-   *         dtype: DT_STRING
-   *         tensor_shape: ...
-   *       }
-   *     }
-   *     outputs {
-   *       key: "loss_output"
-   *       value {
-   *         name: "loss_output_B:0"
-   *         dtype: DT_FLOAT
-   *         tensor_shape: ...
-   *       }
-   *     }
-   *     method_name: "some/package/compute_loss"
-   *   }
-   *   ...
-   * }
    * 

    *
    * Protobuf type {@code tensorflow.SignatureDef}
@@ -1296,13 +1190,12 @@ public Builder putAllOutputs(
     private java.lang.Object methodName_ = "";
     /**
      * 
-     * Extensible method_name information enabling third-party users to mark a
-     * SignatureDef as supporting a particular method. This enables producers and
-     * consumers of SignatureDefs, e.g. a model definition library and a serving
-     * library to have a clear hand-off regarding the semantics of a computation.
-     * Note that multiple SignatureDefs in a single MetaGraphDef may have the same
-     * method_name. This is commonly used to support multi-headed computation,
-     * where a single graph computation may return multiple results.
+     * Deprecated: TensorFlow 2 always sets this to a fixed value;
+     * open-source TF Serving stopped checking by default since release 2.4.
+     * In TensorFlow 1, the method_name enabled users to mark a SignatureDef as
+     * supporting a particular method. Multiple SignatureDefs in a single
+     * MetaGraphDef could have the same method_name (e.g., to support multi-headed
+     * computation).
      * 

      *
      * string method_name = 3;
@@ -1322,13 +1215,12 @@ public java.lang.String getMethodName() {
     }
     /**
      * 
-     * Extensible method_name information enabling third-party users to mark a
-     * SignatureDef as supporting a particular method. This enables producers and
-     * consumers of SignatureDefs, e.g. a model definition library and a serving
-     * library to have a clear hand-off regarding the semantics of a computation.
-     * Note that multiple SignatureDefs in a single MetaGraphDef may have the same
-     * method_name. This is commonly used to support multi-headed computation,
-     * where a single graph computation may return multiple results.
+     * Deprecated: TensorFlow 2 always sets this to a fixed value;
+     * open-source TF Serving stopped checking by default since release 2.4.
+     * In TensorFlow 1, the method_name enabled users to mark a SignatureDef as
+     * supporting a particular method. Multiple SignatureDefs in a single
+     * MetaGraphDef could have the same method_name (e.g., to support multi-headed
+     * computation).
      * 

      *
      * string method_name = 3;
@@ -1349,13 +1241,12 @@ public java.lang.String getMethodName() {
     }
     /**
      * 
-     * Extensible method_name information enabling third-party users to mark a
-     * SignatureDef as supporting a particular method. This enables producers and
-     * consumers of SignatureDefs, e.g. a model definition library and a serving
-     * library to have a clear hand-off regarding the semantics of a computation.
-     * Note that multiple SignatureDefs in a single MetaGraphDef may have the same
-     * method_name. This is commonly used to support multi-headed computation,
-     * where a single graph computation may return multiple results.
+     * Deprecated: TensorFlow 2 always sets this to a fixed value;
+     * open-source TF Serving stopped checking by default since release 2.4.
+     * In TensorFlow 1, the method_name enabled users to mark a SignatureDef as
+     * supporting a particular method. Multiple SignatureDefs in a single
+     * MetaGraphDef could have the same method_name (e.g., to support multi-headed
+     * computation).
      * 

      *
      * string method_name = 3;
@@ -1374,13 +1265,12 @@ public Builder setMethodName(
     }
     /**
      * 
-     * Extensible method_name information enabling third-party users to mark a
-     * SignatureDef as supporting a particular method. This enables producers and
-     * consumers of SignatureDefs, e.g. a model definition library and a serving
-     * library to have a clear hand-off regarding the semantics of a computation.
-     * Note that multiple SignatureDefs in a single MetaGraphDef may have the same
-     * method_name. This is commonly used to support multi-headed computation,
-     * where a single graph computation may return multiple results.
+     * Deprecated: TensorFlow 2 always sets this to a fixed value;
+     * open-source TF Serving stopped checking by default since release 2.4.
+     * In TensorFlow 1, the method_name enabled users to mark a SignatureDef as
+     * supporting a particular method. Multiple SignatureDefs in a single
+     * MetaGraphDef could have the same method_name (e.g., to support multi-headed
+     * computation).
      * 

      *
      * string method_name = 3;
@@ -1394,13 +1284,12 @@ public Builder clearMethodName() {
     }
     /**
      * 
-     * Extensible method_name information enabling third-party users to mark a
-     * SignatureDef as supporting a particular method. This enables producers and
-     * consumers of SignatureDefs, e.g. a model definition library and a serving
-     * library to have a clear hand-off regarding the semantics of a computation.
-     * Note that multiple SignatureDefs in a single MetaGraphDef may have the same
-     * method_name. This is commonly used to support multi-headed computation,
-     * where a single graph computation may return multiple results.
+     * Deprecated: TensorFlow 2 always sets this to a fixed value;
+     * open-source TF Serving stopped checking by default since release 2.4.
+     * In TensorFlow 1, the method_name enabled users to mark a SignatureDef as
+     * supporting a particular method. Multiple SignatureDefs in a single
+     * MetaGraphDef could have the same method_name (e.g., to support multi-headed
+     * computation).
      * 

      *
      * string method_name = 3;
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/SignatureDefOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/SignatureDefOrBuilder.java
index 86ae1bcf3d1..28bd86c8f8a 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/SignatureDefOrBuilder.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/SignatureDefOrBuilder.java
@@ -121,13 +121,12 @@ org.tensorflow.proto.TensorInfo getOutputsOrThrow(
 
   /**
    * 
-   * Extensible method_name information enabling third-party users to mark a
-   * SignatureDef as supporting a particular method. This enables producers and
-   * consumers of SignatureDefs, e.g. a model definition library and a serving
-   * library to have a clear hand-off regarding the semantics of a computation.
-   * Note that multiple SignatureDefs in a single MetaGraphDef may have the same
-   * method_name. This is commonly used to support multi-headed computation,
-   * where a single graph computation may return multiple results.
+   * Deprecated: TensorFlow 2 always sets this to a fixed value;
+   * open-source TF Serving stopped checking by default since release 2.4.
+   * In TensorFlow 1, the method_name enabled users to mark a SignatureDef as
+   * supporting a particular method. Multiple SignatureDefs in a single
+   * MetaGraphDef could have the same method_name (e.g., to support multi-headed
+   * computation).
    * 

    *
    * string method_name = 3;
@@ -136,13 +135,12 @@ org.tensorflow.proto.TensorInfo getOutputsOrThrow(
   java.lang.String getMethodName();
   /**
    * 
-   * Extensible method_name information enabling third-party users to mark a
-   * SignatureDef as supporting a particular method. This enables producers and
-   * consumers of SignatureDefs, e.g. a model definition library and a serving
-   * library to have a clear hand-off regarding the semantics of a computation.
-   * Note that multiple SignatureDefs in a single MetaGraphDef may have the same
-   * method_name. This is commonly used to support multi-headed computation,
-   * where a single graph computation may return multiple results.
+   * Deprecated: TensorFlow 2 always sets this to a fixed value;
+   * open-source TF Serving stopped checking by default since release 2.4.
+   * In TensorFlow 1, the method_name enabled users to mark a SignatureDef as
+   * supporting a particular method. Multiple SignatureDefs in a single
+   * MetaGraphDef could have the same method_name (e.g., to support multi-headed
+   * computation).
    * 

    *
    * string method_name = 3;
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TensorProto.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TensorProto.java
index 0440777955e..ef4157a3352 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TensorProto.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TensorProto.java
@@ -66,6 +66,10 @@ protected java.lang.Object newInstance(
   public static final int DTYPE_FIELD_NUMBER = 1;
   private int dtype_;
   /**
+   * 
+   * Data type of the tensor.
+   * 

+   *
    * .tensorflow.DataType dtype = 1;
    * @return The enum numeric value on the wire for dtype.
    */
@@ -73,6 +77,10 @@ protected java.lang.Object newInstance(
     return dtype_;
   }
   /**
+   * 
+   * Data type of the tensor.
+   * 

+   *
    * .tensorflow.DataType dtype = 1;
    * @return The dtype.
    */
@@ -1929,6 +1937,10 @@ public Builder mergeFrom(
 
     private int dtype_ = 0;
     /**
+     * 
+     * Data type of the tensor.
+     * 

+     *
      * .tensorflow.DataType dtype = 1;
      * @return The enum numeric value on the wire for dtype.
      */
@@ -1936,6 +1948,10 @@ public Builder mergeFrom(
       return dtype_;
     }
     /**
+     * 
+     * Data type of the tensor.
+     * 

+     *
      * .tensorflow.DataType dtype = 1;
      * @param value The enum numeric value on the wire for dtype to set.
      * @return This builder for chaining.
@@ -1947,6 +1963,10 @@ public Builder setDtypeValue(int value) {
       return this;
     }
     /**
+     * 
+     * Data type of the tensor.
+     * 

+     *
      * .tensorflow.DataType dtype = 1;
      * @return The dtype.
      */
@@ -1957,6 +1977,10 @@ public org.tensorflow.proto.DataType getDtype() {
       return result == null ? org.tensorflow.proto.DataType.UNRECOGNIZED : result;
     }
     /**
+     * 
+     * Data type of the tensor.
+     * 

+     *
      * .tensorflow.DataType dtype = 1;
      * @param value The dtype to set.
      * @return This builder for chaining.
@@ -1971,6 +1995,10 @@ public Builder setDtype(org.tensorflow.proto.DataType value) {
       return this;
     }
     /**
+     * 
+     * Data type of the tensor.
+     * 

+     *
      * .tensorflow.DataType dtype = 1;
      * @return This builder for chaining.
      */
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TensorProtoOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TensorProtoOrBuilder.java
index fe901586e8c..9eafe8177e2 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TensorProtoOrBuilder.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TensorProtoOrBuilder.java
@@ -8,11 +8,19 @@ public interface TensorProtoOrBuilder extends
     com.google.protobuf.MessageOrBuilder {
 
   /**
+   * 
+   * Data type of the tensor.
+   * 

+   *
    * .tensorflow.DataType dtype = 1;
    * @return The enum numeric value on the wire for dtype.
    */
   int getDtypeValue();
   /**
+   * 
+   * Data type of the tensor.
+   * 

+   *
    * .tensorflow.DataType dtype = 1;
    * @return The dtype.
    */
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestLogProtos.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestLogProtos.java
deleted file mode 100644
index fb587acc9e8..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestLogProtos.java
+++ /dev/null
@@ -1,287 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-public final class TestLogProtos {
-  private TestLogProtos() {}
-  public static void registerAllExtensions(
-      com.google.protobuf.ExtensionRegistryLite registry) {
-  }
-
-  public static void registerAllExtensions(
-      com.google.protobuf.ExtensionRegistry registry) {
-    registerAllExtensions(
-        (com.google.protobuf.ExtensionRegistryLite) registry);
-  }
-  static final com.google.protobuf.Descriptors.Descriptor
-    internal_static_tensorflow_EntryValue_descriptor;
-  static final 
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-      internal_static_tensorflow_EntryValue_fieldAccessorTable;
-  static final com.google.protobuf.Descriptors.Descriptor
-    internal_static_tensorflow_MetricEntry_descriptor;
-  static final 
-    com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
-      internal_static_tensorflow_MetricEntry_fieldAccessorTable;
-  static final com.google.protobuf.Descriptors.Descriptor
-    internal_static_tensorflow_BenchmarkEntry_descriptor;
-  static final 
-    com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
-      internal_static_tensorflow_BenchmarkEntry_fieldAccessorTable;
-  static final com.google.protobuf.Descriptors.Descriptor
-    internal_static_tensorflow_BenchmarkEntry_ExtrasEntry_descriptor;
-  static final 
-    com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
-      internal_static_tensorflow_BenchmarkEntry_ExtrasEntry_fieldAccessorTable;
-  static final com.google.protobuf.Descriptors.Descriptor
-    internal_static_tensorflow_BenchmarkEntries_descriptor;
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-    internal_static_tensorflow_BuildConfiguration_descriptor;
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-      internal_static_tensorflow_BuildConfiguration_fieldAccessorTable;
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-    internal_static_tensorflow_CommitId_descriptor;
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-    com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
-      internal_static_tensorflow_CommitId_fieldAccessorTable;
-  static final com.google.protobuf.Descriptors.Descriptor
-    internal_static_tensorflow_CPUInfo_descriptor;
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-    com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
-      internal_static_tensorflow_CPUInfo_fieldAccessorTable;
-  static final com.google.protobuf.Descriptors.Descriptor
-    internal_static_tensorflow_CPUInfo_CacheSizeEntry_descriptor;
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-      internal_static_tensorflow_CPUInfo_CacheSizeEntry_fieldAccessorTable;
-  static final com.google.protobuf.Descriptors.Descriptor
-    internal_static_tensorflow_MemoryInfo_descriptor;
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-      internal_static_tensorflow_MemoryInfo_fieldAccessorTable;
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-    internal_static_tensorflow_GPUInfo_descriptor;
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-      internal_static_tensorflow_GPUInfo_fieldAccessorTable;
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-    internal_static_tensorflow_PlatformInfo_descriptor;
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-      internal_static_tensorflow_PlatformInfo_fieldAccessorTable;
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-    internal_static_tensorflow_AvailableDeviceInfo_descriptor;
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-      internal_static_tensorflow_TestResults_fieldAccessorTable;
-
-  public static com.google.protobuf.Descriptors.FileDescriptor
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-  // @@protoc_insertion_point(outer_class_scope)
-}
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestResults.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestResults.java
deleted file mode 100644
index 09ed588ef20..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestResults.java
+++ /dev/null
@@ -1,2685 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-/**
- * 
- * The output of one benchmark / test run.  Each run contains a list of
- * tests or benchmarks, stored as BenchmarkEntry messages.
- * This message should be emitted by the reporter (which runs the
- * test / BM in a subprocess and then reads the emitted BenchmarkEntry messages;
- * usually from a serialized json file, finally collecting them along
- * with additional information about the test run.
- * 

- *
- * Protobuf type {@code tensorflow.TestResults}
- */
-public final class TestResults extends
-    com.google.protobuf.GeneratedMessageV3 implements
-    // @@protoc_insertion_point(message_implements:tensorflow.TestResults)
-    TestResultsOrBuilder {
-private static final long serialVersionUID = 0L;
-  // Use TestResults.newBuilder() to construct.
-  private TestResults(com.google.protobuf.GeneratedMessageV3.Builder builder) {
-    super(builder);
-  }
-  private TestResults() {
-    target_ = "";
-    name_ = "";
-    benchmarkType_ = 0;
-    runMode_ = "";
-    tfVersion_ = "";
-  }
-
-  @java.lang.Override
-  @SuppressWarnings({"unused"})
-  protected java.lang.Object newInstance(
-      UnusedPrivateParameter unused) {
-    return new TestResults();
-  }
-
-  @java.lang.Override
-  public final com.google.protobuf.UnknownFieldSet
-  getUnknownFields() {
-    return this.unknownFields;
-  }
-  public static final com.google.protobuf.Descriptors.Descriptor
-      getDescriptor() {
-    return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_TestResults_descriptor;
-  }
-
-  @java.lang.Override
-  protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
-      internalGetFieldAccessorTable() {
-    return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_TestResults_fieldAccessorTable
-        .ensureFieldAccessorsInitialized(
-            org.tensorflow.proto.TestResults.class, org.tensorflow.proto.TestResults.Builder.class);
-  }
-
-  /**
-   * 
-   * The type of benchmark.
-   * 

-   *
-   * Protobuf enum {@code tensorflow.TestResults.BenchmarkType}
-   */
-  public enum BenchmarkType
-      implements com.google.protobuf.ProtocolMessageEnum {
-    /**
-     * 
-     * Fallback for protos written before Type was introduced.
-     * 

-     *
-     * UNKNOWN = 0;
-     */
-    UNKNOWN(0),
-    /**
-     * CPP_MICROBENCHMARK = 1;
-     */
-    CPP_MICROBENCHMARK(1),
-    /**
-     * PYTHON_BENCHMARK = 2;
-     */
-    PYTHON_BENCHMARK(2),
-    /**
-     * ANDROID_BENCHMARK = 3;
-     */
-    ANDROID_BENCHMARK(3),
-    /**
-     * EDGE_BENCHMARK = 4;
-     */
-    EDGE_BENCHMARK(4),
-    /**
-     * IOS_BENCHMARK = 5;
-     */
-    IOS_BENCHMARK(5),
-    UNRECOGNIZED(-1),
-    ;
-
-    /**
-     * 
-     * Fallback for protos written before Type was introduced.
-     * 

-     *
-     * UNKNOWN = 0;
-     */
-    public static final int UNKNOWN_VALUE = 0;
-    /**
-     * CPP_MICROBENCHMARK = 1;
-     */
-    public static final int CPP_MICROBENCHMARK_VALUE = 1;
-    /**
-     * PYTHON_BENCHMARK = 2;
-     */
-    public static final int PYTHON_BENCHMARK_VALUE = 2;
-    /**
-     * ANDROID_BENCHMARK = 3;
-     */
-    public static final int ANDROID_BENCHMARK_VALUE = 3;
-    /**
-     * EDGE_BENCHMARK = 4;
-     */
-    public static final int EDGE_BENCHMARK_VALUE = 4;
-    /**
-     * IOS_BENCHMARK = 5;
-     */
-    public static final int IOS_BENCHMARK_VALUE = 5;
-
-
-    public final int getNumber() {
-      if (this == UNRECOGNIZED) {
-        throw new java.lang.IllegalArgumentException(
-            "Can't get the number of an unknown enum value.");
-      }
-      return value;
-    }
-
-    /**
-     * @param value The numeric wire value of the corresponding enum entry.
-     * @return The enum associated with the given numeric wire value.
-     * @deprecated Use {@link #forNumber(int)} instead.
-     */
-    @java.lang.Deprecated
-    public static BenchmarkType valueOf(int value) {
-      return forNumber(value);
-    }
-
-    /**
-     * @param value The numeric wire value of the corresponding enum entry.
-     * @return The enum associated with the given numeric wire value.
-     */
-    public static BenchmarkType forNumber(int value) {
-      switch (value) {
-        case 0: return UNKNOWN;
-        case 1: return CPP_MICROBENCHMARK;
-        case 2: return PYTHON_BENCHMARK;
-        case 3: return ANDROID_BENCHMARK;
-        case 4: return EDGE_BENCHMARK;
-        case 5: return IOS_BENCHMARK;
-        default: return null;
-      }
-    }
-
-    public static com.google.protobuf.Internal.EnumLiteMap
-        internalGetValueMap() {
-      return internalValueMap;
-    }
-    private static final com.google.protobuf.Internal.EnumLiteMap<
-        BenchmarkType> internalValueMap =
-          new com.google.protobuf.Internal.EnumLiteMap() {
-            public BenchmarkType findValueByNumber(int number) {
-              return BenchmarkType.forNumber(number);
-            }
-          };
-
-    public final com.google.protobuf.Descriptors.EnumValueDescriptor
-        getValueDescriptor() {
-      if (this == UNRECOGNIZED) {
-        throw new java.lang.IllegalStateException(
-            "Can't get the descriptor of an unrecognized enum value.");
-      }
-      return getDescriptor().getValues().get(ordinal());
-    }
-    public final com.google.protobuf.Descriptors.EnumDescriptor
-        getDescriptorForType() {
-      return getDescriptor();
-    }
-    public static final com.google.protobuf.Descriptors.EnumDescriptor
-        getDescriptor() {
-      return org.tensorflow.proto.TestResults.getDescriptor().getEnumTypes().get(0);
-    }
-
-    private static final BenchmarkType[] VALUES = values();
-
-    public static BenchmarkType valueOf(
-        com.google.protobuf.Descriptors.EnumValueDescriptor desc) {
-      if (desc.getType() != getDescriptor()) {
-        throw new java.lang.IllegalArgumentException(
-          "EnumValueDescriptor is not for this type.");
-      }
-      if (desc.getIndex() == -1) {
-        return UNRECOGNIZED;
-      }
-      return VALUES[desc.getIndex()];
-    }
-
-    private final int value;
-
-    private BenchmarkType(int value) {
-      this.value = value;
-    }
-
-    // @@protoc_insertion_point(enum_scope:tensorflow.TestResults.BenchmarkType)
-  }
-
-  public static final int TARGET_FIELD_NUMBER = 1;
-  private volatile java.lang.Object target_;
-  /**
-   * 
-   * The target of the run, e.g.:
-   *  //tensorflow/core:kernels_adjust_contrast_op_benchmark_test
-   * 

-   *
-   * string target = 1;
-   * @return The target.
-   */
-  @java.lang.Override
-  public java.lang.String getTarget() {
-    java.lang.Object ref = target_;
-    if (ref instanceof java.lang.String) {
-      return (java.lang.String) ref;
-    } else {
-      com.google.protobuf.ByteString bs = 
-          (com.google.protobuf.ByteString) ref;
-      java.lang.String s = bs.toStringUtf8();
-      target_ = s;
-      return s;
-    }
-  }
-  /**
-   * 
-   * The target of the run, e.g.:
-   *  //tensorflow/core:kernels_adjust_contrast_op_benchmark_test
-   * 

-   *
-   * string target = 1;
-   * @return The bytes for target.
-   */
-  @java.lang.Override
-  public com.google.protobuf.ByteString
-      getTargetBytes() {
-    java.lang.Object ref = target_;
-    if (ref instanceof java.lang.String) {
-      com.google.protobuf.ByteString b = 
-          com.google.protobuf.ByteString.copyFromUtf8(
-              (java.lang.String) ref);
-      target_ = b;
-      return b;
-    } else {
-      return (com.google.protobuf.ByteString) ref;
-    }
-  }
-
-  public static final int ENTRIES_FIELD_NUMBER = 2;
-  private org.tensorflow.proto.BenchmarkEntries entries_;
-  /**
-   * 
-   * The list of tests or benchmarks in this run.
-   * 

-   *
-   * .tensorflow.BenchmarkEntries entries = 2;
-   * @return Whether the entries field is set.
-   */
-  @java.lang.Override
-  public boolean hasEntries() {
-    return entries_ != null;
-  }
-  /**
-   * 
-   * The list of tests or benchmarks in this run.
-   * 

-   *
-   * .tensorflow.BenchmarkEntries entries = 2;
-   * @return The entries.
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.BenchmarkEntries getEntries() {
-    return entries_ == null ? org.tensorflow.proto.BenchmarkEntries.getDefaultInstance() : entries_;
-  }
-  /**
-   * 
-   * The list of tests or benchmarks in this run.
-   * 

-   *
-   * .tensorflow.BenchmarkEntries entries = 2;
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.BenchmarkEntriesOrBuilder getEntriesOrBuilder() {
-    return getEntries();
-  }
-
-  public static final int BUILD_CONFIGURATION_FIELD_NUMBER = 3;
-  private org.tensorflow.proto.BuildConfiguration buildConfiguration_;
-  /**
-   * 
-   * The configuration of the build (compiled opt? with cuda? any copts?)
-   * 

-   *
-   * .tensorflow.BuildConfiguration build_configuration = 3;
-   * @return Whether the buildConfiguration field is set.
-   */
-  @java.lang.Override
-  public boolean hasBuildConfiguration() {
-    return buildConfiguration_ != null;
-  }
-  /**
-   * 
-   * The configuration of the build (compiled opt? with cuda? any copts?)
-   * 

-   *
-   * .tensorflow.BuildConfiguration build_configuration = 3;
-   * @return The buildConfiguration.
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.BuildConfiguration getBuildConfiguration() {
-    return buildConfiguration_ == null ? org.tensorflow.proto.BuildConfiguration.getDefaultInstance() : buildConfiguration_;
-  }
-  /**
-   * 
-   * The configuration of the build (compiled opt? with cuda? any copts?)
-   * 

-   *
-   * .tensorflow.BuildConfiguration build_configuration = 3;
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.BuildConfigurationOrBuilder getBuildConfigurationOrBuilder() {
-    return getBuildConfiguration();
-  }
-
-  public static final int COMMIT_ID_FIELD_NUMBER = 4;
-  private org.tensorflow.proto.CommitId commitId_;
-  /**
-   * 
-   * The commit id (git hash or changelist)
-   * 

-   *
-   * .tensorflow.CommitId commit_id = 4;
-   * @return Whether the commitId field is set.
-   */
-  @java.lang.Override
-  public boolean hasCommitId() {
-    return commitId_ != null;
-  }
-  /**
-   * 
-   * The commit id (git hash or changelist)
-   * 

-   *
-   * .tensorflow.CommitId commit_id = 4;
-   * @return The commitId.
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.CommitId getCommitId() {
-    return commitId_ == null ? org.tensorflow.proto.CommitId.getDefaultInstance() : commitId_;
-  }
-  /**
-   * 
-   * The commit id (git hash or changelist)
-   * 

-   *
-   * .tensorflow.CommitId commit_id = 4;
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.CommitIdOrBuilder getCommitIdOrBuilder() {
-    return getCommitId();
-  }
-
-  public static final int START_TIME_FIELD_NUMBER = 5;
-  private long startTime_;
-  /**
-   * 
-   * The time the run started (in seconds of UTC time since Unix epoch)
-   * 

-   *
-   * int64 start_time = 5;
-   * @return The startTime.
-   */
-  @java.lang.Override
-  public long getStartTime() {
-    return startTime_;
-  }
-
-  public static final int RUN_TIME_FIELD_NUMBER = 6;
-  private double runTime_;
-  /**
-   * 
-   * The amount of time the total run took (wall time in seconds)
-   * 

-   *
-   * double run_time = 6;
-   * @return The runTime.
-   */
-  @java.lang.Override
-  public double getRunTime() {
-    return runTime_;
-  }
-
-  public static final int MACHINE_CONFIGURATION_FIELD_NUMBER = 7;
-  private org.tensorflow.proto.MachineConfiguration machineConfiguration_;
-  /**
-   * 
-   * Machine-specific parameters (Platform and CPU info)
-   * 

-   *
-   * .tensorflow.MachineConfiguration machine_configuration = 7;
-   * @return Whether the machineConfiguration field is set.
-   */
-  @java.lang.Override
-  public boolean hasMachineConfiguration() {
-    return machineConfiguration_ != null;
-  }
-  /**
-   * 
-   * Machine-specific parameters (Platform and CPU info)
-   * 

-   *
-   * .tensorflow.MachineConfiguration machine_configuration = 7;
-   * @return The machineConfiguration.
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.MachineConfiguration getMachineConfiguration() {
-    return machineConfiguration_ == null ? org.tensorflow.proto.MachineConfiguration.getDefaultInstance() : machineConfiguration_;
-  }
-  /**
-   * 
-   * Machine-specific parameters (Platform and CPU info)
-   * 

-   *
-   * .tensorflow.MachineConfiguration machine_configuration = 7;
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.MachineConfigurationOrBuilder getMachineConfigurationOrBuilder() {
-    return getMachineConfiguration();
-  }
-
-  public static final int RUN_CONFIGURATION_FIELD_NUMBER = 8;
-  private org.tensorflow.proto.RunConfiguration runConfiguration_;
-  /**
-   * 
-   * Run-specific parameters (arguments, etc)
-   * 

-   *
-   * .tensorflow.RunConfiguration run_configuration = 8;
-   * @return Whether the runConfiguration field is set.
-   */
-  @java.lang.Override
-  public boolean hasRunConfiguration() {
-    return runConfiguration_ != null;
-  }
-  /**
-   * 
-   * Run-specific parameters (arguments, etc)
-   * 

-   *
-   * .tensorflow.RunConfiguration run_configuration = 8;
-   * @return The runConfiguration.
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.RunConfiguration getRunConfiguration() {
-    return runConfiguration_ == null ? org.tensorflow.proto.RunConfiguration.getDefaultInstance() : runConfiguration_;
-  }
-  /**
-   * 
-   * Run-specific parameters (arguments, etc)
-   * 

-   *
-   * .tensorflow.RunConfiguration run_configuration = 8;
-   */
-  @java.lang.Override
-  public org.tensorflow.proto.RunConfigurationOrBuilder getRunConfigurationOrBuilder() {
-    return getRunConfiguration();
-  }
-
-  public static final int NAME_FIELD_NUMBER = 9;
-  private volatile java.lang.Object name_;
-  /**
-   * 
-   * Benchmark target identifier.
-   * 

-   *
-   * string name = 9;
-   * @return The name.
-   */
-  @java.lang.Override
-  public java.lang.String getName() {
-    java.lang.Object ref = name_;
-    if (ref instanceof java.lang.String) {
-      return (java.lang.String) ref;
-    } else {
-      com.google.protobuf.ByteString bs = 
-          (com.google.protobuf.ByteString) ref;
-      java.lang.String s = bs.toStringUtf8();
-      name_ = s;
-      return s;
-    }
-  }
-  /**
-   * 
-   * Benchmark target identifier.
-   * 

-   *
-   * string name = 9;
-   * @return The bytes for name.
-   */
-  @java.lang.Override
-  public com.google.protobuf.ByteString
-      getNameBytes() {
-    java.lang.Object ref = name_;
-    if (ref instanceof java.lang.String) {
-      com.google.protobuf.ByteString b = 
-          com.google.protobuf.ByteString.copyFromUtf8(
-              (java.lang.String) ref);
-      name_ = b;
-      return b;
-    } else {
-      return (com.google.protobuf.ByteString) ref;
-    }
-  }
-
-  public static final int BENCHMARK_TYPE_FIELD_NUMBER = 10;
-  private int benchmarkType_;
-  /**
-   * .tensorflow.TestResults.BenchmarkType benchmark_type = 10;
-   * @return The enum numeric value on the wire for benchmarkType.
-   */
-  @java.lang.Override public int getBenchmarkTypeValue() {
-    return benchmarkType_;
-  }
-  /**
-   * .tensorflow.TestResults.BenchmarkType benchmark_type = 10;
-   * @return The benchmarkType.
-   */
-  @java.lang.Override public org.tensorflow.proto.TestResults.BenchmarkType getBenchmarkType() {
-    @SuppressWarnings("deprecation")
-    org.tensorflow.proto.TestResults.BenchmarkType result = org.tensorflow.proto.TestResults.BenchmarkType.valueOf(benchmarkType_);
-    return result == null ? org.tensorflow.proto.TestResults.BenchmarkType.UNRECOGNIZED : result;
-  }
-
-  public static final int RUN_MODE_FIELD_NUMBER = 11;
-  private volatile java.lang.Object runMode_;
-  /**
-   * 
-   * Used for differentiating between continuous and debug builds.
-   * Must be one of:
-   * * cbuild: results from continuous build.
-   * * presubmit: results from oneshot requests.
-   * * culprit: results from culprit finder rerun.
-   * 

-   *
-   * string run_mode = 11;
-   * @return The runMode.
-   */
-  @java.lang.Override
-  public java.lang.String getRunMode() {
-    java.lang.Object ref = runMode_;
-    if (ref instanceof java.lang.String) {
-      return (java.lang.String) ref;
-    } else {
-      com.google.protobuf.ByteString bs = 
-          (com.google.protobuf.ByteString) ref;
-      java.lang.String s = bs.toStringUtf8();
-      runMode_ = s;
-      return s;
-    }
-  }
-  /**
-   * 
-   * Used for differentiating between continuous and debug builds.
-   * Must be one of:
-   * * cbuild: results from continuous build.
-   * * presubmit: results from oneshot requests.
-   * * culprit: results from culprit finder rerun.
-   * 

-   *
-   * string run_mode = 11;
-   * @return The bytes for runMode.
-   */
-  @java.lang.Override
-  public com.google.protobuf.ByteString
-      getRunModeBytes() {
-    java.lang.Object ref = runMode_;
-    if (ref instanceof java.lang.String) {
-      com.google.protobuf.ByteString b = 
-          com.google.protobuf.ByteString.copyFromUtf8(
-              (java.lang.String) ref);
-      runMode_ = b;
-      return b;
-    } else {
-      return (com.google.protobuf.ByteString) ref;
-    }
-  }
-
-  public static final int TF_VERSION_FIELD_NUMBER = 12;
-  private volatile java.lang.Object tfVersion_;
-  /**
-   * 
-   * TensorFlow version this benchmark runs against.
-   * This can be either set to full version or just the major version.
-   * 

-   *
-   * string tf_version = 12;
-   * @return The tfVersion.
-   */
-  @java.lang.Override
-  public java.lang.String getTfVersion() {
-    java.lang.Object ref = tfVersion_;
-    if (ref instanceof java.lang.String) {
-      return (java.lang.String) ref;
-    } else {
-      com.google.protobuf.ByteString bs = 
-          (com.google.protobuf.ByteString) ref;
-      java.lang.String s = bs.toStringUtf8();
-      tfVersion_ = s;
-      return s;
-    }
-  }
-  /**
-   * 
-   * TensorFlow version this benchmark runs against.
-   * This can be either set to full version or just the major version.
-   * 

-   *
-   * string tf_version = 12;
-   * @return The bytes for tfVersion.
-   */
-  @java.lang.Override
-  public com.google.protobuf.ByteString
-      getTfVersionBytes() {
-    java.lang.Object ref = tfVersion_;
-    if (ref instanceof java.lang.String) {
-      com.google.protobuf.ByteString b = 
-          com.google.protobuf.ByteString.copyFromUtf8(
-              (java.lang.String) ref);
-      tfVersion_ = b;
-      return b;
-    } else {
-      return (com.google.protobuf.ByteString) ref;
-    }
-  }
-
-  private byte memoizedIsInitialized = -1;
-  @java.lang.Override
-  public final boolean isInitialized() {
-    byte isInitialized = memoizedIsInitialized;
-    if (isInitialized == 1) return true;
-    if (isInitialized == 0) return false;
-
-    memoizedIsInitialized = 1;
-    return true;
-  }
-
-  @java.lang.Override
-  public void writeTo(com.google.protobuf.CodedOutputStream output)
-                      throws java.io.IOException {
-    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(target_)) {
-      com.google.protobuf.GeneratedMessageV3.writeString(output, 1, target_);
-    }
-    if (entries_ != null) {
-      output.writeMessage(2, getEntries());
-    }
-    if (buildConfiguration_ != null) {
-      output.writeMessage(3, getBuildConfiguration());
-    }
-    if (commitId_ != null) {
-      output.writeMessage(4, getCommitId());
-    }
-    if (startTime_ != 0L) {
-      output.writeInt64(5, startTime_);
-    }
-    if (java.lang.Double.doubleToRawLongBits(runTime_) != 0) {
-      output.writeDouble(6, runTime_);
-    }
-    if (machineConfiguration_ != null) {
-      output.writeMessage(7, getMachineConfiguration());
-    }
-    if (runConfiguration_ != null) {
-      output.writeMessage(8, getRunConfiguration());
-    }
-    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) {
-      com.google.protobuf.GeneratedMessageV3.writeString(output, 9, name_);
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-    if (benchmarkType_ != org.tensorflow.proto.TestResults.BenchmarkType.UNKNOWN.getNumber()) {
-      output.writeEnum(10, benchmarkType_);
-    }
-    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(runMode_)) {
-      com.google.protobuf.GeneratedMessageV3.writeString(output, 11, runMode_);
-    }
-    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(tfVersion_)) {
-      com.google.protobuf.GeneratedMessageV3.writeString(output, 12, tfVersion_);
-    }
-    getUnknownFields().writeTo(output);
-  }
-
-  @java.lang.Override
-  public int getSerializedSize() {
-    int size = memoizedSize;
-    if (size != -1) return size;
-
-    size = 0;
-    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(target_)) {
-      size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, target_);
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-    if (entries_ != null) {
-      size += com.google.protobuf.CodedOutputStream
-        .computeMessageSize(2, getEntries());
-    }
-    if (buildConfiguration_ != null) {
-      size += com.google.protobuf.CodedOutputStream
-        .computeMessageSize(3, getBuildConfiguration());
-    }
-    if (commitId_ != null) {
-      size += com.google.protobuf.CodedOutputStream
-        .computeMessageSize(4, getCommitId());
-    }
-    if (startTime_ != 0L) {
-      size += com.google.protobuf.CodedOutputStream
-        .computeInt64Size(5, startTime_);
-    }
-    if (java.lang.Double.doubleToRawLongBits(runTime_) != 0) {
-      size += com.google.protobuf.CodedOutputStream
-        .computeDoubleSize(6, runTime_);
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-    if (machineConfiguration_ != null) {
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-    if (runConfiguration_ != null) {
-      size += com.google.protobuf.CodedOutputStream
-        .computeMessageSize(8, getRunConfiguration());
-    }
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-     * .tensorflow.BenchmarkEntries entries = 2;
-     */
-    public Builder clearEntries() {
-      if (entriesBuilder_ == null) {
-        entries_ = null;
-        onChanged();
-      } else {
-        entries_ = null;
-        entriesBuilder_ = null;
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The list of tests or benchmarks in this run.
-     * 

-     *
-     * .tensorflow.BenchmarkEntries entries = 2;
-     */
-    public org.tensorflow.proto.BenchmarkEntries.Builder getEntriesBuilder() {
-      
-      onChanged();
-      return getEntriesFieldBuilder().getBuilder();
-    }
-    /**
-     * 
-     * The list of tests or benchmarks in this run.
-     * 

-     *
-     * .tensorflow.BenchmarkEntries entries = 2;
-     */
-    public org.tensorflow.proto.BenchmarkEntriesOrBuilder getEntriesOrBuilder() {
-      if (entriesBuilder_ != null) {
-        return entriesBuilder_.getMessageOrBuilder();
-      } else {
-        return entries_ == null ?
-            org.tensorflow.proto.BenchmarkEntries.getDefaultInstance() : entries_;
-      }
-    }
-    /**
-     * 
-     * The list of tests or benchmarks in this run.
-     * 

-     *
-     * .tensorflow.BenchmarkEntries entries = 2;
-     */
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.BenchmarkEntries, org.tensorflow.proto.BenchmarkEntries.Builder, org.tensorflow.proto.BenchmarkEntriesOrBuilder> 
-        getEntriesFieldBuilder() {
-      if (entriesBuilder_ == null) {
-        entriesBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
-            org.tensorflow.proto.BenchmarkEntries, org.tensorflow.proto.BenchmarkEntries.Builder, org.tensorflow.proto.BenchmarkEntriesOrBuilder>(
-                getEntries(),
-                getParentForChildren(),
-                isClean());
-        entries_ = null;
-      }
-      return entriesBuilder_;
-    }
-
-    private org.tensorflow.proto.BuildConfiguration buildConfiguration_;
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.BuildConfiguration, org.tensorflow.proto.BuildConfiguration.Builder, org.tensorflow.proto.BuildConfigurationOrBuilder> buildConfigurationBuilder_;
-    /**
-     * 
-     * The configuration of the build (compiled opt? with cuda? any copts?)
-     * 

-     *
-     * .tensorflow.BuildConfiguration build_configuration = 3;
-     * @return Whether the buildConfiguration field is set.
-     */
-    public boolean hasBuildConfiguration() {
-      return buildConfigurationBuilder_ != null || buildConfiguration_ != null;
-    }
-    /**
-     * 
-     * The configuration of the build (compiled opt? with cuda? any copts?)
-     * 

-     *
-     * .tensorflow.BuildConfiguration build_configuration = 3;
-     * @return The buildConfiguration.
-     */
-    public org.tensorflow.proto.BuildConfiguration getBuildConfiguration() {
-      if (buildConfigurationBuilder_ == null) {
-        return buildConfiguration_ == null ? org.tensorflow.proto.BuildConfiguration.getDefaultInstance() : buildConfiguration_;
-      } else {
-        return buildConfigurationBuilder_.getMessage();
-      }
-    }
-    /**
-     * 
-     * The configuration of the build (compiled opt? with cuda? any copts?)
-     * 

-     *
-     * .tensorflow.BuildConfiguration build_configuration = 3;
-     */
-    public Builder setBuildConfiguration(org.tensorflow.proto.BuildConfiguration value) {
-      if (buildConfigurationBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        buildConfiguration_ = value;
-        onChanged();
-      } else {
-        buildConfigurationBuilder_.setMessage(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The configuration of the build (compiled opt? with cuda? any copts?)
-     * 

-     *
-     * .tensorflow.BuildConfiguration build_configuration = 3;
-     */
-    public Builder setBuildConfiguration(
-        org.tensorflow.proto.BuildConfiguration.Builder builderForValue) {
-      if (buildConfigurationBuilder_ == null) {
-        buildConfiguration_ = builderForValue.build();
-        onChanged();
-      } else {
-        buildConfigurationBuilder_.setMessage(builderForValue.build());
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The configuration of the build (compiled opt? with cuda? any copts?)
-     * 

-     *
-     * .tensorflow.BuildConfiguration build_configuration = 3;
-     */
-    public Builder mergeBuildConfiguration(org.tensorflow.proto.BuildConfiguration value) {
-      if (buildConfigurationBuilder_ == null) {
-        if (buildConfiguration_ != null) {
-          buildConfiguration_ =
-            org.tensorflow.proto.BuildConfiguration.newBuilder(buildConfiguration_).mergeFrom(value).buildPartial();
-        } else {
-          buildConfiguration_ = value;
-        }
-        onChanged();
-      } else {
-        buildConfigurationBuilder_.mergeFrom(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The configuration of the build (compiled opt? with cuda? any copts?)
-     * 

-     *
-     * .tensorflow.BuildConfiguration build_configuration = 3;
-     */
-    public Builder clearBuildConfiguration() {
-      if (buildConfigurationBuilder_ == null) {
-        buildConfiguration_ = null;
-        onChanged();
-      } else {
-        buildConfiguration_ = null;
-        buildConfigurationBuilder_ = null;
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The configuration of the build (compiled opt? with cuda? any copts?)
-     * 

-     *
-     * .tensorflow.BuildConfiguration build_configuration = 3;
-     */
-    public org.tensorflow.proto.BuildConfiguration.Builder getBuildConfigurationBuilder() {
-      
-      onChanged();
-      return getBuildConfigurationFieldBuilder().getBuilder();
-    }
-    /**
-     * 
-     * The configuration of the build (compiled opt? with cuda? any copts?)
-     * 

-     *
-     * .tensorflow.BuildConfiguration build_configuration = 3;
-     */
-    public org.tensorflow.proto.BuildConfigurationOrBuilder getBuildConfigurationOrBuilder() {
-      if (buildConfigurationBuilder_ != null) {
-        return buildConfigurationBuilder_.getMessageOrBuilder();
-      } else {
-        return buildConfiguration_ == null ?
-            org.tensorflow.proto.BuildConfiguration.getDefaultInstance() : buildConfiguration_;
-      }
-    }
-    /**
-     * 
-     * The configuration of the build (compiled opt? with cuda? any copts?)
-     * 

-     *
-     * .tensorflow.BuildConfiguration build_configuration = 3;
-     */
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.BuildConfiguration, org.tensorflow.proto.BuildConfiguration.Builder, org.tensorflow.proto.BuildConfigurationOrBuilder> 
-        getBuildConfigurationFieldBuilder() {
-      if (buildConfigurationBuilder_ == null) {
-        buildConfigurationBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
-            org.tensorflow.proto.BuildConfiguration, org.tensorflow.proto.BuildConfiguration.Builder, org.tensorflow.proto.BuildConfigurationOrBuilder>(
-                getBuildConfiguration(),
-                getParentForChildren(),
-                isClean());
-        buildConfiguration_ = null;
-      }
-      return buildConfigurationBuilder_;
-    }
-
-    private org.tensorflow.proto.CommitId commitId_;
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.CommitId, org.tensorflow.proto.CommitId.Builder, org.tensorflow.proto.CommitIdOrBuilder> commitIdBuilder_;
-    /**
-     * 
-     * The commit id (git hash or changelist)
-     * 

-     *
-     * .tensorflow.CommitId commit_id = 4;
-     * @return Whether the commitId field is set.
-     */
-    public boolean hasCommitId() {
-      return commitIdBuilder_ != null || commitId_ != null;
-    }
-    /**
-     * 
-     * The commit id (git hash or changelist)
-     * 

-     *
-     * .tensorflow.CommitId commit_id = 4;
-     * @return The commitId.
-     */
-    public org.tensorflow.proto.CommitId getCommitId() {
-      if (commitIdBuilder_ == null) {
-        return commitId_ == null ? org.tensorflow.proto.CommitId.getDefaultInstance() : commitId_;
-      } else {
-        return commitIdBuilder_.getMessage();
-      }
-    }
-    /**
-     * 
-     * The commit id (git hash or changelist)
-     * 

-     *
-     * .tensorflow.CommitId commit_id = 4;
-     */
-    public Builder setCommitId(org.tensorflow.proto.CommitId value) {
-      if (commitIdBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        commitId_ = value;
-        onChanged();
-      } else {
-        commitIdBuilder_.setMessage(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The commit id (git hash or changelist)
-     * 

-     *
-     * .tensorflow.CommitId commit_id = 4;
-     */
-    public Builder setCommitId(
-        org.tensorflow.proto.CommitId.Builder builderForValue) {
-      if (commitIdBuilder_ == null) {
-        commitId_ = builderForValue.build();
-        onChanged();
-      } else {
-        commitIdBuilder_.setMessage(builderForValue.build());
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The commit id (git hash or changelist)
-     * 

-     *
-     * .tensorflow.CommitId commit_id = 4;
-     */
-    public Builder mergeCommitId(org.tensorflow.proto.CommitId value) {
-      if (commitIdBuilder_ == null) {
-        if (commitId_ != null) {
-          commitId_ =
-            org.tensorflow.proto.CommitId.newBuilder(commitId_).mergeFrom(value).buildPartial();
-        } else {
-          commitId_ = value;
-        }
-        onChanged();
-      } else {
-        commitIdBuilder_.mergeFrom(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The commit id (git hash or changelist)
-     * 

-     *
-     * .tensorflow.CommitId commit_id = 4;
-     */
-    public Builder clearCommitId() {
-      if (commitIdBuilder_ == null) {
-        commitId_ = null;
-        onChanged();
-      } else {
-        commitId_ = null;
-        commitIdBuilder_ = null;
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * The commit id (git hash or changelist)
-     * 

-     *
-     * .tensorflow.CommitId commit_id = 4;
-     */
-    public org.tensorflow.proto.CommitId.Builder getCommitIdBuilder() {
-      
-      onChanged();
-      return getCommitIdFieldBuilder().getBuilder();
-    }
-    /**
-     * 
-     * The commit id (git hash or changelist)
-     * 

-     *
-     * .tensorflow.CommitId commit_id = 4;
-     */
-    public org.tensorflow.proto.CommitIdOrBuilder getCommitIdOrBuilder() {
-      if (commitIdBuilder_ != null) {
-        return commitIdBuilder_.getMessageOrBuilder();
-      } else {
-        return commitId_ == null ?
-            org.tensorflow.proto.CommitId.getDefaultInstance() : commitId_;
-      }
-    }
-    /**
-     * 
-     * The commit id (git hash or changelist)
-     * 

-     *
-     * .tensorflow.CommitId commit_id = 4;
-     */
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.CommitId, org.tensorflow.proto.CommitId.Builder, org.tensorflow.proto.CommitIdOrBuilder> 
-        getCommitIdFieldBuilder() {
-      if (commitIdBuilder_ == null) {
-        commitIdBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
-            org.tensorflow.proto.CommitId, org.tensorflow.proto.CommitId.Builder, org.tensorflow.proto.CommitIdOrBuilder>(
-                getCommitId(),
-                getParentForChildren(),
-                isClean());
-        commitId_ = null;
-      }
-      return commitIdBuilder_;
-    }
-
-    private long startTime_ ;
-    /**
-     * 
-     * The time the run started (in seconds of UTC time since Unix epoch)
-     * 

-     *
-     * int64 start_time = 5;
-     * @return The startTime.
-     */
-    @java.lang.Override
-    public long getStartTime() {
-      return startTime_;
-    }
-    /**
-     * 
-     * The time the run started (in seconds of UTC time since Unix epoch)
-     * 

-     *
-     * int64 start_time = 5;
-     * @param value The startTime to set.
-     * @return This builder for chaining.
-     */
-    public Builder setStartTime(long value) {
-      
-      startTime_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * The time the run started (in seconds of UTC time since Unix epoch)
-     * 

-     *
-     * int64 start_time = 5;
-     * @return This builder for chaining.
-     */
-    public Builder clearStartTime() {
-      
-      startTime_ = 0L;
-      onChanged();
-      return this;
-    }
-
-    private double runTime_ ;
-    /**
-     * 
-     * The amount of time the total run took (wall time in seconds)
-     * 

-     *
-     * double run_time = 6;
-     * @return The runTime.
-     */
-    @java.lang.Override
-    public double getRunTime() {
-      return runTime_;
-    }
-    /**
-     * 
-     * The amount of time the total run took (wall time in seconds)
-     * 

-     *
-     * double run_time = 6;
-     * @param value The runTime to set.
-     * @return This builder for chaining.
-     */
-    public Builder setRunTime(double value) {
-      
-      runTime_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * The amount of time the total run took (wall time in seconds)
-     * 

-     *
-     * double run_time = 6;
-     * @return This builder for chaining.
-     */
-    public Builder clearRunTime() {
-      
-      runTime_ = 0D;
-      onChanged();
-      return this;
-    }
-
-    private org.tensorflow.proto.MachineConfiguration machineConfiguration_;
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.MachineConfiguration, org.tensorflow.proto.MachineConfiguration.Builder, org.tensorflow.proto.MachineConfigurationOrBuilder> machineConfigurationBuilder_;
-    /**
-     * 
-     * Machine-specific parameters (Platform and CPU info)
-     * 

-     *
-     * .tensorflow.MachineConfiguration machine_configuration = 7;
-     * @return Whether the machineConfiguration field is set.
-     */
-    public boolean hasMachineConfiguration() {
-      return machineConfigurationBuilder_ != null || machineConfiguration_ != null;
-    }
-    /**
-     * 
-     * Machine-specific parameters (Platform and CPU info)
-     * 

-     *
-     * .tensorflow.MachineConfiguration machine_configuration = 7;
-     * @return The machineConfiguration.
-     */
-    public org.tensorflow.proto.MachineConfiguration getMachineConfiguration() {
-      if (machineConfigurationBuilder_ == null) {
-        return machineConfiguration_ == null ? org.tensorflow.proto.MachineConfiguration.getDefaultInstance() : machineConfiguration_;
-      } else {
-        return machineConfigurationBuilder_.getMessage();
-      }
-    }
-    /**
-     * 
-     * Machine-specific parameters (Platform and CPU info)
-     * 

-     *
-     * .tensorflow.MachineConfiguration machine_configuration = 7;
-     */
-    public Builder setMachineConfiguration(org.tensorflow.proto.MachineConfiguration value) {
-      if (machineConfigurationBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        machineConfiguration_ = value;
-        onChanged();
-      } else {
-        machineConfigurationBuilder_.setMessage(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * Machine-specific parameters (Platform and CPU info)
-     * 

-     *
-     * .tensorflow.MachineConfiguration machine_configuration = 7;
-     */
-    public Builder setMachineConfiguration(
-        org.tensorflow.proto.MachineConfiguration.Builder builderForValue) {
-      if (machineConfigurationBuilder_ == null) {
-        machineConfiguration_ = builderForValue.build();
-        onChanged();
-      } else {
-        machineConfigurationBuilder_.setMessage(builderForValue.build());
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * Machine-specific parameters (Platform and CPU info)
-     * 

-     *
-     * .tensorflow.MachineConfiguration machine_configuration = 7;
-     */
-    public Builder mergeMachineConfiguration(org.tensorflow.proto.MachineConfiguration value) {
-      if (machineConfigurationBuilder_ == null) {
-        if (machineConfiguration_ != null) {
-          machineConfiguration_ =
-            org.tensorflow.proto.MachineConfiguration.newBuilder(machineConfiguration_).mergeFrom(value).buildPartial();
-        } else {
-          machineConfiguration_ = value;
-        }
-        onChanged();
-      } else {
-        machineConfigurationBuilder_.mergeFrom(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * Machine-specific parameters (Platform and CPU info)
-     * 

-     *
-     * .tensorflow.MachineConfiguration machine_configuration = 7;
-     */
-    public Builder clearMachineConfiguration() {
-      if (machineConfigurationBuilder_ == null) {
-        machineConfiguration_ = null;
-        onChanged();
-      } else {
-        machineConfiguration_ = null;
-        machineConfigurationBuilder_ = null;
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * Machine-specific parameters (Platform and CPU info)
-     * 

-     *
-     * .tensorflow.MachineConfiguration machine_configuration = 7;
-     */
-    public org.tensorflow.proto.MachineConfiguration.Builder getMachineConfigurationBuilder() {
-      
-      onChanged();
-      return getMachineConfigurationFieldBuilder().getBuilder();
-    }
-    /**
-     * 
-     * Machine-specific parameters (Platform and CPU info)
-     * 

-     *
-     * .tensorflow.MachineConfiguration machine_configuration = 7;
-     */
-    public org.tensorflow.proto.MachineConfigurationOrBuilder getMachineConfigurationOrBuilder() {
-      if (machineConfigurationBuilder_ != null) {
-        return machineConfigurationBuilder_.getMessageOrBuilder();
-      } else {
-        return machineConfiguration_ == null ?
-            org.tensorflow.proto.MachineConfiguration.getDefaultInstance() : machineConfiguration_;
-      }
-    }
-    /**
-     * 
-     * Machine-specific parameters (Platform and CPU info)
-     * 

-     *
-     * .tensorflow.MachineConfiguration machine_configuration = 7;
-     */
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.MachineConfiguration, org.tensorflow.proto.MachineConfiguration.Builder, org.tensorflow.proto.MachineConfigurationOrBuilder> 
-        getMachineConfigurationFieldBuilder() {
-      if (machineConfigurationBuilder_ == null) {
-        machineConfigurationBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
-            org.tensorflow.proto.MachineConfiguration, org.tensorflow.proto.MachineConfiguration.Builder, org.tensorflow.proto.MachineConfigurationOrBuilder>(
-                getMachineConfiguration(),
-                getParentForChildren(),
-                isClean());
-        machineConfiguration_ = null;
-      }
-      return machineConfigurationBuilder_;
-    }
-
-    private org.tensorflow.proto.RunConfiguration runConfiguration_;
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.RunConfiguration, org.tensorflow.proto.RunConfiguration.Builder, org.tensorflow.proto.RunConfigurationOrBuilder> runConfigurationBuilder_;
-    /**
-     * 
-     * Run-specific parameters (arguments, etc)
-     * 

-     *
-     * .tensorflow.RunConfiguration run_configuration = 8;
-     * @return Whether the runConfiguration field is set.
-     */
-    public boolean hasRunConfiguration() {
-      return runConfigurationBuilder_ != null || runConfiguration_ != null;
-    }
-    /**
-     * 
-     * Run-specific parameters (arguments, etc)
-     * 

-     *
-     * .tensorflow.RunConfiguration run_configuration = 8;
-     * @return The runConfiguration.
-     */
-    public org.tensorflow.proto.RunConfiguration getRunConfiguration() {
-      if (runConfigurationBuilder_ == null) {
-        return runConfiguration_ == null ? org.tensorflow.proto.RunConfiguration.getDefaultInstance() : runConfiguration_;
-      } else {
-        return runConfigurationBuilder_.getMessage();
-      }
-    }
-    /**
-     * 
-     * Run-specific parameters (arguments, etc)
-     * 

-     *
-     * .tensorflow.RunConfiguration run_configuration = 8;
-     */
-    public Builder setRunConfiguration(org.tensorflow.proto.RunConfiguration value) {
-      if (runConfigurationBuilder_ == null) {
-        if (value == null) {
-          throw new NullPointerException();
-        }
-        runConfiguration_ = value;
-        onChanged();
-      } else {
-        runConfigurationBuilder_.setMessage(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * Run-specific parameters (arguments, etc)
-     * 

-     *
-     * .tensorflow.RunConfiguration run_configuration = 8;
-     */
-    public Builder setRunConfiguration(
-        org.tensorflow.proto.RunConfiguration.Builder builderForValue) {
-      if (runConfigurationBuilder_ == null) {
-        runConfiguration_ = builderForValue.build();
-        onChanged();
-      } else {
-        runConfigurationBuilder_.setMessage(builderForValue.build());
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * Run-specific parameters (arguments, etc)
-     * 

-     *
-     * .tensorflow.RunConfiguration run_configuration = 8;
-     */
-    public Builder mergeRunConfiguration(org.tensorflow.proto.RunConfiguration value) {
-      if (runConfigurationBuilder_ == null) {
-        if (runConfiguration_ != null) {
-          runConfiguration_ =
-            org.tensorflow.proto.RunConfiguration.newBuilder(runConfiguration_).mergeFrom(value).buildPartial();
-        } else {
-          runConfiguration_ = value;
-        }
-        onChanged();
-      } else {
-        runConfigurationBuilder_.mergeFrom(value);
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * Run-specific parameters (arguments, etc)
-     * 

-     *
-     * .tensorflow.RunConfiguration run_configuration = 8;
-     */
-    public Builder clearRunConfiguration() {
-      if (runConfigurationBuilder_ == null) {
-        runConfiguration_ = null;
-        onChanged();
-      } else {
-        runConfiguration_ = null;
-        runConfigurationBuilder_ = null;
-      }
-
-      return this;
-    }
-    /**
-     * 
-     * Run-specific parameters (arguments, etc)
-     * 

-     *
-     * .tensorflow.RunConfiguration run_configuration = 8;
-     */
-    public org.tensorflow.proto.RunConfiguration.Builder getRunConfigurationBuilder() {
-      
-      onChanged();
-      return getRunConfigurationFieldBuilder().getBuilder();
-    }
-    /**
-     * 
-     * Run-specific parameters (arguments, etc)
-     * 

-     *
-     * .tensorflow.RunConfiguration run_configuration = 8;
-     */
-    public org.tensorflow.proto.RunConfigurationOrBuilder getRunConfigurationOrBuilder() {
-      if (runConfigurationBuilder_ != null) {
-        return runConfigurationBuilder_.getMessageOrBuilder();
-      } else {
-        return runConfiguration_ == null ?
-            org.tensorflow.proto.RunConfiguration.getDefaultInstance() : runConfiguration_;
-      }
-    }
-    /**
-     * 
-     * Run-specific parameters (arguments, etc)
-     * 

-     *
-     * .tensorflow.RunConfiguration run_configuration = 8;
-     */
-    private com.google.protobuf.SingleFieldBuilderV3<
-        org.tensorflow.proto.RunConfiguration, org.tensorflow.proto.RunConfiguration.Builder, org.tensorflow.proto.RunConfigurationOrBuilder> 
-        getRunConfigurationFieldBuilder() {
-      if (runConfigurationBuilder_ == null) {
-        runConfigurationBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
-            org.tensorflow.proto.RunConfiguration, org.tensorflow.proto.RunConfiguration.Builder, org.tensorflow.proto.RunConfigurationOrBuilder>(
-                getRunConfiguration(),
-                getParentForChildren(),
-                isClean());
-        runConfiguration_ = null;
-      }
-      return runConfigurationBuilder_;
-    }
-
-    private java.lang.Object name_ = "";
-    /**
-     * 
-     * Benchmark target identifier.
-     * 

-     *
-     * string name = 9;
-     * @return The name.
-     */
-    public java.lang.String getName() {
-      java.lang.Object ref = name_;
-      if (!(ref instanceof java.lang.String)) {
-        com.google.protobuf.ByteString bs =
-            (com.google.protobuf.ByteString) ref;
-        java.lang.String s = bs.toStringUtf8();
-        name_ = s;
-        return s;
-      } else {
-        return (java.lang.String) ref;
-      }
-    }
-    /**
-     * 
-     * Benchmark target identifier.
-     * 

-     *
-     * string name = 9;
-     * @return The bytes for name.
-     */
-    public com.google.protobuf.ByteString
-        getNameBytes() {
-      java.lang.Object ref = name_;
-      if (ref instanceof String) {
-        com.google.protobuf.ByteString b = 
-            com.google.protobuf.ByteString.copyFromUtf8(
-                (java.lang.String) ref);
-        name_ = b;
-        return b;
-      } else {
-        return (com.google.protobuf.ByteString) ref;
-      }
-    }
-    /**
-     * 
-     * Benchmark target identifier.
-     * 

-     *
-     * string name = 9;
-     * @param value The name to set.
-     * @return This builder for chaining.
-     */
-    public Builder setName(
-        java.lang.String value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  
-      name_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * Benchmark target identifier.
-     * 

-     *
-     * string name = 9;
-     * @return This builder for chaining.
-     */
-    public Builder clearName() {
-      
-      name_ = getDefaultInstance().getName();
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * Benchmark target identifier.
-     * 

-     *
-     * string name = 9;
-     * @param value The bytes for name to set.
-     * @return This builder for chaining.
-     */
-    public Builder setNameBytes(
-        com.google.protobuf.ByteString value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  checkByteStringIsUtf8(value);
-      
-      name_ = value;
-      onChanged();
-      return this;
-    }
-
-    private int benchmarkType_ = 0;
-    /**
-     * .tensorflow.TestResults.BenchmarkType benchmark_type = 10;
-     * @return The enum numeric value on the wire for benchmarkType.
-     */
-    @java.lang.Override public int getBenchmarkTypeValue() {
-      return benchmarkType_;
-    }
-    /**
-     * .tensorflow.TestResults.BenchmarkType benchmark_type = 10;
-     * @param value The enum numeric value on the wire for benchmarkType to set.
-     * @return This builder for chaining.
-     */
-    public Builder setBenchmarkTypeValue(int value) {
-      
-      benchmarkType_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * .tensorflow.TestResults.BenchmarkType benchmark_type = 10;
-     * @return The benchmarkType.
-     */
-    @java.lang.Override
-    public org.tensorflow.proto.TestResults.BenchmarkType getBenchmarkType() {
-      @SuppressWarnings("deprecation")
-      org.tensorflow.proto.TestResults.BenchmarkType result = org.tensorflow.proto.TestResults.BenchmarkType.valueOf(benchmarkType_);
-      return result == null ? org.tensorflow.proto.TestResults.BenchmarkType.UNRECOGNIZED : result;
-    }
-    /**
-     * .tensorflow.TestResults.BenchmarkType benchmark_type = 10;
-     * @param value The benchmarkType to set.
-     * @return This builder for chaining.
-     */
-    public Builder setBenchmarkType(org.tensorflow.proto.TestResults.BenchmarkType value) {
-      if (value == null) {
-        throw new NullPointerException();
-      }
-      
-      benchmarkType_ = value.getNumber();
-      onChanged();
-      return this;
-    }
-    /**
-     * .tensorflow.TestResults.BenchmarkType benchmark_type = 10;
-     * @return This builder for chaining.
-     */
-    public Builder clearBenchmarkType() {
-      
-      benchmarkType_ = 0;
-      onChanged();
-      return this;
-    }
-
-    private java.lang.Object runMode_ = "";
-    /**
-     * 
-     * Used for differentiating between continuous and debug builds.
-     * Must be one of:
-     * * cbuild: results from continuous build.
-     * * presubmit: results from oneshot requests.
-     * * culprit: results from culprit finder rerun.
-     * 

-     *
-     * string run_mode = 11;
-     * @return The runMode.
-     */
-    public java.lang.String getRunMode() {
-      java.lang.Object ref = runMode_;
-      if (!(ref instanceof java.lang.String)) {
-        com.google.protobuf.ByteString bs =
-            (com.google.protobuf.ByteString) ref;
-        java.lang.String s = bs.toStringUtf8();
-        runMode_ = s;
-        return s;
-      } else {
-        return (java.lang.String) ref;
-      }
-    }
-    /**
-     * 
-     * Used for differentiating between continuous and debug builds.
-     * Must be one of:
-     * * cbuild: results from continuous build.
-     * * presubmit: results from oneshot requests.
-     * * culprit: results from culprit finder rerun.
-     * 

-     *
-     * string run_mode = 11;
-     * @return The bytes for runMode.
-     */
-    public com.google.protobuf.ByteString
-        getRunModeBytes() {
-      java.lang.Object ref = runMode_;
-      if (ref instanceof String) {
-        com.google.protobuf.ByteString b = 
-            com.google.protobuf.ByteString.copyFromUtf8(
-                (java.lang.String) ref);
-        runMode_ = b;
-        return b;
-      } else {
-        return (com.google.protobuf.ByteString) ref;
-      }
-    }
-    /**
-     * 
-     * Used for differentiating between continuous and debug builds.
-     * Must be one of:
-     * * cbuild: results from continuous build.
-     * * presubmit: results from oneshot requests.
-     * * culprit: results from culprit finder rerun.
-     * 

-     *
-     * string run_mode = 11;
-     * @param value The runMode to set.
-     * @return This builder for chaining.
-     */
-    public Builder setRunMode(
-        java.lang.String value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  
-      runMode_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * Used for differentiating between continuous and debug builds.
-     * Must be one of:
-     * * cbuild: results from continuous build.
-     * * presubmit: results from oneshot requests.
-     * * culprit: results from culprit finder rerun.
-     * 

-     *
-     * string run_mode = 11;
-     * @return This builder for chaining.
-     */
-    public Builder clearRunMode() {
-      
-      runMode_ = getDefaultInstance().getRunMode();
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * Used for differentiating between continuous and debug builds.
-     * Must be one of:
-     * * cbuild: results from continuous build.
-     * * presubmit: results from oneshot requests.
-     * * culprit: results from culprit finder rerun.
-     * 

-     *
-     * string run_mode = 11;
-     * @param value The bytes for runMode to set.
-     * @return This builder for chaining.
-     */
-    public Builder setRunModeBytes(
-        com.google.protobuf.ByteString value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  checkByteStringIsUtf8(value);
-      
-      runMode_ = value;
-      onChanged();
-      return this;
-    }
-
-    private java.lang.Object tfVersion_ = "";
-    /**
-     * 
-     * TensorFlow version this benchmark runs against.
-     * This can be either set to full version or just the major version.
-     * 

-     *
-     * string tf_version = 12;
-     * @return The tfVersion.
-     */
-    public java.lang.String getTfVersion() {
-      java.lang.Object ref = tfVersion_;
-      if (!(ref instanceof java.lang.String)) {
-        com.google.protobuf.ByteString bs =
-            (com.google.protobuf.ByteString) ref;
-        java.lang.String s = bs.toStringUtf8();
-        tfVersion_ = s;
-        return s;
-      } else {
-        return (java.lang.String) ref;
-      }
-    }
-    /**
-     * 
-     * TensorFlow version this benchmark runs against.
-     * This can be either set to full version or just the major version.
-     * 

-     *
-     * string tf_version = 12;
-     * @return The bytes for tfVersion.
-     */
-    public com.google.protobuf.ByteString
-        getTfVersionBytes() {
-      java.lang.Object ref = tfVersion_;
-      if (ref instanceof String) {
-        com.google.protobuf.ByteString b = 
-            com.google.protobuf.ByteString.copyFromUtf8(
-                (java.lang.String) ref);
-        tfVersion_ = b;
-        return b;
-      } else {
-        return (com.google.protobuf.ByteString) ref;
-      }
-    }
-    /**
-     * 
-     * TensorFlow version this benchmark runs against.
-     * This can be either set to full version or just the major version.
-     * 

-     *
-     * string tf_version = 12;
-     * @param value The tfVersion to set.
-     * @return This builder for chaining.
-     */
-    public Builder setTfVersion(
-        java.lang.String value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  
-      tfVersion_ = value;
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * TensorFlow version this benchmark runs against.
-     * This can be either set to full version or just the major version.
-     * 

-     *
-     * string tf_version = 12;
-     * @return This builder for chaining.
-     */
-    public Builder clearTfVersion() {
-      
-      tfVersion_ = getDefaultInstance().getTfVersion();
-      onChanged();
-      return this;
-    }
-    /**
-     * 
-     * TensorFlow version this benchmark runs against.
-     * This can be either set to full version or just the major version.
-     * 

-     *
-     * string tf_version = 12;
-     * @param value The bytes for tfVersion to set.
-     * @return This builder for chaining.
-     */
-    public Builder setTfVersionBytes(
-        com.google.protobuf.ByteString value) {
-      if (value == null) {
-    throw new NullPointerException();
-  }
-  checkByteStringIsUtf8(value);
-      
-      tfVersion_ = value;
-      onChanged();
-      return this;
-    }
-    @java.lang.Override
-    public final Builder setUnknownFields(
-        final com.google.protobuf.UnknownFieldSet unknownFields) {
-      return super.setUnknownFields(unknownFields);
-    }
-
-    @java.lang.Override
-    public final Builder mergeUnknownFields(
-        final com.google.protobuf.UnknownFieldSet unknownFields) {
-      return super.mergeUnknownFields(unknownFields);
-    }
-
-
-    // @@protoc_insertion_point(builder_scope:tensorflow.TestResults)
-  }
-
-  // @@protoc_insertion_point(class_scope:tensorflow.TestResults)
-  private static final org.tensorflow.proto.TestResults DEFAULT_INSTANCE;
-  static {
-    DEFAULT_INSTANCE = new org.tensorflow.proto.TestResults();
-  }
-
-  public static org.tensorflow.proto.TestResults getDefaultInstance() {
-    return DEFAULT_INSTANCE;
-  }
-
-  private static final com.google.protobuf.Parser
-      PARSER = new com.google.protobuf.AbstractParser() {
-    @java.lang.Override
-    public TestResults parsePartialFrom(
-        com.google.protobuf.CodedInputStream input,
-        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
-        throws com.google.protobuf.InvalidProtocolBufferException {
-      Builder builder = newBuilder();
-      try {
-        builder.mergeFrom(input, extensionRegistry);
-      } catch (com.google.protobuf.InvalidProtocolBufferException e) {
-        throw e.setUnfinishedMessage(builder.buildPartial());
-      } catch (com.google.protobuf.UninitializedMessageException e) {
-        throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial());
-      } catch (java.io.IOException e) {
-        throw new com.google.protobuf.InvalidProtocolBufferException(e)
-            .setUnfinishedMessage(builder.buildPartial());
-      }
-      return builder.buildPartial();
-    }
-  };
-
-  public static com.google.protobuf.Parser parser() {
-    return PARSER;
-  }
-
-  @java.lang.Override
-  public com.google.protobuf.Parser getParserForType() {
-    return PARSER;
-  }
-
-  @java.lang.Override
-  public org.tensorflow.proto.TestResults getDefaultInstanceForType() {
-    return DEFAULT_INSTANCE;
-  }
-
-}
-
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestResultsOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestResultsOrBuilder.java
deleted file mode 100644
index 3afd736b478..00000000000
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestResultsOrBuilder.java
+++ /dev/null
@@ -1,267 +0,0 @@
-// Generated by the protocol buffer compiler.  DO NOT EDIT!
-// source: tsl/protobuf/test_log.proto
-
-package org.tensorflow.proto;
-
-public interface TestResultsOrBuilder extends
-    // @@protoc_insertion_point(interface_extends:tensorflow.TestResults)
-    com.google.protobuf.MessageOrBuilder {
-
-  /**
-   * 
-   * The target of the run, e.g.:
-   *  //tensorflow/core:kernels_adjust_contrast_op_benchmark_test
-   * 

-   *
-   * string target = 1;
-   * @return The target.
-   */
-  java.lang.String getTarget();
-  /**
-   * 
-   * The target of the run, e.g.:
-   *  //tensorflow/core:kernels_adjust_contrast_op_benchmark_test
-   * 

-   *
-   * string target = 1;
-   * @return The bytes for target.
-   */
-  com.google.protobuf.ByteString
-      getTargetBytes();
-
-  /**
-   * 
-   * The list of tests or benchmarks in this run.
-   * 

-   *
-   * .tensorflow.BenchmarkEntries entries = 2;
-   * @return Whether the entries field is set.
-   */
-  boolean hasEntries();
-  /**
-   * 
-   * The list of tests or benchmarks in this run.
-   * 

-   *
-   * .tensorflow.BenchmarkEntries entries = 2;
-   * @return The entries.
-   */
-  org.tensorflow.proto.BenchmarkEntries getEntries();
-  /**
-   * 
-   * The list of tests or benchmarks in this run.
-   * 

-   *
-   * .tensorflow.BenchmarkEntries entries = 2;
-   */
-  org.tensorflow.proto.BenchmarkEntriesOrBuilder getEntriesOrBuilder();
-
-  /**
-   * 
-   * The configuration of the build (compiled opt? with cuda? any copts?)
-   * 

-   *
-   * .tensorflow.BuildConfiguration build_configuration = 3;
-   * @return Whether the buildConfiguration field is set.
-   */
-  boolean hasBuildConfiguration();
-  /**
-   * 
-   * The configuration of the build (compiled opt? with cuda? any copts?)
-   * 

-   *
-   * .tensorflow.BuildConfiguration build_configuration = 3;
-   * @return The buildConfiguration.
-   */
-  org.tensorflow.proto.BuildConfiguration getBuildConfiguration();
-  /**
-   * 
-   * The configuration of the build (compiled opt? with cuda? any copts?)
-   * 

-   *
-   * .tensorflow.BuildConfiguration build_configuration = 3;
-   */
-  org.tensorflow.proto.BuildConfigurationOrBuilder getBuildConfigurationOrBuilder();
-
-  /**
-   * 
-   * The commit id (git hash or changelist)
-   * 

-   *
-   * .tensorflow.CommitId commit_id = 4;
-   * @return Whether the commitId field is set.
-   */
-  boolean hasCommitId();
-  /**
-   * 
-   * The commit id (git hash or changelist)
-   * 

-   *
-   * .tensorflow.CommitId commit_id = 4;
-   * @return The commitId.
-   */
-  org.tensorflow.proto.CommitId getCommitId();
-  /**
-   * 
-   * The commit id (git hash or changelist)
-   * 

-   *
-   * .tensorflow.CommitId commit_id = 4;
-   */
-  org.tensorflow.proto.CommitIdOrBuilder getCommitIdOrBuilder();
-
-  /**
-   * 
-   * The time the run started (in seconds of UTC time since Unix epoch)
-   * 

-   *
-   * int64 start_time = 5;
-   * @return The startTime.
-   */
-  long getStartTime();
-
-  /**
-   * 
-   * The amount of time the total run took (wall time in seconds)
-   * 

-   *
-   * double run_time = 6;
-   * @return The runTime.
-   */
-  double getRunTime();
-
-  /**
-   * 
-   * Machine-specific parameters (Platform and CPU info)
-   * 

-   *
-   * .tensorflow.MachineConfiguration machine_configuration = 7;
-   * @return Whether the machineConfiguration field is set.
-   */
-  boolean hasMachineConfiguration();
-  /**
-   * 
-   * Machine-specific parameters (Platform and CPU info)
-   * 

-   *
-   * .tensorflow.MachineConfiguration machine_configuration = 7;
-   * @return The machineConfiguration.
-   */
-  org.tensorflow.proto.MachineConfiguration getMachineConfiguration();
-  /**
-   * 
-   * Machine-specific parameters (Platform and CPU info)
-   * 

-   *
-   * .tensorflow.MachineConfiguration machine_configuration = 7;
-   */
-  org.tensorflow.proto.MachineConfigurationOrBuilder getMachineConfigurationOrBuilder();
-
-  /**
-   * 
-   * Run-specific parameters (arguments, etc)
-   * 

-   *
-   * .tensorflow.RunConfiguration run_configuration = 8;
-   * @return Whether the runConfiguration field is set.
-   */
-  boolean hasRunConfiguration();
-  /**
-   * 
-   * Run-specific parameters (arguments, etc)
-   * 

-   *
-   * .tensorflow.RunConfiguration run_configuration = 8;
-   * @return The runConfiguration.
-   */
-  org.tensorflow.proto.RunConfiguration getRunConfiguration();
-  /**
-   * 
-   * Run-specific parameters (arguments, etc)
-   * 

-   *
-   * .tensorflow.RunConfiguration run_configuration = 8;
-   */
-  org.tensorflow.proto.RunConfigurationOrBuilder getRunConfigurationOrBuilder();
-
-  /**
-   * 
-   * Benchmark target identifier.
-   * 

-   *
-   * string name = 9;
-   * @return The name.
-   */
-  java.lang.String getName();
-  /**
-   * 
-   * Benchmark target identifier.
-   * 

-   *
-   * string name = 9;
-   * @return The bytes for name.
-   */
-  com.google.protobuf.ByteString
-      getNameBytes();
-
-  /**
-   * .tensorflow.TestResults.BenchmarkType benchmark_type = 10;
-   * @return The enum numeric value on the wire for benchmarkType.
-   */
-  int getBenchmarkTypeValue();
-  /**
-   * .tensorflow.TestResults.BenchmarkType benchmark_type = 10;
-   * @return The benchmarkType.
-   */
-  org.tensorflow.proto.TestResults.BenchmarkType getBenchmarkType();
-
-  /**
-   * 
-   * Used for differentiating between continuous and debug builds.
-   * Must be one of:
-   * * cbuild: results from continuous build.
-   * * presubmit: results from oneshot requests.
-   * * culprit: results from culprit finder rerun.
-   * 

-   *
-   * string run_mode = 11;
-   * @return The runMode.
-   */
-  java.lang.String getRunMode();
-  /**
-   * 
-   * Used for differentiating between continuous and debug builds.
-   * Must be one of:
-   * * cbuild: results from continuous build.
-   * * presubmit: results from oneshot requests.
-   * * culprit: results from culprit finder rerun.
-   * 

-   *
-   * string run_mode = 11;
-   * @return The bytes for runMode.
-   */
-  com.google.protobuf.ByteString
-      getRunModeBytes();
-
-  /**
-   * 
-   * TensorFlow version this benchmark runs against.
-   * This can be either set to full version or just the major version.
-   * 

-   *
-   * string tf_version = 12;
-   * @return The tfVersion.
-   */
-  java.lang.String getTfVersion();
-  /**
-   * 
-   * TensorFlow version this benchmark runs against.
-   * This can be either set to full version or just the major version.
-   * 

-   *
-   * string tf_version = 12;
-   * @return The bytes for tfVersion.
-   */
-  com.google.protobuf.ByteString
-      getTfVersionBytes();
-}
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/data/DatasetOptions.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/data/DatasetOptions.java
index c7d43294b14..424adecedbd 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/data/DatasetOptions.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/data/DatasetOptions.java
@@ -381,6 +381,17 @@ public interface AutotuneOptionsOrBuilder extends
      */
     org.tensorflow.proto.data.model.Model.AutotuneAlgorithm getAutotuneAlgorithm();
 
+    /**
+     * int64 initial_parallelism = 5;
+     * @return Whether the initialParallelism field is set.
+     */
+    boolean hasInitialParallelism();
+    /**
+     * int64 initial_parallelism = 5;
+     * @return The initialParallelism.
+     */
+    long getInitialParallelism();
+
     public org.tensorflow.proto.data.DatasetOptions.AutotuneOptions.OptionalEnabledCase getOptionalEnabledCase();
 
     public org.tensorflow.proto.data.DatasetOptions.AutotuneOptions.OptionalCpuBudgetCase getOptionalCpuBudgetCase();
@@ -388,10 +399,12 @@ public interface AutotuneOptionsOrBuilder extends
     public org.tensorflow.proto.data.DatasetOptions.AutotuneOptions.OptionalRamBudgetCase getOptionalRamBudgetCase();
 
     public org.tensorflow.proto.data.DatasetOptions.AutotuneOptions.OptionalAutotuneAlgorithmCase getOptionalAutotuneAlgorithmCase();
+
+    public org.tensorflow.proto.data.DatasetOptions.AutotuneOptions.OptionalInitialParallelismCase getOptionalInitialParallelismCase();
   }
   /**
    * 
-   * next: 5
+   * next: 6
    * 

    *
    * Protobuf type {@code tensorflow.data.AutotuneOptions}
@@ -589,6 +602,45 @@ public int getNumber() {
           optionalAutotuneAlgorithmCase_);
     }
 
+    private int optionalInitialParallelismCase_ = 0;
+    private java.lang.Object optionalInitialParallelism_;
+    public enum OptionalInitialParallelismCase
+        implements com.google.protobuf.Internal.EnumLite,
+            com.google.protobuf.AbstractMessage.InternalOneOfEnum {
+      INITIAL_PARALLELISM(5),
+      OPTIONALINITIALPARALLELISM_NOT_SET(0);
+      private final int value;
+      private OptionalInitialParallelismCase(int value) {
+        this.value = value;
+      }
+      /**
+       * @param value The number of the enum to look for.
+       * @return The enum associated with the given number.
+       * @deprecated Use {@link #forNumber(int)} instead.
+       */
+      @java.lang.Deprecated
+      public static OptionalInitialParallelismCase valueOf(int value) {
+        return forNumber(value);
+      }
+
+      public static OptionalInitialParallelismCase forNumber(int value) {
+        switch (value) {
+          case 5: return INITIAL_PARALLELISM;
+          case 0: return OPTIONALINITIALPARALLELISM_NOT_SET;
+          default: return null;
+        }
+      }
+      public int getNumber() {
+        return this.value;
+      }
+    };
+
+    public OptionalInitialParallelismCase
+    getOptionalInitialParallelismCase() {
+      return OptionalInitialParallelismCase.forNumber(
+          optionalInitialParallelismCase_);
+    }
+
     public static final int ENABLED_FIELD_NUMBER = 1;
     /**
      * bool enabled = 1;
@@ -684,6 +736,27 @@ public org.tensorflow.proto.data.model.Model.AutotuneAlgorithm getAutotuneAlgori
       return org.tensorflow.proto.data.model.Model.AutotuneAlgorithm.DEFAULT;
     }
 
+    public static final int INITIAL_PARALLELISM_FIELD_NUMBER = 5;
+    /**
+     * int64 initial_parallelism = 5;
+     * @return Whether the initialParallelism field is set.
+     */
+    @java.lang.Override
+    public boolean hasInitialParallelism() {
+      return optionalInitialParallelismCase_ == 5;
+    }
+    /**
+     * int64 initial_parallelism = 5;
+     * @return The initialParallelism.
+     */
+    @java.lang.Override
+    public long getInitialParallelism() {
+      if (optionalInitialParallelismCase_ == 5) {
+        return (java.lang.Long) optionalInitialParallelism_;
+      }
+      return 0L;
+    }
+
     private byte memoizedIsInitialized = -1;
     @java.lang.Override
     public final boolean isInitialized() {
@@ -713,6 +786,10 @@ public void writeTo(com.google.protobuf.CodedOutputStream output)
       if (optionalAutotuneAlgorithmCase_ == 4) {
         output.writeEnum(4, ((java.lang.Integer) optionalAutotuneAlgorithm_));
       }
+      if (optionalInitialParallelismCase_ == 5) {
+        output.writeInt64(
+            5, (long)((java.lang.Long) optionalInitialParallelism_));
+      }
       getUnknownFields().writeTo(output);
     }
 
@@ -741,6 +818,11 @@ public int getSerializedSize() {
         size += com.google.protobuf.CodedOutputStream
           .computeEnumSize(4, ((java.lang.Integer) optionalAutotuneAlgorithm_));
       }
+      if (optionalInitialParallelismCase_ == 5) {
+        size += com.google.protobuf.CodedOutputStream
+          .computeInt64Size(
+              5, (long)((java.lang.Long) optionalInitialParallelism_));
+      }
       size += getUnknownFields().getSerializedSize();
       memoizedSize = size;
       return size;
@@ -792,6 +874,15 @@ public boolean equals(final java.lang.Object obj) {
         case 0:
         default:
       }
+      if (!getOptionalInitialParallelismCase().equals(other.getOptionalInitialParallelismCase())) return false;
+      switch (optionalInitialParallelismCase_) {
+        case 5:
+          if (getInitialParallelism()
+              != other.getInitialParallelism()) return false;
+          break;
+        case 0:
+        default:
+      }
       if (!getUnknownFields().equals(other.getUnknownFields())) return false;
       return true;
     }
@@ -837,6 +928,15 @@ public int hashCode() {
         case 0:
         default:
       }
+      switch (optionalInitialParallelismCase_) {
+        case 5:
+          hash = (37 * hash) + INITIAL_PARALLELISM_FIELD_NUMBER;
+          hash = (53 * hash) + com.google.protobuf.Internal.hashLong(
+              getInitialParallelism());
+          break;
+        case 0:
+        default:
+      }
       hash = (29 * hash) + getUnknownFields().hashCode();
       memoizedHashCode = hash;
       return hash;
@@ -934,7 +1034,7 @@ protected Builder newBuilderForType(
     }
     /**
      * 
-     * next: 5
+     * next: 6
      * 

      *
      * Protobuf type {@code tensorflow.data.AutotuneOptions}
@@ -977,6 +1077,8 @@ public Builder clear() {
         optionalRamBudget_ = null;
         optionalAutotuneAlgorithmCase_ = 0;
         optionalAutotuneAlgorithm_ = null;
+        optionalInitialParallelismCase_ = 0;
+        optionalInitialParallelism_ = null;
         return this;
       }
 
@@ -1015,10 +1117,14 @@ public org.tensorflow.proto.data.DatasetOptions.AutotuneOptions buildPartial() {
         if (optionalAutotuneAlgorithmCase_ == 4) {
           result.optionalAutotuneAlgorithm_ = optionalAutotuneAlgorithm_;
         }
+        if (optionalInitialParallelismCase_ == 5) {
+          result.optionalInitialParallelism_ = optionalInitialParallelism_;
+        }
         result.optionalEnabledCase_ = optionalEnabledCase_;
         result.optionalCpuBudgetCase_ = optionalCpuBudgetCase_;
         result.optionalRamBudgetCase_ = optionalRamBudgetCase_;
         result.optionalAutotuneAlgorithmCase_ = optionalAutotuneAlgorithmCase_;
+        result.optionalInitialParallelismCase_ = optionalInitialParallelismCase_;
         onBuilt();
         return result;
       }
@@ -1103,6 +1209,15 @@ public Builder mergeFrom(org.tensorflow.proto.data.DatasetOptions.AutotuneOption
             break;
           }
         }
+        switch (other.getOptionalInitialParallelismCase()) {
+          case INITIAL_PARALLELISM: {
+            setInitialParallelism(other.getInitialParallelism());
+            break;
+          }
+          case OPTIONALINITIALPARALLELISM_NOT_SET: {
+            break;
+          }
+        }
         this.mergeUnknownFields(other.getUnknownFields());
         onChanged();
         return this;
@@ -1150,6 +1265,11 @@ public Builder mergeFrom(
                 optionalAutotuneAlgorithm_ = rawValue;
                 break;
               } // case 32
+              case 40: {
+                optionalInitialParallelism_ = input.readInt64();
+                optionalInitialParallelismCase_ = 5;
+                break;
+              } // case 40
               default: {
                 if (!super.parseUnknownField(input, extensionRegistry, tag)) {
                   done = true; // was an endgroup tag
@@ -1225,6 +1345,21 @@ public Builder clearOptionalAutotuneAlgorithm() {
         return this;
       }
 
+      private int optionalInitialParallelismCase_ = 0;
+      private java.lang.Object optionalInitialParallelism_;
+      public OptionalInitialParallelismCase
+          getOptionalInitialParallelismCase() {
+        return OptionalInitialParallelismCase.forNumber(
+            optionalInitialParallelismCase_);
+      }
+
+      public Builder clearOptionalInitialParallelism() {
+        optionalInitialParallelismCase_ = 0;
+        optionalInitialParallelism_ = null;
+        onChanged();
+        return this;
+      }
+
 
       /**
        * bool enabled = 1;
@@ -1419,6 +1554,47 @@ public Builder clearAutotuneAlgorithm() {
         }
         return this;
       }
+
+      /**
+       * int64 initial_parallelism = 5;
+       * @return Whether the initialParallelism field is set.
+       */
+      public boolean hasInitialParallelism() {
+        return optionalInitialParallelismCase_ == 5;
+      }
+      /**
+       * int64 initial_parallelism = 5;
+       * @return The initialParallelism.
+       */
+      public long getInitialParallelism() {
+        if (optionalInitialParallelismCase_ == 5) {
+          return (java.lang.Long) optionalInitialParallelism_;
+        }
+        return 0L;
+      }
+      /**
+       * int64 initial_parallelism = 5;
+       * @param value The initialParallelism to set.
+       * @return This builder for chaining.
+       */
+      public Builder setInitialParallelism(long value) {
+        optionalInitialParallelismCase_ = 5;
+        optionalInitialParallelism_ = value;
+        onChanged();
+        return this;
+      }
+      /**
+       * int64 initial_parallelism = 5;
+       * @return This builder for chaining.
+       */
+      public Builder clearInitialParallelism() {
+        if (optionalInitialParallelismCase_ == 5) {
+          optionalInitialParallelismCase_ = 0;
+          optionalInitialParallelism_ = null;
+          onChanged();
+        }
+        return this;
+      }
       @java.lang.Override
       public final Builder setUnknownFields(
           final com.google.protobuf.UnknownFieldSet unknownFields) {
@@ -5349,60 +5525,47 @@ public org.tensorflow.proto.data.DatasetOptions.OptimizationOptions getDefaultIn
 
   }
 
-  public interface ThreadingOptionsOrBuilder extends
-      // @@protoc_insertion_point(interface_extends:tensorflow.data.ThreadingOptions)
+  public interface ServiceOptionsOrBuilder extends
+      // @@protoc_insertion_point(interface_extends:tensorflow.data.ServiceOptions)
       com.google.protobuf.MessageOrBuilder {
 
     /**
-     * int32 max_intra_op_parallelism = 1;
-     * @return Whether the maxIntraOpParallelism field is set.
-     */
-    boolean hasMaxIntraOpParallelism();
-    /**
-     * int32 max_intra_op_parallelism = 1;
-     * @return The maxIntraOpParallelism.
-     */
-    int getMaxIntraOpParallelism();
-
-    /**
-     * int32 private_threadpool_size = 2;
-     * @return Whether the privateThreadpoolSize field is set.
+     * bool pinned = 1;
+     * @return Whether the pinned field is set.
      */
-    boolean hasPrivateThreadpoolSize();
+    boolean hasPinned();
     /**
-     * int32 private_threadpool_size = 2;
-     * @return The privateThreadpoolSize.
+     * bool pinned = 1;
+     * @return The pinned.
      */
-    int getPrivateThreadpoolSize();
-
-    public org.tensorflow.proto.data.DatasetOptions.ThreadingOptions.OptionalMaxIntraOpParallelismCase getOptionalMaxIntraOpParallelismCase();
+    boolean getPinned();
 
-    public org.tensorflow.proto.data.DatasetOptions.ThreadingOptions.OptionalPrivateThreadpoolSizeCase getOptionalPrivateThreadpoolSizeCase();
+    public org.tensorflow.proto.data.DatasetOptions.ServiceOptions.OptionalPinnedCase getOptionalPinnedCase();
   }
   /**
    * 
-   * next: 3
+   * next: 2
    * 

    *
-   * Protobuf type {@code tensorflow.data.ThreadingOptions}
+   * Protobuf type {@code tensorflow.data.ServiceOptions}
    */
-  public static final class ThreadingOptions extends
+  public static final class ServiceOptions extends
       com.google.protobuf.GeneratedMessageV3 implements
-      // @@protoc_insertion_point(message_implements:tensorflow.data.ThreadingOptions)
-      ThreadingOptionsOrBuilder {
+      // @@protoc_insertion_point(message_implements:tensorflow.data.ServiceOptions)
+      ServiceOptionsOrBuilder {
   private static final long serialVersionUID = 0L;
-    // Use ThreadingOptions.newBuilder() to construct.
-    private ThreadingOptions(com.google.protobuf.GeneratedMessageV3.Builder builder) {
+    // Use ServiceOptions.newBuilder() to construct.
+    private ServiceOptions(com.google.protobuf.GeneratedMessageV3.Builder builder) {
       super(builder);
     }
-    private ThreadingOptions() {
+    private ServiceOptions() {
     }
 
     @java.lang.Override
     @SuppressWarnings({"unused"})
     protected java.lang.Object newInstance(
         UnusedPrivateParameter unused) {
-      return new ThreadingOptions();
+      return new ServiceOptions();
     }
 
     @java.lang.Override
@@ -5412,65 +5575,26 @@ protected java.lang.Object newInstance(
     }
     public static final com.google.protobuf.Descriptors.Descriptor
         getDescriptor() {
-      return org.tensorflow.proto.data.DatasetOptions.internal_static_tensorflow_data_ThreadingOptions_descriptor;
+      return org.tensorflow.proto.data.DatasetOptions.internal_static_tensorflow_data_ServiceOptions_descriptor;
     }
 
     @java.lang.Override
     protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
         internalGetFieldAccessorTable() {
-      return org.tensorflow.proto.data.DatasetOptions.internal_static_tensorflow_data_ThreadingOptions_fieldAccessorTable
+      return org.tensorflow.proto.data.DatasetOptions.internal_static_tensorflow_data_ServiceOptions_fieldAccessorTable
           .ensureFieldAccessorsInitialized(
-              org.tensorflow.proto.data.DatasetOptions.ThreadingOptions.class, org.tensorflow.proto.data.DatasetOptions.ThreadingOptions.Builder.class);
-    }
-
-    private int optionalMaxIntraOpParallelismCase_ = 0;
-    private java.lang.Object optionalMaxIntraOpParallelism_;
-    public enum OptionalMaxIntraOpParallelismCase
-        implements com.google.protobuf.Internal.EnumLite,
-            com.google.protobuf.AbstractMessage.InternalOneOfEnum {
-      MAX_INTRA_OP_PARALLELISM(1),
-      OPTIONALMAXINTRAOPPARALLELISM_NOT_SET(0);
-      private final int value;
-      private OptionalMaxIntraOpParallelismCase(int value) {
-        this.value = value;
-      }
-      /**
-       * @param value The number of the enum to look for.
-       * @return The enum associated with the given number.
-       * @deprecated Use {@link #forNumber(int)} instead.
-       */
-      @java.lang.Deprecated
-      public static OptionalMaxIntraOpParallelismCase valueOf(int value) {
-        return forNumber(value);
-      }
-
-      public static OptionalMaxIntraOpParallelismCase forNumber(int value) {
-        switch (value) {
-          case 1: return MAX_INTRA_OP_PARALLELISM;
-          case 0: return OPTIONALMAXINTRAOPPARALLELISM_NOT_SET;
-          default: return null;
-        }
-      }
-      public int getNumber() {
-        return this.value;
-      }
-    };
-
-    public OptionalMaxIntraOpParallelismCase
-    getOptionalMaxIntraOpParallelismCase() {
-      return OptionalMaxIntraOpParallelismCase.forNumber(
-          optionalMaxIntraOpParallelismCase_);
+              org.tensorflow.proto.data.DatasetOptions.ServiceOptions.class, org.tensorflow.proto.data.DatasetOptions.ServiceOptions.Builder.class);
     }
 
-    private int optionalPrivateThreadpoolSizeCase_ = 0;
-    private java.lang.Object optionalPrivateThreadpoolSize_;
-    public enum OptionalPrivateThreadpoolSizeCase
+    private int optionalPinnedCase_ = 0;
+    private java.lang.Object optionalPinned_;
+    public enum OptionalPinnedCase
         implements com.google.protobuf.Internal.EnumLite,
             com.google.protobuf.AbstractMessage.InternalOneOfEnum {
-      PRIVATE_THREADPOOL_SIZE(2),
-      OPTIONALPRIVATETHREADPOOLSIZE_NOT_SET(0);
+      PINNED(1),
+      OPTIONALPINNED_NOT_SET(0);
       private final int value;
-      private OptionalPrivateThreadpoolSizeCase(int value) {
+      private OptionalPinnedCase(int value) {
         this.value = value;
       }
       /**
@@ -5479,14 +5603,14 @@ private OptionalPrivateThreadpoolSizeCase(int value) {
        * @deprecated Use {@link #forNumber(int)} instead.
        */
       @java.lang.Deprecated
-      public static OptionalPrivateThreadpoolSizeCase valueOf(int value) {
+      public static OptionalPinnedCase valueOf(int value) {
         return forNumber(value);
       }
 
-      public static OptionalPrivateThreadpoolSizeCase forNumber(int value) {
+      public static OptionalPinnedCase forNumber(int value) {
         switch (value) {
-          case 2: return PRIVATE_THREADPOOL_SIZE;
-          case 0: return OPTIONALPRIVATETHREADPOOLSIZE_NOT_SET;
+          case 1: return PINNED;
+          case 0: return OPTIONALPINNED_NOT_SET;
           default: return null;
         }
       }
@@ -5495,52 +5619,31 @@ public int getNumber() {
       }
     };
 
-    public OptionalPrivateThreadpoolSizeCase
-    getOptionalPrivateThreadpoolSizeCase() {
-      return OptionalPrivateThreadpoolSizeCase.forNumber(
-          optionalPrivateThreadpoolSizeCase_);
-    }
-
-    public static final int MAX_INTRA_OP_PARALLELISM_FIELD_NUMBER = 1;
-    /**
-     * int32 max_intra_op_parallelism = 1;
-     * @return Whether the maxIntraOpParallelism field is set.
-     */
-    @java.lang.Override
-    public boolean hasMaxIntraOpParallelism() {
-      return optionalMaxIntraOpParallelismCase_ == 1;
-    }
-    /**
-     * int32 max_intra_op_parallelism = 1;
-     * @return The maxIntraOpParallelism.
-     */
-    @java.lang.Override
-    public int getMaxIntraOpParallelism() {
-      if (optionalMaxIntraOpParallelismCase_ == 1) {
-        return (java.lang.Integer) optionalMaxIntraOpParallelism_;
-      }
-      return 0;
+    public OptionalPinnedCase
+    getOptionalPinnedCase() {
+      return OptionalPinnedCase.forNumber(
+          optionalPinnedCase_);
     }
 
-    public static final int PRIVATE_THREADPOOL_SIZE_FIELD_NUMBER = 2;
+    public static final int PINNED_FIELD_NUMBER = 1;
     /**
-     * int32 private_threadpool_size = 2;
-     * @return Whether the privateThreadpoolSize field is set.
+     * bool pinned = 1;
+     * @return Whether the pinned field is set.
      */
     @java.lang.Override
-    public boolean hasPrivateThreadpoolSize() {
-      return optionalPrivateThreadpoolSizeCase_ == 2;
+    public boolean hasPinned() {
+      return optionalPinnedCase_ == 1;
     }
     /**
-     * int32 private_threadpool_size = 2;
-     * @return The privateThreadpoolSize.
+     * bool pinned = 1;
+     * @return The pinned.
      */
     @java.lang.Override
-    public int getPrivateThreadpoolSize() {
-      if (optionalPrivateThreadpoolSizeCase_ == 2) {
-        return (java.lang.Integer) optionalPrivateThreadpoolSize_;
+    public boolean getPinned() {
+      if (optionalPinnedCase_ == 1) {
+        return (java.lang.Boolean) optionalPinned_;
       }
-      return 0;
+      return false;
     }
 
     private byte memoizedIsInitialized = -1;
@@ -5557,13 +5660,9 @@ public final boolean isInitialized() {
     @java.lang.Override
     public void writeTo(com.google.protobuf.CodedOutputStream output)
                         throws java.io.IOException {
-      if (optionalMaxIntraOpParallelismCase_ == 1) {
-        output.writeInt32(
-            1, (int)((java.lang.Integer) optionalMaxIntraOpParallelism_));
-      }
-      if (optionalPrivateThreadpoolSizeCase_ == 2) {
-        output.writeInt32(
-            2, (int)((java.lang.Integer) optionalPrivateThreadpoolSize_));
+      if (optionalPinnedCase_ == 1) {
+        output.writeBool(
+            1, (boolean)((java.lang.Boolean) optionalPinned_));
       }
       getUnknownFields().writeTo(output);
     }
@@ -5574,15 +5673,10 @@ public int getSerializedSize() {
       if (size != -1) return size;
 
       size = 0;
-      if (optionalMaxIntraOpParallelismCase_ == 1) {
-        size += com.google.protobuf.CodedOutputStream
-          .computeInt32Size(
-              1, (int)((java.lang.Integer) optionalMaxIntraOpParallelism_));
-      }
-      if (optionalPrivateThreadpoolSizeCase_ == 2) {
+      if (optionalPinnedCase_ == 1) {
         size += com.google.protobuf.CodedOutputStream
-          .computeInt32Size(
-              2, (int)((java.lang.Integer) optionalPrivateThreadpoolSize_));
+          .computeBoolSize(
+              1, (boolean)((java.lang.Boolean) optionalPinned_));
       }
       size += getUnknownFields().getSerializedSize();
       memoizedSize = size;
@@ -5594,25 +5688,16 @@ public boolean equals(final java.lang.Object obj) {
       if (obj == this) {
        return true;
       }
-      if (!(obj instanceof org.tensorflow.proto.data.DatasetOptions.ThreadingOptions)) {
+      if (!(obj instanceof org.tensorflow.proto.data.DatasetOptions.ServiceOptions)) {
         return super.equals(obj);
       }
-      org.tensorflow.proto.data.DatasetOptions.ThreadingOptions other = (org.tensorflow.proto.data.DatasetOptions.ThreadingOptions) obj;
+      org.tensorflow.proto.data.DatasetOptions.ServiceOptions other = (org.tensorflow.proto.data.DatasetOptions.ServiceOptions) obj;
 
-      if (!getOptionalMaxIntraOpParallelismCase().equals(other.getOptionalMaxIntraOpParallelismCase())) return false;
-      switch (optionalMaxIntraOpParallelismCase_) {
+      if (!getOptionalPinnedCase().equals(other.getOptionalPinnedCase())) return false;
+      switch (optionalPinnedCase_) {
         case 1:
-          if (getMaxIntraOpParallelism()
-              != other.getMaxIntraOpParallelism()) return false;
-          break;
-        case 0:
-        default:
-      }
-      if (!getOptionalPrivateThreadpoolSizeCase().equals(other.getOptionalPrivateThreadpoolSizeCase())) return false;
-      switch (optionalPrivateThreadpoolSizeCase_) {
-        case 2:
-          if (getPrivateThreadpoolSize()
-              != other.getPrivateThreadpoolSize()) return false;
+          if (getPinned()
+              != other.getPinned()) return false;
           break;
         case 0:
         default:
@@ -5628,18 +5713,693 @@ public int hashCode() {
       }
       int hash = 41;
       hash = (19 * hash) + getDescriptor().hashCode();
-      switch (optionalMaxIntraOpParallelismCase_) {
+      switch (optionalPinnedCase_) {
         case 1:
-          hash = (37 * hash) + MAX_INTRA_OP_PARALLELISM_FIELD_NUMBER;
-          hash = (53 * hash) + getMaxIntraOpParallelism();
-          break;
-        case 0:
-        default:
-      }
-      switch (optionalPrivateThreadpoolSizeCase_) {
-        case 2:
-          hash = (37 * hash) + PRIVATE_THREADPOOL_SIZE_FIELD_NUMBER;
-          hash = (53 * hash) + getPrivateThreadpoolSize();
+          hash = (37 * hash) + PINNED_FIELD_NUMBER;
+          hash = (53 * hash) + com.google.protobuf.Internal.hashBoolean(
+              getPinned());
+          break;
+        case 0:
+        default:
+      }
+      hash = (29 * hash) + getUnknownFields().hashCode();
+      memoizedHashCode = hash;
+      return hash;
+    }
+
+    public static org.tensorflow.proto.data.DatasetOptions.ServiceOptions parseFrom(
+        java.nio.ByteBuffer data)
+        throws com.google.protobuf.InvalidProtocolBufferException {
+      return PARSER.parseFrom(data);
+    }
+    public static org.tensorflow.proto.data.DatasetOptions.ServiceOptions parseFrom(
+        java.nio.ByteBuffer data,
+        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+        throws com.google.protobuf.InvalidProtocolBufferException {
+      return PARSER.parseFrom(data, extensionRegistry);
+    }
+    public static org.tensorflow.proto.data.DatasetOptions.ServiceOptions parseFrom(
+        com.google.protobuf.ByteString data)
+        throws com.google.protobuf.InvalidProtocolBufferException {
+      return PARSER.parseFrom(data);
+    }
+    public static org.tensorflow.proto.data.DatasetOptions.ServiceOptions parseFrom(
+        com.google.protobuf.ByteString data,
+        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+        throws com.google.protobuf.InvalidProtocolBufferException {
+      return PARSER.parseFrom(data, extensionRegistry);
+    }
+    public static org.tensorflow.proto.data.DatasetOptions.ServiceOptions parseFrom(byte[] data)
+        throws com.google.protobuf.InvalidProtocolBufferException {
+      return PARSER.parseFrom(data);
+    }
+    public static org.tensorflow.proto.data.DatasetOptions.ServiceOptions parseFrom(
+        byte[] data,
+        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+        throws com.google.protobuf.InvalidProtocolBufferException {
+      return PARSER.parseFrom(data, extensionRegistry);
+    }
+    public static org.tensorflow.proto.data.DatasetOptions.ServiceOptions parseFrom(java.io.InputStream input)
+        throws java.io.IOException {
+      return com.google.protobuf.GeneratedMessageV3
+          .parseWithIOException(PARSER, input);
+    }
+    public static org.tensorflow.proto.data.DatasetOptions.ServiceOptions parseFrom(
+        java.io.InputStream input,
+        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+        throws java.io.IOException {
+      return com.google.protobuf.GeneratedMessageV3
+          .parseWithIOException(PARSER, input, extensionRegistry);
+    }
+    public static org.tensorflow.proto.data.DatasetOptions.ServiceOptions parseDelimitedFrom(java.io.InputStream input)
+        throws java.io.IOException {
+      return com.google.protobuf.GeneratedMessageV3
+          .parseDelimitedWithIOException(PARSER, input);
+    }
+    public static org.tensorflow.proto.data.DatasetOptions.ServiceOptions parseDelimitedFrom(
+        java.io.InputStream input,
+        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+        throws java.io.IOException {
+      return com.google.protobuf.GeneratedMessageV3
+          .parseDelimitedWithIOException(PARSER, input, extensionRegistry);
+    }
+    public static org.tensorflow.proto.data.DatasetOptions.ServiceOptions parseFrom(
+        com.google.protobuf.CodedInputStream input)
+        throws java.io.IOException {
+      return com.google.protobuf.GeneratedMessageV3
+          .parseWithIOException(PARSER, input);
+    }
+    public static org.tensorflow.proto.data.DatasetOptions.ServiceOptions parseFrom(
+        com.google.protobuf.CodedInputStream input,
+        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+        throws java.io.IOException {
+      return com.google.protobuf.GeneratedMessageV3
+          .parseWithIOException(PARSER, input, extensionRegistry);
+    }
+
+    @java.lang.Override
+    public Builder newBuilderForType() { return newBuilder(); }
+    public static Builder newBuilder() {
+      return DEFAULT_INSTANCE.toBuilder();
+    }
+    public static Builder newBuilder(org.tensorflow.proto.data.DatasetOptions.ServiceOptions prototype) {
+      return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype);
+    }
+    @java.lang.Override
+    public Builder toBuilder() {
+      return this == DEFAULT_INSTANCE
+          ? new Builder() : new Builder().mergeFrom(this);
+    }
+
+    @java.lang.Override
+    protected Builder newBuilderForType(
+        com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
+      Builder builder = new Builder(parent);
+      return builder;
+    }
+    /**
+     * 
+     * next: 2
+     * 

+     *
+     * Protobuf type {@code tensorflow.data.ServiceOptions}
+     */
+    public static final class Builder extends
+        com.google.protobuf.GeneratedMessageV3.Builder implements
+        // @@protoc_insertion_point(builder_implements:tensorflow.data.ServiceOptions)
+        org.tensorflow.proto.data.DatasetOptions.ServiceOptionsOrBuilder {
+      public static final com.google.protobuf.Descriptors.Descriptor
+          getDescriptor() {
+        return org.tensorflow.proto.data.DatasetOptions.internal_static_tensorflow_data_ServiceOptions_descriptor;
+      }
+
+      @java.lang.Override
+      protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
+          internalGetFieldAccessorTable() {
+        return org.tensorflow.proto.data.DatasetOptions.internal_static_tensorflow_data_ServiceOptions_fieldAccessorTable
+            .ensureFieldAccessorsInitialized(
+                org.tensorflow.proto.data.DatasetOptions.ServiceOptions.class, org.tensorflow.proto.data.DatasetOptions.ServiceOptions.Builder.class);
+      }
+
+      // Construct using org.tensorflow.proto.data.DatasetOptions.ServiceOptions.newBuilder()
+      private Builder() {
+
+      }
+
+      private Builder(
+          com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
+        super(parent);
+
+      }
+      @java.lang.Override
+      public Builder clear() {
+        super.clear();
+        optionalPinnedCase_ = 0;
+        optionalPinned_ = null;
+        return this;
+      }
+
+      @java.lang.Override
+      public com.google.protobuf.Descriptors.Descriptor
+          getDescriptorForType() {
+        return org.tensorflow.proto.data.DatasetOptions.internal_static_tensorflow_data_ServiceOptions_descriptor;
+      }
+
+      @java.lang.Override
+      public org.tensorflow.proto.data.DatasetOptions.ServiceOptions getDefaultInstanceForType() {
+        return org.tensorflow.proto.data.DatasetOptions.ServiceOptions.getDefaultInstance();
+      }
+
+      @java.lang.Override
+      public org.tensorflow.proto.data.DatasetOptions.ServiceOptions build() {
+        org.tensorflow.proto.data.DatasetOptions.ServiceOptions result = buildPartial();
+        if (!result.isInitialized()) {
+          throw newUninitializedMessageException(result);
+        }
+        return result;
+      }
+
+      @java.lang.Override
+      public org.tensorflow.proto.data.DatasetOptions.ServiceOptions buildPartial() {
+        org.tensorflow.proto.data.DatasetOptions.ServiceOptions result = new org.tensorflow.proto.data.DatasetOptions.ServiceOptions(this);
+        if (optionalPinnedCase_ == 1) {
+          result.optionalPinned_ = optionalPinned_;
+        }
+        result.optionalPinnedCase_ = optionalPinnedCase_;
+        onBuilt();
+        return result;
+      }
+
+      @java.lang.Override
+      public Builder clone() {
+        return super.clone();
+      }
+      @java.lang.Override
+      public Builder setField(
+          com.google.protobuf.Descriptors.FieldDescriptor field,
+          java.lang.Object value) {
+        return super.setField(field, value);
+      }
+      @java.lang.Override
+      public Builder clearField(
+          com.google.protobuf.Descriptors.FieldDescriptor field) {
+        return super.clearField(field);
+      }
+      @java.lang.Override
+      public Builder clearOneof(
+          com.google.protobuf.Descriptors.OneofDescriptor oneof) {
+        return super.clearOneof(oneof);
+      }
+      @java.lang.Override
+      public Builder setRepeatedField(
+          com.google.protobuf.Descriptors.FieldDescriptor field,
+          int index, java.lang.Object value) {
+        return super.setRepeatedField(field, index, value);
+      }
+      @java.lang.Override
+      public Builder addRepeatedField(
+          com.google.protobuf.Descriptors.FieldDescriptor field,
+          java.lang.Object value) {
+        return super.addRepeatedField(field, value);
+      }
+      @java.lang.Override
+      public Builder mergeFrom(com.google.protobuf.Message other) {
+        if (other instanceof org.tensorflow.proto.data.DatasetOptions.ServiceOptions) {
+          return mergeFrom((org.tensorflow.proto.data.DatasetOptions.ServiceOptions)other);
+        } else {
+          super.mergeFrom(other);
+          return this;
+        }
+      }
+
+      public Builder mergeFrom(org.tensorflow.proto.data.DatasetOptions.ServiceOptions other) {
+        if (other == org.tensorflow.proto.data.DatasetOptions.ServiceOptions.getDefaultInstance()) return this;
+        switch (other.getOptionalPinnedCase()) {
+          case PINNED: {
+            setPinned(other.getPinned());
+            break;
+          }
+          case OPTIONALPINNED_NOT_SET: {
+            break;
+          }
+        }
+        this.mergeUnknownFields(other.getUnknownFields());
+        onChanged();
+        return this;
+      }
+
+      @java.lang.Override
+      public final boolean isInitialized() {
+        return true;
+      }
+
+      @java.lang.Override
+      public Builder mergeFrom(
+          com.google.protobuf.CodedInputStream input,
+          com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+          throws java.io.IOException {
+        if (extensionRegistry == null) {
+          throw new java.lang.NullPointerException();
+        }
+        try {
+          boolean done = false;
+          while (!done) {
+            int tag = input.readTag();
+            switch (tag) {
+              case 0:
+                done = true;
+                break;
+              case 8: {
+                optionalPinned_ = input.readBool();
+                optionalPinnedCase_ = 1;
+                break;
+              } // case 8
+              default: {
+                if (!super.parseUnknownField(input, extensionRegistry, tag)) {
+                  done = true; // was an endgroup tag
+                }
+                break;
+              } // default:
+            } // switch (tag)
+          } // while (!done)
+        } catch (com.google.protobuf.InvalidProtocolBufferException e) {
+          throw e.unwrapIOException();
+        } finally {
+          onChanged();
+        } // finally
+        return this;
+      }
+      private int optionalPinnedCase_ = 0;
+      private java.lang.Object optionalPinned_;
+      public OptionalPinnedCase
+          getOptionalPinnedCase() {
+        return OptionalPinnedCase.forNumber(
+            optionalPinnedCase_);
+      }
+
+      public Builder clearOptionalPinned() {
+        optionalPinnedCase_ = 0;
+        optionalPinned_ = null;
+        onChanged();
+        return this;
+      }
+
+
+      /**
+       * bool pinned = 1;
+       * @return Whether the pinned field is set.
+       */
+      public boolean hasPinned() {
+        return optionalPinnedCase_ == 1;
+      }
+      /**
+       * bool pinned = 1;
+       * @return The pinned.
+       */
+      public boolean getPinned() {
+        if (optionalPinnedCase_ == 1) {
+          return (java.lang.Boolean) optionalPinned_;
+        }
+        return false;
+      }
+      /**
+       * bool pinned = 1;
+       * @param value The pinned to set.
+       * @return This builder for chaining.
+       */
+      public Builder setPinned(boolean value) {
+        optionalPinnedCase_ = 1;
+        optionalPinned_ = value;
+        onChanged();
+        return this;
+      }
+      /**
+       * bool pinned = 1;
+       * @return This builder for chaining.
+       */
+      public Builder clearPinned() {
+        if (optionalPinnedCase_ == 1) {
+          optionalPinnedCase_ = 0;
+          optionalPinned_ = null;
+          onChanged();
+        }
+        return this;
+      }
+      @java.lang.Override
+      public final Builder setUnknownFields(
+          final com.google.protobuf.UnknownFieldSet unknownFields) {
+        return super.setUnknownFields(unknownFields);
+      }
+
+      @java.lang.Override
+      public final Builder mergeUnknownFields(
+          final com.google.protobuf.UnknownFieldSet unknownFields) {
+        return super.mergeUnknownFields(unknownFields);
+      }
+
+
+      // @@protoc_insertion_point(builder_scope:tensorflow.data.ServiceOptions)
+    }
+
+    // @@protoc_insertion_point(class_scope:tensorflow.data.ServiceOptions)
+    private static final org.tensorflow.proto.data.DatasetOptions.ServiceOptions DEFAULT_INSTANCE;
+    static {
+      DEFAULT_INSTANCE = new org.tensorflow.proto.data.DatasetOptions.ServiceOptions();
+    }
+
+    public static org.tensorflow.proto.data.DatasetOptions.ServiceOptions getDefaultInstance() {
+      return DEFAULT_INSTANCE;
+    }
+
+    private static final com.google.protobuf.Parser
+        PARSER = new com.google.protobuf.AbstractParser() {
+      @java.lang.Override
+      public ServiceOptions parsePartialFrom(
+          com.google.protobuf.CodedInputStream input,
+          com.google.protobuf.ExtensionRegistryLite extensionRegistry)
+          throws com.google.protobuf.InvalidProtocolBufferException {
+        Builder builder = newBuilder();
+        try {
+          builder.mergeFrom(input, extensionRegistry);
+        } catch (com.google.protobuf.InvalidProtocolBufferException e) {
+          throw e.setUnfinishedMessage(builder.buildPartial());
+        } catch (com.google.protobuf.UninitializedMessageException e) {
+          throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial());
+        } catch (java.io.IOException e) {
+          throw new com.google.protobuf.InvalidProtocolBufferException(e)
+              .setUnfinishedMessage(builder.buildPartial());
+        }
+        return builder.buildPartial();
+      }
+    };
+
+    public static com.google.protobuf.Parser parser() {
+      return PARSER;
+    }
+
+    @java.lang.Override
+    public com.google.protobuf.Parser getParserForType() {
+      return PARSER;
+    }
+
+    @java.lang.Override
+    public org.tensorflow.proto.data.DatasetOptions.ServiceOptions getDefaultInstanceForType() {
+      return DEFAULT_INSTANCE;
+    }
+
+  }
+
+  public interface ThreadingOptionsOrBuilder extends
+      // @@protoc_insertion_point(interface_extends:tensorflow.data.ThreadingOptions)
+      com.google.protobuf.MessageOrBuilder {
+
+    /**
+     * int32 max_intra_op_parallelism = 1;
+     * @return Whether the maxIntraOpParallelism field is set.
+     */
+    boolean hasMaxIntraOpParallelism();
+    /**
+     * int32 max_intra_op_parallelism = 1;
+     * @return The maxIntraOpParallelism.
+     */
+    int getMaxIntraOpParallelism();
+
+    /**
+     * int32 private_threadpool_size = 2;
+     * @return Whether the privateThreadpoolSize field is set.
+     */
+    boolean hasPrivateThreadpoolSize();
+    /**
+     * int32 private_threadpool_size = 2;
+     * @return The privateThreadpoolSize.
+     */
+    int getPrivateThreadpoolSize();
+
+    public org.tensorflow.proto.data.DatasetOptions.ThreadingOptions.OptionalMaxIntraOpParallelismCase getOptionalMaxIntraOpParallelismCase();
+
+    public org.tensorflow.proto.data.DatasetOptions.ThreadingOptions.OptionalPrivateThreadpoolSizeCase getOptionalPrivateThreadpoolSizeCase();
+  }
+  /**
+   * 
+   * next: 3
+   * 

+   *
+   * Protobuf type {@code tensorflow.data.ThreadingOptions}
+   */
+  public static final class ThreadingOptions extends
+      com.google.protobuf.GeneratedMessageV3 implements
+      // @@protoc_insertion_point(message_implements:tensorflow.data.ThreadingOptions)
+      ThreadingOptionsOrBuilder {
+  private static final long serialVersionUID = 0L;
+    // Use ThreadingOptions.newBuilder() to construct.
+    private ThreadingOptions(com.google.protobuf.GeneratedMessageV3.Builder builder) {
+      super(builder);
+    }
+    private ThreadingOptions() {
+    }
+
+    @java.lang.Override
+    @SuppressWarnings({"unused"})
+    protected java.lang.Object newInstance(
+        UnusedPrivateParameter unused) {
+      return new ThreadingOptions();
+    }
+
+    @java.lang.Override
+    public final com.google.protobuf.UnknownFieldSet
+    getUnknownFields() {
+      return this.unknownFields;
+    }
+    public static final com.google.protobuf.Descriptors.Descriptor
+        getDescriptor() {
+      return org.tensorflow.proto.data.DatasetOptions.internal_static_tensorflow_data_ThreadingOptions_descriptor;
+    }
+
+    @java.lang.Override
+    protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
+        internalGetFieldAccessorTable() {
+      return org.tensorflow.proto.data.DatasetOptions.internal_static_tensorflow_data_ThreadingOptions_fieldAccessorTable
+          .ensureFieldAccessorsInitialized(
+              org.tensorflow.proto.data.DatasetOptions.ThreadingOptions.class, org.tensorflow.proto.data.DatasetOptions.ThreadingOptions.Builder.class);
+    }
+
+    private int optionalMaxIntraOpParallelismCase_ = 0;
+    private java.lang.Object optionalMaxIntraOpParallelism_;
+    public enum OptionalMaxIntraOpParallelismCase
+        implements com.google.protobuf.Internal.EnumLite,
+            com.google.protobuf.AbstractMessage.InternalOneOfEnum {
+      MAX_INTRA_OP_PARALLELISM(1),
+      OPTIONALMAXINTRAOPPARALLELISM_NOT_SET(0);
+      private final int value;
+      private OptionalMaxIntraOpParallelismCase(int value) {
+        this.value = value;
+      }
+      /**
+       * @param value The number of the enum to look for.
+       * @return The enum associated with the given number.
+       * @deprecated Use {@link #forNumber(int)} instead.
+       */
+      @java.lang.Deprecated
+      public static OptionalMaxIntraOpParallelismCase valueOf(int value) {
+        return forNumber(value);
+      }
+
+      public static OptionalMaxIntraOpParallelismCase forNumber(int value) {
+        switch (value) {
+          case 1: return MAX_INTRA_OP_PARALLELISM;
+          case 0: return OPTIONALMAXINTRAOPPARALLELISM_NOT_SET;
+          default: return null;
+        }
+      }
+      public int getNumber() {
+        return this.value;
+      }
+    };
+
+    public OptionalMaxIntraOpParallelismCase
+    getOptionalMaxIntraOpParallelismCase() {
+      return OptionalMaxIntraOpParallelismCase.forNumber(
+          optionalMaxIntraOpParallelismCase_);
+    }
+
+    private int optionalPrivateThreadpoolSizeCase_ = 0;
+    private java.lang.Object optionalPrivateThreadpoolSize_;
+    public enum OptionalPrivateThreadpoolSizeCase
+        implements com.google.protobuf.Internal.EnumLite,
+            com.google.protobuf.AbstractMessage.InternalOneOfEnum {
+      PRIVATE_THREADPOOL_SIZE(2),
+      OPTIONALPRIVATETHREADPOOLSIZE_NOT_SET(0);
+      private final int value;
+      private OptionalPrivateThreadpoolSizeCase(int value) {
+        this.value = value;
+      }
+      /**
+       * @param value The number of the enum to look for.
+       * @return The enum associated with the given number.
+       * @deprecated Use {@link #forNumber(int)} instead.
+       */
+      @java.lang.Deprecated
+      public static OptionalPrivateThreadpoolSizeCase valueOf(int value) {
+        return forNumber(value);
+      }
+
+      public static OptionalPrivateThreadpoolSizeCase forNumber(int value) {
+        switch (value) {
+          case 2: return PRIVATE_THREADPOOL_SIZE;
+          case 0: return OPTIONALPRIVATETHREADPOOLSIZE_NOT_SET;
+          default: return null;
+        }
+      }
+      public int getNumber() {
+        return this.value;
+      }
+    };
+
+    public OptionalPrivateThreadpoolSizeCase
+    getOptionalPrivateThreadpoolSizeCase() {
+      return OptionalPrivateThreadpoolSizeCase.forNumber(
+          optionalPrivateThreadpoolSizeCase_);
+    }
+
+    public static final int MAX_INTRA_OP_PARALLELISM_FIELD_NUMBER = 1;
+    /**
+     * int32 max_intra_op_parallelism = 1;
+     * @return Whether the maxIntraOpParallelism field is set.
+     */
+    @java.lang.Override
+    public boolean hasMaxIntraOpParallelism() {
+      return optionalMaxIntraOpParallelismCase_ == 1;
+    }
+    /**
+     * int32 max_intra_op_parallelism = 1;
+     * @return The maxIntraOpParallelism.
+     */
+    @java.lang.Override
+    public int getMaxIntraOpParallelism() {
+      if (optionalMaxIntraOpParallelismCase_ == 1) {
+        return (java.lang.Integer) optionalMaxIntraOpParallelism_;
+      }
+      return 0;
+    }
+
+    public static final int PRIVATE_THREADPOOL_SIZE_FIELD_NUMBER = 2;
+    /**
+     * int32 private_threadpool_size = 2;
+     * @return Whether the privateThreadpoolSize field is set.
+     */
+    @java.lang.Override
+    public boolean hasPrivateThreadpoolSize() {
+      return optionalPrivateThreadpoolSizeCase_ == 2;
+    }
+    /**
+     * int32 private_threadpool_size = 2;
+     * @return The privateThreadpoolSize.
+     */
+    @java.lang.Override
+    public int getPrivateThreadpoolSize() {
+      if (optionalPrivateThreadpoolSizeCase_ == 2) {
+        return (java.lang.Integer) optionalPrivateThreadpoolSize_;
+      }
+      return 0;
+    }
+
+    private byte memoizedIsInitialized = -1;
+    @java.lang.Override
+    public final boolean isInitialized() {
+      byte isInitialized = memoizedIsInitialized;
+      if (isInitialized == 1) return true;
+      if (isInitialized == 0) return false;
+
+      memoizedIsInitialized = 1;
+      return true;
+    }
+
+    @java.lang.Override
+    public void writeTo(com.google.protobuf.CodedOutputStream output)
+                        throws java.io.IOException {
+      if (optionalMaxIntraOpParallelismCase_ == 1) {
+        output.writeInt32(
+            1, (int)((java.lang.Integer) optionalMaxIntraOpParallelism_));
+      }
+      if (optionalPrivateThreadpoolSizeCase_ == 2) {
+        output.writeInt32(
+            2, (int)((java.lang.Integer) optionalPrivateThreadpoolSize_));
+      }
+      getUnknownFields().writeTo(output);
+    }
+
+    @java.lang.Override
+    public int getSerializedSize() {
+      int size = memoizedSize;
+      if (size != -1) return size;
+
+      size = 0;
+      if (optionalMaxIntraOpParallelismCase_ == 1) {
+        size += com.google.protobuf.CodedOutputStream
+          .computeInt32Size(
+              1, (int)((java.lang.Integer) optionalMaxIntraOpParallelism_));
+      }
+      if (optionalPrivateThreadpoolSizeCase_ == 2) {
+        size += com.google.protobuf.CodedOutputStream
+          .computeInt32Size(
+              2, (int)((java.lang.Integer) optionalPrivateThreadpoolSize_));
+      }
+      size += getUnknownFields().getSerializedSize();
+      memoizedSize = size;
+      return size;
+    }
+
+    @java.lang.Override
+    public boolean equals(final java.lang.Object obj) {
+      if (obj == this) {
+       return true;
+      }
+      if (!(obj instanceof org.tensorflow.proto.data.DatasetOptions.ThreadingOptions)) {
+        return super.equals(obj);
+      }
+      org.tensorflow.proto.data.DatasetOptions.ThreadingOptions other = (org.tensorflow.proto.data.DatasetOptions.ThreadingOptions) obj;
+
+      if (!getOptionalMaxIntraOpParallelismCase().equals(other.getOptionalMaxIntraOpParallelismCase())) return false;
+      switch (optionalMaxIntraOpParallelismCase_) {
+        case 1:
+          if (getMaxIntraOpParallelism()
+              != other.getMaxIntraOpParallelism()) return false;
+          break;
+        case 0:
+        default:
+      }
+      if (!getOptionalPrivateThreadpoolSizeCase().equals(other.getOptionalPrivateThreadpoolSizeCase())) return false;
+      switch (optionalPrivateThreadpoolSizeCase_) {
+        case 2:
+          if (getPrivateThreadpoolSize()
+              != other.getPrivateThreadpoolSize()) return false;
+          break;
+        case 0:
+        default:
+      }
+      if (!getUnknownFields().equals(other.getUnknownFields())) return false;
+      return true;
+    }
+
+    @java.lang.Override
+    public int hashCode() {
+      if (memoizedHashCode != 0) {
+        return memoizedHashCode;
+      }
+      int hash = 41;
+      hash = (19 * hash) + getDescriptor().hashCode();
+      switch (optionalMaxIntraOpParallelismCase_) {
+        case 1:
+          hash = (37 * hash) + MAX_INTRA_OP_PARALLELISM_FIELD_NUMBER;
+          hash = (53 * hash) + getMaxIntraOpParallelism();
+          break;
+        case 0:
+        default:
+      }
+      switch (optionalPrivateThreadpoolSizeCase_) {
+        case 2:
+          hash = (37 * hash) + PRIVATE_THREADPOOL_SIZE_FIELD_NUMBER;
+          hash = (53 * hash) + getPrivateThreadpoolSize();
           break;
         case 0:
         default:
@@ -6261,6 +7021,33 @@ public interface OptionsOrBuilder extends
      */
     org.tensorflow.proto.data.DatasetOptions.OptimizationOptionsOrBuilder getOptimizationOptionsOrBuilder();
 
+    /**
+     * 
+     * The tf.data service options associated with the dataset.
+     * 

+     *
+     * .tensorflow.data.ServiceOptions service_options = 12;
+     * @return Whether the serviceOptions field is set.
+     */
+    boolean hasServiceOptions();
+    /**
+     * 
+     * The tf.data service options associated with the dataset.
+     * 

+     *
+     * .tensorflow.data.ServiceOptions service_options = 12;
+     * @return The serviceOptions.
+     */
+    org.tensorflow.proto.data.DatasetOptions.ServiceOptions getServiceOptions();
+    /**
+     * 
+     * The tf.data service options associated with the dataset.
+     * 

+     *
+     * .tensorflow.data.ServiceOptions service_options = 12;
+     */
+    org.tensorflow.proto.data.DatasetOptions.ServiceOptionsOrBuilder getServiceOptionsOrBuilder();
+
     /**
      * bool slack = 4;
      * @return Whether the slack field is set.
@@ -6353,7 +7140,7 @@ public interface OptionsOrBuilder extends
    * 
    * Message stored with Dataset objects to control how datasets are processed and
    * optimized.
-   * next: 12
+   * next: 13
    * 

    *
    * Protobuf type {@code tensorflow.data.Options}
@@ -6868,6 +7655,44 @@ public org.tensorflow.proto.data.DatasetOptions.OptimizationOptionsOrBuilder get
       return getOptimizationOptions();
     }
 
+    public static final int SERVICE_OPTIONS_FIELD_NUMBER = 12;
+    private org.tensorflow.proto.data.DatasetOptions.ServiceOptions serviceOptions_;
+    /**
+     * 
+     * The tf.data service options associated with the dataset.
+     * 

+     *
+     * .tensorflow.data.ServiceOptions service_options = 12;
+     * @return Whether the serviceOptions field is set.
+     */
+    @java.lang.Override
+    public boolean hasServiceOptions() {
+      return serviceOptions_ != null;
+    }
+    /**
+     * 
+     * The tf.data service options associated with the dataset.
+     * 

+     *
+     * .tensorflow.data.ServiceOptions service_options = 12;
+     * @return The serviceOptions.
+     */
+    @java.lang.Override
+    public org.tensorflow.proto.data.DatasetOptions.ServiceOptions getServiceOptions() {
+      return serviceOptions_ == null ? org.tensorflow.proto.data.DatasetOptions.ServiceOptions.getDefaultInstance() : serviceOptions_;
+    }
+    /**
+     * 
+     * The tf.data service options associated with the dataset.
+     * 

+     *
+     * .tensorflow.data.ServiceOptions service_options = 12;
+     */
+    @java.lang.Override
+    public org.tensorflow.proto.data.DatasetOptions.ServiceOptionsOrBuilder getServiceOptionsOrBuilder() {
+      return getServiceOptions();
+    }
+
     public static final int SLACK_FIELD_NUMBER = 4;
     /**
      * bool slack = 4;
@@ -7052,6 +7877,9 @@ public void writeTo(com.google.protobuf.CodedOutputStream output)
       for (int i = 0; i < frameworkType_.size(); i++) {
         com.google.protobuf.GeneratedMessageV3.writeString(output, 11, frameworkType_.getRaw(i));
       }
+      if (serviceOptions_ != null) {
+        output.writeMessage(12, getServiceOptions());
+      }
       getUnknownFields().writeTo(output);
     }
 
@@ -7112,6 +7940,10 @@ public int getSerializedSize() {
         size += dataSize;
         size += 1 * getFrameworkTypeList().size();
       }
+      if (serviceOptions_ != null) {
+        size += com.google.protobuf.CodedOutputStream
+          .computeMessageSize(12, getServiceOptions());
+      }
       size += getUnknownFields().getSerializedSize();
       memoizedSize = size;
       return size;
@@ -7144,6 +7976,11 @@ public boolean equals(final java.lang.Object obj) {
         if (!getOptimizationOptions()
             .equals(other.getOptimizationOptions())) return false;
       }
+      if (hasServiceOptions() != other.hasServiceOptions()) return false;
+      if (hasServiceOptions()) {
+        if (!getServiceOptions()
+            .equals(other.getServiceOptions())) return false;
+      }
       if (hasThreadingOptions() != other.hasThreadingOptions()) return false;
       if (hasThreadingOptions()) {
         if (!getThreadingOptions()
@@ -7230,6 +8067,10 @@ public int hashCode() {
         hash = (37 * hash) + OPTIMIZATION_OPTIONS_FIELD_NUMBER;
         hash = (53 * hash) + getOptimizationOptions().hashCode();
       }
+      if (hasServiceOptions()) {
+        hash = (37 * hash) + SERVICE_OPTIONS_FIELD_NUMBER;
+        hash = (53 * hash) + getServiceOptions().hashCode();
+      }
       if (hasThreadingOptions()) {
         hash = (37 * hash) + THREADING_OPTIONS_FIELD_NUMBER;
         hash = (53 * hash) + getThreadingOptions().hashCode();
@@ -7385,7 +8226,7 @@ protected Builder newBuilderForType(
      * 
      * Message stored with Dataset objects to control how datasets are processed and
      * optimized.
-     * next: 12
+     * next: 13
      * 

      *
      * Protobuf type {@code tensorflow.data.Options}
@@ -7440,6 +8281,12 @@ public Builder clear() {
           optimizationOptions_ = null;
           optimizationOptionsBuilder_ = null;
         }
+        if (serviceOptionsBuilder_ == null) {
+          serviceOptions_ = null;
+        } else {
+          serviceOptions_ = null;
+          serviceOptionsBuilder_ = null;
+        }
         if (threadingOptionsBuilder_ == null) {
           threadingOptions_ = null;
         } else {
@@ -7511,6 +8358,11 @@ public org.tensorflow.proto.data.DatasetOptions.Options buildPartial() {
         } else {
           result.optimizationOptions_ = optimizationOptionsBuilder_.build();
         }
+        if (serviceOptionsBuilder_ == null) {
+          result.serviceOptions_ = serviceOptions_;
+        } else {
+          result.serviceOptions_ = serviceOptionsBuilder_.build();
+        }
         if (optionalSlackCase_ == 4) {
           result.optionalSlack_ = optionalSlack_;
         }
@@ -7601,6 +8453,9 @@ public Builder mergeFrom(org.tensorflow.proto.data.DatasetOptions.Options other)
         if (other.hasOptimizationOptions()) {
           mergeOptimizationOptions(other.getOptimizationOptions());
         }
+        if (other.hasServiceOptions()) {
+          mergeServiceOptions(other.getServiceOptions());
+        }
         if (other.hasThreadingOptions()) {
           mergeThreadingOptions(other.getThreadingOptions());
         }
@@ -7752,6 +8607,13 @@ public Builder mergeFrom(
                 frameworkType_.add(s);
                 break;
               } // case 90
+              case 98: {
+                input.readMessage(
+                    getServiceOptionsFieldBuilder().getBuilder(),
+                    extensionRegistry);
+
+                break;
+              } // case 98
               default: {
                 if (!super.parseUnknownField(input, extensionRegistry, tag)) {
                   done = true; // was an endgroup tag
@@ -8608,6 +9470,161 @@ public org.tensorflow.proto.data.DatasetOptions.OptimizationOptionsOrBuilder get
         return optimizationOptionsBuilder_;
       }
 
+      private org.tensorflow.proto.data.DatasetOptions.ServiceOptions serviceOptions_;
+      private com.google.protobuf.SingleFieldBuilderV3<
+          org.tensorflow.proto.data.DatasetOptions.ServiceOptions, org.tensorflow.proto.data.DatasetOptions.ServiceOptions.Builder, org.tensorflow.proto.data.DatasetOptions.ServiceOptionsOrBuilder> serviceOptionsBuilder_;
+      /**
+       * 
+       * The tf.data service options associated with the dataset.
+       * 

+       *
+       * .tensorflow.data.ServiceOptions service_options = 12;
+       * @return Whether the serviceOptions field is set.
+       */
+      public boolean hasServiceOptions() {
+        return serviceOptionsBuilder_ != null || serviceOptions_ != null;
+      }
+      /**
+       * 
+       * The tf.data service options associated with the dataset.
+       * 

+       *
+       * .tensorflow.data.ServiceOptions service_options = 12;
+       * @return The serviceOptions.
+       */
+      public org.tensorflow.proto.data.DatasetOptions.ServiceOptions getServiceOptions() {
+        if (serviceOptionsBuilder_ == null) {
+          return serviceOptions_ == null ? org.tensorflow.proto.data.DatasetOptions.ServiceOptions.getDefaultInstance() : serviceOptions_;
+        } else {
+          return serviceOptionsBuilder_.getMessage();
+        }
+      }
+      /**
+       * 
+       * The tf.data service options associated with the dataset.
+       * 

+       *
+       * .tensorflow.data.ServiceOptions service_options = 12;
+       */
+      public Builder setServiceOptions(org.tensorflow.proto.data.DatasetOptions.ServiceOptions value) {
+        if (serviceOptionsBuilder_ == null) {
+          if (value == null) {
+            throw new NullPointerException();
+          }
+          serviceOptions_ = value;
+          onChanged();
+        } else {
+          serviceOptionsBuilder_.setMessage(value);
+        }
+
+        return this;
+      }
+      /**
+       * 
+       * The tf.data service options associated with the dataset.
+       * 

+       *
+       * .tensorflow.data.ServiceOptions service_options = 12;
+       */
+      public Builder setServiceOptions(
+          org.tensorflow.proto.data.DatasetOptions.ServiceOptions.Builder builderForValue) {
+        if (serviceOptionsBuilder_ == null) {
+          serviceOptions_ = builderForValue.build();
+          onChanged();
+        } else {
+          serviceOptionsBuilder_.setMessage(builderForValue.build());
+        }
+
+        return this;
+      }
+      /**
+       * 
+       * The tf.data service options associated with the dataset.
+       * 

+       *
+       * .tensorflow.data.ServiceOptions service_options = 12;
+       */
+      public Builder mergeServiceOptions(org.tensorflow.proto.data.DatasetOptions.ServiceOptions value) {
+        if (serviceOptionsBuilder_ == null) {
+          if (serviceOptions_ != null) {
+            serviceOptions_ =
+              org.tensorflow.proto.data.DatasetOptions.ServiceOptions.newBuilder(serviceOptions_).mergeFrom(value).buildPartial();
+          } else {
+            serviceOptions_ = value;
+          }
+          onChanged();
+        } else {
+          serviceOptionsBuilder_.mergeFrom(value);
+        }
+
+        return this;
+      }
+      /**
+       * 
+       * The tf.data service options associated with the dataset.
+       * 

+       *
+       * .tensorflow.data.ServiceOptions service_options = 12;
+       */
+      public Builder clearServiceOptions() {
+        if (serviceOptionsBuilder_ == null) {
+          serviceOptions_ = null;
+          onChanged();
+        } else {
+          serviceOptions_ = null;
+          serviceOptionsBuilder_ = null;
+        }
+
+        return this;
+      }
+      /**
+       * 
+       * The tf.data service options associated with the dataset.
+       * 

+       *
+       * .tensorflow.data.ServiceOptions service_options = 12;
+       */
+      public org.tensorflow.proto.data.DatasetOptions.ServiceOptions.Builder getServiceOptionsBuilder() {
+        
+        onChanged();
+        return getServiceOptionsFieldBuilder().getBuilder();
+      }
+      /**
+       * 
+       * The tf.data service options associated with the dataset.
+       * 

+       *
+       * .tensorflow.data.ServiceOptions service_options = 12;
+       */
+      public org.tensorflow.proto.data.DatasetOptions.ServiceOptionsOrBuilder getServiceOptionsOrBuilder() {
+        if (serviceOptionsBuilder_ != null) {
+          return serviceOptionsBuilder_.getMessageOrBuilder();
+        } else {
+          return serviceOptions_ == null ?
+              org.tensorflow.proto.data.DatasetOptions.ServiceOptions.getDefaultInstance() : serviceOptions_;
+        }
+      }
+      /**
+       * 
+       * The tf.data service options associated with the dataset.
+       * 

+       *
+       * .tensorflow.data.ServiceOptions service_options = 12;
+       */
+      private com.google.protobuf.SingleFieldBuilderV3<
+          org.tensorflow.proto.data.DatasetOptions.ServiceOptions, org.tensorflow.proto.data.DatasetOptions.ServiceOptions.Builder, org.tensorflow.proto.data.DatasetOptions.ServiceOptionsOrBuilder> 
+          getServiceOptionsFieldBuilder() {
+        if (serviceOptionsBuilder_ == null) {
+          serviceOptionsBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
+              org.tensorflow.proto.data.DatasetOptions.ServiceOptions, org.tensorflow.proto.data.DatasetOptions.ServiceOptions.Builder, org.tensorflow.proto.data.DatasetOptions.ServiceOptionsOrBuilder>(
+                  getServiceOptions(),
+                  getParentForChildren(),
+                  isClean());
+          serviceOptions_ = null;
+        }
+        return serviceOptionsBuilder_;
+      }
+
       /**
        * bool slack = 4;
        * @return Whether the slack field is set.
@@ -9040,6 +10057,11 @@ public org.tensorflow.proto.data.DatasetOptions.Options getDefaultInstanceForTyp
   private static final 
     com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
       internal_static_tensorflow_data_OptimizationOptions_fieldAccessorTable;
+  private static final com.google.protobuf.Descriptors.Descriptor
+    internal_static_tensorflow_data_ServiceOptions_descriptor;
+  private static final 
+    com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
+      internal_static_tensorflow_data_ServiceOptions_fieldAccessorTable;
   private static final com.google.protobuf.Descriptors.Descriptor
     internal_static_tensorflow_data_ThreadingOptions_descriptor;
   private static final 
@@ -9061,70 +10083,74 @@ public org.tensorflow.proto.data.DatasetOptions.Options getDefaultInstanceForTyp
     java.lang.String[] descriptorData = {
       "\n/tensorflow/core/framework/dataset_opti" +
       "ons.proto\022\017tensorflow.data\032%tensorflow/c" +
-      "ore/framework/model.proto\"\371\001\n\017AutotuneOp" +
+      "ore/framework/model.proto\"\270\002\n\017AutotuneOp" +
       "tions\022\021\n\007enabled\030\001 \001(\010H\000\022\024\n\ncpu_budget\030\002" +
       " \001(\005H\001\022\024\n\nram_budget\030\003 \001(\003H\002\022F\n\022autotune" +
       "_algorithm\030\004 \001(\0162(.tensorflow.data.model" +
-      ".AutotuneAlgorithmH\003B\022\n\020optional_enabled" +
-      "B\025\n\023optional_cpu_budgetB\025\n\023optional_ram_" +
-      "budgetB\035\n\033optional_autotune_algorithm\"\321\001" +
-      "\n\022CardinalityOptions\022G\n\rcompute_level\030\001 " +
-      "\001(\01620.tensorflow.data.CardinalityOptions" +
-      ".ComputeLevel\"r\n\014ComputeLevel\022#\n\037CARDINA" +
-      "LITY_COMPUTE_UNSPECIFIED\020\000\022\033\n\027CARDINALIT" +
-      "Y_COMPUTE_LOW\020\001\022 \n\034CARDINALITY_COMPUTE_M" +
-      "ODERATE\020\002\"\177\n\021DistributeOptions\022;\n\021auto_s" +
-      "hard_policy\030\001 \001(\0162 .tensorflow.data.Auto" +
-      "ShardPolicy\022\025\n\013num_devices\030\002 \001(\005H\000B\026\n\024op" +
-      "tional_num_devices\"\271\006\n\023OptimizationOptio" +
-      "ns\022%\n\033apply_default_optimizations\030\001 \001(\010H" +
-      "\000\022\027\n\rfilter_fusion\030\006 \001(\010H\001\022\036\n\024map_and_ba" +
-      "tch_fusion\030\t \001(\010H\002\022\037\n\025map_and_filter_fus" +
-      "ion\030\n \001(\010H\003\022\024\n\nmap_fusion\030\013 \001(\010H\004\022\035\n\023map" +
-      "_parallelization\030\014 \001(\010H\005\022\032\n\020noop_elimina" +
-      "tion\030\016 \001(\010H\006\022\030\n\016parallel_batch\030\017 \001(\010H\007\022#" +
-      "\n\031shuffle_and_repeat_fusion\030\021 \001(\010H\010\022 \n\026f" +
-      "ilter_parallelization\030\022 \001(\010H\t\022\031\n\017inject_" +
-      "prefetch\030\023 \001(\010H\n\022!\n\027seq_interleave_prefe" +
-      "tch\030\025 \001(\010H\013B&\n$optional_apply_default_op" +
-      "timizationsB\030\n\026optional_filter_fusionB\037\n" +
-      "\035optional_map_and_batch_fusionB \n\036option" +
-      "al_map_and_filter_fusionB\025\n\023optional_map" +
-      "_fusionB\036\n\034optional_map_parallelizationB" +
-      "\033\n\031optional_noop_eliminationB\031\n\027optional" +
-      "_parallel_batchB$\n\"optional_shuffle_and_" +
-      "repeat_fusionB!\n\037optional_filter_paralle" +
-      "lizationB\032\n\030optional_inject_prefetchB\"\n " +
-      "optional_seq_interleave_prefetchJ\004\010\002\020\003J\004" +
-      "\010\003\020\004J\004\010\004\020\005J\004\010\005\020\006J\004\010\007\020\010J\004\010\010\020\tJ\004\010\r\020\016J\004\010\020\020\021" +
-      "J\004\010\024\020\025\"\242\001\n\020ThreadingOptions\022\"\n\030max_intra" +
-      "_op_parallelism\030\001 \001(\005H\000\022!\n\027private_threa" +
-      "dpool_size\030\002 \001(\005H\001B#\n!optional_max_intra" +
-      "_op_parallelismB\"\n optional_private_thre" +
-      "adpool_size\"\373\004\n\007Options\022\026\n\014dataset_name\030" +
-      "\n \001(\tH\000\022\026\n\016framework_type\030\013 \003(\t\022\027\n\rdeter" +
-      "ministic\030\001 \001(\010H\001\022:\n\020autotune_options\030\007 \001" +
-      "(\0132 .tensorflow.data.AutotuneOptions\022>\n\022" +
-      "distribute_options\030\002 \001(\0132\".tensorflow.da" +
-      "ta.DistributeOptions\022B\n\024optimization_opt" +
-      "ions\030\003 \001(\0132$.tensorflow.data.Optimizatio" +
-      "nOptions\022\017\n\005slack\030\004 \001(\010H\002\022<\n\021threading_o" +
-      "ptions\030\005 \001(\0132!.tensorflow.data.Threading" +
-      "Options\022E\n\025external_state_policy\030\006 \001(\0162$" +
-      ".tensorflow.data.ExternalStatePolicyH\003\022\035" +
-      "\n\023symbolic_checkpoint\030\010 \001(\010H\004\022\024\n\nwarm_st" +
-      "art\030\t \001(\010H\005B\027\n\025optional_dataset_nameB\030\n\026" +
-      "optional_deterministicB\020\n\016optional_slack" +
-      "B \n\036optional_external_state_policyB\036\n\034op" +
-      "tional_symbolic_checkpointB\025\n\023optional_w" +
-      "arm_start*K\n\017AutoShardPolicy\022\010\n\004AUTO\020\000\022\010" +
-      "\n\004FILE\020\001\022\010\n\004DATA\020\002\022\010\n\004HINT\020\003\022\020\n\003OFF\020\377\377\377\377" +
-      "\377\377\377\377\377\001*J\n\023ExternalStatePolicy\022\017\n\013POLICY_" +
-      "WARN\020\000\022\021\n\rPOLICY_IGNORE\020\001\022\017\n\013POLICY_FAIL" +
-      "\020\002Bs\n\031org.tensorflow.proto.dataZVgithub." +
-      "com/tensorflow/tensorflow/tensorflow/go/" +
-      "core/framework/dataset_options_go_protob" +
-      "\006proto3"
+      ".AutotuneAlgorithmH\003\022\035\n\023initial_parallel" +
+      "ism\030\005 \001(\003H\004B\022\n\020optional_enabledB\025\n\023optio" +
+      "nal_cpu_budgetB\025\n\023optional_ram_budgetB\035\n" +
+      "\033optional_autotune_algorithmB\036\n\034optional" +
+      "_initial_parallelism\"\321\001\n\022CardinalityOpti" +
+      "ons\022G\n\rcompute_level\030\001 \001(\01620.tensorflow." +
+      "data.CardinalityOptions.ComputeLevel\"r\n\014" +
+      "ComputeLevel\022#\n\037CARDINALITY_COMPUTE_UNSP" +
+      "ECIFIED\020\000\022\033\n\027CARDINALITY_COMPUTE_LOW\020\001\022 " +
+      "\n\034CARDINALITY_COMPUTE_MODERATE\020\002\"\177\n\021Dist" +
+      "ributeOptions\022;\n\021auto_shard_policy\030\001 \001(\016" +
+      "2 .tensorflow.data.AutoShardPolicy\022\025\n\013nu" +
+      "m_devices\030\002 \001(\005H\000B\026\n\024optional_num_device" +
+      "s\"\271\006\n\023OptimizationOptions\022%\n\033apply_defau" +
+      "lt_optimizations\030\001 \001(\010H\000\022\027\n\rfilter_fusio" +
+      "n\030\006 \001(\010H\001\022\036\n\024map_and_batch_fusion\030\t \001(\010H" +
+      "\002\022\037\n\025map_and_filter_fusion\030\n \001(\010H\003\022\024\n\nma" +
+      "p_fusion\030\013 \001(\010H\004\022\035\n\023map_parallelization\030" +
+      "\014 \001(\010H\005\022\032\n\020noop_elimination\030\016 \001(\010H\006\022\030\n\016p" +
+      "arallel_batch\030\017 \001(\010H\007\022#\n\031shuffle_and_rep" +
+      "eat_fusion\030\021 \001(\010H\010\022 \n\026filter_paralleliza" +
+      "tion\030\022 \001(\010H\t\022\031\n\017inject_prefetch\030\023 \001(\010H\n\022" +
+      "!\n\027seq_interleave_prefetch\030\025 \001(\010H\013B&\n$op" +
+      "tional_apply_default_optimizationsB\030\n\026op" +
+      "tional_filter_fusionB\037\n\035optional_map_and" +
+      "_batch_fusionB \n\036optional_map_and_filter" +
+      "_fusionB\025\n\023optional_map_fusionB\036\n\034option" +
+      "al_map_parallelizationB\033\n\031optional_noop_" +
+      "eliminationB\031\n\027optional_parallel_batchB$" +
+      "\n\"optional_shuffle_and_repeat_fusionB!\n\037" +
+      "optional_filter_parallelizationB\032\n\030optio" +
+      "nal_inject_prefetchB\"\n optional_seq_inte" +
+      "rleave_prefetchJ\004\010\002\020\003J\004\010\003\020\004J\004\010\004\020\005J\004\010\005\020\006J" +
+      "\004\010\007\020\010J\004\010\010\020\tJ\004\010\r\020\016J\004\010\020\020\021J\004\010\024\020\025\"5\n\016Service" +
+      "Options\022\020\n\006pinned\030\001 \001(\010H\000B\021\n\017optional_pi" +
+      "nned\"\242\001\n\020ThreadingOptions\022\"\n\030max_intra_o" +
+      "p_parallelism\030\001 \001(\005H\000\022!\n\027private_threadp" +
+      "ool_size\030\002 \001(\005H\001B#\n!optional_max_intra_o" +
+      "p_parallelismB\"\n optional_private_thread" +
+      "pool_size\"\265\005\n\007Options\022\026\n\014dataset_name\030\n " +
+      "\001(\tH\000\022\026\n\016framework_type\030\013 \003(\t\022\027\n\rdetermi" +
+      "nistic\030\001 \001(\010H\001\022:\n\020autotune_options\030\007 \001(\013" +
+      "2 .tensorflow.data.AutotuneOptions\022>\n\022di" +
+      "stribute_options\030\002 \001(\0132\".tensorflow.data" +
+      ".DistributeOptions\022B\n\024optimization_optio" +
+      "ns\030\003 \001(\0132$.tensorflow.data.OptimizationO" +
+      "ptions\0228\n\017service_options\030\014 \001(\0132\037.tensor" +
+      "flow.data.ServiceOptions\022\017\n\005slack\030\004 \001(\010H" +
+      "\002\022<\n\021threading_options\030\005 \001(\0132!.tensorflo" +
+      "w.data.ThreadingOptions\022E\n\025external_stat" +
+      "e_policy\030\006 \001(\0162$.tensorflow.data.Externa" +
+      "lStatePolicyH\003\022\035\n\023symbolic_checkpoint\030\010 " +
+      "\001(\010H\004\022\024\n\nwarm_start\030\t \001(\010H\005B\027\n\025optional_" +
+      "dataset_nameB\030\n\026optional_deterministicB\020" +
+      "\n\016optional_slackB \n\036optional_external_st" +
+      "ate_policyB\036\n\034optional_symbolic_checkpoi" +
+      "ntB\025\n\023optional_warm_start*K\n\017AutoShardPo" +
+      "licy\022\010\n\004AUTO\020\000\022\010\n\004FILE\020\001\022\010\n\004DATA\020\002\022\010\n\004HI" +
+      "NT\020\003\022\020\n\003OFF\020\377\377\377\377\377\377\377\377\377\001*J\n\023ExternalStateP" +
+      "olicy\022\017\n\013POLICY_WARN\020\000\022\021\n\rPOLICY_IGNORE\020" +
+      "\001\022\017\n\013POLICY_FAIL\020\002Bs\n\031org.tensorflow.pro" +
+      "to.dataZVgithub.com/tensorflow/tensorflo" +
+      "w/tensorflow/go/core/framework/dataset_o" +
+      "ptions_go_protob\006proto3"
     };
     descriptor = com.google.protobuf.Descriptors.FileDescriptor
       .internalBuildGeneratedFileFrom(descriptorData,
@@ -9136,7 +10162,7 @@ public org.tensorflow.proto.data.DatasetOptions.Options getDefaultInstanceForTyp
     internal_static_tensorflow_data_AutotuneOptions_fieldAccessorTable = new
       com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
         internal_static_tensorflow_data_AutotuneOptions_descriptor,
-        new java.lang.String[] { "Enabled", "CpuBudget", "RamBudget", "AutotuneAlgorithm", "OptionalEnabled", "OptionalCpuBudget", "OptionalRamBudget", "OptionalAutotuneAlgorithm", });
+        new java.lang.String[] { "Enabled", "CpuBudget", "RamBudget", "AutotuneAlgorithm", "InitialParallelism", "OptionalEnabled", "OptionalCpuBudget", "OptionalRamBudget", "OptionalAutotuneAlgorithm", "OptionalInitialParallelism", });
     internal_static_tensorflow_data_CardinalityOptions_descriptor =
       getDescriptor().getMessageTypes().get(1);
     internal_static_tensorflow_data_CardinalityOptions_fieldAccessorTable = new
@@ -9155,18 +10181,24 @@ public org.tensorflow.proto.data.DatasetOptions.Options getDefaultInstanceForTyp
       com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
         internal_static_tensorflow_data_OptimizationOptions_descriptor,
         new java.lang.String[] { "ApplyDefaultOptimizations", "FilterFusion", "MapAndBatchFusion", "MapAndFilterFusion", "MapFusion", "MapParallelization", "NoopElimination", "ParallelBatch", "ShuffleAndRepeatFusion", "FilterParallelization", "InjectPrefetch", "SeqInterleavePrefetch", "OptionalApplyDefaultOptimizations", "OptionalFilterFusion", "OptionalMapAndBatchFusion", "OptionalMapAndFilterFusion", "OptionalMapFusion", "OptionalMapParallelization", "OptionalNoopElimination", "OptionalParallelBatch", "OptionalShuffleAndRepeatFusion", "OptionalFilterParallelization", "OptionalInjectPrefetch", "OptionalSeqInterleavePrefetch", });
-    internal_static_tensorflow_data_ThreadingOptions_descriptor =
+    internal_static_tensorflow_data_ServiceOptions_descriptor =
       getDescriptor().getMessageTypes().get(4);
+    internal_static_tensorflow_data_ServiceOptions_fieldAccessorTable = new
+      com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
+        internal_static_tensorflow_data_ServiceOptions_descriptor,
+        new java.lang.String[] { "Pinned", "OptionalPinned", });
+    internal_static_tensorflow_data_ThreadingOptions_descriptor =
+      getDescriptor().getMessageTypes().get(5);
     internal_static_tensorflow_data_ThreadingOptions_fieldAccessorTable = new
       com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
         internal_static_tensorflow_data_ThreadingOptions_descriptor,
         new java.lang.String[] { "MaxIntraOpParallelism", "PrivateThreadpoolSize", "OptionalMaxIntraOpParallelism", "OptionalPrivateThreadpoolSize", });
     internal_static_tensorflow_data_Options_descriptor =
-      getDescriptor().getMessageTypes().get(5);
+      getDescriptor().getMessageTypes().get(6);
     internal_static_tensorflow_data_Options_fieldAccessorTable = new
       com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
         internal_static_tensorflow_data_Options_descriptor,
-        new java.lang.String[] { "DatasetName", "FrameworkType", "Deterministic", "AutotuneOptions", "DistributeOptions", "OptimizationOptions", "Slack", "ThreadingOptions", "ExternalStatePolicy", "SymbolicCheckpoint", "WarmStart", "OptionalDatasetName", "OptionalDeterministic", "OptionalSlack", "OptionalExternalStatePolicy", "OptionalSymbolicCheckpoint", "OptionalWarmStart", });
+        new java.lang.String[] { "DatasetName", "FrameworkType", "Deterministic", "AutotuneOptions", "DistributeOptions", "OptimizationOptions", "ServiceOptions", "Slack", "ThreadingOptions", "ExternalStatePolicy", "SymbolicCheckpoint", "WarmStart", "OptionalDatasetName", "OptionalDeterministic", "OptionalSlack", "OptionalExternalStatePolicy", "OptionalSymbolicCheckpoint", "OptionalWarmStart", });
     org.tensorflow.proto.data.model.Model.getDescriptor();
   }
 
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/data/experimental/ServiceConfig.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/data/experimental/ServiceConfig.java
index 5d143f7c9f8..de029b2baa5 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/data/experimental/ServiceConfig.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/data/experimental/ServiceConfig.java
@@ -2261,7 +2261,11 @@ public interface WorkerConfigOrBuilder extends
 
     /**
      * 
-     * The protocol for the worker to use when transferring data to clients.
+     * If set, the name of an alternative data transfer protocol for which the
+     * worker starts an additional server ("data transfer server"); the trainer
+     * can then get data from this server. If not set, no such server is started,
+     * and the trainer can only get data from the regular worker server over
+     * `protocol`.
      * 

      *
      * string data_transfer_protocol = 7;
@@ -2270,7 +2274,11 @@ public interface WorkerConfigOrBuilder extends
     java.lang.String getDataTransferProtocol();
     /**
      * 
-     * The protocol for the worker to use when transferring data to clients.
+     * If set, the name of an alternative data transfer protocol for which the
+     * worker starts an additional server ("data transfer server"); the trainer
+     * can then get data from this server. If not set, no such server is started,
+     * and the trainer can only get data from the regular worker server over
+     * `protocol`.
      * 

      *
      * string data_transfer_protocol = 7;
@@ -2281,9 +2289,21 @@ public interface WorkerConfigOrBuilder extends
 
     /**
      * 
-     * The data transfer address of the worker server. The substring "%port%", if
-     * specified, will be replaced with the worker's bound port. This is useful
-     * when the port is set to `0`.
+     * If `data_transfer_protocol` is set, the port to which the data transfer
+     * server binds. If set to `0`, the server binds to any available port.
+     * 

+     *
+     * int64 data_transfer_port = 13;
+     * @return The dataTransferPort.
+     */
+    long getDataTransferPort();
+
+    /**
+     * 
+     * If `data_transfer_protocol` is set, the address of the data transfer
+     * server. The substring "%dts_port%" can be used to represent -- and is
+     * replaced with -- the bound port of the data transfer server; this is useful
+     * when `data_transfer_port` is set to `0`.
      * 

      *
      * string data_transfer_address = 8;
@@ -2292,9 +2312,10 @@ public interface WorkerConfigOrBuilder extends
     java.lang.String getDataTransferAddress();
     /**
      * 
-     * The data transfer address of the worker server. The substring "%port%", if
-     * specified, will be replaced with the worker's bound port. This is useful
-     * when the port is set to `0`.
+     * If `data_transfer_protocol` is set, the address of the data transfer
+     * server. The substring "%dts_port%" can be used to represent -- and is
+     * replaced with -- the bound port of the data transfer server; this is useful
+     * when `data_transfer_port` is set to `0`.
      * 

      *
      * string data_transfer_address = 8;
@@ -2340,7 +2361,7 @@ public interface WorkerConfigOrBuilder extends
   /**
    * 
    * Configuration for a tf.data service WorkerServer.
-   * Next id: 13
+   * Next id: 14
    * 

    *
    * Protobuf type {@code tensorflow.data.experimental.WorkerConfig}
@@ -2646,7 +2667,11 @@ public long getDispatcherTimeoutMs() {
     private volatile java.lang.Object dataTransferProtocol_;
     /**
      * 
-     * The protocol for the worker to use when transferring data to clients.
+     * If set, the name of an alternative data transfer protocol for which the
+     * worker starts an additional server ("data transfer server"); the trainer
+     * can then get data from this server. If not set, no such server is started,
+     * and the trainer can only get data from the regular worker server over
+     * `protocol`.
      * 

      *
      * string data_transfer_protocol = 7;
@@ -2667,7 +2692,11 @@ public java.lang.String getDataTransferProtocol() {
     }
     /**
      * 
-     * The protocol for the worker to use when transferring data to clients.
+     * If set, the name of an alternative data transfer protocol for which the
+     * worker starts an additional server ("data transfer server"); the trainer
+     * can then get data from this server. If not set, no such server is started,
+     * and the trainer can only get data from the regular worker server over
+     * `protocol`.
      * 

      *
      * string data_transfer_protocol = 7;
@@ -2688,13 +2717,30 @@ public java.lang.String getDataTransferProtocol() {
       }
     }
 
+    public static final int DATA_TRANSFER_PORT_FIELD_NUMBER = 13;
+    private long dataTransferPort_;
+    /**
+     * 
+     * If `data_transfer_protocol` is set, the port to which the data transfer
+     * server binds. If set to `0`, the server binds to any available port.
+     * 

+     *
+     * int64 data_transfer_port = 13;
+     * @return The dataTransferPort.
+     */
+    @java.lang.Override
+    public long getDataTransferPort() {
+      return dataTransferPort_;
+    }
+
     public static final int DATA_TRANSFER_ADDRESS_FIELD_NUMBER = 8;
     private volatile java.lang.Object dataTransferAddress_;
     /**
      * 
-     * The data transfer address of the worker server. The substring "%port%", if
-     * specified, will be replaced with the worker's bound port. This is useful
-     * when the port is set to `0`.
+     * If `data_transfer_protocol` is set, the address of the data transfer
+     * server. The substring "%dts_port%" can be used to represent -- and is
+     * replaced with -- the bound port of the data transfer server; this is useful
+     * when `data_transfer_port` is set to `0`.
      * 

      *
      * string data_transfer_address = 8;
@@ -2715,9 +2761,10 @@ public java.lang.String getDataTransferAddress() {
     }
     /**
      * 
-     * The data transfer address of the worker server. The substring "%port%", if
-     * specified, will be replaced with the worker's bound port. This is useful
-     * when the port is set to `0`.
+     * If `data_transfer_protocol` is set, the address of the data transfer
+     * server. The substring "%dts_port%" can be used to represent -- and is
+     * replaced with -- the bound port of the data transfer server; this is useful
+     * when `data_transfer_port` is set to `0`.
      * 

      *
      * string data_transfer_address = 8;
@@ -2837,6 +2884,9 @@ public void writeTo(com.google.protobuf.CodedOutputStream output)
       if (snapshotMaxChunkSizeBytes_ != 0L) {
         output.writeInt64(12, snapshotMaxChunkSizeBytes_);
       }
+      if (dataTransferPort_ != 0L) {
+        output.writeInt64(13, dataTransferPort_);
+      }
       getUnknownFields().writeTo(output);
     }
 
@@ -2893,6 +2943,10 @@ public int getSerializedSize() {
         size += com.google.protobuf.CodedOutputStream
           .computeInt64Size(12, snapshotMaxChunkSizeBytes_);
       }
+      if (dataTransferPort_ != 0L) {
+        size += com.google.protobuf.CodedOutputStream
+          .computeInt64Size(13, dataTransferPort_);
+      }
       size += getUnknownFields().getSerializedSize();
       memoizedSize = size;
       return size;
@@ -2924,6 +2978,8 @@ public boolean equals(final java.lang.Object obj) {
           != other.getDispatcherTimeoutMs()) return false;
       if (!getDataTransferProtocol()
           .equals(other.getDataTransferProtocol())) return false;
+      if (getDataTransferPort()
+          != other.getDataTransferPort()) return false;
       if (!getDataTransferAddress()
           .equals(other.getDataTransferAddress())) return false;
       if (getCrossTrainerCacheSizeBytes()
@@ -2964,6 +3020,9 @@ public int hashCode() {
           getDispatcherTimeoutMs());
       hash = (37 * hash) + DATA_TRANSFER_PROTOCOL_FIELD_NUMBER;
       hash = (53 * hash) + getDataTransferProtocol().hashCode();
+      hash = (37 * hash) + DATA_TRANSFER_PORT_FIELD_NUMBER;
+      hash = (53 * hash) + com.google.protobuf.Internal.hashLong(
+          getDataTransferPort());
       hash = (37 * hash) + DATA_TRANSFER_ADDRESS_FIELD_NUMBER;
       hash = (53 * hash) + getDataTransferAddress().hashCode();
       hash = (37 * hash) + CROSS_TRAINER_CACHE_SIZE_BYTES_FIELD_NUMBER;
@@ -3073,7 +3132,7 @@ protected Builder newBuilderForType(
     /**
      * 
      * Configuration for a tf.data service WorkerServer.
-     * Next id: 13
+     * Next id: 14
      * 

      *
      * Protobuf type {@code tensorflow.data.experimental.WorkerConfig}
@@ -3124,6 +3183,8 @@ public Builder clear() {
 
         dataTransferProtocol_ = "";
 
+        dataTransferPort_ = 0L;
+
         dataTransferAddress_ = "";
 
         crossTrainerCacheSizeBytes_ = 0L;
@@ -3171,6 +3232,7 @@ public org.tensorflow.proto.data.experimental.ServiceConfig.WorkerConfig buildPa
         result.heartbeatIntervalMs_ = heartbeatIntervalMs_;
         result.dispatcherTimeoutMs_ = dispatcherTimeoutMs_;
         result.dataTransferProtocol_ = dataTransferProtocol_;
+        result.dataTransferPort_ = dataTransferPort_;
         result.dataTransferAddress_ = dataTransferAddress_;
         result.crossTrainerCacheSizeBytes_ = crossTrainerCacheSizeBytes_;
         result.snapshotMaxChunkSizeBytes_ = snapshotMaxChunkSizeBytes_;
@@ -3258,6 +3320,9 @@ public Builder mergeFrom(org.tensorflow.proto.data.experimental.ServiceConfig.Wo
           dataTransferProtocol_ = other.dataTransferProtocol_;
           onChanged();
         }
+        if (other.getDataTransferPort() != 0L) {
+          setDataTransferPort(other.getDataTransferPort());
+        }
         if (!other.getDataTransferAddress().isEmpty()) {
           dataTransferAddress_ = other.dataTransferAddress_;
           onChanged();
@@ -3358,6 +3423,11 @@ public Builder mergeFrom(
 
                 break;
               } // case 96
+              case 104: {
+                dataTransferPort_ = input.readInt64();
+
+                break;
+              } // case 104
               default: {
                 if (!super.parseUnknownField(input, extensionRegistry, tag)) {
                   done = true; // was an endgroup tag
@@ -3990,7 +4060,11 @@ public Builder clearDispatcherTimeoutMs() {
       private java.lang.Object dataTransferProtocol_ = "";
       /**
        * 
-       * The protocol for the worker to use when transferring data to clients.
+       * If set, the name of an alternative data transfer protocol for which the
+       * worker starts an additional server ("data transfer server"); the trainer
+       * can then get data from this server. If not set, no such server is started,
+       * and the trainer can only get data from the regular worker server over
+       * `protocol`.
        * 

        *
        * string data_transfer_protocol = 7;
@@ -4010,7 +4084,11 @@ public java.lang.String getDataTransferProtocol() {
       }
       /**
        * 
-       * The protocol for the worker to use when transferring data to clients.
+       * If set, the name of an alternative data transfer protocol for which the
+       * worker starts an additional server ("data transfer server"); the trainer
+       * can then get data from this server. If not set, no such server is started,
+       * and the trainer can only get data from the regular worker server over
+       * `protocol`.
        * 

        *
        * string data_transfer_protocol = 7;
@@ -4031,7 +4109,11 @@ public java.lang.String getDataTransferProtocol() {
       }
       /**
        * 
-       * The protocol for the worker to use when transferring data to clients.
+       * If set, the name of an alternative data transfer protocol for which the
+       * worker starts an additional server ("data transfer server"); the trainer
+       * can then get data from this server. If not set, no such server is started,
+       * and the trainer can only get data from the regular worker server over
+       * `protocol`.
        * 

        *
        * string data_transfer_protocol = 7;
@@ -4050,7 +4132,11 @@ public Builder setDataTransferProtocol(
       }
       /**
        * 
-       * The protocol for the worker to use when transferring data to clients.
+       * If set, the name of an alternative data transfer protocol for which the
+       * worker starts an additional server ("data transfer server"); the trainer
+       * can then get data from this server. If not set, no such server is started,
+       * and the trainer can only get data from the regular worker server over
+       * `protocol`.
        * 

        *
        * string data_transfer_protocol = 7;
@@ -4064,7 +4150,11 @@ public Builder clearDataTransferProtocol() {
       }
       /**
        * 
-       * The protocol for the worker to use when transferring data to clients.
+       * If set, the name of an alternative data transfer protocol for which the
+       * worker starts an additional server ("data transfer server"); the trainer
+       * can then get data from this server. If not set, no such server is started,
+       * and the trainer can only get data from the regular worker server over
+       * `protocol`.
        * 

        *
        * string data_transfer_protocol = 7;
@@ -4083,12 +4173,59 @@ public Builder setDataTransferProtocolBytes(
         return this;
       }
 
+      private long dataTransferPort_ ;
+      /**
+       * 
+       * If `data_transfer_protocol` is set, the port to which the data transfer
+       * server binds. If set to `0`, the server binds to any available port.
+       * 

+       *
+       * int64 data_transfer_port = 13;
+       * @return The dataTransferPort.
+       */
+      @java.lang.Override
+      public long getDataTransferPort() {
+        return dataTransferPort_;
+      }
+      /**
+       * 
+       * If `data_transfer_protocol` is set, the port to which the data transfer
+       * server binds. If set to `0`, the server binds to any available port.
+       * 

+       *
+       * int64 data_transfer_port = 13;
+       * @param value The dataTransferPort to set.
+       * @return This builder for chaining.
+       */
+      public Builder setDataTransferPort(long value) {
+        
+        dataTransferPort_ = value;
+        onChanged();
+        return this;
+      }
+      /**
+       * 
+       * If `data_transfer_protocol` is set, the port to which the data transfer
+       * server binds. If set to `0`, the server binds to any available port.
+       * 

+       *
+       * int64 data_transfer_port = 13;
+       * @return This builder for chaining.
+       */
+      public Builder clearDataTransferPort() {
+        
+        dataTransferPort_ = 0L;
+        onChanged();
+        return this;
+      }
+
       private java.lang.Object dataTransferAddress_ = "";
       /**
        * 
-       * The data transfer address of the worker server. The substring "%port%", if
-       * specified, will be replaced with the worker's bound port. This is useful
-       * when the port is set to `0`.
+       * If `data_transfer_protocol` is set, the address of the data transfer
+       * server. The substring "%dts_port%" can be used to represent -- and is
+       * replaced with -- the bound port of the data transfer server; this is useful
+       * when `data_transfer_port` is set to `0`.
        * 

        *
        * string data_transfer_address = 8;
@@ -4108,9 +4245,10 @@ public java.lang.String getDataTransferAddress() {
       }
       /**
        * 
-       * The data transfer address of the worker server. The substring "%port%", if
-       * specified, will be replaced with the worker's bound port. This is useful
-       * when the port is set to `0`.
+       * If `data_transfer_protocol` is set, the address of the data transfer
+       * server. The substring "%dts_port%" can be used to represent -- and is
+       * replaced with -- the bound port of the data transfer server; this is useful
+       * when `data_transfer_port` is set to `0`.
        * 

        *
        * string data_transfer_address = 8;
@@ -4131,9 +4269,10 @@ public java.lang.String getDataTransferAddress() {
       }
       /**
        * 
-       * The data transfer address of the worker server. The substring "%port%", if
-       * specified, will be replaced with the worker's bound port. This is useful
-       * when the port is set to `0`.
+       * If `data_transfer_protocol` is set, the address of the data transfer
+       * server. The substring "%dts_port%" can be used to represent -- and is
+       * replaced with -- the bound port of the data transfer server; this is useful
+       * when `data_transfer_port` is set to `0`.
        * 

        *
        * string data_transfer_address = 8;
@@ -4152,9 +4291,10 @@ public Builder setDataTransferAddress(
       }
       /**
        * 
-       * The data transfer address of the worker server. The substring "%port%", if
-       * specified, will be replaced with the worker's bound port. This is useful
-       * when the port is set to `0`.
+       * If `data_transfer_protocol` is set, the address of the data transfer
+       * server. The substring "%dts_port%" can be used to represent -- and is
+       * replaced with -- the bound port of the data transfer server; this is useful
+       * when `data_transfer_port` is set to `0`.
        * 

        *
        * string data_transfer_address = 8;
@@ -4168,9 +4308,10 @@ public Builder clearDataTransferAddress() {
       }
       /**
        * 
-       * The data transfer address of the worker server. The substring "%port%", if
-       * specified, will be replaced with the worker's bound port. This is useful
-       * when the port is set to `0`.
+       * If `data_transfer_protocol` is set, the address of the data transfer
+       * server. The substring "%dts_port%" can be used to represent -- and is
+       * replaced with -- the bound port of the data transfer server; this is useful
+       * when `data_transfer_port` is set to `0`.
        * 

        *
        * string data_transfer_address = 8;
@@ -4424,19 +4565,20 @@ public org.tensorflow.proto.data.experimental.ServiceConfig.WorkerConfig getDefa
       "s\030\006 \001(\003\022 \n\030gc_dynamic_sharding_jobs\030\013 \001(" +
       "\010\022\031\n\021client_timeout_ms\030\010 \001(\003\022\031\n\021worker_t" +
       "imeout_ms\030\n \001(\003\022\'\n\037worker_max_concurrent" +
-      "_snapshots\030\014 \001(\003\"\345\002\n\014WorkerConfig\022\014\n\004por" +
+      "_snapshots\030\014 \001(\003\"\201\003\n\014WorkerConfig\022\014\n\004por" +
       "t\030\001 \001(\003\022\020\n\010protocol\030\002 \001(\t\022\032\n\022dispatcher_" +
       "address\030\003 \001(\t\022\026\n\016worker_address\030\004 \001(\t\022\023\n" +
       "\013worker_tags\030\n \003(\t\022\035\n\025heartbeat_interval" +
       "_ms\030\005 \001(\003\022\035\n\025dispatcher_timeout_ms\030\006 \001(\003" +
-      "\022\036\n\026data_transfer_protocol\030\007 \001(\t\022\035\n\025data" +
-      "_transfer_address\030\010 \001(\t\022&\n\036cross_trainer" +
-      "_cache_size_bytes\030\013 \001(\003\022%\n\035snapshot_max_" +
-      "chunk_size_bytes\030\014 \001(\003\022 \n\030shutdown_quiet" +
-      "_period_ms\030\t \001(\003B\177\n&org.tensorflow.proto" +
-      ".data.experimentalZUgithub.com/tensorflo" +
-      "w/tensorflow/tensorflow/go/core/protobuf" +
-      "/for_core_protos_go_protob\006proto3"
+      "\022\036\n\026data_transfer_protocol\030\007 \001(\t\022\032\n\022data" +
+      "_transfer_port\030\r \001(\003\022\035\n\025data_transfer_ad" +
+      "dress\030\010 \001(\t\022&\n\036cross_trainer_cache_size_" +
+      "bytes\030\013 \001(\003\022%\n\035snapshot_max_chunk_size_b" +
+      "ytes\030\014 \001(\003\022 \n\030shutdown_quiet_period_ms\030\t" +
+      " \001(\003B\177\n&org.tensorflow.proto.data.experi" +
+      "mentalZUgithub.com/tensorflow/tensorflow" +
+      "/tensorflow/go/core/protobuf/for_core_pr" +
+      "otos_go_protob\006proto3"
     };
     descriptor = com.google.protobuf.Descriptors.FileDescriptor
       .internalBuildGeneratedFileFrom(descriptorData,
@@ -4454,7 +4596,7 @@ public org.tensorflow.proto.data.experimental.ServiceConfig.WorkerConfig getDefa
     internal_static_tensorflow_data_experimental_WorkerConfig_fieldAccessorTable = new
       com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
         internal_static_tensorflow_data_experimental_WorkerConfig_descriptor,
-        new java.lang.String[] { "Port", "Protocol", "DispatcherAddress", "WorkerAddress", "WorkerTags", "HeartbeatIntervalMs", "DispatcherTimeoutMs", "DataTransferProtocol", "DataTransferAddress", "CrossTrainerCacheSizeBytes", "SnapshotMaxChunkSizeBytes", "ShutdownQuietPeriodMs", });
+        new java.lang.String[] { "Port", "Protocol", "DispatcherAddress", "WorkerAddress", "WorkerTags", "HeartbeatIntervalMs", "DispatcherTimeoutMs", "DataTransferProtocol", "DataTransferPort", "DataTransferAddress", "CrossTrainerCacheSizeBytes", "SnapshotMaxChunkSizeBytes", "ShutdownQuietPeriodMs", });
     org.tensorflow.proto.data.DataService.getDescriptor();
   }
 
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/BfcMemoryMap.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/BfcMemoryMap.java
index 9ddd1a3d74f..e957b7817fb 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/BfcMemoryMap.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/BfcMemoryMap.java
@@ -24,18 +24,18 @@ public static void registerAllExtensions(
   static {
     java.lang.String[] descriptorData = {
       "\n-tensorflow/core/protobuf/bfc_memory_ma" +
-      "p.proto\022\020tensorflow.dummy\032!tsl/protobuf/" +
-      "bfc_memory_map.protoBs\n\032org.tensorflow.p" +
-      "roto.dummyZUgithub.com/tensorflow/tensor" +
-      "flow/tensorflow/go/core/protobuf/for_cor" +
-      "e_protos_go_protoP\000b\006proto3"
+      "p.proto\022\020tensorflow.dummy\032%xla/tsl/proto" +
+      "buf/bfc_memory_map.protoBs\n\032org.tensorfl" +
+      "ow.proto.dummyZUgithub.com/tensorflow/te" +
+      "nsorflow/tensorflow/go/core/protobuf/for" +
+      "_core_protos_go_protoP\000b\006proto3"
     };
     descriptor = com.google.protobuf.Descriptors.FileDescriptor
       .internalBuildGeneratedFileFrom(descriptorData,
         new com.google.protobuf.Descriptors.FileDescriptor[] {
-          org.tensorflow.proto.BfcMemoryMap.getDescriptor(),
+          tensorflow.BfcMemoryMap.getDescriptor(),
         });
-    org.tensorflow.proto.BfcMemoryMap.getDescriptor();
+    tensorflow.BfcMemoryMap.getDescriptor();
   }
 
   // @@protoc_insertion_point(outer_class_scope)
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/TestLog.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/TestLog.java
index 7f4925fa6b5..73eae05fd2f 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/TestLog.java
+++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/TestLog.java
@@ -24,16 +24,16 @@ public static void registerAllExtensions(
   static {
     java.lang.String[] descriptorData = {
       "\n#tensorflow/core/util/test_log.proto\022\020t" +
-      "ensorflow.dummy\032\033tsl/protobuf/test_log.p" +
-      "rotoB\034\n\032org.tensorflow.proto.dummyP\000b\006pr" +
-      "oto3"
+      "ensorflow.dummy\032\037xla/tsl/protobuf/test_l" +
+      "og.protoB\034\n\032org.tensorflow.proto.dummyP\000" +
+      "b\006proto3"
     };
     descriptor = com.google.protobuf.Descriptors.FileDescriptor
       .internalBuildGeneratedFileFrom(descriptorData,
         new com.google.protobuf.Descriptors.FileDescriptor[] {
-          org.tensorflow.proto.TestLogProtos.getDescriptor(),
+          org.tensorflow.util.testlog.TestLogProtos.getDescriptor(),
         });
-    org.tensorflow.proto.TestLogProtos.getDescriptor();
+    org.tensorflow.util.testlog.TestLogProtos.getDescriptor();
   }
 
   // @@protoc_insertion_point(outer_class_scope)
diff --git a/tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_AssignVariableXlaConcatND.pbtxt b/tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_AssignVariableXlaConcatND.pbtxt
index 646f602af22..6bd6bcd8d05 100644
--- a/tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_AssignVariableXlaConcatND.pbtxt
+++ b/tensorflow-core/tensorflow-core-native/src/gen/resources/org/tensorflow/base_api/api_def_AssignVariableXlaConcatND.pbtxt
@@ -5,17 +5,13 @@ op {
     name: "resource"
     description: <

    *
-   * @param  data type for {@code z} output
    * @param x The x value
    * @param y The y value
    * @param  data type for {@code BitwiseAnd} output and operands
@@ -91,7 +90,6 @@ public  BitwiseAnd bitwiseAnd(Operand x, Operand y)
    *    tf.assert_equal(tf.cast(res,  tf.float32), exp)  # TRUE
    *  

    *
-   * @param  data type for {@code z} output
    * @param x The x value
    * @param y The y value
    * @param  data type for {@code BitwiseOr} output and operands
@@ -121,7 +119,6 @@ public  BitwiseOr bitwiseOr(Operand x, Operand y) {
    *    tf.assert_equal(tf.cast(res, tf.float32), exp) # TRUE
    *  

    *
-   * @param  data type for {@code z} output
    * @param x The x value
    * @param y The y value
    * @param  data type for {@code BitwiseXor} output and operands
@@ -172,7 +169,6 @@ public  BitwiseXor bitwiseXor(Operand x, Operand y)
    *      tf.assert_equal(tf.cast(inverted, tf.float32), tf.cast(expected, tf.float32))
    *  

    *
-   * @param  data type for {@code y} output
    * @param x The x value
    * @param  data type for {@code Invert} output and operands
    * @return a new instance of Invert
@@ -212,7 +208,6 @@ public  Invert invert(Operand x) {
    *  # <tf.Tensor: shape=(4,), dtype=int8, numpy=array([ -2,  64, 101,  32], dtype=int8)>
    *
* - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code LeftShift} output and operands @@ -255,7 +250,6 @@ public LeftShift leftShift(Operand x, Operand y) { * # <tf.Tensor: shape=(4,), dtype=int8, numpy=array([ -2, 64, 101, 32], dtype=int8)> * * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code RightShift} output and operands diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/CollectiveOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/CollectiveOps.java index 23a96e4bfdf..de786dc95fe 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/CollectiveOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/CollectiveOps.java @@ -49,7 +49,6 @@ public final class CollectiveOps { /** * Mutually exchanges multiple tensors of identical type and shape. * - * @param data type for {@code data} output * @param input The input value * @param communicator The communicator value * @param groupAssignment The groupAssignment value @@ -79,7 +78,6 @@ public CollectiveAssignGroup collectiveAssignGroup(Operand groupAssignme /** * Receives a tensor value broadcast from another device. * - * @param data type for {@code data} output * @param groupSize The groupSize value * @param groupKey The groupKey value * @param instanceKey The instanceKey value @@ -98,7 +96,6 @@ public CollectiveBcastRecv collectiveBcastRecv(Operand data type for {@code data} output * @param input The input value * @param groupSize The groupSize value * @param groupKey The groupKey value @@ -119,7 +116,6 @@ public CollectiveBcastSend collectiveBcastSend(Operand i * collective ops. In this case, keys that are unique at runtime * (e.g. {@code instance_key}) should be used to distinguish collective groups. * - * @param data type for {@code data} output * @param input The input value * @param groupSize The groupSize value * @param groupKey The groupKey value @@ -157,7 +153,6 @@ public CollectiveInitializeCommunicator collectiveInitializeCommunicator(Operand * source_target_pairs={@code [[0,1],[1,2],[2,3],[3,0]]} gets the outputs: * {@code [D, A, B, C]}. * - * @param data type for {@code output} output * @param input The local input to be permuted. Currently only supports float and * bfloat16. * @param sourceTargetPairs A tensor with shape [num_pairs, 2]. @@ -172,7 +167,6 @@ public CollectivePermute collectivePermute(Operand input /** * Mutually reduces multiple tensors of identical type and shape. * - * @param data type for {@code data} output * @param input The input value * @param communicator The communicator value * @param groupAssignment The groupAssignment value @@ -193,7 +187,6 @@ public CollectiveReduce collectiveReduce(Operand input * collective ops. In this case, keys that are unique at runtime * (e.g. {@code instance_key}) should be used to distinguish collective groups. * - * @param data type for {@code data} output * @param input The input value * @param groupSize The groupSize value * @param groupKey The groupKey value diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java index 49f7e238a3f..5a3a14b799e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java @@ -59,6 +59,7 @@ import org.tensorflow.op.data.GroupByReducerDataset; import org.tensorflow.op.data.GroupByWindowDataset; import org.tensorflow.op.data.IgnoreErrorsDataset; +import org.tensorflow.op.data.IndexFlatMapDataset; import org.tensorflow.op.data.InitializeTableFromDataset; import org.tensorflow.op.data.InterleaveDataset; import org.tensorflow.op.data.Iterator; @@ -819,6 +820,28 @@ public IgnoreErrorsDataset ignoreErrorsDataset(Operand inputDat return IgnoreErrorsDataset.create(scope, inputDataset, outputTypes, outputShapes, options); } + /** + * The IndexFlatMapDataset operation + * + * @param inputDataset The inputDataset value + * @param mapFuncOtherArgs The mapFuncOtherArgs value + * @param indexMapFuncOtherArgs The indexMapFuncOtherArgs value + * @param outputCardinality The outputCardinality value + * @param mapFunc The value of the mapFunc attribute + * @param indexMapFunc The value of the indexMapFunc attribute + * @param outputTypes The value of the outputTypes attribute + * @param outputShapes The value of the outputShapes attribute + * @param options carries optional attribute values + * @return a new instance of IndexFlatMapDataset + */ + public IndexFlatMapDataset indexFlatMapDataset(Operand inputDataset, + Iterable> mapFuncOtherArgs, Iterable> indexMapFuncOtherArgs, + Operand outputCardinality, ConcreteFunction mapFunc, ConcreteFunction indexMapFunc, + List> outputTypes, List outputShapes, + IndexFlatMapDataset.Options... options) { + return IndexFlatMapDataset.create(scope, inputDataset, mapFuncOtherArgs, indexMapFuncOtherArgs, outputCardinality, mapFunc, indexMapFunc, outputTypes, outputShapes, options); + } + /** * The InitializeTableFromDataset operation * @@ -987,7 +1010,6 @@ public LatencyStatsDataset latencyStatsDataset(Operand inputDat /** * Computes rectified linear gradients for a LeakyRelu operation. * - * @param data type for {@code backprops} output * @param gradients The backpropagated gradients to the corresponding LeakyRelu operation. * @param features The features passed as input to the corresponding LeakyRelu operation, * OR the outputs of that operation (both work equivalently). diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DebuggingOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DebuggingOps.java index b50f697f8d5..4ea1efd10db 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DebuggingOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DebuggingOps.java @@ -43,7 +43,6 @@ public final class DebuggingOps { * tensor. Unlike CheckNumerics (V1), CheckNumericsV2 distinguishes -Inf and +Inf * in the errors it throws. * - * @param data type for {@code output} output * @param tensor The tensor value * @param message Prefix of the error message. * @param data type for {@code CheckNumericsV2} output and operands diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DistributeOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DistributeOps.java index e5a6c71c20a..4f30df6352d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DistributeOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DistributeOps.java @@ -52,7 +52,6 @@ public final class DistributeOps { * num_devices: The number of devices participating in this reduction. * shared_name: Identifier that shared between ops of the same reduction. * - * @param data type for {@code data} output * @param input The input value * @param reduction The value of the reduction attribute * @param numDevices The value of the numDevices attribute @@ -74,7 +73,6 @@ public NcclAllReduce ncclAllReduce(Operand input, Stri * output: The same as input. * shape: The shape of the input tensor. * - * @param data type for {@code output} output * @param input The input value * @param shape The value of the shape attribute * @param data type for {@code NcclBroadcast} output and operands @@ -93,7 +91,6 @@ public NcclBroadcast ncclBroadcast(Operand input, Shap * data: the value of the reduction across all {@code num_devices} devices. * reduction: the reduction operation to perform. * - * @param data type for {@code data} output * @param input The input value * @param reduction The value of the reduction attribute * @param data type for {@code NcclReduce} output and operands diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java index 3ef6847d4f7..42f59c161d7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java @@ -69,7 +69,6 @@ public AsString asString(Operand input, AsString.Options... opt /** * Cast x of type SrcT to y of DstT. * - * @param data type for {@code y} output * @param x The x value * @param DstT The value of the DstT attribute * @param options carries optional attribute values @@ -95,7 +94,6 @@ public Cast cast(Operand x, Class DstT, * tf.complex(real, imag) ==> [[2.25 + 4.75j], [3.25 + 5.75j]] * * - * @param data type for {@code out} output * @param real The real value * @param imag The imag value * @param Tout The value of the Tout attribute diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java index 559ffc0d80a..f3fa3e6bbc0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java @@ -93,7 +93,6 @@ public final class ImageOps { * channel and then adjusts each component of each pixel to * {@code (x - mean) * contrast_factor + mean}. * - * @param data type for {@code output} output * @param images Images to adjust. At least 3-D. * @param contrastFactor A float multiplier for adjusting contrast. * @param data type for {@code AdjustContrastv2} output and operands @@ -112,7 +111,6 @@ public AdjustContrast adjustContrast(Operand images, * colors are first mapped into HSV. A delta is then applied all the hue values, * and then remapped back to RGB colorspace. * - * @param data type for {@code output} output * @param images Images to adjust. At least 3-D. * @param delta A float delta to add to the hue. * @param data type for {@code AdjustHue} output and operands @@ -130,7 +128,6 @@ public AdjustHue adjustHue(Operand images, Operand data type for {@code output} output * @param images Images to adjust. At least 3-D. * @param scale A float scale to add to the saturation. * @param data type for {@code AdjustSaturation} output and operands @@ -250,7 +247,6 @@ public CropAndResizeGradBoxes cropAndResizeGradBoxes(Operand grads, /** * Computes the gradient of the crop_and_resize op wrt the input image tensor. * - * @param data type for {@code output} output * @param grads A 4-D tensor of shape {@code [num_boxes, crop_height, crop_width, depth]}. * @param boxes A 2-D tensor of shape {@code [num_boxes, 4]}. The {@code i}-th row of the tensor * specifies the coordinates of a box in the {@code box_ind[i]} image and is specified @@ -357,7 +353,6 @@ public DecodeGif decodeGif(Operand contents) { * first frame that does not occupy the entire canvas, it uses the previous * frame to fill the unoccupied areas. * - * @param data type for {@code image} output * @param contents 0-D. The encoded image bytes. * @param options carries optional attribute values * @return a new instance of DecodeImage, with default output types @@ -384,7 +379,6 @@ public DecodeImage decodeImage(Operand contents, DecodeImage.Op * first frame that does not occupy the entire canvas, it uses the previous * frame to fill the unoccupied areas. * - * @param data type for {@code image} output * @param contents 0-D. The encoded image bytes. * @param dtype The desired DType of the returned Tensor. * @param options carries optional attribute values @@ -438,7 +432,6 @@ public DecodeJpeg decodeJpeg(Operand contents, DecodeJpeg.Options... op *

This op also supports decoding JPEGs and non-animated GIFs since the interface * is the same, though it is cleaner to use {@code tf.io.decode_image}. * - * @param data type for {@code image} output * @param contents 0-D. The PNG-encoded image. * @param options carries optional attribute values * @return a new instance of DecodePng, with default output types @@ -463,7 +456,6 @@ public DecodePng decodePng(Operand contents, DecodePng.Options[ *

This op also supports decoding JPEGs and non-animated GIFs since the interface * is the same, though it is cleaner to use {@code tf.io.decode_image}. * - * @param data type for {@code image} output * @param contents 0-D. The PNG-encoded image. * @param dtype The value of the dtype attribute * @param options carries optional attribute values @@ -487,7 +479,6 @@ public DecodePng decodePng(Operand contents, Cla * the bounding box will be {@code (40, 10)} to {@code (100, 50)} (in (x,y) coordinates). *

Parts of the bounding box may fall outside the image. * - * @param data type for {@code output} output * @param images 4-D with shape {@code [batch, height, width, depth]}. A batch of images. * @param boxes 3-D with shape {@code [batch, num_bounding_boxes, 4]} containing bounding * boxes. @@ -602,7 +593,6 @@ public ExtractGlimpse extractGlimpse(Operand input, Operand si /** * Extract {@code patches} from {@code images} and put them in the "depth" output dimension. * - * @param data type for {@code patches} output * @param images 4-D Tensor with shape {@code [batch, in_rows, in_cols, depth]}. * @param ksizes The size of the sliding window for each dimension of {@code images}. * @param strides How far the centers of two consecutive patches are in @@ -626,7 +616,6 @@ public ExtractImagePatches extractImagePatches(Operand i * Extract the shape information of a JPEG-encoded image. * This op only parses the image header, so it is much faster than DecodeJpeg. * - * @param data type for {@code image_shape} output * @param contents 0-D. The JPEG-encoded image. * @return a new instance of ExtractJpegShape, with default output types */ @@ -638,7 +627,6 @@ public ExtractJpegShape extractJpegShape(Operand contents) { * Extract the shape information of a JPEG-encoded image. * This op only parses the image header, so it is much faster than DecodeJpeg. * - * @param data type for {@code image_shape} output * @param contents 0-D. The JPEG-encoded image. * @param outputType (Optional) The output type of the operation (int32 or int64). * Defaults to int32. @@ -691,7 +679,6 @@ public GenerateBoundingBoxProposals generateBoundingBoxProposals(OperandSee {@code rgb_to_hsv} for a description of the HSV encoding. * - * @param data type for {@code output} output * @param images 1-D or higher rank. HSV data to convert. Last dimension must be size 3. * @param data type for {@code HSVToRGB} output and operands * @return a new instance of HsvToRgb @@ -708,7 +695,6 @@ public HsvToRgb hsvToRgb(Operand images) { * {@code k = c0 x + c1 y + 1}. If the transformed point lays outside of the input * image, the output pixel is set to 0. * - * @param data type for {@code transformed_images} output * @param images 4-D with shape {@code [batch, height, width, channels]}. * @param transforms 2-D Tensor, {@code [batch, 8]} or {@code [1, 8]} matrix, where each row corresponds to a 3 x 3 * projective transformation matrix, with the last entry assumed to be 1. If there @@ -733,7 +719,6 @@ public ImageProjectiveTransformV2 imageProjectiveTransfor * {@code k = c0 x + c1 y + 1}. If the transformed point lays outside of the input * image, the output pixel is set to fill_value. * - * @param data type for {@code transformed_images} output * @param images 4-D with shape {@code [batch, height, width, channels]}. * @param transforms 2-D Tensor, {@code [batch, 8]} or {@code [1, 8]} matrix, where each row corresponds to a 3 x 3 * projective transformation matrix, with the last entry assumed to be 1. If there @@ -794,7 +779,6 @@ public NearestNeighbors nearestNeighbors(Operand points, Operand data type for {@code selected_scores} output * @param boxes A 2-D float tensor of shape {@code [num_boxes, 4]}. * @param scores A 1-D float tensor of shape {@code [num_boxes]} representing a single * score corresponding to each box (each row of boxes). @@ -854,7 +838,6 @@ public NonMaxSuppressionWithOverlaps nonMaxSuppressionWithOverlaps(Operand data type for {@code resized_images} output * @param images 4-D with shape {@code [batch, height, width, channels]}. * @param sizeOutput = A 1-D int32 Tensor of 2 elements: {@code new_height, new_width}. The * new size for the images. @@ -878,7 +861,6 @@ public QuantizedResizeBilinear quantizedResizeBilinear(Op * rectangle from that location. The random location is picked so the cropped * area will fit inside the original image. * - * @param data type for {@code output} output * @param image 3-D of shape {@code [height, width, channels]}. * @param sizeOutput 1-D of length 2 containing: {@code crop_height}, {@code crop_width}.. * @param options carries optional attribute values @@ -931,7 +913,6 @@ public ResizeBicubic resizeBicubic(Operand images, Operand data type for {@code output} output * @param grads 4-D with shape {@code [batch, height, width, channels]}. * @param originalImage 4-D with shape {@code [batch, orig_height, orig_width, channels]}, * The image tensor that was resized. @@ -962,7 +943,6 @@ public ResizeBilinear resizeBilinear(Operand images, /** * Computes the gradient of bilinear interpolation. * - * @param data type for {@code output} output * @param grads 4-D with shape {@code [batch, height, width, channels]}. * @param originalImage 4-D with shape {@code [batch, orig_height, orig_width, channels]}, * The image tensor that was resized. @@ -978,7 +958,6 @@ public ResizeBilinearGrad resizeBilinearGrad(Operand data type for {@code resized_images} output * @param images 4-D with shape {@code [batch, height, width, channels]}. * @param sizeOutput = A 1-D int32 Tensor of 2 elements: {@code new_height, new_width}. The * new size for the images. @@ -994,7 +973,6 @@ public ResizeNearestNeighbor resizeNearestNeighbor(Operan /** * Computes the gradient of nearest neighbor interpolation. * - * @param data type for {@code output} output * @param grads 4-D with shape {@code [batch, height, width, channels]}. * @param sizeOutput = A 1-D int32 Tensor of 2 elements: {@code orig_height, orig_width}. The * original input size. @@ -1031,7 +1009,6 @@ public ResizeNearestNeighborGrad resizeNearestNeighborGra * * * - * @param data type for {@code output} output * @param images 1-D or higher rank. RGB data to convert. Last dimension must be size 3. * @param data type for {@code RGBToHSV} output and operands * @return a new instance of RgbToHsv @@ -1076,7 +1053,6 @@ public RgbToHsv rgbToHsv(Operand images) { * bounding box covering the whole image. If {@code use_image_if_no_bounding_boxes} is * false and no bounding boxes are supplied, an error is raised. * - * @param data type for {@code begin} output * @param imageSize 1-D, containing {@code [height, width, channels]}. * @param boundingBoxes 3-D with shape {@code [batch, N, 4]} describing the N bounding boxes * associated with the image. @@ -1113,7 +1089,6 @@ public ScaleAndTranslate scaleAndTranslate(Operand images, /** * The ScaleAndTranslateGrad operation * - * @param data type for {@code output} output * @param grads The grads value * @param originalImage The originalImage value * @param scale The scale value @@ -1189,7 +1164,6 @@ public ScaleAndTranslateGrad scaleAndTranslateGrad(Operan * bounding box covering the whole image. If {@code use_image_if_no_bounding_boxes} is * false and no bounding boxes are supplied, an error is raised. * - * @param data type for {@code begin} output * @param imageSize 1-D, containing {@code [height, width, channels]}. * @param boundingBoxes 3-D with shape {@code [batch, N, 4]} describing the N bounding boxes * associated with the image. diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java index e038446af4a..5c33c56e962 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java @@ -160,7 +160,6 @@ public DecodeJsonExample decodeJsonExample(Operand jsonExamples) { /** * Reinterpret the bytes of a string as a vector of numbers. * - * @param data type for {@code output} output * @param inputBytes Tensor of string to be decoded. * @param fixedLength Length in bytes for each element of the decoded output. Must be a multiple * of the size of the output type. @@ -177,7 +176,6 @@ public DecodePaddedRaw decodePaddedRaw(Operand i /** * Reinterpret the bytes of a string as a vector of numbers. * - * @param data type for {@code output} output * @param bytes All the elements must have the same length. * @param outType The value of the outType attribute * @param options carries optional attribute values @@ -231,7 +229,6 @@ public DecodeRaw decodeRaw(Operand bytes, Class * shape = [2 50] * * - * @param data type for {@code sparse_values} output * @param serializedSparse 2-D, The {@code N} serialized {@code SparseTensor} objects. * Must have 3 columns. * @param dtype The {@code dtype} of the serialized {@code SparseTensor} objects. @@ -581,7 +578,6 @@ public ParseSingleSequenceExample parseSingleSequenceExample(Operand se /** * Transforms a serialized tensorflow.TensorProto proto into a Tensor. * - * @param data type for {@code output} output * @param serialized A scalar string containing a serialized TensorProto proto. * @param outType The type of the serialized tensor. The provided type must match the * type of the serialized tensor and no implicit conversion will take place. @@ -883,7 +879,6 @@ public ReaderSerializeState readerSerializeState(Operand reader * rank {@code R-1}. *

The minibatch size {@code N} is extracted from {@code sparse_shape[0]}. * - * @param data type for {@code serialized_sparse} output * @param sparseIndices 2-D. The {@code indices} of the minibatch {@code SparseTensor}. * @param sparseValues 1-D. The {@code values} of the minibatch {@code SparseTensor}. * @param sparseShape 1-D. The {@code shape} of the minibatch {@code SparseTensor}. @@ -903,7 +898,6 @@ public SerializeManySparse serializeManySparse(Operand sparseIn * rank {@code R-1}. *

The minibatch size {@code N} is extracted from {@code sparse_shape[0]}. * - * @param data type for {@code serialized_sparse} output * @param sparseIndices 2-D. The {@code indices} of the minibatch {@code SparseTensor}. * @param sparseValues 1-D. The {@code values} of the minibatch {@code SparseTensor}. * @param sparseShape 1-D. The {@code shape} of the minibatch {@code SparseTensor}. @@ -920,7 +914,6 @@ public SerializeManySparse serializeManySparse(Operand data type for {@code serialized_sparse} output * @param sparseIndices 2-D. The {@code indices} of the {@code SparseTensor}. * @param sparseValues 1-D. The {@code values} of the {@code SparseTensor}. * @param sparseShape 1-D. The {@code shape} of the {@code SparseTensor}. @@ -934,7 +927,6 @@ public SerializeSparse serializeSparse(Operand sparseIndices, /** * Serialize a {@code SparseTensor} into a {@code [3]} {@code Tensor} object. * - * @param data type for {@code serialized_sparse} output * @param sparseIndices 2-D. The {@code indices} of the {@code SparseTensor}. * @param sparseValues 1-D. The {@code values} of the {@code SparseTensor}. * @param sparseShape 1-D. The {@code shape} of the {@code SparseTensor}. diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java index 87d87f85dcf..7cb8027ca3a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java @@ -127,7 +127,6 @@ public final class LinalgOps { * tf.linalg.band_part(input, 0, 0) ==> Diagonal. * * - * @param data type for {@code band} output * @param input Rank {@code k} tensor. * @param numLower 0-D tensor. Number of subdiagonals to keep. If negative, keep entire * lower triangle. @@ -145,7 +144,6 @@ public BandPart bandPart(Operand inpu /** * The BandedTriangularSolve operation * - * @param data type for {@code output} output * @param matrix The matrix value * @param rhs The rhs value * @param options carries optional attribute values @@ -160,7 +158,6 @@ public BandedTriangularSolve bandedTriangularSolve(Operand< /** * The BatchCholesky operation * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code BatchCholesky} output and operands * @return a new instance of BatchCholesky @@ -172,7 +169,6 @@ public BatchCholesky batchCholesky(Operand input) { /** * The BatchCholeskyGrad operation * - * @param data type for {@code output} output * @param l The l value * @param grad The grad value * @param data type for {@code BatchCholeskyGrad} output and operands @@ -185,7 +181,6 @@ public BatchCholeskyGrad batchCholeskyGrad(Operand l, /** * The BatchMatrixBandPart operation * - * @param data type for {@code band} output * @param input The input value * @param numLower The numLower value * @param numUpper The numUpper value @@ -200,7 +195,6 @@ public BatchMatrixBandPart batchMatrixBandPart(Operand i /** * The BatchMatrixDeterminant operation * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code BatchMatrixDeterminant} output and operands * @return a new instance of BatchMatrixDeterminant @@ -212,7 +206,6 @@ public BatchMatrixDeterminant batchMatrixDeterminant(Operan /** * The BatchMatrixDiag operation * - * @param data type for {@code output} output * @param diagonal The diagonal value * @param data type for {@code BatchMatrixDiag} output and operands * @return a new instance of BatchMatrixDiag @@ -224,7 +217,6 @@ public BatchMatrixDiag batchMatrixDiag(Operand diagonal) /** * The BatchMatrixDiagPart operation * - * @param data type for {@code diagonal} output * @param input The input value * @param data type for {@code BatchMatrixDiagPart} output and operands * @return a new instance of BatchMatrixDiagPart @@ -235,8 +227,11 @@ public BatchMatrixDiagPart batchMatrixDiagPart(Operand i /** * The BatchMatrixInverse operation + * DEPRECATED: This operation is deprecated and will be removed in a future version. + * Use tf.linalg.inv instead. + *

Computes the inverse of one or more square invertible matrices or their + * adjoints (conjugate transposes). * - * @param data type for {@code output} output * @param input The input value * @param options carries optional attribute values * @param data type for {@code BatchMatrixInverse} output and operands @@ -250,7 +245,6 @@ public BatchMatrixInverse batchMatrixInverse(Operand i /** * The BatchMatrixSetDiag operation * - * @param data type for {@code output} output * @param input The input value * @param diagonal The diagonal value * @param data type for {@code BatchMatrixSetDiag} output and operands @@ -264,7 +258,6 @@ public BatchMatrixSetDiag batchMatrixSetDiag(Operand inp /** * The BatchMatrixSolve operation * - * @param data type for {@code output} output * @param matrix The matrix value * @param rhs The rhs value * @param options carries optional attribute values @@ -279,7 +272,6 @@ public BatchMatrixSolve batchMatrixSolve(Operand matri /** * The BatchMatrixSolveLs operation * - * @param data type for {@code output} output * @param matrix The matrix value * @param rhs The rhs value * @param l2Regularizer The l2Regularizer value @@ -295,7 +287,6 @@ public BatchMatrixSolveLs batchMatrixSolveLs(Operand m /** * The BatchMatrixTriangularSolve operation * - * @param data type for {@code output} output * @param matrix The matrix value * @param rhs The rhs value * @param options carries optional attribute values @@ -310,7 +301,6 @@ public BatchMatrixTriangularSolve batchMatrixTriangularSo /** * The BatchSelfAdjointEigV2 operation * - * @param data type for {@code e} output * @param input The input value * @param options carries optional attribute values * @param data type for {@code BatchSelfAdjointEigV2} output and operands @@ -324,7 +314,6 @@ public BatchSelfAdjointEig batchSelfAdjointEig(Operand /** * The BatchSvd operation * - * @param data type for {@code s} output * @param input The input value * @param options carries optional attribute values * @param data type for {@code BatchSvd} output and operands @@ -347,7 +336,6 @@ public BatchSvd batchSvd(Operand input, BatchSvd.Options * not for large batch dimensions when the submatrices are small. In this * case it might be faster to use the CPU. * - * @param data type for {@code output} output * @param input Shape is {@code [..., M, M]}. * @param data type for {@code Cholesky} output and operands * @return a new instance of Cholesky @@ -361,7 +349,6 @@ public Cholesky cholesky(Operand input) { * For an explanation see "Differentiation of the Cholesky algorithm" by * Iain Murray http://arxiv.org/abs/1602.07527. * - * @param data type for {@code output} output * @param l Output of batch Cholesky algorithm l = cholesky(A). Shape is {@code [..., M, M]}. * Algorithm depends only on lower triangular part of the innermost matrices of * this tensor. @@ -381,7 +368,6 @@ public CholeskyGrad choleskyGrad(Operand l, Operand * {@code y.shape[i] == x.shape[perm[i]] for i in [0, 1, ..., rank(x) - 1]} * {@code y[i,j,k,...,s,t,u] == conj(x[perm[i], perm[j], perm[k],...,perm[s], perm[t], perm[u]])} * - * @param data type for {@code y} output * @param x The x value * @param perm The perm value * @param data type for {@code ConjugateTranspose} output and operands @@ -398,7 +384,6 @@ public ConjugateTranspose conjugateTranspose(Operand x, * or any shape where the innermost dimension is 3. In the latter case, each pair * of corresponding 3-element vectors is cross-multiplied independently. * - * @param data type for {@code product} output * @param a A tensor containing 3-element vectors. * @param b Another tensor, of same type and shape as {@code a}. * @param data type for {@code Cross} output and operands @@ -414,7 +399,6 @@ public Cross cross(Operand a, Operand b) { * form square matrices. The output is a tensor containing the determinants * for all input submatrices {@code [..., :, :]}. * - * @param data type for {@code output} output * @param input Shape is {@code [..., M, M]}. * @param data type for {@code MatrixDeterminant} output and operands * @return a new instance of Det @@ -436,7 +420,6 @@ public Det det(Operand input) { * e = eig(a, compute_v=False) * * - * @param data type for {@code e} output * @param input {@code Tensor} input of shape {@code [N, N]}. * @param Tout The value of the Tout attribute * @param options carries optional attribute values @@ -514,7 +497,6 @@ public Eig eig(Operand input, Class Tou *
{@literal @}end_compatibility * * - * @param data type for {@code output} output * @param inputs List of 1 or 2 Tensors. * @param equation String describing the Einstein Summation operation; in the format of np.einsum. * @param data type for {@code Einsum} output and operands @@ -531,7 +513,6 @@ public Einsum einsum(Iterable> inputs, String eq * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -554,7 +535,6 @@ public EuclideanNorm euclideanNorm(Operand input, * may detect the condition and raise an exception or it may simply return a * garbage result. * - * @param data type for {@code output} output * @param input Shape is {@code [..., M, M]}. * @param options carries optional attribute values * @param data type for {@code MatrixInverse} output and operands @@ -632,7 +612,6 @@ public LoadAndRemapMatrix loadAndRemapMatrix(Operand ckptPath, * is the {@code LU} decomposition of the input and {@code P} is the corresponding * permutation matrix. * - * @param data type for {@code sign} output * @param input Shape is {@code [N, M, M]}. * @param data type for {@code LogMatrixDeterminant} output and operands * @return a new instance of LogMatrixDeterminant @@ -657,8 +636,6 @@ public LogMatrixDeterminant logMatrixDeterminant(Operand * and {@code M-1}, inclusive. If P_mat denotes the permutation matrix corresponding to * P, then the L, U and P satisfies P_mat * input = L * U. * - * @param data type for {@code lu} output - * @param data type for {@code p} output * @param input A tensor of shape {@code [..., M, M]} whose inner-most 2 dimensions form matrices of * size {@code [M, M]}. * @param data type for {@code Lu} output and operands @@ -684,8 +661,6 @@ public Lu lu(Operand input) { * and {@code M-1}, inclusive. If P_mat denotes the permutation matrix corresponding to * P, then the L, U and P satisfies P_mat * input = L * U. * - * @param data type for {@code lu} output - * @param data type for {@code p} output * @param input A tensor of shape {@code [..., M, M]} whose inner-most 2 dimensions form matrices of * size {@code [M, M]}. * @param outputIdxType The value of the outputIdxType attribute @@ -707,7 +682,6 @@ public Lu lu(Operand input, *

Note: The default kernel implementation for MatMul on GPUs uses * cublas. * - * @param data type for {@code product} output * @param a The a value * @param b The b value * @param options carries optional attribute values @@ -801,7 +775,6 @@ public MatMul matMul(Operand a, Operand b, MatMul.Opt * [9, 2]] * * - * @param data type for {@code output} output * @param diagonal Rank {@code r}, where {@code r >= 1} * @param k Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main * diagonal, and negative value means subdiagonals. {@code k} can be a single integer @@ -886,7 +859,6 @@ public MatrixDiag matrixDiag(Operand diagonal, Operand * - * @param data type for {@code diagonal} output * @param input Rank {@code r} tensor where {@code r >= 2}. * @param k Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main * diagonal, and negative value means subdiagonals. {@code k} can be a single integer @@ -995,7 +967,6 @@ public MatrixDiagPart matrixDiagPart(Operand input, Oper * * * - * @param data type for {@code diagonal} output * @param input Rank {@code r} tensor where {@code r >= 2}. * @param k Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main * diagonal, and negative value means subdiagonals. {@code k} can be a single integer @@ -1123,7 +1094,6 @@ public MatrixDiagPartV3 matrixDiagPartV3(Operand input, * * * - * @param data type for {@code output} output * @param diagonal Rank {@code r}, where {@code r >= 1} * @param k Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main * diagonal, and negative value means subdiagonals. {@code k} can be a single integer @@ -1150,7 +1120,6 @@ public MatrixDiagV3 matrixDiagV3(Operand diagonal, Opera /** * Deprecated, use python implementation tf.linalg.matrix_exponential. * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code MatrixExponential} output and operands * @return a new instance of MatrixExponential @@ -1173,7 +1142,6 @@ public MatrixExponential matrixExponential(Operand input * form square matrices. The output is a tensor of the same shape as the input * containing the exponential for all input submatrices {@code [..., :, :]}. * - * @param data type for {@code output} output * @param input Shape is {@code [..., M, M]}. * @param data type for {@code MatrixLogarithm} output and operands * @return a new instance of MatrixLogarithm @@ -1281,7 +1249,6 @@ public MatrixLogarithm matrixLogarithm(Operand input) { * * * - * @param data type for {@code output} output * @param input Rank {@code r+1}, where {@code r >= 1}. * @param diagonal Rank {@code r} when {@code k} is an integer or {@code k[0] == k[1]}. Otherwise, it has rank {@code r+1}. * {@code k >= 1}. @@ -1331,7 +1298,6 @@ public MatrixSetDiag matrixSetDiag(Operand input, Operan * typically 6-7 times slower than the fast path. If {@code fast} is {@code False} then * {@code l2_regularizer} is ignored. * - * @param data type for {@code output} output * @param matrix Shape is {@code [..., M, N]}. * @param rhs Shape is {@code [..., M, K]}. * @param l2Regularizer Scalar tensor. @@ -1362,7 +1328,6 @@ public MatrixSolveLs matrixSolveLs(Operand matrix, Opera * q_full, r_full = qr(a, full_matrices=True) * * - * @param data type for {@code q} output * @param input A tensor of shape {@code [..., M, N]} whose inner-most 2 dimensions * form matrices of size {@code [M, N]}. Let {@code P} be the minimum of {@code M} and {@code N}. * @param options carries optional attribute values @@ -1380,7 +1345,6 @@ public Qr qr(Operand input, Qr.Options... options) { * outer dimension of {@code b} (after being transposed if {@code transposed_b} is * non-zero). * - * @param data type for {@code out} output * @param a Must be a two-dimensional tensor. * @param b Must be a two-dimensional tensor. * @param minA The float value that the lowest quantized {@code a} value represents. @@ -1411,7 +1375,6 @@ public QuantizedMatMul quantizedMatMul * non-zero). Then do broadcast add operation with bias values on the matrix * multiplication result. The bias size must match inner dimension of {@code b}. * - * @param data type for {@code out} output * @param a A matrix to be multiplied. Must be a two-dimensional tensor of type {@code quint8}. * @param b A matrix to be multiplied and must be a two-dimensional tensor of type {@code qint8}. * @param bias A 1D bias tensor with size matching inner dimension of {@code b} (after being @@ -1442,7 +1405,6 @@ public QuantizedMatMulWithBias quantizedMatMulWithBias( * multiplication result. The bias size must match inner dimension of {@code b}. Then do * relu activation to get non-negative result. * - * @param data type for {@code out} output * @param a A matrix to be multiplied. Must be a two-dimensional tensor of type {@code quint8}. * @param b A matrix to be multiplied and must be a two-dimensional tensor of type {@code qint8}. * @param bias A 1D bias tensor with size matching with inner dimension of {@code b} (after being @@ -1474,7 +1436,6 @@ public QuantizedMatMulWithBiasAndRelu quantizedMatMulWith * relu activation to get non-negative result. Then do requantize operation to get * final uint8 result. * - * @param data type for {@code out} output * @param a A matrix to be multiplied. Must be a two-dimensional tensor of type {@code quint8}. * @param b A matrix to be multiplied and must be a two-dimensional tensor of type {@code qint8}. * @param bias A 1D bias tensor with size matching with inner dimension of {@code b} (after being @@ -1512,7 +1473,6 @@ public QuantizedMatMulWithBiasAndReluAndRequantize quanti * e = self_adjoint_eig(a, compute_v=False) * * - * @param data type for {@code e} output * @param input {@code Tensor} input of shape {@code [N, N]}. * @param options carries optional attribute values * @param data type for {@code SelfAdjointEigV2} output and operands @@ -1532,7 +1492,6 @@ public SelfAdjointEig selfAdjointEig(Operand input, * If {@code adjoint} is {@code True} then each output matrix satisfies * {@code adjoint(matrix[..., :, :]) * output[..., :, :] = rhs[..., :, :]}. * - * @param data type for {@code output} output * @param matrix Shape is {@code [..., M, M]}. * @param rhs Shape is {@code [..., M, K]}. * @param options carries optional attribute values @@ -1559,7 +1518,6 @@ public Solve solve(Operand matrix, Operand rhs, * form square matrices. The output is a tensor of the same shape as the input * containing the matrix square root for all input submatrices {@code [..., :, :]}. * - * @param data type for {@code output} output * @param input Shape is {@code [..., M, M]}. * @param data type for {@code MatrixSquareRoot} output and operands * @return a new instance of Sqrtm @@ -1581,7 +1539,6 @@ public Sqrtm sqrtm(Operand input) { * s, _, _ = svd(a, compute_uv=False) * * - * @param data type for {@code s} output * @param input A tensor of shape {@code [..., M, N]} whose inner-most 2 dimensions * form matrices of size {@code [M, N]}. Let {@code P} be the minimum of {@code M} and {@code N}. * @param options carries optional attribute values @@ -1608,7 +1565,6 @@ public Svd svd(Operand input, Svd.Options... options) { * [0, 0, 0, 4]] * * - * @param data type for {@code output} output * @param diagonal Rank k tensor where k is at most 1. * @param data type for {@code Diag} output and operands * @return a new instance of TensorDiag @@ -1634,7 +1590,6 @@ public TensorDiag tensorDiag(Operand diagonal) { * tf.diag_part(input) ==> [1, 2, 3, 4] * * - * @param data type for {@code diagonal} output * @param input Rank k tensor where k is even and not zero. * @param data type for {@code DiagPart} output and operands * @return a new instance of TensorDiagPart @@ -1648,7 +1603,6 @@ public TensorDiagPart tensorDiagPart(Operand input) { * The output {@code y} has the same rank as {@code x}. The shapes of {@code x} and {@code y} satisfy: * {@code y.shape[i] == x.shape[perm[i]] for i in [0, 1, ..., rank(x) - 1]} * - * @param data type for {@code y} output * @param x The x value * @param perm The perm value * @param data type for {@code Transpose} output and operands @@ -1703,7 +1657,6 @@ public Transpose transpose(Operand x, Operand * - * @param data type for {@code output} output * @param matrix Shape is {@code [..., M, M]}. * @param rhs Shape is {@code [..., M, K]}. * @param options carries optional attribute values @@ -1719,7 +1672,6 @@ public TriangularSolve triangularSolve(Operand matrix, O * Calculate product with tridiagonal matrix. * Calculates product of two matrices, where left matrix is a tridiagonal matrix. * - * @param data type for {@code output} output * @param superdiag Tensor of shape {@code [..., 1, M]}, representing superdiagonals of * tri-diagonal matrices to the left of multiplication. Last element is ignored. * @param maindiag Tensor of shape {@code [..., 1, M]}, representing main diagonals of tri-diagonal @@ -1746,7 +1698,6 @@ public TridiagonalMatMul tridiagonalMatMul(Operand super * library is used: https://docs.nvidia.com/cuda/cusparse/index.html#gtsv * Partial pivoting is not yet supported by XLA backends. * - * @param data type for {@code output} output * @param diagonals Tensor of shape {@code [..., 3, M]} whose innermost 2 dimensions represent the * tridiagonal matrices with three rows being the superdiagonal, diagonals, and * subdiagonals, in order. The last element of the superdiagonal and the first diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgSparseOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgSparseOps.java index ed8c4fdbb90..7210249ba1f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgSparseOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgSparseOps.java @@ -59,7 +59,6 @@ public final class LinalgSparseOps { * This op is meant only for debugging / testing, and its interface is not expected * to be stable. * - * @param data type for {@code values} output * @param csrSparseMatrix A batched CSRSparseMatrix. * @param index The index in {@code csr_sparse_matrix}'s batch. * @param type The value of the type attribute @@ -74,7 +73,6 @@ public CSRSparseMatrixComponents cSRSparseMatrixComponents( /** * Convert a (possibly batched) CSRSparseMatrix to dense. * - * @param data type for {@code dense_output} output * @param sparseInput A batched CSRSparseMatrix. * @param type The value of the type attribute * @param data type for {@code CSRSparseMatrixToDense} output and operands @@ -88,7 +86,6 @@ public CSRSparseMatrixToDense cSRSparseMatrixToDense( /** * Converts a (possibly batched) CSRSparesMatrix to a SparseTensor. * - * @param data type for {@code values} output * @param sparseMatrix A (possibly batched) CSRSparseMatrix. * @param type The value of the type attribute * @param data type for {@code CSRSparseMatrixToSparseTensor} output and operands @@ -152,7 +149,6 @@ public SparseMatrixAdd sparseMatrixAdd(Operand * - * @param data type for {@code output} output * @param a A CSRSparseMatrix. * @param b A dense tensor. * @param options carries optional attribute values diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java index ee2e3a46c27..d3dcfc686ad 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java @@ -168,7 +168,6 @@ public final class MathOps { * value of each element in {@code x}. For example, if x is an input element and y is * an output element, this operation computes \(y = |x|\). * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Abs} output and operands * @return a new instance of Abs @@ -186,7 +185,6 @@ public Abs abs(Operand x) { *

Unlike the original {@code accumulate_n}, {@code accumulate_n_v2} is differentiable. *

Returns a {@code Tensor} of same shape and type as the elements of {@code inputs}. * - * @param data type for {@code sum} output * @param inputs A list of {@code Tensor} objects, each with same shape and type. * @param shape Shape of elements of {@code inputs}. * @param data type for {@code AccumulateNV2} output and operands @@ -201,7 +199,6 @@ public AccumulateN accumulateN(Iterable> inputs, * Provided an input tensor, the {@code tf.math.acos} operation returns the inverse cosine of each element of the tensor. If {@code y = tf.math.cos(x)} then, {@code x = tf.math.acos(y)}. *

Input range is {@code [-1, 1]} and the output has a range of {@code [0, pi]}. * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Acos} output and operands * @return a new instance of Acos @@ -219,7 +216,6 @@ public Acos acos(Operand x) { * tf.math.acosh(x) ==> [nan nan 0. 0.62236255 5.9914584 9.903487 inf] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Acosh} output and operands * @return a new instance of Acosh @@ -235,7 +231,6 @@ public Acosh acosh(Operand x) { *

Given two input tensors, the {@code tf.add} operation computes the sum for every element in the tensor. *

Both input and output have a range {@code (-inf, inf)}. * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Add} output and operands @@ -253,7 +248,6 @@ public Add add(Operand x, Operand y) { * tf.math.add_n(x) ==> 26 * * - * @param data type for {@code sum} output * @param inputs The inputs value * @param data type for {@code AddN} output and operands * @return a new instance of AddN @@ -278,7 +272,6 @@ public AddN addN(Iterable> inputs) { * Equivalent to np.angle. *
{@literal @}end_compatibility * - * @param data type for {@code output} output * @param input The input value * @return a new instance of Angle, with default output types */ @@ -302,7 +295,6 @@ public Angle angle(Operand input) { * Equivalent to np.angle. *
{@literal @}end_compatibility * - * @param data type for {@code output} output * @param input The input value * @param Tout The value of the Tout attribute * @param data type for {@code Angle} output and operands @@ -339,7 +331,6 @@ public ApproximateEqual approximateEqual(Operand x, Operand * # here a[4] = 166.32 which is the largest element of a across axis 0 * * - * @param data type for {@code output} output * @param input The input value * @param dimension int16, int32 or int64, must be in the range {@code [-rank(input), rank(input))}. * Describes which dimension of the input Tensor to reduce across. For vectors, @@ -364,7 +355,6 @@ public ArgMax argMax(Operand input, * # here a[4] = 166.32 which is the largest element of a across axis 0 * * - * @param data type for {@code output} output * @param input The input value * @param dimension int16, int32 or int64, must be in the range {@code [-rank(input), rank(input))}. * Describes which dimension of the input Tensor to reduce across. For vectors, @@ -391,7 +381,6 @@ public ArgMax argMax(Operand input, * # here a[0] = 1 which is the smallest element of a across axis 0 * * - * @param data type for {@code output} output * @param input The input value * @param dimension int32 or int64, must be in the range {@code [-rank(input), rank(input))}. * Describes which dimension of the input Tensor to reduce across. For vectors, @@ -416,7 +405,6 @@ public ArgMin argMin(Operand input, * # here a[0] = 1 which is the smallest element of a across axis 0 * * - * @param data type for {@code output} output * @param input The input value * @param dimension int32 or int64, must be in the range {@code [-rank(input), rank(input))}. * Describes which dimension of the input Tensor to reduce across. For vectors, @@ -445,7 +433,6 @@ public ArgMin argMin(Operand input, * tf.math.asin(y) # [1.047, 0.785] = x * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Asin} output and operands * @return a new instance of Asin @@ -464,7 +451,6 @@ public Asin asin(Operand x) { * tf.math.asinh(x) ==> [-inf -1.4436355 -0.4812118 0.8813736 1.0159732 5.991471 9.903487 inf] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Asinh} output and operands * @return a new instance of Asinh @@ -488,7 +474,6 @@ public Asinh asinh(Operand x) { * tf.math.atan(y) # [1.047, 0.785] = x * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Atan} output and operands * @return a new instance of Atan @@ -516,7 +501,6 @@ public Atan atan(Operand x) { * * * - * @param data type for {@code z} output * @param y The y value * @param x The x value * @param data type for {@code Atan2} output and operands @@ -538,7 +522,6 @@ public Atan2 atan2(Operand y, Operand x) { * tf.math.atanh(x) ==> [nan -inf -0.54930615 inf 0. 0.54930615 nan nan] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Atanh} output and operands * @return a new instance of Atanh @@ -550,7 +533,6 @@ public Atanh atanh(Operand x) { /** * The BesselI0 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselI0} output and operands * @return a new instance of BesselI0 @@ -562,7 +544,6 @@ public BesselI0 besselI0(Operand x) { /** * The BesselI0e operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselI0e} output and operands * @return a new instance of BesselI0e @@ -574,7 +555,6 @@ public BesselI0e besselI0e(Operand x) { /** * The BesselI1 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselI1} output and operands * @return a new instance of BesselI1 @@ -586,7 +566,6 @@ public BesselI1 besselI1(Operand x) { /** * The BesselI1e operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselI1e} output and operands * @return a new instance of BesselI1e @@ -604,7 +583,6 @@ public BesselI1e besselI1e(Operand x) { *

is the incomplete beta function and \(B(a, b)\) is the complete * beta function. * - * @param data type for {@code z} output * @param a The a value * @param b The b value * @param x The x value @@ -624,7 +602,6 @@ public Betainc betainc(Operand a, Operand b, Operan * {@code i}. *

Values in {@code arr} outside of the range [0, size) are ignored. * - * @param data type for {@code bins} output * @param arr int32 {@code Tensor}. * @param sizeOutput non-negative int32 scalar {@code Tensor}. * @param weights is an int32, int64, float32, or float64 {@code Tensor} with the same @@ -641,7 +618,6 @@ public Bincount bincount(Operand arr, Operand data type for {@code y} output * @param x The x value * @param data type for {@code Ceil} output and operands * @return a new instance of Ceil @@ -667,7 +643,6 @@ public Ceil ceil(Operand x) { * * * - * @param data type for {@code y} output * @param x The x value * @return a new instance of ComplexAbs, with default output types */ @@ -692,7 +667,6 @@ public ComplexAbs complexAbs(Operand x) { * * * - * @param data type for {@code y} output * @param x The x value * @param Tout The value of the Tout attribute * @param data type for {@code ComplexAbs} output and operands @@ -715,7 +689,6 @@ public ComplexAbs complexAbs(Operand x, * tf.conj(input) ==> [-2.25 - 4.75j, 3.25 - 5.75j] * * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code Conj} output and operands * @return a new instance of Conj @@ -735,7 +708,6 @@ public Conj conj(Operand input) { * tf.math.cos(x) ==> [nan -0.91113025 0.87758255 0.5403023 0.36235774 0.48718765 -0.95215535 nan] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Cos} output and operands * @return a new instance of Cos @@ -754,7 +726,6 @@ public Cos cos(Operand x) { * tf.math.cosh(x) ==> [inf 4.0515420e+03 1.1276259e+00 1.5430807e+00 1.8106556e+00 3.7621956e+00 1.1013233e+04 inf] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Cosh} output and operands * @return a new instance of Cosh @@ -786,7 +757,6 @@ public Cosh cosh(Operand x) { * tf.cumprod([a, b, c], exclusive=True, reverse=True) # => [b * c, c, 1] * * - * @param data type for {@code out} output * @param x A {@code Tensor}. Must be one of the following types: {@code float32}, {@code float64}, * {@code int64}, {@code int32}, {@code uint8}, {@code uint16}, {@code int16}, {@code int8}, {@code complex64}, * {@code complex128}, {@code qint8}, {@code quint8}, {@code qint32}, {@code half}. @@ -824,7 +794,6 @@ public Cumprod cumprod(Operand x, Operand * - * @param data type for {@code out} output * @param x A {@code Tensor}. Must be one of the following types: {@code float32}, {@code float64}, * {@code int64}, {@code int32}, {@code uint8}, {@code uint16}, {@code int16}, {@code int8}, {@code complex64}, * {@code complex128}, {@code qint8}, {@code quint8}, {@code qint32}, {@code half}. @@ -858,7 +827,6 @@ public Cumsum cumsum(Operand x, OperandBy setting the {@code reverse} kwarg to {@code True}, the cumulative log-sum-exp is performed in the * opposite direction. * - * @param data type for {@code out} output * @param x A {@code Tensor}. Must be one of the following types: {@code float16}, {@code float32}, {@code float64}. * @param axis A {@code Tensor} of type {@code int32} (default: 0). Must be in the range * {@code [-rank(x), rank(x))}. @@ -880,7 +848,6 @@ public CumulativeLogsumexp cumulativeLogsumexp(Operand * {@code i}. *

Values in {@code arr} outside of the range [0, size) are ignored. * - * @param data type for {@code output} output * @param input 1D or 2D int {@code Tensor}. * @param sizeOutput non-negative int scalar {@code Tensor}. * @param weights is an int32, int64, float32, or float64 {@code Tensor} with the same @@ -900,7 +867,6 @@ public DenseBincount denseBincount(Ope * Computes Psi, the derivative of Lgamma (the log of the absolute value of * {@code Gamma(x)}), element-wise. * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Digamma} output and operands * @return a new instance of Digamma @@ -914,7 +880,6 @@ public Digamma digamma(Operand x) { * NOTE: {@code math.Div} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Div} output and operands @@ -929,7 +894,6 @@ public Div div(Operand x, Operand y) { * NOTE: {@code math.DivNoNan} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code DivNoNan} output and operands @@ -966,7 +930,6 @@ public Equal equal(Operand x, Operand y, Equal.Options.. /** * Computes the Gauss error function of {@code x} element-wise. In statistics, for non-negative values of $x$, the error function has the following interpretation: for a random variable $Y$ that is normally distributed with mean 0 and variance $1/\sqrt{2}$, $erf(x)$ is the probability that $Y$ falls in the range $[−x, x]$. * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Erf} output and operands * @return a new instance of Erf @@ -978,7 +941,6 @@ public Erf erf(Operand x) { /** * Computes the complementary error function of {@code x} element-wise. * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Erfc} output and operands * @return a new instance of Erfc @@ -990,7 +952,6 @@ public Erfc erfc(Operand x) { /** * The Erfinv operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Erfinv} output and operands * @return a new instance of erfinv @@ -1023,7 +984,6 @@ public erfinv erfinv(Operand x) { * tf.math.exp(x) ==> 1.4686939399158851+2.2873552871788423j * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Exp} output and operands * @return a new instance of Exp @@ -1047,7 +1007,6 @@ public Exp exp(Operand x) { * tf.math.expm1(x) ==> (0.46869393991588515+2.2873552871788423j) * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Expm1} output and operands * @return a new instance of Expm1 @@ -1068,7 +1027,6 @@ public Fact fact() { /** * Returns element-wise largest integer not greater than x. * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Floor} output and operands * @return a new instance of Floor @@ -1082,7 +1040,6 @@ public Floor floor(Operand x) { * NOTE: {@code math.FloorDiv} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code FloorDiv} output and operands @@ -1100,7 +1057,6 @@ public FloorDiv floorDiv(Operand x, Operand y) { *

NOTE: {@code math.FloorMod} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code FloorMod} output and operands @@ -1168,7 +1124,6 @@ public GreaterEqual greaterEqual(Operand x, Operand y) *

Note, above {@code Q(a, x)} ({@code Igammac}) is the upper regularized complete * Gamma function. * - * @param data type for {@code z} output * @param a The a value * @param x The x value * @param data type for {@code Igamma} output and operands @@ -1181,7 +1136,6 @@ public Igamma igamma(Operand a, Operand x) { /** * Computes the gradient of {@code igamma(a, x)} wrt {@code a}. * - * @param data type for {@code z} output * @param a The a value * @param x The x value * @param data type for {@code IgammaGradA} output and operands @@ -1201,7 +1155,6 @@ public IgammaGradA igammaGradA(Operand a, Operand x *

Note, above {@code P(a, x)} ({@code Igamma}) is the lower regularized complete * Gamma function. * - * @param data type for {@code z} output * @param a The a value * @param x The x value * @param data type for {@code Igammac} output and operands @@ -1223,7 +1176,6 @@ public Igammac igammac(Operand a, Operand x) { * tf.imag(input) ==> [4.75, 5.75] * * - * @param data type for {@code output} output * @param input The input value * @return a new instance of Imag, with default output types */ @@ -1243,7 +1195,6 @@ public Imag imag(Operand input) { * tf.imag(input) ==> [4.75, 5.75] * * - * @param data type for {@code output} output * @param input The input value * @param Tout The value of the Tout attribute * @param data type for {@code Imag} output and operands @@ -1267,7 +1218,6 @@ public Imag imag(Operand input, Class * invert_permutation(x) ==> [2, 4, 3, 0, 1] * * - * @param data type for {@code y} output * @param x 1-D. * @param data type for {@code InvertPermutation} output and operands * @return a new instance of InvertPermutation @@ -1388,7 +1338,6 @@ public LessEqual lessEqual(Operand x, Operand y) { * tf.math.lgamma(x) ==> [inf, 0.5723649, 0., 2.4537368, inf, -4.6477685] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Lgamma} output and operands * @return a new instance of Lgamma @@ -1406,7 +1355,6 @@ public Lgamma lgamma(Operand x) { * tf.math.log(x) ==> [-inf, -0.6931472, 0. , 1.609438] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Log} output and operands * @return a new instance of Log @@ -1424,7 +1372,6 @@ public Log log(Operand x) { * tf.math.log1p(x) ==> [0., 0.4054651, 0.6931472, 1.7917595] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Log1p} output and operands * @return a new instance of Log1p @@ -1474,7 +1421,6 @@ public LogicalOr logicalOr(Operand x, Operand y) { * NOTE: {@code math.Maximum} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Maximum} output and operands @@ -1491,7 +1437,6 @@ public Maximum maximum(Operand x, Operand y) { * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -1509,7 +1454,6 @@ public Mean mean(Operand input, OperandNOTE: {@code math.Minimum} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Minimum} output and operands @@ -1526,7 +1470,6 @@ public Minimum minimum(Operand x, Operand y) { *

NOTE: {@code math.Mod} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Mod} output and operands @@ -1541,7 +1484,6 @@ public Mod mod(Operand x, Operand y) { * NOTE: {@code math.Mul} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Mul} output and operands @@ -1556,7 +1498,6 @@ public Mul mul(Operand x, Operand y) { * NOTE: {@code math.MulNoNan} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code MulNoNan} output and operands @@ -1569,7 +1510,6 @@ public MulNoNan mulNoNan(Operand x, Operand y) { /** * The Ndtri operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Ndtri} output and operands * @return a new instance of Ndtri @@ -1582,7 +1522,6 @@ public Ndtri ndtri(Operand x) { * Computes numerical negative value element-wise. * I.e., \(y = -x\). * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Neg} output and operands * @return a new instance of Neg @@ -1599,7 +1538,6 @@ public Neg neg(Operand x) { * Equivalent to C++ std::nextafter function. *
{@literal @}end_compatibility * - * @param data type for {@code output} output * @param x1 The x1 value * @param x2 The x2 value * @param data type for {@code NextAfter} output and operands @@ -1632,7 +1570,6 @@ public NotEqual notEqual(Operand x, Operand y, *

where \(\psi(x)\) is the digamma function. * The polygamma function is defined only for non-negative integer orders \a\. * - * @param data type for {@code z} output * @param a The a value * @param x The x value * @param data type for {@code Polygamma} output and operands @@ -1667,7 +1604,6 @@ public PopulationCount populationCount(Operand x) { * tf.pow(x, y) ==> [[256, 65536], [9, 27]] * * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Pow} output and operands @@ -1680,7 +1616,6 @@ public Pow pow(Operand x, Operand y) { /** * Returns x + y element-wise, working on quantized buffers. * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param minX The float value that the lowest quantized {@code x} value represents. @@ -1700,7 +1635,6 @@ public QuantizedAdd quantizedAdd(Operand data type for {@code z} output * @param x The x value * @param y The y value * @param minX The float value that the lowest quantized {@code x} value represents. @@ -1729,7 +1663,6 @@ public QuantizedMul quantizedMul(Operand * - * @param data type for {@code output} output * @param input The input value * @return a new instance of Real, with default output types */ @@ -1749,7 +1682,6 @@ public Real real(Operand input) { * tf.real(input) ==> [-2.25, 3.25] * * - * @param data type for {@code output} output * @param input The input value * @param Tout The value of the Tout attribute * @param data type for {@code Real} output and operands @@ -1765,7 +1697,6 @@ public Real real(Operand input, Class *

NOTE: {@code Div} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code RealDiv} output and operands @@ -1779,7 +1710,6 @@ public RealDiv realDiv(Operand x, Operand y) { * Computes the reciprocal of x element-wise. * I.e., \(y = 1 / x\). * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Reciprocal} output and operands * @return a new instance of Reciprocal @@ -1793,7 +1723,6 @@ public Reciprocal reciprocal(Operand x) { * Specifically, {@code grad = -dy * y*y}, where {@code y = 1/x}, and {@code dy} * is the corresponding input gradient. * - * @param data type for {@code z} output * @param y The y value * @param dy The dy value * @param data type for {@code ReciprocalGrad} output and operands @@ -1822,7 +1751,6 @@ public RequantizationRangePerChannel requantizationRangePerChannel( /** * Requantizes input with min and max values known per channel. * - * @param data type for {@code output} output * @param input The original input tensor. * @param inputMin The minimum value of the input tensor * @param inputMax The maximum value of the input tensor. @@ -1850,7 +1778,6 @@ public RequantizePerChannel requantizePerChannel( * rint([-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0]) ==> [-2., -2., -0., 0., 2., 2., 2.] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Rint} output and operands * @return a new instance of Rint @@ -1864,7 +1791,6 @@ public Rint rint(Operand x) { * Rounds half to even. Also known as bankers rounding. If you want to round * according to the current system rounding mode use std::cint. * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Round} output and operands * @return a new instance of Round @@ -1877,7 +1803,6 @@ public Round round(Operand x) { * Computes reciprocal of square root of x element-wise. * I.e., \(y = 1 / \sqrt{x}\). * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Rsqrt} output and operands * @return a new instance of Rsqrt @@ -1891,7 +1816,6 @@ public Rsqrt rsqrt(Operand x) { * Specifically, {@code grad = dy * -0.5 * y^3}, where {@code y = rsqrt(x)}, and {@code dy} * is the corresponding input gradient. * - * @param data type for {@code z} output * @param y The y value * @param dy The dy value * @param data type for {@code RsqrtGrad} output and operands @@ -1942,7 +1866,6 @@ public RsqrtGrad rsqrtGrad(Operand y, Operand dy) { * * * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s * first dimension. Values should be sorted and can be repeated. @@ -1989,7 +1912,6 @@ public SegmentMax segmentMax(Operand data, * * * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s * first dimension. Values should be sorted and can be repeated. @@ -2044,7 +1966,6 @@ public SegmentMean segmentMean(Operand data, * * * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s * first dimension. Values should be sorted and can be repeated. @@ -2093,7 +2014,6 @@ public SegmentMin segmentMin(Operand data, * * * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s * first dimension. Values should be sorted and can be repeated. @@ -2119,9 +2039,7 @@ public SegmentProd segmentProd(Operand data, * that {@code segment_ids[j] == i}. *

If the sum is empty for a given segment ID {@code i}, {@code output[i] = 0}. *

Note that this op is currently only supported with jit_compile=True. - * * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s * first dimension. Values should be sorted and can be repeated. @@ -2141,7 +2059,6 @@ public SegmentSum segmentSum(Operand data, * Computes sigmoid of {@code x} element-wise. * Specifically, {@code y = 1 / (1 + exp(-x))}. * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Sigmoid} output and operands * @return a new instance of Sigmoid @@ -2155,7 +2072,6 @@ public Sigmoid sigmoid(Operand x) { * Specifically, {@code grad = dy * y * (1 - y)}, where {@code y = sigmoid(x)}, and * {@code dy} is the corresponding input gradient. * - * @param data type for {@code z} output * @param y The y value * @param dy The dy value * @param data type for {@code SigmoidGrad} output and operands @@ -2179,7 +2095,6 @@ public SigmoidGrad sigmoidGrad(Operand y, Operand dy) * * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Sign} output and operands * @return a new instance of Sign @@ -2198,7 +2113,6 @@ public Sign sign(Operand x) { * tf.math.sin(x) ==> [nan -0.4121185 -0.47942555 0.84147096 0.9320391 -0.87329733 -0.54402107 nan] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Sin} output and operands * @return a new instance of Sin @@ -2217,7 +2131,6 @@ public Sin sin(Operand x) { * tf.math.sinh(x) ==> [-inf -4.0515420e+03 -5.2109528e-01 1.1752012e+00 1.5094614e+00 3.6268604e+00 1.1013232e+04 inf] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Sinh} output and operands * @return a new instance of Sinh @@ -2231,7 +2144,6 @@ public Sinh sinh(Operand x) { * Creates a Sobol sequence with {@code num_results} samples. Each sample has dimension * {@code dim}. Skips the first {@code skip} samples. * - * @param data type for {@code samples} output * @param dim Positive scalar {@code Tensor} representing each sample's dimension. * @param numResults Positive scalar {@code Tensor} of dtype int32. The number of Sobol points to return * in the output. @@ -2249,7 +2161,6 @@ public SobolSample sobolSample(Operand dim, Operand nu * Creates a Sobol sequence with {@code num_results} samples. Each sample has dimension * {@code dim}. Skips the first {@code skip} samples. * - * @param data type for {@code samples} output * @param dim Positive scalar {@code Tensor} representing each sample's dimension. * @param numResults Positive scalar {@code Tensor} of dtype int32. The number of Sobol points to return * in the output. @@ -2267,7 +2178,6 @@ public SobolSample sobolSample(Operand dim, /** * The Softplus operation * - * @param data type for {@code activations} output * @param features The features value * @param data type for {@code Softplus} output and operands * @return a new instance of Softplus @@ -2279,7 +2189,6 @@ public Softplus softplus(Operand features) { /** * Computes softplus gradients for a softplus operation. * - * @param data type for {@code backprops} output * @param gradients The backpropagated gradients to the corresponding softplus operation. * @param features The features passed as input to the corresponding softplus operation. * @param data type for {@code SoftplusGrad} output and operands @@ -2294,7 +2203,6 @@ public SoftplusGrad softplusGrad(Operand gradients, * Computes square root of x element-wise. * I.e., \(y = \sqrt{x} = x^{1/2}\). * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Sqrt} output and operands * @return a new instance of Sqrt @@ -2308,7 +2216,6 @@ public Sqrt sqrt(Operand x) { * Specifically, {@code grad = dy * 0.5 / y}, where {@code y = sqrt(x)}, and {@code dy} * is the corresponding input gradient. * - * @param data type for {@code z} output * @param y The y value * @param dy The dy value * @param data type for {@code SqrtGrad} output and operands @@ -2322,7 +2229,6 @@ public SqrtGrad sqrtGrad(Operand y, Operand dy) { * Computes square of x element-wise. * I.e., \(y = x * x = x^2\). * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Square} output and operands * @return a new instance of Square @@ -2336,7 +2242,6 @@ public Square square(Operand x) { * NOTE: {@code math.SquaredDifference} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code SquaredDifference} output and operands @@ -2351,7 +2256,6 @@ public SquaredDifference squaredDifference(Operand x, Op * NOTE: {@code math.Sub} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Sub} output and operands @@ -2372,7 +2276,6 @@ public Sub sub(Operand x, Operand y) { * tf.math.tan(x) ==> [nan 0.45231566 -0.5463025 1.5574077 2.572152 -1.7925274 0.32097113 nan] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Tan} output and operands * @return a new instance of Tan @@ -2398,7 +2301,6 @@ public Tan tan(Operand x) { * * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Tanh} output and operands * @return a new instance of Tanh @@ -2412,7 +2314,6 @@ public Tanh tanh(Operand x) { * Specifically, {@code grad = dy * (1 - y*y)}, where {@code y = tanh(x)}, and {@code dy} * is the corresponding input gradient. * - * @param data type for {@code z} output * @param y The y value * @param dy The dy value * @param data type for {@code TanhGrad} output and operands @@ -2431,7 +2332,6 @@ public TanhGrad tanhGrad(Operand y, Operand dy) { *

NOTE: {@code math.TruncateDiv} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code TruncateDiv} output and operands @@ -2447,7 +2347,6 @@ public TruncateDiv truncateDiv(Operand x, Operand y) *

NOTE: {@code math.TruncateMod} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code TruncateMod} output and operands @@ -2475,7 +2374,6 @@ public TruncateMod truncateMod(Operand x, Operand y * if {@code operand.quantization_axis} >= 0 and {@code output.quantization_axis} >= 0, * {@code operand.dims} - {@code operand.quantization_axis} must be equal to {@code output.dims} - {@code output.quantization_axis}. * - * @param data type for {@code output} output * @param lhs Must be a quantized tensor. * @param rhs Must be a quantized tensor. * @param lhsScales The float value(s) used as scale factors when quantizing the original data that {@code lhs} represents. @@ -2547,7 +2445,6 @@ public UniformQuantizedAdd uniformQuantizedAdd(Operand * * * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}. * The values must be less than {@code num_segments}. @@ -2594,7 +2491,6 @@ public UnsortedSegmentMax unsortedSegmentMax(Operand d * out-of-bound indices or outputting a tensor with a 0 stored in the first * dimension of its shape if {@code num_segments} is 0. * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}. * The values must be less than {@code num_segments}. @@ -2640,7 +2536,6 @@ public UnsortedSegmentMin unsortedSegmentMin(Operand d * out-of-bound indices or outputting a tensor with a 0 stored in the first * dimension of its shape if {@code num_segments} is 0. * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}. * The values must be less than {@code num_segments}. @@ -2689,7 +2584,6 @@ public UnsortedSegmentProd unsortedSegmentProd(Operand d * * * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}. * The values must be less than {@code num_segments}. @@ -2707,7 +2601,6 @@ public UnsortedSegmentSum unsortedSegmentSum(Operand dat /** * Returns 0 if x == 0, and x / y otherwise, elementwise. * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Xdivy} output and operands @@ -2720,7 +2613,6 @@ public Xdivy xdivy(Operand x, Operand y) { /** * Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise. * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Xlog1py} output and operands @@ -2733,7 +2625,6 @@ public Xlog1py xlog1py(Operand x, Operand y) { /** * Returns 0 if x == 0, and x * log(y) otherwise, elementwise. * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Xlogy} output and operands @@ -2748,7 +2639,6 @@ public Xlogy xlogy(Operand x, Operand y) { * The Hurwitz zeta function is defined as: *

\(\zeta(x, q) = \sum_{n=0}^{\infty} (q + n)^{-x}\) * - * @param data type for {@code z} output * @param x The x value * @param q The q value * @param data type for {@code Zeta} output and operands diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathSpecialOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathSpecialOps.java index 05af5fe921d..e486615af1b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathSpecialOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathSpecialOps.java @@ -51,7 +51,6 @@ public final class MathSpecialOps { /** * The BesselJ0 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselJ0} output and operands * @return a new instance of BesselJ0 @@ -63,7 +62,6 @@ public BesselJ0 besselJ0(Operand x) { /** * The BesselJ1 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselJ1} output and operands * @return a new instance of BesselJ1 @@ -75,7 +73,6 @@ public BesselJ1 besselJ1(Operand x) { /** * The BesselK0 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselK0} output and operands * @return a new instance of BesselK0 @@ -87,7 +84,6 @@ public BesselK0 besselK0(Operand x) { /** * The BesselK0e operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselK0e} output and operands * @return a new instance of BesselK0e @@ -99,7 +95,6 @@ public BesselK0e besselK0e(Operand x) { /** * The BesselK1 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselK1} output and operands * @return a new instance of BesselK1 @@ -111,7 +106,6 @@ public BesselK1 besselK1(Operand x) { /** * The BesselK1e operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselK1e} output and operands * @return a new instance of BesselK1e @@ -123,7 +117,6 @@ public BesselK1e besselK1e(Operand x) { /** * The BesselY0 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselY0} output and operands * @return a new instance of BesselY0 @@ -135,7 +128,6 @@ public BesselY0 besselY0(Operand x) { /** * The BesselY1 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselY1} output and operands * @return a new instance of BesselY1 @@ -147,7 +139,6 @@ public BesselY1 besselY1(Operand x) { /** * The Dawsn operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Dawsn} output and operands * @return a new instance of Dawsn @@ -159,7 +150,6 @@ public Dawsn dawsn(Operand x) { /** * The Expint operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Expint} output and operands * @return a new instance of Expint @@ -171,7 +161,6 @@ public Expint expint(Operand x) { /** * The FresnelCos operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code FresnelCos} output and operands * @return a new instance of FresnelCos @@ -183,7 +172,6 @@ public FresnelCos fresnelCos(Operand x) { /** * The FresnelSin operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code FresnelSin} output and operands * @return a new instance of FresnelSin @@ -195,7 +183,6 @@ public FresnelSin fresnelSin(Operand x) { /** * The Spence operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Spence} output and operands * @return a new instance of Spence diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java index 2e20b52b946..9859a308562 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java @@ -155,7 +155,6 @@ public final class NnOps { * Each entry in {@code output} is the mean of the corresponding size {@code ksize} * window in {@code value}. * - * @param data type for {@code output} output * @param value 4-D with shape {@code [batch, height, width, channels]}. * @param ksize The size of the sliding window for each dimension of {@code value}. * @param strides The stride of the sliding window for each dimension of {@code value}. @@ -174,7 +173,6 @@ public AvgPool avgPool(Operand value, List ksize * Each entry in {@code output} is the mean of the corresponding size {@code ksize} window in * {@code value}. * - * @param data type for {@code output} output * @param input Shape {@code [batch, depth, rows, cols, channels]} tensor to pool over. * @param ksize 1-D tensor of length 5. The size of the window for each dimension of * the input tensor. Must have {@code ksize[0] = ksize[4] = 1}. @@ -193,7 +191,6 @@ public AvgPool3d avgPool3d(Operand input, List k /** * Computes gradients of average pooling function. * - * @param data type for {@code output} output * @param origInputShape The original input dimensions. * @param grad Output backprop of shape {@code [batch, depth, rows, cols, channels]}. * @param ksize 1-D tensor of length 5. The size of the window for each dimension of @@ -214,7 +211,6 @@ public AvgPool3dGrad avgPool3dGrad(Operand origIn /** * Computes gradients of the average pooling function. * - * @param data type for {@code output} output * @param origInputShape 1-D. Shape of the original input to {@code avg_pool}. * @param grad 4-D with shape {@code [batch, height, width, channels]}. Gradients w.r.t. * the output of {@code avg_pool}. @@ -235,7 +231,6 @@ public AvgPoolGrad avgPoolGrad(Operand origInputS * Batch normalization. * This op is deprecated. Prefer {@code tf.nn.batch_normalization}. * - * @param data type for {@code result} output * @param t A 4D input Tensor. * @param m A 1D mean Tensor with size matching the last dimension of t. * This is the first output from tf.nn.moments, @@ -264,7 +259,6 @@ public BatchNormWithGlobalNormalization batchNormWithGlobal * Gradients for batch normalization. * This op is deprecated. See {@code tf.nn.batch_normalization}. * - * @param data type for {@code dx} output * @param t A 4D input Tensor. * @param m A 1D mean Tensor with size matching the last dimension of t. * This is the first output from tf.nn.moments, @@ -293,7 +287,6 @@ public BatchNormWithGlobalNormalizationGrad batchNormWithGl * This is a special case of {@code tf.add} where {@code bias} is restricted to be 1-D. * Broadcasting is supported, so {@code value} may have any number of dimensions. * - * @param data type for {@code output} output * @param value Any number of dimensions. * @param bias 1-D with size the last dimension of {@code value}. * @param options carries optional attribute values @@ -311,7 +304,6 @@ public BiasAdd biasAdd(Operand value, Operand bias, * For NHWC data format, the feature dimension is the last. For NCHW data format, * the feature dimension is the third-to-last. * - * @param data type for {@code output} output * @param outBackprop Any number of dimensions. * @param options carries optional attribute values * @param data type for {@code BiasAddGrad} output and operands @@ -345,7 +337,6 @@ public BiasAddGrad biasAddGrad(Operand outBackprop, * all gate-related outputs should be reordered. * * - * @param data type for {@code i} output * @param seqLenMax Maximum time length actually used by this input. Outputs are padded * with zeros beyond this length. * @param x The sequence input to the LSTM, shape (timelen, batch_size, num_inputs). @@ -370,7 +361,6 @@ public BlockLSTM blockLSTM(Operand seqLenMax, Ope * Computes the LSTM cell backward propagation for the entire time sequence. * This implementation is to be used in conjunction of BlockLSTMV2. * - * @param data type for {@code x_grad} output * @param seqLenMax Maximum time length actually used by this input. Outputs are padded * with zeros beyond this length. * @param x The sequence input to the LSTM, shape (timelen, batch_size, num_inputs). @@ -445,7 +435,6 @@ public ComputeAccidentalHits computeAccidentalHits(Operand trueClasses, * General function for computing a N-D convolution. It is required that * {@code 1 <= N <= 3}. * - * @param data type for {@code output} output * @param input Tensor of type T and shape {@code batch_shape + spatial_shape + [in_channels]} in the * case that {@code channels_last_format = true} or shape * {@code batch_shape + [in_channels] + spatial_shape} if {@code channels_last_format = false}. @@ -490,7 +479,6 @@ public Conv conv(Operand input, Operand filter, Lis *

Must have {@code strides[0] = strides[3] = 1}. For the most common case of the same * horizontal and vertices strides, {@code strides = [1, stride, stride, 1]}. * - * @param data type for {@code output} output * @param input A 4-D tensor. The dimension order is interpreted according to the value * of {@code data_format}, see below for details. * @param filter A 4-D tensor of shape @@ -511,7 +499,6 @@ public Conv2d conv2d(Operand input, Operand filter, /** * Computes the gradients of convolution with respect to the filter. * - * @param data type for {@code output} output * @param input 4-D with shape {@code [batch, in_height, in_width, in_channels]}. * @param filterSizes An integer vector representing the tensor shape of {@code filter}, * where {@code filter} is a 4-D @@ -535,7 +522,6 @@ public Conv2dBackpropFilter conv2dBackpropFilter(Operand< /** * Computes the gradients of convolution with respect to the input. * - * @param data type for {@code output} output * @param inputSizes An integer vector representing the shape of {@code input}, * where {@code input} is a 4-D {@code [batch, height, width, channels]} tensor. * @param filter 4-D with shape @@ -563,7 +549,6 @@ public Conv2dBackpropInput conv2dBackpropInput(OperandOur Conv3D implements a form of cross-correlation. * - * @param data type for {@code output} output * @param input Shape {@code [batch, in_depth, in_height, in_width, in_channels]}. * @param filter Shape {@code [filter_depth, filter_height, filter_width, in_channels, out_channels]}. {@code in_channels} must match between {@code input} and {@code filter}. * @param strides 1-D tensor of length 5. The stride of the sliding window for each @@ -581,7 +566,6 @@ public Conv3d conv3d(Operand input, Operand filter, /** * Computes the gradients of 3-D convolution with respect to the filter. * - * @param data type for {@code output} output * @param input Shape {@code [batch, depth, rows, cols, in_channels]}. * @param filterSizes An integer vector representing the tensor shape of {@code filter}, * where {@code filter} is a 5-D @@ -604,7 +588,6 @@ public Conv3dBackpropFilter conv3dBackpropFilter(Operand< /** * Computes the gradients of 3-D convolution with respect to the input. * - * @param data type for {@code output} output * @param inputSizes An integer vector representing the tensor shape of {@code input}, * where {@code input} is a 5-D * {@code [batch, depth, rows, cols, in_channels]} tensor. @@ -632,7 +615,6 @@ public Conv3dBackpropInput conv3dBackpropInput( * "A B" is returned if merge_repeated = True but "A B B B B" is * returned if merge_repeated = False. * - * @param data type for {@code log_probability} output * @param inputs 3-D, shape: {@code (max_time x batch_size x num_classes)}, the logits. * @param sequenceLength A vector containing sequence lengths, size {@code (batch)}. * @param beamWidth A scalar >= 0 (beam search beam width). @@ -658,7 +640,6 @@ public CtcBeamSearchDecoder ctcBeamSearchDecoder(Operand< * time and batch corresponds to the blank, index {@code (num_classes - 1)}, no new * element is emitted. * - * @param data type for {@code log_probability} output * @param inputs 3-D, shape: {@code (max_time x batch_size x num_classes)}, the logits. * @param sequenceLength A vector containing sequence lengths, size {@code (batch_size)}. * @param options carries optional attribute values @@ -675,7 +656,6 @@ public CtcGreedyDecoder ctcGreedyDecoder(Operand input * the gradient. This class performs the softmax operation for you, so inputs * should be e.g. linear projections of outputs by an LSTM. * - * @param data type for {@code loss} output * @param inputs 3-D, shape: {@code (max_time x batch_size x num_classes)}, the logits. * @param labelsIndices The indices of a {@code SparseTensor}. * {@code labels_indices(i, :) == [b, t]} means {@code labels_values(i)} stores the id for @@ -730,7 +710,6 @@ public CtcLoss ctcLoss(Operand inputs, Operand * reserve_space: An opaque tensor that can be used in backprop calculation. It * is only produced if is_training is true. * - * @param data type for {@code output} output * @param input The input value * @param inputH The inputH value * @param inputC The inputC value @@ -795,7 +774,6 @@ public CudnnRNN cudnnRNN(Operand input, Operand inp * params_backprop: The backprop to the params buffer in the forward pass. Has the * same shape as params. * - * @param data type for {@code input_backprop} output * @param input The input value * @param inputH The inputH value * @param inputC The inputC value @@ -852,7 +830,6 @@ public CudnnRNNBackprop cudnnRNNBackprop(Operand input * num_proj: The output dimensionality for the projection matrices. If None or 0, * no projection is performed. * - * @param data type for {@code params} output * @param numLayers The numLayers value * @param numUnits The numUnits value * @param inputSize The inputSize value @@ -900,7 +877,6 @@ public CudnnRNNCanonicalToParams cudnnRNNCanonicalToParam * num_proj: The output dimensionality for the projection matrices. If None or 0, * no projection is performed. * - * @param data type for {@code weights} output * @param numLayers The numLayers value * @param numUnits The numUnits value * @param inputSize The inputSize value @@ -941,7 +917,6 @@ public CudnnRNNParamsToCanonical cudnnRNNParamsToCanonica * CudnnRNNParamsBiases to save and restore them in a way that is compatible * across different runs. * - * @param data type for {@code params_size} output * @param numLayers The numLayers value * @param numUnits The numUnits value * @param inputSize The inputSize value @@ -962,7 +937,6 @@ public CudnnRnnParamsSize cudnnRnnPara * Returns the dimension index in the destination data format given the one in * the source data format. * - * @param data type for {@code y} output * @param x A Tensor with each element as a dimension index in source data format. * Must be in the range [-4, 4). * @param options carries optional attribute values @@ -1006,7 +980,6 @@ public DataFormatDimMap dataFormatDimMap(Operand x, * [1, 2] * * - * @param data type for {@code y} output * @param x Tensor of rank 1 or 2 in source data format. * @param options carries optional attribute values * @param data type for {@code DataFormatVecPermute} output and operands @@ -1094,7 +1067,6 @@ public DataFormatVecPermute dataFormatVecPermute(Operand< * * * - * @param data type for {@code output} output * @param input The input value * @param blockSize The size of the spatial block, same as in Space2Depth. * @param options carries optional attribute values @@ -1125,7 +1097,6 @@ public DepthToSpace depthToSpace(Operand input, Long blo *

Must have {@code strides[0] = strides[3] = 1}. For the most common case of the same * horizontal and vertices strides, {@code strides = [1, stride, stride, 1]}. * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param strides 1-D of length 4. The stride of the sliding window for each dimension @@ -1144,7 +1115,6 @@ public DepthwiseConv2dNative depthwiseConv2dNative(Operan /** * Computes the gradients of depthwise convolution with respect to the filter. * - * @param data type for {@code output} output * @param input 4-D with shape based on {@code data_format}. For example, if * {@code data_format} is 'NHWC' then {@code input} is a 4-D {@code [batch, in_height, in_width, in_channels]} tensor. * @param filterSizes An integer vector representing the tensor shape of {@code filter}, @@ -1170,7 +1140,6 @@ public DepthwiseConv2dNativeBackpropFilter depthwiseConv2 /** * Computes the gradients of depthwise convolution with respect to the input. * - * @param data type for {@code output} output * @param inputSizes An integer vector representing the shape of {@code input}, based * on {@code data_format}. For example, if {@code data_format} is 'NHWC' then * {@code input} is a 4-D {@code [batch, height, width, channels]} tensor. @@ -1217,7 +1186,6 @@ public DepthwiseConv2dNativeBackpropInput depthwiseConv2d *

Note on duality: The dilation of {@code input} by the {@code filter} is equal to the * negation of the erosion of {@code -input} by the reflected {@code filter}. * - * @param data type for {@code output} output * @param input 4-D with shape {@code [batch, in_height, in_width, depth]}. * @param filter 3-D with shape {@code [filter_height, filter_width, depth]}. * @param strides The stride of the sliding window for each dimension of the input @@ -1236,7 +1204,6 @@ public Dilation2d dilation2d(Operand input, Operand /** * Computes the gradient of morphological 2-D dilation with respect to the filter. * - * @param data type for {@code filter_backprop} output * @param input 4-D with shape {@code [batch, in_height, in_width, depth]}. * @param filter 3-D with shape {@code [filter_height, filter_width, depth]}. * @param outBackprop 4-D with shape {@code [batch, out_height, out_width, depth]}. @@ -1257,7 +1224,6 @@ public Dilation2dBackpropFilter dilation2dBackpropFilter( /** * Computes the gradient of morphological 2-D dilation with respect to the input. * - * @param data type for {@code in_backprop} output * @param input 4-D with shape {@code [batch, in_height, in_width, depth]}. * @param filter 3-D with shape {@code [filter_height, filter_width, depth]}. * @param outBackprop 4-D with shape {@code [batch, out_height, out_width, depth]}. @@ -1298,7 +1264,6 @@ public Dilation2dBackpropInput dilation2dBackpropInput(Op *

See Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) * * - * @param data type for {@code activations} output * @param features The features value * @param data type for {@code Elu} output and operands * @return a new instance of Elu @@ -1310,7 +1275,6 @@ public Elu elu(Operand features) { /** * Computes gradients for the exponential linear (Elu) operation. * - * @param data type for {@code backprops} output * @param gradients The backpropagated gradients to the corresponding Elu operation. * @param outputs The outputs of the corresponding Elu operation. * @param data type for {@code EluGrad} output and operands @@ -1358,7 +1322,6 @@ public FixedUnigramCandidateSampler fixedUnigramCandidateSampler(Operand * generated, a mean operation is performed instead of a max operation in each * pooling region. * - * @param data type for {@code output} output * @param value 4-D with shape {@code [batch, height, width, channels]}. * @param poolingRatio Pooling ratio for each dimension of {@code value}, currently only * supports row and col dimension and should be >= 1.0. For example, a valid @@ -1383,7 +1346,6 @@ public FractionalAvgPool fractionalAvgPool(Operand val * just need to know the shape of original input tensor, instead of the whole * tensor. * - * @param data type for {@code output} output * @param origInputTensorShape Original input tensor shape for {@code fractional_avg_pool} * @param outBackprop 4-D with shape {@code [batch, height, width, channels]}. Gradients * w.r.t. the output of {@code fractional_avg_pool}. @@ -1431,7 +1393,6 @@ public FractionalAvgPoolGrad fractionalAvgPoolGrad( *

For more details on fractional max pooling, see this paper: * Benjamin Graham, Fractional Max-Pooling * - * @param data type for {@code output} output * @param value 4-D with shape {@code [batch, height, width, channels]}. * @param poolingRatio Pooling ratio for each dimension of {@code value}, currently only * supports row and col dimension and should be >= 1.0. For example, a valid @@ -1451,7 +1412,6 @@ public FractionalMaxPool fractionalMaxPool(Operand val /** * Computes gradient of the FractionalMaxPool function. * - * @param data type for {@code output} output * @param origInput Original input for {@code fractional_max_pool} * @param origOutput Original output for {@code fractional_max_pool} * @param outBackprop 4-D with shape {@code [batch, height, width, channels]}. Gradients @@ -1475,8 +1435,6 @@ public FractionalMaxPoolGrad fractionalMaxPoolGrad(Operan * Note that the size of 4D Tensors are defined by either "NHWC" or "NCHW". * The size of 1D Tensors matches the dimension C of the 4D Tensors. * - * @param data type for {@code y} output - * @param data type for {@code batch_mean} output * @param x A 4D Tensor for input data. * @param scale A 1D Tensor for scaling factor, to scale the normalized x. * @param offset A 1D Tensor for offset, to shift to the normalized x. @@ -1500,8 +1458,6 @@ public FusedBatchNorm fusedBatchNor * Note that the size of 4D Tensors are defined by either "NHWC" or "NCHW". * The size of 1D Tensors matches the dimension C of the 4D Tensors. * - * @param data type for {@code x_backprop} output - * @param data type for {@code scale_backprop} output * @param yBackprop A 4D Tensor for the gradient with respect to y. * @param x A 4D Tensor for input data. * @param scale A 1D Tensor for scaling factor, to scale the normalized x. @@ -1542,7 +1498,6 @@ public FusedBatchNormGrad fusedBatc * will block if multiple versions are being run in parallel. This is because this * operator is primarily an optimization to minimize memory usage. * - * @param data type for {@code output} output * @param input 4-D with shape {@code [batch, in_height, in_width, in_channels]}. * @param paddings A two-column matrix specifying the padding sizes. The number of * rows must be the same as the rank of {@code input}. @@ -1574,7 +1529,6 @@ public FusedPadConv2d fusedPadConv2d(Operand input, * will block if multiple versions are being run in parallel. This is because this * operator is primarily an optimization to minimize memory usage. * - * @param data type for {@code output} output * @param input 4-D with shape {@code [batch, in_height, in_width, in_channels]}. * @param sizeOutput A 1-D int32 Tensor of 2 elements: {@code new_height, new_width}. The * new size for the images. @@ -1637,7 +1591,6 @@ public FusedResizeAndPadConv2d fusedResizeAndPadConv2d(Op * h = (1-u) \circ c + u \circ h_prev * * - * @param data type for {@code r} output * @param x The x value * @param hPrev The hPrev value * @param wRu The wRu value @@ -1728,7 +1681,6 @@ public GRUBlockCell gRUBlockCell(Operand x, Operand * d_b_c = sum of d_c_bar along axis = 0 * * - * @param data type for {@code d_x} output * @param x The x value * @param hPrev The hPrev value * @param wRu The wRu value @@ -1778,7 +1730,6 @@ public InTopK inTopK(Operand predictions, Operand< * Specifically, {@code grad = -dy * y*y}, where {@code y = 1/x}, and {@code dy} * is the corresponding input gradient. * - * @param data type for {@code z} output * @param y The y value * @param dy The dy value * @param data type for {@code InvGrad} output and operands @@ -1791,7 +1742,6 @@ public InvGrad invGrad(Operand y, Operand dy) { /** * Solves a batch of isotonic regression problems. * - * @param data type for {@code output} output * @param input A (batch_size, dim)-tensor holding a batch of inputs. * @return a new instance of IsotonicRegression, with default output types */ @@ -1802,7 +1752,6 @@ public IsotonicRegression isotonicRegression(Operand data type for {@code output} output * @param input A (batch_size, dim)-tensor holding a batch of inputs. * @param outputDtype Dtype of output. * @param data type for {@code IsotonicRegression} output and operands @@ -1820,7 +1769,6 @@ public IsotonicRegression isotonicRegression( * output = sum(t ** 2) / 2 * * - * @param data type for {@code output} output * @param t Typically 2-D, but may have any dimensions. * @param data type for {@code L2Loss} output and operands * @return a new instance of L2Loss @@ -1854,7 +1802,6 @@ public L2Loss l2Loss(Operand t) { * h = co .* o * * - * @param data type for {@code i} output * @param x The input to the LSTM cell, shape (batch_size, num_inputs). * @param csPrev Value of the cell state at previous time step. * @param hPrev Output of the previous cell at previous time step. @@ -1877,7 +1824,6 @@ public LSTMBlockCell lSTMBlockCell(Operand x, Operand< * Computes the LSTM cell backward propagation for 1 timestep. * This implementation is to be used in conjunction of LSTMBlockCell. * - * @param data type for {@code cs_prev_grad} output * @param x The input to the LSTM cell, shape (batch_size, num_inputs). * @param csPrev The previous cell state. * @param hPrev The previous h state. @@ -1908,7 +1854,6 @@ public LSTMBlockCellGrad lSTMBlockCellGrad(Operand x, /** * Computes rectified linear: {@code max(features, features * alpha)}. * - * @param data type for {@code activations} output * @param features The features value * @param options carries optional attribute values * @param data type for {@code LeakyRelu} output and operands @@ -1960,7 +1905,6 @@ public LearnedUnigramCandidateSampler learnedUnigramCandidateSampler(OperandFor details, see Krizhevsky et al., ImageNet classification with deep * convolutional neural networks (NIPS 2012) . * - * @param data type for {@code output} output * @param input 4-D. * @param options carries optional attribute values * @param data type for {@code LRN} output and operands @@ -1974,7 +1918,6 @@ public LocalResponseNormalization localResponseNormalizat /** * Gradients for Local Response Normalization. * - * @param data type for {@code output} output * @param inputGrads 4-D with shape {@code [batch, height, width, channels]}. * @param inputImage 4-D with shape {@code [batch, height, width, channels]}. * @param outputImage 4-D with shape {@code [batch, height, width, channels]}. @@ -1995,7 +1938,6 @@ public LocalResponseNormalizationGrad localResponseNormal * logsoftmax[i, j] = logits[i, j] - log(sum(exp(logits[i]))) * * - * @param data type for {@code logsoftmax} output * @param logits 2-D with shape {@code [batch_size, num_classes]}. * @param data type for {@code LogSoftmax} output and operands * @return a new instance of LogSoftmax @@ -2007,7 +1949,6 @@ public LogSoftmax logSoftmax(Operand logits) { /** * Performs max pooling on the input. * - * @param data type for {@code output} output * @param input 4-D input to pool over. * @param ksize The size of the window for each dimension of the input tensor. * @param strides The stride of the sliding window for each dimension of the @@ -2025,7 +1966,6 @@ public MaxPool maxPool(Operand input, Operand /** * Performs 3D max pooling on the input. * - * @param data type for {@code output} output * @param input Shape {@code [batch, depth, rows, cols, channels]} tensor to pool over. * @param ksize 1-D tensor of length 5. The size of the window for each dimension of * the input tensor. Must have {@code ksize[0] = ksize[4] = 1}. @@ -2044,7 +1984,6 @@ public MaxPool3d maxPool3d(Operand input, List k /** * Computes gradients of 3D max pooling function. * - * @param data type for {@code output} output * @param origInput The original input tensor. * @param origOutput The original output tensor. * @param grad Output backprop of shape {@code [batch, depth, rows, cols, channels]}. @@ -2067,7 +2006,6 @@ public MaxPool3dGrad maxPool3dGrad(Ope /** * Computes second-order gradients of the maxpooling function. * - * @param data type for {@code output} output * @param origInput The original input tensor. * @param origOutput The original output tensor. * @param grad Output backprop of shape {@code [batch, depth, rows, cols, channels]}. @@ -2089,7 +2027,6 @@ public MaxPool3dGradGrad maxPool3dGradGrad(Operand ori /** * Computes gradients of the maxpooling function. * - * @param data type for {@code output} output * @param origInput The original input tensor. * @param origOutput The original output tensor. * @param grad 4-D. Gradients w.r.t. the output of {@code max_pool}. @@ -2110,7 +2047,6 @@ public MaxPoolGrad maxPoolGrad(Operand origInput, Oper /** * Computes second-order gradients of the maxpooling function. * - * @param data type for {@code output} output * @param origInput The original input tensor. * @param origOutput The original output tensor. * @param grad 4-D. Gradients of gradients w.r.t. the input of {@code max_pool}. @@ -2131,7 +2067,6 @@ public MaxPoolGradGrad maxPoolGradGrad(Operand origInp /** * Computes second-order gradients of the maxpooling function. * - * @param data type for {@code output} output * @param input The original input. * @param grad 4-D with shape {@code [batch, height, width, channels]}. Gradients w.r.t. the * input of {@code max_pool}. @@ -2153,7 +2088,6 @@ public MaxPoolGradGradWithArgmax maxPoolGradGradWithArgma /** * Computes gradients of the maxpooling function. * - * @param data type for {@code output} output * @param input The original input. * @param grad 4-D with shape {@code [batch, height, width, channels]}. Gradients w.r.t. the * output of {@code max_pool}. @@ -2183,8 +2117,6 @@ public MaxPoolGradWithArgmax maxPoolGradWithArgmax(Operan * (either negative or too large). This is a bug, but fixing it is difficult to do * in a safe backwards compatible way, especially due to flattening. * - * @param data type for {@code output} output - * @param data type for {@code argmax} output * @param input 4-D with shape {@code [batch, height, width, channels]}. Input to pool over. * @param ksize The size of the window for each dimension of the input tensor. * @param strides The stride of the sliding window for each dimension of the @@ -2210,8 +2142,6 @@ public MaxPoolWithArgmax maxPoolWithArgmax(Operan * (either negative or too large). This is a bug, but fixing it is difficult to do * in a safe backwards compatible way, especially due to flattening. * - * @param data type for {@code output} output - * @param data type for {@code argmax} output * @param input 4-D with shape {@code [batch, height, width, channels]}. Input to pool over. * @param ksize The size of the window for each dimension of the input tensor. * @param strides The stride of the sliding window for each dimension of the @@ -2239,7 +2169,6 @@ public MaxPoolWithArgmax maxPoolWit * values.shape = input.shape[:-1] * * - * @param data type for {@code values} output * @param input 1-D or higher with last dimension at least {@code n+1}. * @param n 0-D. Position of sorted vector to select along the last dimension (along * each row for matrices). Valid range of n is {@code [0, input.shape[:-1])} @@ -2255,7 +2184,6 @@ public NthElement nthElement(Operand input, Operand data type for {@code output} output * @param input 4-D with shape {@code [batch, height, width, channels]}. * @param minInput The float value that the lowest quantized input value represents. * @param maxInput The float value that the highest quantized input value represents. @@ -2278,7 +2206,6 @@ public QuantizedAvgPool quantizedAvgPool(Operand input * This op is deprecated and will be removed in the future. Prefer * {@code tf.nn.batch_normalization}. * - * @param data type for {@code result} output * @param t A 4D input Tensor. * @param tMin The value represented by the lowest quantized input. * @param tMax The value represented by the highest quantized input. @@ -2322,7 +2249,6 @@ public QuantizedBatchNormWithGlobalNormal * Adds Tensor 'bias' to Tensor 'input' for Quantized types. * Broadcasts the values of bias on dimensions 0..N-2 of 'input'. * - * @param data type for {@code output} output * @param input The input value * @param bias A 1D bias Tensor with size matching the last dimension of 'input'. * @param minInput The float value that the lowest quantized input value represents. @@ -2342,7 +2268,6 @@ public QuantizedBiasAdd quantizedBiasAdd(Operand data type for {@code output} output * @param input The input value * @param filter The filter value * @param minInput The minInput value @@ -2367,7 +2292,6 @@ public QuantizedConv2DAndRelu quantizedConv2DAndRelu( /** * The QuantizedConv2DAndReluAndRequantize operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param minInput The minInput value @@ -2395,7 +2319,6 @@ public QuantizedConv2DAndReluAndRequantize quantizedConv2 /** * The QuantizedConv2DAndRequantize operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param minInput The minInput value @@ -2423,7 +2346,6 @@ public QuantizedConv2DAndRequantize quantizedConv2DAndReq /** * Computes QuantizedConv2D per channel. * - * @param data type for {@code output} output * @param input The original input tensor. * @param filter The original filter tensor. * @param minInput The minimum value of the input tensor @@ -2448,7 +2370,6 @@ public QuantizedConv2DPerChannel quantizedConv2DPerChanne /** * The QuantizedConv2DWithBias operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param bias The bias value @@ -2474,7 +2395,6 @@ public QuantizedConv2DWithBias quantizedConv2DWithBias( /** * The QuantizedConv2DWithBiasAndRelu operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param bias The bias value @@ -2500,7 +2420,6 @@ public QuantizedConv2DWithBiasAndRelu quantizedConv2DWith /** * The QuantizedConv2DWithBiasAndReluAndRequantize operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param bias The bias value @@ -2529,7 +2448,6 @@ public QuantizedConv2DWithBiasAndReluAndRequantize quanti /** * The QuantizedConv2DWithBiasAndRequantize operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param bias The bias value @@ -2558,7 +2476,6 @@ public QuantizedConv2DWithBiasAndRequantize quantizedConv /** * The QuantizedConv2DWithBiasSignedSumAndReluAndRequantize operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param bias The bias value @@ -2592,7 +2509,6 @@ public QuantizedConv2DWithBiasSignedSumAndReluAndRequantize< /** * The QuantizedConv2DWithBiasSumAndRelu operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param bias The bias value @@ -2619,7 +2535,6 @@ public QuantizedConv2DWithBiasSumAndRelu quantizedConv2DW /** * The QuantizedConv2DWithBiasSumAndReluAndRequantize operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param bias The bias value @@ -2657,7 +2572,6 @@ public QuantizedConv2DWithBiasSumAndReluAndRequantize qua * This means that you can only interpret the quantized output in the same way, by * taking the returned minimum and maximum values into account. * - * @param data type for {@code output} output * @param input The input value * @param filter filter's input_depth dimension must match input's depth dimensions. * @param minInput The float value that the lowest quantized input value represents. @@ -2682,7 +2596,6 @@ public QuantizedConv2d quantizedConv2d(Operand data type for {@code output} output * @param input The original input tensor. * @param filter The original filter tensor. * @param minInput The float value that the minimum quantized input value represents. @@ -2707,7 +2620,6 @@ public QuantizedDepthwiseConv2D quantizedDepthwiseConv2D( /** * Computes quantized depthwise Conv2D with Bias. * - * @param data type for {@code output} output * @param input The original input tensor. * @param filter The original filter tensor. * @param bias The original bias tensor. @@ -2733,7 +2645,6 @@ public QuantizedDepthwiseConv2DWithBias quantizedDepthwis /** * Computes quantized depthwise Conv2D with Bias and Relu. * - * @param data type for {@code output} output * @param input The original input tensor. * @param filter The original filter tensor. * @param bias The original bias tensor. @@ -2759,7 +2670,6 @@ public QuantizedDepthwiseConv2DWithBiasAndRelu quantizedD /** * Computes quantized depthwise Conv2D with Bias, Relu and Requantize. * - * @param data type for {@code output} output * @param input The original input tensor. * @param filter The original filter tensor. * @param bias The original bias tensor. @@ -2788,7 +2698,6 @@ public QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize< /** * Quantized Instance normalization. * - * @param data type for {@code y} output * @param x A 4D input Tensor. * @param xMin The value represented by the lowest quantized input. * @param xMax The value represented by the highest quantized input. @@ -2804,7 +2713,6 @@ public QuantizedInstanceNorm quantizedInstanceNorm(Operan /** * Produces the max pool of the input tensor for quantized types. * - * @param data type for {@code output} output * @param input The 4D (batch x rows x cols x depth) Tensor to MaxReduce over. * @param minInput The float value that the lowest quantized input value represents. * @param maxInput The float value that the highest quantized input value represents. @@ -2825,7 +2733,6 @@ public QuantizedMaxPool quantizedMaxPool(Operand input /** * Computes Quantized Rectified Linear: {@code max(features, 0)} * - * @param data type for {@code activations} output * @param features The features value * @param minFeatures The float value that the lowest quantized value represents. * @param maxFeatures The float value that the highest quantized value represents. @@ -2841,7 +2748,6 @@ public QuantizedRelu quantizedRelu(Operand data type for {@code activations} output * @param features The features value * @param minFeatures The float value that the lowest quantized value represents. * @param maxFeatures The float value that the highest quantized value represents. @@ -2857,7 +2763,6 @@ public QuantizedRelu6 quantizedRelu6(Operand data type for {@code activations} output * @param features The features value * @param maxValue The maxValue value * @param minFeatures The float value that the lowest quantized value represents. @@ -2885,7 +2790,6 @@ public QuantizedReluX quantizedReluX(Operand * * - * @param data type for {@code activations} output * @param features The features value * @param data type for {@code Relu} output and operands * @return a new instance of Relu @@ -2897,7 +2801,6 @@ public Relu relu(Operand features) { /** * Computes rectified linear 6: {@code min(max(features, 0), 6)}. * - * @param data type for {@code activations} output * @param features The features value * @param data type for {@code Relu6} output and operands * @return a new instance of Relu6 @@ -2909,7 +2812,6 @@ public Relu6 relu6(Operand features) { /** * Computes rectified linear 6 gradients for a Relu6 operation. * - * @param data type for {@code backprops} output * @param gradients The backpropagated gradients to the corresponding Relu6 operation. * @param features The features passed as input to the corresponding Relu6 operation, or * its output; using either one produces the same result. @@ -2923,7 +2825,6 @@ public Relu6Grad relu6Grad(Operand gradients, Operand< /** * Computes rectified linear gradients for a Relu operation. * - * @param data type for {@code backprops} output * @param gradients The backpropagated gradients to the corresponding Relu operation. * @param features The features passed as input to the corresponding Relu operation, OR * the outputs of that operation (both work equivalently). @@ -2942,7 +2843,6 @@ public ReluGrad reluGrad(Operand gradients, Operand * For correct dropout, use {@code tf.contrib.nn.alpha_dropout}. *

See Self-Normalizing Neural Networks * - * @param data type for {@code activations} output * @param features The features value * @param data type for {@code Selu} output and operands * @return a new instance of Selu @@ -2954,7 +2854,6 @@ public Selu selu(Operand features) { /** * Computes gradients for the scaled exponential linear (Selu) operation. * - * @param data type for {@code backprops} output * @param gradients The backpropagated gradients to the corresponding Selu operation. * @param outputs The outputs of the corresponding Selu operation. * @param data type for {@code SeluGrad} output and operands @@ -2971,7 +2870,6 @@ public SeluGrad seluGrad(Operand gradients, Operand * $$softmax[i, j] = exp(logits[i, j]) / sum_j(exp(logits[i, j]))$$ * * - * @param data type for {@code softmax} output * @param logits 2-D with shape {@code [batch_size, num_classes]}. * @param data type for {@code Softmax} output and operands * @return a new instance of Softmax @@ -2984,7 +2882,6 @@ public Softmax softmax(Operand logits) { * Computes softmax cross entropy cost and gradients to backpropagate. * Inputs are the logits, not probabilities. * - * @param data type for {@code loss} output * @param features batch_size x num_classes matrix * @param labels batch_size x num_classes matrix * The caller must ensure that each batch of labels represents a valid @@ -3000,7 +2897,6 @@ public SoftmaxCrossEntropyWithLogits softmaxCrossEntropyW /** * Computes softsign: {@code features / (abs(features) + 1)}. * - * @param data type for {@code activations} output * @param features The features value * @param data type for {@code Softsign} output and operands * @return a new instance of Softsign @@ -3012,7 +2908,6 @@ public Softsign softsign(Operand features) { /** * Computes softsign gradients for a softsign operation. * - * @param data type for {@code backprops} output * @param gradients The backpropagated gradients to the corresponding softsign operation. * @param features The features passed as input to the corresponding softsign operation. * @param data type for {@code SoftsignGrad} output and operands @@ -3090,7 +2985,6 @@ public SoftsignGrad softsignGrad(Operand gradients, *

Among others, this operation is useful for reducing atrous convolution into * regular convolution. * - * @param data type for {@code output} output * @param input 4-D with shape {@code [batch, height, width, depth]}. * @param paddings 2-D tensor of non-negative integers with shape {@code [2, 2]}. It specifies * the padding of the input with zeros across the spatial dimensions as follows: @@ -3182,7 +3076,6 @@ public SpaceToBatch spaceToBatch(Operand input, * [13, 14, 15, 16]]]] * * - * @param data type for {@code output} output * @param input The input value * @param blockSize The size of the spatial block. * @param options carries optional attribute values @@ -3202,7 +3095,6 @@ public SpaceToDepth spaceToDepth(Operand input, Long blo * given row. *

Inputs are the logits, not probabilities. * - * @param data type for {@code loss} output * @param features batch_size x num_classes matrix * @param labels batch_size vector with values in [0, num_classes). * This is the label for the given minibatch entry. @@ -3226,8 +3118,6 @@ public SparseSoftmaxCrossEntropyWithLogits sparseSoftmaxC * *

If two elements are equal, the lower-index element appears first. * - * @param data type for {@code values} output - * @param data type for {@code indices} output * @param input 1-D or higher with last dimension at least {@code k}. * @param k 0-D. Number of top elements to look for along the last dimension (along each * row for matrices). @@ -3252,8 +3142,6 @@ public TopK topK(Operand input, Operand *

If two elements are equal, the lower-index element appears first. * - * @param data type for {@code values} output - * @param data type for {@code indices} output * @param input 1-D or higher with last dimension at least {@code k}. * @param k 0-D. Number of top elements to look for along the last dimension (along each * row for matrices). @@ -3287,7 +3175,6 @@ public TopK topK(Operand input, *

{@code output} is also quantized, using the same formula. * If {@code rhs} is per-tensor quantized, {@code output} must be also per-tensor quantized. * - * @param data type for {@code output} output * @param lhs Must be a quantized tensor, rank >= 3. * @param rhs Must be a quantized tensor, same rank as {@code lhs}. * @param lhsScales The float value(s) used as scale factors when quantizing the original data that {@code lhs} represents. @@ -3358,7 +3245,6 @@ public UniformQuantizedConvolution uni *

{@code rhs} must be quantized Tensor, where its data value is quantized using the formula: * quantized_data = clip(original_data / scale + zero_point, quantization_min_val, quantization_max_val). * - * @param data type for {@code output} output * @param lhs Must be a non-quantized Tensor of {@code Tlhs}, rank >= 3. * @param rhs Must be a quantized Tensor of {@code Trhs}, same rank as {@code lhs}. * @param rhsScales The float value(s) used as scale factors when quantizing the original data that {@code rhs} represents. diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java index 93a6a3eb05c..8483a4efb61 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java @@ -77,6 +77,7 @@ import org.tensorflow.op.core.BroadcastTo; import org.tensorflow.op.core.Bucketize; import org.tensorflow.op.core.Case; +import org.tensorflow.op.core.CheckPinned; import org.tensorflow.op.core.ClipByValue; import org.tensorflow.op.core.CompositeTensorVariantFromComponents; import org.tensorflow.op.core.CompositeTensorVariantToComponents; @@ -407,10 +408,10 @@ public final class Ops { public final CollectiveOps collective; - public final AudioOps audio; - public final DistributeOps distribute; + public final AudioOps audio; + public final SignalOps signal; public final TrainOps train; @@ -419,10 +420,10 @@ public final class Ops { public final SummaryOps summary; - public final ImageOps image; - public final RaggedOps ragged; + public final ImageOps image; + public final ShapeOps shape; public final IoOps io; @@ -450,14 +451,14 @@ public final class Ops { bitwise = new BitwiseOps(this); debugging = new DebuggingOps(this); collective = new CollectiveOps(this); - audio = new AudioOps(this); distribute = new DistributeOps(this); + audio = new AudioOps(this); signal = new SignalOps(this); train = new TrainOps(this); quantization = new QuantizationOps(this); summary = new SummaryOps(this); - image = new ImageOps(this); ragged = new RaggedOps(this); + image = new ImageOps(this); shape = new ShapeOps(this); io = new IoOps(this); dtypes = new DtypesOps(this); @@ -618,7 +619,6 @@ public Any any(Operand input, Operand axis, Any.Option * See https://arxiv.org/abs/2206.14286 for the algorithm details. * This op is only optimized on TPU currently. * - * @param data type for {@code values} output * @param input Array to search. Must be at least 1-D of the floating type * @param k Specifies the number of min/max-k. * @param options carries optional attribute values @@ -732,7 +732,6 @@ public AssertThat assertThat(Operand condition, Iterable> data * This operation outputs "ref" after the assignment is done. * This makes it easier to chain operations that need to use the reset value. * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. May be uninitialized. * @param value The value to be assigned to the variable. * @param options carries optional attribute values @@ -749,7 +748,6 @@ public Assign assign(Operand ref, Operand value, * This operation outputs "ref" after the update is done. * This makes it easier to chain operations that need to use the reset value. * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param value The value to be added to the variable. * @param options carries optional attribute values @@ -780,7 +778,6 @@ public AssignAddVariableOp assignAddVariableOp(Operand resource * This operation outputs "ref" after the update is done. * This makes it easier to chain operations that need to use the reset value. * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param value The value to be subtracted to the variable. * @param options carries optional attribute values @@ -1027,7 +1024,6 @@ public BatchFunction batchFunction(Iterable> inTensors, * dimension are moved in spatial blocks to the {@code height} and {@code width} dimensions, * followed by cropping along the {@code height} and {@code width} dimensions. * - * @param data type for {@code output} output * @param input 4-D tensor with shape * {@code [batch*block_size*block_size, height_pad/block_size, width_pad/block_size, depth]}. Note that the batch size of the input tensor must be divisible by * {@code block_size * block_size}. @@ -1055,7 +1051,6 @@ public BatchToSpace batchToSpace(Operand input, * optionally cropped according to {@code crops} to produce the output. This is the * reverse of SpaceToBatch. See below for a precise description. * - * @param data type for {@code output} output * @param input N-D with shape {@code input_shape = [batch] + spatial_shape + remaining_shape}, * where spatial_shape has M dimensions. * @param blockShape 1-D with shape {@code [M]}, all values must be >= 1. @@ -1221,7 +1216,6 @@ public BatchToSpaceNd batchToSpaceNd(Operand input, * buffer is made on BE machines when types are of different sizes in order to get * the same casting results as on LE machines. * - * @param data type for {@code output} output * @param input The input value * @param type The value of the type attribute * @param data type for {@code Bitcast} output and operands @@ -1292,7 +1286,6 @@ public Operand booleanMaskUpdate(Operand tensor, Operand * Given {@code s0} and {@code s1}, tensors that represent shapes, compute {@code r0}, the * broadcasted shape. {@code s0}, {@code s1} and {@code r0} are all integer vectors. * - * @param data type for {@code r0} output * @param s0 The s0 value * @param s1 The s1 value * @param data type for {@code BroadcastArgs} output and operands @@ -1307,7 +1300,6 @@ public BroadcastDynamicShape broadcastDynamicShape(Operan * Return the reduction indices for computing gradients of s0 op s1 with broadcast. * This is typically used by gradient computations for a broadcasting operation. * - * @param data type for {@code r0} output * @param s0 The s0 value * @param s1 The s1 value * @param data type for {@code BroadcastGradientArgs} output and operands @@ -1357,7 +1349,6 @@ public BroadcastGradientArgs broadcastGradientArgs(Operan * shape. (In a graph context, {@code broadcast_to} might be fused to * subsequent operation and then be optimized away, however.) * - * @param data type for {@code output} output * @param input A Tensor to broadcast. * @param shape An 1-D {@code int} Tensor. The shape of the desired output. * @param data type for {@code BroadcastTo} output and operands @@ -1451,6 +1442,22 @@ public Case caseOp(Operand branchIndex, Iterable> input, return Case.create(scope, branchIndex, input, Tout, branches, options); } + /** + * Checks whether a tensor is located in host memory pinned for GPU. + * When run: + *

    + *
  • Reports an {@code InvalidArgument} error if {@code tensor} is not in pinned memory.
    • + *
  • Reports a {@code FailedPrecondition} error if not built with CUDA.
    • + *
+ * + * @param tensor The tensor value + * @param data type for {@code CheckPinned} output and operands + * @return a new instance of CheckPinned + */ + public CheckPinned checkPinned(Operand tensor) { + return CheckPinned.create(scope, tensor); + } + /** * Clips tensor values to a specified min and max. * Given a tensor {@code t}, this operation returns a tensor of the same type and @@ -1458,7 +1465,6 @@ public Case caseOp(Operand branchIndex, Iterable> input, * Any values less than {@code clip_value_min} are set to {@code clip_value_min}. Any values * greater than {@code clip_value_max} are set to {@code clip_value_max}. * - * @param data type for {@code output} output * @param t A {@code Tensor}. * @param clipValueMin A 0-D (scalar) {@code Tensor}, or a {@code Tensor} with the same shape * as {@code t}. The minimum value to clip by. @@ -1508,7 +1514,6 @@ public CompositeTensorVariantToComponents compositeTensorVariantToComponents( /** * Concatenates tensors along one dimension. * - * @param data type for {@code output} output * @param values List of {@code N} Tensors to concatenate. Their ranks and types must match, * and their sizes must match in all dimensions except {@code concat_dim}. * @param axis 0-D. The dimension along which to concatenate. Must be in the @@ -1531,14 +1536,13 @@ public Concat concat(Iterable> values, * y = [2, 3, 7] * z = [2, 9, 7] * offsets = concat_offset(1, [x, y, z]) - * [list(off.numpy()) for off in offsets] + * [[a.item() for a in list(off.numpy())] for off in offsets] * [[0, 0, 0], [0, 2, 0], [0, 5, 0]] * * * *

This is typically used by gradient computations for a concat operation. * - * @param data type for {@code offset} output * @param concatDim The dimension along which to concatenate. * @param shape The {@code N} int32 or int64 vectors representing shape of tensors being concatenated. * @param data type for {@code ConcatOffset} output and operands @@ -2262,11 +2266,7 @@ public Constant constant(Class type, Shape shape, ByteDa /** * Create a constant by making an immutable copy of {@code tensor}. {@code tensor} may be closed - * afterwards without issue. - * - *

Note: this endpoint cannot be simply called {@code constant} since it will conflict with - * other endpoints accepting an NdArray in parameter {e.g. {@link #tensorOf(Scope, - * FloatNdArray)}}. + * afterward without issue. * * @param tensor a Tensor holding the constant value * @return a constant of the same data type as `tensor` @@ -2318,7 +2318,6 @@ public ControlTrigger controlTrigger() { /** * The CopyToMesh operation * - * @param data type for {@code output} output * @param input The input value * @param mesh The value of the mesh attribute * @param data type for {@code CopyToMesh} output and operands @@ -2331,7 +2330,6 @@ public CopyToMesh copyToMesh(Operand input, String mesh) /** * The CopyToMeshGrad operation * - * @param data type for {@code output} output * @param input The input value * @param forwardInput The forwardInput value * @param data type for {@code CopyToMeshGrad} output and operands @@ -2345,7 +2343,6 @@ public CopyToMeshGrad copyToMeshGrad(Operand input, /** * Increments 'ref' until it reaches 'limit'. * - * @param data type for {@code output} output * @param ref Should be from a scalar {@code Variable} node. * @param limit If incrementing ref would bring it above limit, instead generates an * 'OutOfRange' error. @@ -2440,7 +2437,6 @@ public DecodeProto decodeProto(Operand bytes, String messageType, /** * Makes a copy of {@code x}. * - * @param data type for {@code y} output * @param x The source tensor of type {@code T}. * @param data type for {@code DeepCopy} output and operands * @return a new instance of DeepCopy @@ -2482,7 +2478,6 @@ public DestroyResourceOp destroyResourceOp(Operand resource, * using control dependencies. *

Outputs the final value of the tensor pointed to by 'ref'. * - * @param data type for {@code value} output * @param ref A reference to the temporary variable tensor. * @param varName Name of the temporary variable, usually the name of the matching * 'TemporaryVariable' op. @@ -2560,7 +2555,6 @@ public DummyMemoryCache dummyMemoryCache() { * * * - * @param data type for {@code outputs} output * @param data The data value * @param partitions Any shape. Indices in the range {@code [0, num_partitions)}. * @param numPartitions The number of partitions to output. @@ -2628,7 +2622,6 @@ public DynamicPartition dynamicPartition(Operand data, * * * - * @param data type for {@code merged} output * @param indices The indices value * @param data The data value * @param data type for {@code DynamicStitch} output and operands @@ -2672,7 +2665,6 @@ public EditDistance editDistance(Operand hypothesisInd * Creates a tensor with the given shape. *

This operation creates a tensor of {@code shape} and {@code dtype}. * - * @param data type for {@code output} output * @param shape 1-D. Represents the shape of the output tensor. * @param dtype The value of the dtype attribute * @param options carries optional attribute values @@ -2778,7 +2770,6 @@ public EncodeProto encodeProto(Operand sizes, Iterable> value * Raises an error if the input tensor's shape does not match the specified shape. * Returns the input tensor otherwise. * - * @param data type for {@code output} output * @param input A tensor, whose shape is to be validated. * @param shape The expected (possibly partially specified) shape of the input tensor. * @param data type for {@code EnsureShape} output and operands @@ -2796,7 +2787,6 @@ public EnsureShape ensureShape(Operand input, Shape shap * it may be changed in the child frame. At most {@code parallel_iterations} iterations * are run in parallel in the child frame. * - * @param data type for {@code output} output * @param data The tensor to be made available to the child frame. * @param frameName The name of the child frame. * @param options carries optional attribute values @@ -2812,7 +2802,6 @@ public Enter enter(Operand data, String frameName, * Exits the current frame to its parent frame. * Exit makes its input {@code data} available to the parent frame. * - * @param data type for {@code output} output * @param data The tensor to be made available to the parent frame. * @param data type for {@code Exit} output and operands * @return a new instance of Exit @@ -2847,7 +2836,6 @@ public Exit exit(Operand data) { *

This operation is related to {@code squeeze()}, which removes dimensions of * size 1. * - * @param data type for {@code output} output * @param input The input value * @param axis 0-D (scalar). Specifies the dimension index at which to * expand the shape of {@code input}. Must be in the range @@ -2863,7 +2851,6 @@ public ExpandDims expandDims(Operand input, /** * Extract {@code patches} from {@code input} and put them in the {@code "depth"} output dimension. 3D extension of {@code extract_image_patches}. * - * @param data type for {@code patches} output * @param input 5-D Tensor with shape {@code [batch, in_planes, in_rows, in_cols, depth]}. * @param ksizes The size of the sliding window for each dimension of {@code input}. * @param strides 1-D of length 5. How far the centers of two consecutive patches are in @@ -2888,7 +2875,6 @@ public ExtractVolumePatches extractVolumePatches(Operand< * function input) or guaranteed not to be used (e.g. if mirroring an * intermediate output needed for the gradient computation of the other branch). * - * @param data type for {@code output} output * @param dtype The type of the output. * @param shape 

    *  The purported shape of the output. This is only used for shape inference;
@@ -2934,7 +2920,6 @@ public FileSystemSetConfiguration fileSystemSetConfiguration(Operand sc
    *  based on other runtime Tensors, unlike {@code tf.constant}.
    *  
    *
-   * @param  data type for {@code output} output
    * @param dims 1-D. Represents the shape of the output tensor.
    * @param value 0-D (scalar). Value to fill the returned tensor.
    *  
{@literal @}compatibility(numpy)

@@ -3028,9 +3013,11 @@ public For forOp(Operand start, Operand limit, Operand d
    *  
Note that on CPU, if an out of bound index is found, an error is returned.
    *  On GPU, if an out of bound index is found, a 0 is stored in the
    *  corresponding output value.
+   *  
Note that on TPU, if any dimension of {@code params} is of size 0 then the output will
+   *  be the expected shape filled with zeros. On CPU and GPU an error will be
+   *  returned.
    *  
See also {@code tf.batch_gather} and {@code tf.gather_nd}.
    *
-   * @param  data type for {@code output} output
    * @param params The tensor from which to gather values. Must be at least rank
    *  {@code axis + 1}.
    * @param indices Index tensor. Must be in range {@code [0, params.shape[axis])}.
@@ -3068,9 +3055,17 @@ public  Gather gather(Operand params, Operand
    *  indices.shape[:-1] + params.shape[indices.shape[-1]:]
    *
- *

Note that on CPU, if an out of bound index is found, an error is returned. - * On GPU, if an out of bound index is found, a 0 is stored in the - * corresponding output value. + *

If {@code indices} contains any out-of-bound indices, depending on + * {@code bad_indices_policy}, the op will either return an error or ignore the + * out-of-bound indices. {@code bad_indices_policy} can be one of the following values: + *

    + *
  1. "" or "DEFAULT": raises on CPU and ignore on GPU. This is because + * historically on CPU and GPU we handle errors in different ways, and for + * backward compatibility we keep the default behavior.
    2. + *
  2. "ERROR": raises error; GPU does not support this value.
    3. + *
  3. "IGNORE": ignore error and set the corresponding output to 0; + * supported on both CPU and GPU.
    4. + *
*

Some examples below. *

Simple indexing into a matrix: * 

@@ -3137,15 +3132,15 @@ public  Gather gather(Operand params, Operand
    *  
See also {@code tf.gather} and {@code tf.batch_gather}.
    *
-   * @param  data type for {@code output} output
    * @param params The tensor from which to gather values.
    * @param indices Index tensor.
+   * @param options carries optional attribute values
    * @param  data type for {@code GatherNd} output and operands
    * @return a new instance of GatherNd
    */
   public  GatherNd gatherNd(Operand params,
-      Operand indices) {
-    return GatherNd.create(scope, params, indices);
+      Operand indices, GatherNd.Options... options) {
+    return GatherNd.create(scope, params, indices, options);
   }
 
   /**
@@ -3185,7 +3180,6 @@ public GetSessionHandle getSessionHandle(Operand value) {
   /**
    * Get the value of the tensor specified by its handle.
    *
-   * @param  data type for {@code value} output
    * @param handle The handle for a tensor stored in the session state.
    * @param dtype The type of the output value.
    * @param  data type for {@code GetSessionTensor} output and operands
@@ -3250,7 +3244,6 @@ public Gradients gradients(Iterable> y, IterableReturns the input tensor without modification.
    *
-   * @param  data type for {@code output} output
    * @param input The input value
    * @param  data type for {@code GuaranteeConst} output and operands
    * @return a new instance of GuaranteeConst
@@ -3294,7 +3287,6 @@ public  HashTable hashTable(Class keyDtype,
    *    sess.run(hist) => [2, 1, 1, 0, 2]
    *
* - * @param data type for {@code out} output * @param values Numeric {@code Tensor}. * @param valueRange Shape [2] {@code Tensor} of same {@code dtype} as {@code values}. * values <= value_range[0] will be mapped to hist[0], @@ -3325,7 +3317,6 @@ public HistogramFixedWidth histogramFixedWidth(Opera * sess.run(hist) => [2, 1, 1, 0, 2] * * - * @param data type for {@code out} output * @param values Numeric {@code Tensor}. * @param valueRange Shape [2] {@code Tensor} of same {@code dtype} as {@code values}. * values <= value_range[0] will be mapped to hist[0], @@ -3344,7 +3335,6 @@ public HistogramFixedWidth histogramFi /** * Returns a constant tensor on the host. Only for writing C++ tests. * - * @param data type for {@code output} output * @param value Attr {@code value} is the tensor to return. * @param dtype The value of the dtype attribute * @param data type for {@code HostConst} output and operands @@ -3357,7 +3347,6 @@ public HostConst hostConst(Tensor value, Class dtype) { /** * Return a tensor with the same shape and contents as the input tensor or value. * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code Identity} output and operands * @return a new instance of Identity @@ -3425,7 +3414,6 @@ public If ifOp(Operand cond, Iterable> input, * Returns immutable tensor from memory region. * The current implementation memmaps the tensor from a file. * - * @param data type for {@code tensor} output * @param dtype Type of the returned tensor. * @param shape Shape of the returned tensor. * @param memoryRegionName Name of readonly memory region used by the tensor, see @@ -3485,7 +3473,6 @@ public InitializeTableFromTextFile initializeTableFromTextFile( * Computes y = x; y[i, :] += v; return y. * * - * @param data type for {@code y} output * @param x A {@code Tensor} of type T. * @param i A vector. Indices into the left-most dimension of {@code x}. * @param v A {@code Tensor} of type T. Same dimension sizes as x except the first dimension, which must be the same as i's size. @@ -3503,7 +3490,6 @@ public InplaceAdd inplaceAdd(Operand x, Operand * Computes y = x; y[i, :] -= v; return y. * * - * @param data type for {@code y} output * @param x A {@code Tensor} of type T. * @param i A vector. Indices into the left-most dimension of {@code x}. * @param v A {@code Tensor} of type T. Same dimension sizes as x except the first dimension, which must be the same as i's size. @@ -3520,7 +3506,6 @@ public InplaceSub inplaceSub(Operand x, Operand *

Originally this function is mutative however for compilation we make this * operation create / operate on a copy of {@code x}. * - * @param data type for {@code y} output * @param x A tensor of type {@code T}. * @param i A vector. Indices into the left-most dimension of {@code x}. * @param v A {@code Tensor} of type T. Same dimension sizes as x except the first dimension, which must be the same as i's size. @@ -3578,7 +3563,6 @@ public KthOrderStatistic kthOrderStatistic(Operand input, Long k) { * tf.linspace(10.0, 12.0, 3, name="linspace") => [ 10.0 11.0 12.0] * * - * @param data type for {@code output} output * @param start 0-D tensor. First entry in the range. * @param stop 0-D tensor. Last entry in the range. * @param num 0-D tensor. Number of values to generate. @@ -3593,8 +3577,6 @@ public LinSpace linSpace(Operand start, Operand sto /** * Outputs all keys and values in the table. * - * @param data type for {@code keys} output - * @param data type for {@code values} output * @param tableHandle Handle to the table. * @param Tkeys The value of the Tkeys attribute * @param Tvalues The value of the Tvalues attribute @@ -3614,7 +3596,6 @@ public LookupTableExport lookupTableExp *

The scalar {@code default_value} is the value output for keys not present in the * table. It must also be of the same type as the table values. * - * @param data type for {@code values} output * @param tableHandle Handle to the table. * @param keys Any shape. Keys to look up. * @param defaultValue The defaultValue value @@ -3708,7 +3689,6 @@ public LoopCond loopCond(Operand input) { *

result == [[1, 2, 2], * [0, 1, 5]] * - * @param data type for {@code output} output * @param sortedInputs 2-D Tensor where each row is ordered. * @param values 2-D Tensor with the same numbers of rows as {@code sorted_search_values}. Contains * the values that will be searched for in {@code sorted_search_values}. @@ -3736,7 +3716,6 @@ public LowerBound lowerBound(Operand sortedInputs, *

result == [[1, 2, 2], * [0, 1, 5]] * - * @param data type for {@code output} output * @param sortedInputs 2-D Tensor where each row is ordered. * @param values 2-D Tensor with the same numbers of rows as {@code sorted_search_values}. Contains * the values that will be searched for in {@code sorted_search_values}. @@ -3901,7 +3880,6 @@ public MapUnstageNoKey mapUnstageNoKey(Operand indices, * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -3921,7 +3899,6 @@ public Max max(Operand input, Operand{@code Merge} forwards the first tensor to become available to {@code output}, and sets * {@code value_index} to its index in {@code inputs}. * - * @param data type for {@code output} output * @param inputs The input tensors, exactly one of which will become available. * @param data type for {@code Merge} output and operands * @return a new instance of Merge @@ -3937,7 +3914,6 @@ public Merge merge(Iterable> inputs) { * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -3974,7 +3950,6 @@ public Min min(Operand input, Operand * - * @param data type for {@code output} output * @param input The input tensor to be padded. * @param paddings A two-column matrix specifying the padding sizes. The number of * rows must be the same as the rank of {@code input}. @@ -4008,7 +3983,6 @@ public MirrorPad mirrorPad(Operand input, * [11, 28]] * * - * @param data type for {@code output} output * @param input The input tensor to be folded. * @param paddings A two-column matrix specifying the padding sizes. The number of * rows must be the same as the rank of {@code input}. @@ -4187,7 +4161,6 @@ public MutexLock mutexLock(Operand mutex) { * num_devices: The number of devices participating in this reduction. * shared_name: Identifier that shared between ops of the same reduction. * - * @param data type for {@code data} output * @deprecated use {@link org.tensorflow.op.distribute.NcclAllReduce} instead * @param input The input value * @param reduction The value of the reduction attribute @@ -4211,7 +4184,6 @@ public NcclAllReduce ncclAllReduce(Operand input, Stri * output: The same as input. * shape: The shape of the input tensor. * - * @param data type for {@code output} output * @deprecated use {@link org.tensorflow.op.distribute.NcclBroadcast} instead * @param input The input value * @param shape The value of the shape attribute @@ -4232,7 +4204,6 @@ public NcclBroadcast ncclBroadcast(Operand input, Shap * data: the value of the reduction across all {@code num_devices} devices. * reduction: the reduction operation to perform. * - * @param data type for {@code data} output * @deprecated use {@link org.tensorflow.op.distribute.NcclReduce} instead * @param input The input value * @param reduction The value of the reduction attribute @@ -4248,7 +4219,6 @@ public NcclReduce ncclReduce(Iterable> input, /** * Makes its input available to the next iteration. * - * @param data type for {@code output} output * @param data The tensor to be made available to the next iteration. * @param data type for {@code NextIteration} output and operands * @return a new instance of NextIteration @@ -4343,7 +4313,6 @@ public NoOp noOp() { * ] * * - * @param data type for {@code output} output * @param indices A tensor of indices. * @param depth A scalar defining the depth of the one hot dimension. * @param onValue A scalar defining the value to fill in output when {@code indices[j] = i}. @@ -4372,7 +4341,6 @@ public Ones ones(Operand dims, Class /** * Returns a tensor of ones with the same shape and type as x. * - * @param data type for {@code y} output * @param x a tensor of type T. * @param data type for {@code OnesLike} output and operands * @return a new instance of OnesLike @@ -4506,7 +4474,6 @@ public OrderedMapUnstageNoKey orderedMapUnstageNoKey(Operand indices, * [0, 0, 0, 0, 0, 0]] * * - * @param data type for {@code output} output * @param input The input value * @param paddings The paddings value * @param constantValues The constantValues value @@ -4534,7 +4501,6 @@ public Pad pad(Operand input, Operand * will copy pieces of the input into the output as they become available, in * some situations this can provide a performance benefit. * - * @param data type for {@code output} output * @param values Tensors to be concatenated. All must have size 1 in the first dimension * and same shape. * @param shape the final shape of the result; should be equal to the shapes of any input @@ -4602,7 +4568,6 @@ public ParallelConcat parallelConcat(Iterable> v * * * - * @param data type for {@code merged} output * @param indices The indices value * @param data The data value * @param data type for {@code ParallelDynamicStitch} output and operands @@ -4641,7 +4606,6 @@ public PartitionedCall partitionedCall(Iterable> args, * intended as a way to represent a value that will always be fed, and to * provide attrs that enable the fed value to be checked at runtime. * - * @param data type for {@code output} output * @param dtype The type of elements in the tensor. * @param options carries optional attribute values * @param data type for {@code Placeholder} output and operands @@ -4655,7 +4619,6 @@ public Placeholder placeholder(Class dtype, /** * A placeholder op that passes through {@code input} when its output is not fed. * - * @param data type for {@code output} output * @param input The default value to produce when {@code output} is not fed. * @param shape The (possibly partial) shape of the tensor. * @param data type for {@code PlaceholderWithDefault} output and operands @@ -4685,7 +4648,6 @@ public Print print(Operand input, Print.Options... options) { * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -4701,7 +4663,6 @@ public Prod prod(Operand input, Operand data type for {@code output} output * @param tensor The tensor value * @param shape Defines the shape of the output tensor. * @param inputMin The minimum value of the input. @@ -4721,7 +4682,6 @@ public QuantizedReshape quantizedReshape(Operand tensor, * first dimension must match. *

The outputs are deterministic. * - * @param data type for {@code output} output * @param index A scalar tensor or a vector of dtype {@code dtype}. The index (or indices) to be shuffled. Must be within [0, max_index]. * @param seed A tensor of dtype {@code Tseed} and shape [3] or [n, 3]. The random seed. * @param maxIndex A scalar tensor or vector of dtype {@code dtype}. The upper bound(s) of the interval (inclusive). @@ -4746,7 +4706,6 @@ public RandomIndexShuffle randomIndexShuffle(Operand i * tf.range(start, limit, delta) ==> [3, 6, 9, 12, 15] * * - * @param data type for {@code output} output * @param start 0-D (scalar). First entry in the sequence. * @param limit 0-D (scalar). Upper limit of sequence, exclusive. * @param delta 0-D (scalar). Optional. Default is 1. Number that increments {@code start}. @@ -4785,7 +4744,6 @@ public Rank rank(Operand input) { * influenced by any of the writes which depend directly or indirectly on this * operation. * - * @param data type for {@code value} output * @param resource handle to the resource in which to store the variable. * @param dtype the dtype of the value. * @param data type for {@code ReadVariableOp} output and operands @@ -4799,7 +4757,6 @@ public ReadVariableOp readVariableOp(Operand data type for {@code tensor} output * @param tensorType The value of the tensorType attribute * @param tensorName The name of the tensor to receive. * @param sendDevice The name of the device sending the tensor. @@ -4857,7 +4814,6 @@ public ReduceAny reduceAny(Operand input, Operand axis * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -4877,7 +4833,6 @@ public ReduceMax reduceMax(Operand input, * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -4897,7 +4852,6 @@ public ReduceMin reduceMin(Operand input, * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -4917,7 +4871,6 @@ public ReduceProd reduceProd(Operand input, * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -4937,7 +4890,6 @@ public ReduceSum reduceSum(Operand input, Operand data type for {@code output} output * @param data The tensor to be made available to the child frame. * @param frameName The name of the child frame. * @param options carries optional attribute values @@ -4953,7 +4905,6 @@ public RefEnter refEnter(Operand data, String frameName, * Exits the current frame to its parent frame. * Exit makes its input {@code data} available to the parent frame. * - * @param data type for {@code output} output * @param data The tensor to be made available to the parent frame. * @param data type for {@code RefExit} output and operands * @return a new instance of RefExit @@ -4965,7 +4916,6 @@ public RefExit refExit(Operand data) { /** * Return the same ref tensor as the input ref tensor. * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code RefIdentity} output and operands * @return a new instance of RefIdentity @@ -4981,7 +4931,6 @@ public RefIdentity refIdentity(Operand input) { *

{@code Merge} forwards the first tensor for become available to {@code output}, and sets * {@code value_index} to its index in {@code inputs}. * - * @param data type for {@code output} output * @param inputs The input tensors, exactly one of which will become available. * @param data type for {@code RefMerge} output and operands * @return a new instance of RefMerge @@ -4993,7 +4942,6 @@ public RefMerge refMerge(Iterable> inputs) { /** * Makes its input available to the next iteration. * - * @param data type for {@code output} output * @param data The tensor to be made available to the next iteration. * @param data type for {@code RefNextIteration} output and operands * @return a new instance of RefNextIteration @@ -5005,7 +4953,6 @@ public RefNextIteration refNextIteration(Operand data) { /** * Forwards the {@code index}th element of {@code inputs} to {@code output}. * - * @param data type for {@code output} output * @param index A scalar that determines the input that gets selected. * @param inputs A list of ref tensors, one of which will be forwarded to {@code output}. * @param data type for {@code RefSelect} output and operands @@ -5022,7 +4969,6 @@ public RefSelect refSelect(Operand index, * the data goes to {@code output_false}. *

See also {@code Switch} and {@code Merge}. * - * @param data type for {@code output_false} output * @param data The ref tensor to be forwarded to the appropriate output. * @param pred A scalar that specifies which output port will receive data. * @param data type for {@code RefSwitch} output and operands @@ -5035,7 +4981,6 @@ public RefSwitch refSwitch(Operand data, Operand /** * The Relayout operation * - * @param data type for {@code output} output * @param input The input value * @param layout The value of the layout attribute * @param data type for {@code Relayout} output and operands @@ -5048,7 +4993,6 @@ public Relayout relayout(Operand input, String layout) { /** * The RelayoutLike operation * - * @param data type for {@code output} output * @param input The input value * @param layoutInput The layoutInput value * @param data type for {@code RelayoutLike} output and operands @@ -5130,7 +5074,6 @@ public RemoteCall remoteCall(Operand target, Iterable> args, * reshape(t, []) ==> 7 * * - * @param data type for {@code output} output * @param tensor The tensor value * @param shape Defines the shape of the output tensor. * @param data type for {@code Reshape} output and operands @@ -5143,7 +5086,6 @@ public Reshape reshape(Operand tensor, Operand data type for {@code output} output * @param resource Should be from a scalar {@code Variable} node. * @param limit If incrementing ref would bring it above limit, instead generates an * 'OutOfRange' error. @@ -5171,7 +5113,6 @@ public ResourceCountUpTo resourceCountUpTo( * output[i, ..., j, :, ... :] = params[indices[i, ..., j], :, ..., :] * * - * @param data type for {@code output} output * @param resource The resource value * @param indices The indices value * @param dtype The value of the dtype attribute @@ -5187,7 +5128,6 @@ public ResourceGather resourceGather(Operand data type for {@code output} output * @param resource The resource value * @param indices The indices value * @param dtype The value of the dtype attribute @@ -5633,7 +5573,6 @@ public ResourceStridedSliceAssign resourceStridedSliceAssign * [12, 13, 14, 15]]]] * * - * @param data type for {@code output} output * @param tensor Up to 8-D. * @param axis 1-D. The indices of the dimensions to reverse. Must be in the range * {@code [-rank(tensor), rank(tensor))}. @@ -5695,7 +5634,6 @@ public Reverse reverse(Operand tensor, Operand * - * @param data type for {@code output} output * @param input The input to reverse. * @param seqLengths 1-D with length {@code input.dims(batch_dim)} and * {@code max(seq_lengths) <= input.dims(seq_dim)} @@ -5730,7 +5668,6 @@ public ReverseSequence reverseSequence(Operand input, * roll(t, shift=[2, -3], axis=[1, 1]) ==> [[1, 2, 3, 4, 0], [6, 7, 8, 9, 5]] * * - * @param data type for {@code output} output * @param input The input value * @param shift Dimension must be 0-D or 1-D. {@code shift[i]} specifies the number of places by which * elements are shifted positively (towards larger indices) along the dimension @@ -5770,7 +5707,6 @@ public Roll roll(Operand input, Operand * * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param indices A tensor of indices into the first dimension of {@code ref}. * @param updates A tensor of updated values to add to {@code ref}. @@ -5802,7 +5738,6 @@ public ScatterAdd scatterAdd(Operand ref, * the same location, their contributions divide. *

Requires {@code updates.shape = indices.shape + ref.shape[1:]} or {@code updates.shape = []}. * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param indices A tensor of indices into the first dimension of {@code ref}. * @param updates A tensor of values that {@code ref} is divided by. @@ -5837,7 +5772,6 @@ public ScatterDiv scatterDiv(Operand ref, * * * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param indices A tensor of indices into the first dimension of {@code ref}. * @param updates A tensor of updated values to reduce into {@code ref}. @@ -5872,7 +5806,6 @@ public ScatterMax scatterMax(Operand ref, * * * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param indices A tensor of indices into the first dimension of {@code ref}. * @param updates A tensor of updated values to reduce into {@code ref}. @@ -5904,7 +5837,6 @@ public ScatterMin scatterMin(Operand ref, * the same location, their contributions multiply. *

Requires {@code updates.shape = indices.shape + ref.shape[1:]} or {@code updates.shape = []}. * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param indices A tensor of indices into the first dimension of {@code ref}. * @param updates A tensor of updated values to multiply to {@code ref}. @@ -5990,20 +5922,28 @@ public ScatterMul scatterMul(Operand ref, * [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]], * [[5, 5, 5, 5], [6, 6, 6, 6], [7, 7, 7, 7], [8, 8, 8, 8]]] * - *

Note that on CPU, if an out of bound index is found, an error is returned. - * On GPU, if an out of bound index is found, the index is ignored. + *

If {@code indices} contains any out-of-bound indices, depending on + * {@code bad_indices_policy}, the op will either return an error or ignore the + * out-of-bound indices. {@code bad_indices_policy} can be one of the following values: + *

    + *
  1. "" or "DEFAULT": raises on CPU and ignore on GPU. This is because + * historically on CPU and GPU we handle errors in different ways, and for + * backward compatibility we keep the default behavior.
    2. + *
  2. "ERROR": raises error; GPU does not support this value.
    3. + *
  3. "IGNORE": ignore the bad indices; supported on both CPU and GPU.
    4. + *
* - * @param data type for {@code output} output * @param indices Tensor of indices. * @param updates Values to scatter into the output tensor. * @param shape 1-D. The shape of the output tensor. + * @param options carries optional attribute values * @param data type for {@code ScatterNd} output and operands * @param data type for {@code ScatterNd} output and operands * @return a new instance of ScatterNd */ public ScatterNd scatterNd(Operand indices, - Operand updates, Operand shape) { - return ScatterNd.create(scope, indices, updates, shape); + Operand updates, Operand shape, ScatterNd.Options... options) { + return ScatterNd.create(scope, indices, updates, shape, options); } /** @@ -6035,7 +5975,6 @@ public ScatterNd scatterNd(Operand in *

See {@code tf.scatter_nd} for more details about how to make updates to * slices. * - * @param data type for {@code output_ref} output * @param ref A mutable Tensor. Should be from a Variable node. * @param indices A Tensor. Must be one of the following types: int32, int64. * A tensor of indices into ref. @@ -6053,7 +5992,6 @@ public ScatterNdAdd scatterNdAdd(Operand ref, /** * Computes element-wise maximum. * - * @param data type for {@code output_ref} output * @param ref A mutable Tensor. Should be from a Variable node. * @param indices A Tensor. Must be one of the following types: int32, int64. * A tensor of indices into ref. @@ -6071,7 +6009,6 @@ public ScatterNdMax scatterNdMax(Operand ref, /** * Computes element-wise minimum. * - * @param data type for {@code output_ref} output * @param ref A mutable Tensor. Should be from a Variable node. * @param indices A Tensor. Must be one of the following types: int32, int64. * A tensor of indices into ref. @@ -6116,18 +6053,19 @@ public ScatterNdMin scatterNdMin(Operand ref, * *

See {@code tf.scatter_nd} for more details about how to make updates to slices. * - * @param data type for {@code output} output * @param input A Tensor. * @param indices A Tensor. Must be one of the following types: {@code int32}, {@code int64}. * A tensor of indices into {@code input}. * @param updates A Tensor. Must have the same type as ref. A tensor of updated values * to add to {@code input}. + * @param options carries optional attribute values * @param data type for {@code ScatterNdNonAliasingAdd} output and operands * @return a new instance of ScatterNdNonAliasingAdd */ public ScatterNdNonAliasingAdd scatterNdNonAliasingAdd(Operand input, - Operand indices, Operand updates) { - return ScatterNdNonAliasingAdd.create(scope, input, indices, updates); + Operand indices, Operand updates, + ScatterNdNonAliasingAdd.Options... options) { + return ScatterNdNonAliasingAdd.create(scope, input, indices, updates, options); } /** @@ -6160,7 +6098,6 @@ public ScatterNdNonAliasingAdd scatterNdNonAliasingAdd(Oper *

See {@code tf.scatter_nd} for more details about how to make updates to * slices. * - * @param data type for {@code output_ref} output * @param ref A mutable Tensor. Should be from a Variable node. * @param indices A Tensor. Must be one of the following types: int32, int64. * A tensor of indices into ref. @@ -6204,7 +6141,6 @@ public ScatterNdSub scatterNdSub(Operand ref, * slices. *

See also {@code tf.scatter_update} and {@code tf.batch_scatter_update}. * - * @param data type for {@code output_ref} output * @param ref A mutable Tensor. Should be from a Variable node. * @param indices A Tensor. Must be one of the following types: int32, int64. * A tensor of indices into ref. @@ -6240,7 +6176,6 @@ public ScatterNdUpdate scatterNdUpdate(Operand ref, * * * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param indices A tensor of indices into the first dimension of {@code ref}. * @param updates A tensor of updated values to subtract from {@code ref}. @@ -6277,7 +6212,6 @@ public ScatterSub scatterSub(Operand ref, * *

See also {@code tf.batch_scatter_update} and {@code tf.scatter_nd_update}. * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param indices A tensor of indices into the first dimension of {@code ref}. * @param updates A tensor of updated values to store in {@code ref}. @@ -6293,7 +6227,6 @@ public ScatterUpdate scatterUpdate(Operand ref, /** * The SelectV2 operation * - * @param data type for {@code output} output * @param condition The condition value * @param t The t value * @param e The e value @@ -6339,8 +6272,6 @@ public Send send(Operand tensor, String tensorName, String send * idx ==> [1, 3, 5] * * - * @param data type for {@code out} output - * @param data type for {@code idx} output * @param x 1-D. Values to keep. * @param y 1-D. Values to remove. * @param data type for {@code ListDiff} output and operands @@ -6369,8 +6300,6 @@ public SetDiff1d setDiff1d(Operand x, Operand * idx ==> [1, 3, 5] * * - * @param data type for {@code out} output - * @param data type for {@code idx} output * @param x 1-D. Values to keep. * @param y 1-D. Values to remove. * @param outIdx The value of the outIdx attribute @@ -6412,7 +6341,6 @@ public SetSize setSize(Operand setIndices, Operand setV * shape(t) ==> [2, 2, 3] * * - * @param data type for {@code output} output * @param input The input value * @return a new instance of Shape, with default output types */ @@ -6429,7 +6357,6 @@ public org.tensorflow.op.core.Shape shape(Operand input * shape(t) ==> [2, 2, 3] * * - * @param data type for {@code output} output * @param input The input value * @param outType The value of the outType attribute * @param data type for {@code Shape} output and operands @@ -6444,7 +6371,6 @@ public org.tensorflow.op.core.Shape shape(Operand data type for {@code output} output * @param input The input value * @return a new instance of ShapeN, with default output types */ @@ -6456,7 +6382,6 @@ public ShapeN shapeN(Iterable> input) { * Returns shape of tensors. * This operation returns N 1-D integer tensors representing shape of {@code input[i]s}. * - * @param data type for {@code output} output * @param input The input value * @param outType The value of the outType attribute * @param data type for {@code ShapeN} output and operands @@ -6477,7 +6402,6 @@ public ShapeN shapeN(Iterable> i * size(t) ==> 12 * * - * @param data type for {@code output} output * @param input The input value * @return a new instance of Size, with default output types */ @@ -6495,7 +6419,6 @@ public Size size(Operand input) { * size(t) ==> 12 * * - * @param data type for {@code output} output * @param input The input value * @param outType The value of the outType attribute * @param data type for {@code Size} output and operands @@ -6525,7 +6448,6 @@ public Skipgram skipgram(String filename, Long batchSize, Skipgram.Options... op *

Requirements: * 0 <= begin[i] <= begin[i] + size[i] <= Di for i in [0, n) * - * @param data type for {@code output} output * @param input The input value * @param begin begin[i] specifies the offset into the 'i'th dimension of * 'input' to slice from. @@ -6545,7 +6467,6 @@ public Slice slice(Operand input, Ope /** * Returns a copy of the input tensor. * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code Snapshot} output and operands * @return a new instance of Snapshot @@ -6653,7 +6574,6 @@ public Snapshot snapshot(Operand input) { *

Among others, this operation is useful for reducing atrous convolution into * regular convolution. * - * @param data type for {@code output} output * @param input N-D with shape {@code input_shape = [batch] + spatial_shape + remaining_shape}, * where spatial_shape has {@code M} dimensions. * @param blockShape 1-D with shape {@code [M]}, all values must be >= 1. @@ -6672,7 +6592,6 @@ public SpaceToBatchNd spaceToBatchNd(Operand input, /** * Splits a tensor into {@code num_split} tensors along one dimension. * - * @param data type for {@code output} output * @param axis 0-D. The dimension along which to split. Must be in the range * {@code [-rank(value), rank(value))}. * @param value The tensor to split. @@ -6688,7 +6607,6 @@ public Split split(Operand axis, Operand value, /** * Splits a tensor into {@code num_split} tensors along one dimension. * - * @param data type for {@code output} output * @param value The tensor to split. * @param sizeSplits list containing the sizes of each output tensor along the split * dimension. Must sum to the dimension of value along split_dim. @@ -6721,7 +6639,6 @@ public SplitV splitV(Operand value, Operand * - * @param data type for {@code output} output * @param input The {@code input} to squeeze. * @param options carries optional attribute values * @param data type for {@code Squeeze} output and operands @@ -6749,7 +6666,6 @@ public Squeeze squeeze(Operand input, Squeeze.Options... * *

This is the opposite of {@code unpack}. * - * @param data type for {@code output} output * @param values Must be of same shape and type. * @param options carries optional attribute values * @param data type for {@code Pack} output and operands @@ -6787,7 +6703,6 @@ public StackCreate stackCreate(Operand maxSize, Class< /** * Pop the element at the top of the stack. * - * @param data type for {@code elem} output * @param handle The handle to a stack. * @param elemType The type of the elem that is popped. * @param data type for {@code StackPopV2} output and operands @@ -6801,7 +6716,6 @@ public StackPop stackPop(Operand handle, /** * Push an element onto the stack. * - * @param data type for {@code output} output * @param handle The handle to a stack. * @param elem The tensor to be pushed onto the stack. * @param options carries optional attribute values @@ -7083,7 +6997,6 @@ public StatelessWhile statelessWhile(Iterable> input, ConcreteFunctio * The values are cast with a deterministic pseudo-random tensor from a uniform distribution generated from user given key, counter, algorithm. Values will saturate if out of the specified integer type range, and will become zero if inputs are NaN. *

The outputs are a deterministic function of {@code input}, {@code key}, {@code counter}, {@code alg}. * - * @param data type for {@code output} output * @param input The operand to stochastically cast to int. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -7151,7 +7064,6 @@ public StochasticCastToInt stochasticCastToInt( * example generation process. * * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code StopGradient} output and operands * @return a new instance of StopGradient @@ -7169,16 +7081,17 @@ public StopGradient stopGradient(Operand input) { * equal to `n`, but this need not be the case. Each range specification entry can be one of the * following: * - *

- An ellipsis (...) using {@link Indices#ellipsis()}. Ellipses are used to imply zero or - * more dimensions of full-dimension selection. For example, {@code stridedSlice(foo, - * Indices.ellipsis()} is the identity slice. + *

- An ellipsis (...) using {@link org.tensorflow.ndarray.index.Indices#ellipsis()}. Ellipses + * are used to imply zero or more dimensions of full-dimension selection. For example, {@code + * stridedSlice(foo, Indices.ellipsis()} is the identity slice. * - *

- A new axis using {@link Indices#newAxis()}. This is used to insert a new shape=1 - * dimension. For example, `{@code stridedSlice(foo, Indices.newAxis())} where {@code foo} is - * shape {@code (3, 4)} produces a {@code (1, 3, 4)} tensor. + *

- A new axis using {@link org.tensorflow.ndarray.index.Indices#newAxis()}. This is used to + * insert a new shape=1 dimension. For example, `{@code stridedSlice(foo, Indices.newAxis())} + * where {@code foo} is shape {@code (3, 4)} produces a {@code (1, 3, 4)} tensor. * - *

- A range {@code begin:end:stride} using {@link Indices#slice(Long, Long, long)} - * Index.slice()} or {@link Indices#all()}. This is used to specify how much to choose from a + *

- A range {@code begin:end:stride} using {@link + * org.tensorflow.ndarray.index.Indices#slice(Long, Long, long)} Index.slice()} or {@link + * org.tensorflow.ndarray.index.Indices#all()}. This is used to specify how much to choose from a * given dimension. {@code stride} can be any integer but 0. {@code begin} is an integer which * represents the index of the first value to select while {@code end} represents the index of the * last value to select (exclusive). Begin and end can be null, in which case the index begins or @@ -7195,10 +7108,11 @@ public StopGradient stopGradient(Operand input) { * elements). For example {@code foo = [1,2,3,4]; stridedSlice(foo, Indices.slice(-2, null, -1)} * is {@code [4,3]}. * - *

- A single index using {@link Indices#at(long)}. This is used to keep only elements that - * have a given index. For example ({@code stridedSlice(foo, Indices.at(2))} on a shape {@code - * (5,6)} tensor produces a shape {@code (6,)} tensor. The dimension can be kept with size one - * using {@link Indices#at(long, boolean)}. + *

- A single index using {@link org.tensorflow.ndarray.index.Indices#at(long)}. This is used + * to keep only elements that have a given index. For example ({@code stridedSlice(foo, + * Indices.at(2))} on a shape {@code (5,6)} tensor produces a shape {@code (6,)} tensor. The + * dimension can be kept with size one using {@link org.tensorflow.ndarray.index.Indices#at(long, + * boolean)}. * *

These semantics generally follow NumPy's indexing semantics, which can be found here: https://numpy.org/doc/stable/reference/arrays.indexing.html @@ -7206,9 +7120,9 @@ public StopGradient stopGradient(Operand input) { *

Requirements: `0 != strides[i] for i in [0, m)` Only one ellipsis. * * @param data type for {@code output()} output - * @param indices The indices to slice. See {@link Indices}. + * @param indices The indices to slice. See {@link org.tensorflow.ndarray.index.Indices}. * @return a new instance of StridedSlice - * @see Indices + * @see org.tensorflow.ndarray.index.Indices */ public StridedSlice stridedSlice(Operand input, Index... indices) { return StridedSliceHelper.stridedSlice(scope, input, indices); @@ -7314,7 +7228,6 @@ public StridedSlice stridedSlice(Operand input, Index... * {@code 0 != strides[i] for i in [0, m)} * {@code ellipsis_mask must be a power of two (only one ellipsis)} * - * @param data type for {@code output} output * @param input The input value * @param begin {@code begin[k]} specifies the offset into the {@code k}th range specification. * The exact dimension this corresponds to will be determined by context. @@ -7351,9 +7264,10 @@ public StridedSlice stridedSlice(Operand * @param data type for {@code outputRef()} output * @param ref the tensor to assign to. * @param value the value to assign. - * @param indices The indices to slice. See {@link Indices}. + * @param indices The indices to slice. See {@link org.tensorflow.ndarray.index.Indices}. * @return a new instance of StridedSliceAssign - * @see org.tensorflow.op.Ops#stridedSlice(Operand, Index...) + * @see org.tensorflow.op.Ops#stridedSlice(org.tensorflow.Operand, + * org.tensorflow.ndarray.index.Index...) */ public StridedSliceAssign stridedSliceAssign(Operand ref, Operand value, Index... indices) { @@ -7368,7 +7282,6 @@ public StridedSliceAssign stridedSliceAssign(Operand ref *

NOTE this op currently does not support broadcasting and so {@code value}'s * shape must be exactly the shape produced by the slice of {@code ref}. * - * @param data type for {@code output_ref} output * @param ref The ref value * @param begin The begin value * @param end The end value @@ -7395,7 +7308,6 @@ public StridedSliceAssign stridedSliceAs * {@code dy} is the input gradient to be propagated and {@code shape} is the * shape of {@code StridedSlice}'s {@code input}. * - * @param data type for {@code output} output * @param shape The shape value * @param begin The begin value * @param end The end value @@ -7419,7 +7331,6 @@ public StridedSliceGrad stridedSliceGrad * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -7438,7 +7349,6 @@ public Sum sum(Operand input, Operand * the data goes to {@code output_false}. *

See also {@code RefSwitch} and {@code Merge}. * - * @param data type for {@code output_false} output * @param data The tensor to be forwarded to the appropriate output. * @param pred A scalar that specifies which output port will receive data. * @param data type for {@code Switch} output and operands @@ -7473,7 +7383,6 @@ public SyncDevice syncDevice() { * var = state_ops.assign_add(var, [[6.0, 7.0]]) * final = state_ops._destroy_temporary_variable(var, var_name=var_name) * - * @param data type for {@code ref} output * @param shape The shape of the variable tensor. * @param dtype The type of elements in the variable tensor. * @param options carries optional attribute values @@ -7524,7 +7433,6 @@ public TensorArrayClose tensorArrayClose(Operand handle) { * *

All elements must have the same shape (excepting the first dimension). * - * @param data type for {@code value} output * @param handle The handle to a TensorArray. * @param flowIn A float scalar that enforces proper chaining of operations. * @param dtype The type of the elem that is returned. @@ -7541,7 +7449,6 @@ public TensorArrayConcat tensorArrayConcat(Operand data type for {@code value} output * @param handle The handle to a TensorArray. * @param indices The locations in the TensorArray from which to read tensor elements. * @param flowIn A float scalar that enforces proper chaining of operations. @@ -7622,7 +7529,6 @@ public TensorArrayGradWithShape tensorArrayGradWithShape(Operand data type for {@code value} output * @param handle The handle value * @param flowIn The flowIn value * @param dtype The value of the dtype attribute @@ -7638,7 +7544,6 @@ public TensorArrayPack tensorArrayPack(Operand han /** * Read an element from the TensorArray into output {@code value}. * - * @param data type for {@code value} output * @param handle The handle to a TensorArray. * @param index The index value * @param flowIn A float scalar that enforces proper chaining of operations. @@ -7750,7 +7655,6 @@ public TensorArrayWrite tensorArrayWrite(Operand handle, Operan * tensor: The concated result. * lengths: Output tensor containing sizes of the 0th dimension of tensors in the list, used for computing the gradient. * - * @param data type for {@code tensor} output * @param inputHandle The inputHandle value * @param elementShape The elementShape value * @param leadingDims The leadingDims value @@ -7783,7 +7687,6 @@ public TensorListConcatLists tensorListConcatLists( * input_handle: the list * element_shape: the shape of elements of the list * - * @param data type for {@code element_shape} output * @param inputHandle The inputHandle value * @param shapeType The value of the shapeType attribute * @param data type for {@code TensorListElementShape} output and operands @@ -7817,7 +7720,6 @@ public TensorListFromTensor tensorListFromTensor(Operand tensor * indices: The indices used to index into the list. * values: The tensor. * - * @param data type for {@code values} output * @param inputHandle The inputHandle value * @param indices The indices value * @param elementShape The elementShape value @@ -7837,7 +7739,6 @@ public TensorListGather tensorListGather( * index: the position in the list from which an element will be retrieved * item: the element at that position * - * @param data type for {@code item} output * @param inputHandle The inputHandle value * @param index The index value * @param elementShape The elementShape value @@ -7871,7 +7772,6 @@ public TensorListLength tensorListLength(Operand inputHandle) { * element_dtype: the type of elements in the list * element_shape: the shape of the output tensor * - * @param data type for {@code tensor} output * @param inputHandle The inputHandle value * @param elementShape The elementShape value * @param elementDtype The value of the elementDtype attribute @@ -8033,7 +7933,6 @@ public TensorListSplit tensorListSplit(Operand tensor, * tensor: the gathered result * num_elements: optional. If not -1, the number of elements in the list. * - * @param data type for {@code tensor} output * @param inputHandle The inputHandle value * @param elementShape The elementShape value * @param elementDtype The value of the elementDtype attribute @@ -8101,7 +8000,6 @@ public TensorMapInsert tensorMapInsert(Operand inputHandle, * key: the key to be looked up * value: the value found from the given key * - * @param data type for {@code value} output * @param inputHandle The inputHandle value * @param key The key value * @param valueDtype The value of the valueDtype attribute @@ -8130,7 +8028,6 @@ public TensorMapSize tensorMapSize(Operand inputHandle) { * input_handle: the input map * keys: the returned Tensor of all keys in the map * - * @param data type for {@code keys} output * @param inputHandle The inputHandle value * @param keyDtype The value of the keyDtype attribute * @param data type for {@code TensorMapStackKeys} output and operands @@ -8201,19 +8098,28 @@ public TensorMapStackKeys tensorMapStackKeys( * * * - *

Note: on CPU, if an out of bound index is found, an error is returned. - * On GPU, if an out of bound index is found, the index is ignored. + *

If {@code indices} contains any out-of-bound indices, depending on + * {@code bad_indices_policy}, the op will either return an error or ignore the + * out-of-bound indices. {@code bad_indices_policy} can be one of the following values: + *

    + *
  1. "" or "DEFAULT": raises on CPU and ignore on GPU. This is because + * historically on CPU and GPU we handle errors in different ways, and for + * backward compatibility we keep the default behavior.
    2. + *
  2. "ERROR": raises error; GPU does not support this value.
    3. + *
  3. "IGNORE": ignore the bad indices; supported on both CPU and GPU.
    4. + *
* - * @param data type for {@code output} output * @param tensor Tensor to copy/update. * @param indices Index tensor. * @param updates Updates to scatter into output. + * @param options carries optional attribute values * @param data type for {@code TensorScatterAdd} output and operands * @return a new instance of TensorScatterNdAdd */ public TensorScatterNdAdd tensorScatterNdAdd(Operand tensor, - Operand indices, Operand updates) { - return TensorScatterNdAdd.create(scope, tensor, indices, updates); + Operand indices, Operand updates, + TensorScatterNdAdd.Options... options) { + return TensorScatterNdAdd.create(scope, tensor, indices, updates, options); } /** @@ -8233,31 +8139,33 @@ public TensorScatterNdAdd tensorScatterNdAdd(Operand ten * *

Refer to {@code tf.tensor_scatter_nd_update} for more details. * - * @param data type for {@code output} output * @param tensor Tensor to update. * @param indices Index tensor. * @param updates Updates to scatter into output. + * @param options carries optional attribute values * @param data type for {@code TensorScatterMax} output and operands * @return a new instance of TensorScatterNdMax */ public TensorScatterNdMax tensorScatterNdMax(Operand tensor, - Operand indices, Operand updates) { - return TensorScatterNdMax.create(scope, tensor, indices, updates); + Operand indices, Operand updates, + TensorScatterNdMax.Options... options) { + return TensorScatterNdMax.create(scope, tensor, indices, updates, options); } /** * The TensorScatterMin operation * - * @param data type for {@code output} output * @param tensor Tensor to update. * @param indices Index tensor. * @param updates Updates to scatter into output. + * @param options carries optional attribute values * @param data type for {@code TensorScatterMin} output and operands * @return a new instance of TensorScatterNdMin */ public TensorScatterNdMin tensorScatterNdMin(Operand tensor, - Operand indices, Operand updates) { - return TensorScatterNdMin.create(scope, tensor, indices, updates); + Operand indices, Operand updates, + TensorScatterNdMin.Options... options) { + return TensorScatterNdMin.create(scope, tensor, indices, updates, options); } /** @@ -8318,16 +8226,17 @@ public TensorScatterNdMin tensorScatterNdMin(Operand ten *

Note that on CPU, if an out of bound index is found, an error is returned. * On GPU, if an out of bound index is found, the index is ignored. * - * @param data type for {@code output} output * @param tensor Tensor to copy/update. * @param indices Index tensor. * @param updates Updates to scatter into output. + * @param options carries optional attribute values * @param data type for {@code TensorScatterSub} output and operands * @return a new instance of TensorScatterNdSub */ public TensorScatterNdSub tensorScatterNdSub(Operand tensor, - Operand indices, Operand updates) { - return TensorScatterNdSub.create(scope, tensor, indices, updates); + Operand indices, Operand updates, + TensorScatterNdSub.Options... options) { + return TensorScatterNdSub.create(scope, tensor, indices, updates, options); } /** @@ -8338,7 +8247,6 @@ public TensorScatterNdSub tensorScatterNdSub(Operand ten * scattered onto an existing tensor (as opposed to a zero-tensor). If the memory * for the existing tensor cannot be re-used, a copy is made and updated. *

If {@code indices} contains duplicates, then we pick the last update for the index. - *

If an out of bound index is found on CPU, an error is returned. *

WARNING: There are some GPU specific semantics for this operation. *

    *
  • If an out of bound index is found, the index is ignored.
    • @@ -8360,18 +8268,29 @@ public TensorScatterNdSub tensorScatterNdSub(Operand ten * 
        *  indices.shape[:-1] + tensor.shape[indices.shape[-1]:]
    *
    + *

    If {@code indices} contains any out-of-bound indices, depending on + * {@code bad_indices_policy}, the op will either return an error or ignore the + * out-of-bound indices. {@code bad_indices_policy} can be one of the following values: + *

      + *
    1. "" or "DEFAULT": raises on CPU and ignore on GPU. This is because + * historically on CPU and GPU we handle errors in different ways, and for + * backward compatibility we keep the default behavior.
      2. + *
    2. "ERROR": raises error; GPU does not support this value.
      3. + *
    3. "IGNORE": ignore the bad indices; supported on both CPU and GPU.
      4. + *
    *

    For usage examples see the python tf.tensor_scatter_nd_update {@link org.tensorflow.op.Ops#tensorScatterNdUpdate} function * - * @param data type for {@code output} output * @param tensor Tensor to copy/update. * @param indices Index tensor. * @param updates Updates to scatter into output. + * @param options carries optional attribute values * @param data type for {@code TensorScatterUpdate} output and operands * @return a new instance of TensorScatterNdUpdate */ public TensorScatterNdUpdate tensorScatterNdUpdate(Operand tensor, - Operand indices, Operand updates) { - return TensorScatterNdUpdate.create(scope, tensor, indices, updates); + Operand indices, Operand updates, + TensorScatterNdUpdate.Options... options) { + return TensorScatterNdUpdate.create(scope, tensor, indices, updates, options); } /** @@ -8382,7 +8301,6 @@ public TensorScatterNdUpdate tensorScatterNdUpdate(Operand< *

    NOTE this op currently does not support broadcasting and so {@code value}'s shape * must be exactly the shape produced by the slice of {@code input}. * - * @param data type for {@code output} output * @param input The input value * @param begin The begin value * @param end The end value @@ -8433,7 +8351,6 @@ public TensorStridedSliceUpdate tensorSt * * * - * @param data type for {@code output} output * @param input Can be of any rank. * @param multiples 1-D. Length must be the same as the number of dimensions in {@code input} * @param data type for {@code Tile} output and operands @@ -8522,7 +8439,6 @@ public TopKWithUnique topKWithUnique(Operand input, Long k) { * assumed to possibly belong to the same batch. If left empty, the op name will * be used as the shared name. * - * @param data type for {@code unbatched_tensor} output * @param batchedTensor The batchedTensor value * @param batchIndex The batchIndex value * @param id The id value @@ -8552,7 +8468,6 @@ public Unbatch unbatch(Operand batchedTensor, Operand data type for {@code batched_grad} output * @param originalInput The originalInput value * @param batchIndex The batchIndex value * @param grad The grad value @@ -8573,7 +8488,6 @@ public UnbatchGrad unbatchGrad(Operand originalInput, * If quantization_axis is -1 (per-tensor quantized), the entire operand is clipped using scalar min, max. * Otherwise (per-channel quantized), the clipping is also done per-channel. * - * @param data type for {@code output} output * @param operand Must be a Tensor of T. * @param min The min value(s) to clip operand. Must be a Tensor of T. * Must be a scalar Tensor if quantization_axis is -1 (per-tensor quantization), otherwise 1D Tensor of size (operand.dim_size(quantization_axis),) (per-axis quantization). @@ -8635,8 +8549,6 @@ public UniformQuantizedClipByValue uniformQuantizedClipBy * idx ==> [0, 1, 1] * * - * @param data type for {@code y} output - * @param data type for {@code idx} output * @param x A {@code Tensor}. * @param axis A {@code Tensor} of type {@code int32} (default: None). The axis of the Tensor to * find the unique elements. @@ -8686,8 +8598,6 @@ public Unique unique(Operand x, Operand * - * @param data type for {@code y} output - * @param data type for {@code idx} output * @param x A {@code Tensor}. * @param axis A {@code Tensor} of type {@code int32} (default: None). The axis of the Tensor to * find the unique elements. @@ -8744,8 +8654,6 @@ public Unique unique(Operand x, * count ==> [1, 2] * * - * @param data type for {@code y} output - * @param data type for {@code idx} output * @param x A {@code Tensor}. * @param axis A {@code Tensor} of type {@code int32} (default: None). The axis of the Tensor to * find the unique elements. @@ -8800,8 +8708,6 @@ public UniqueWithCounts uniqueWithCounts(Operand * count ==> [1, 2] * * - * @param data type for {@code y} output - * @param data type for {@code idx} output * @param x A {@code Tensor}. * @param axis A {@code Tensor} of type {@code int32} (default: None). The axis of the Tensor to * find the unique elements. @@ -8835,7 +8741,6 @@ public UniqueWithCounts uniqueWithCou * Equivalent to np.unravel_index *
    {@literal @}end_compatibility * - * @param data type for {@code output} output * @param indices An 0-D or 1-D {@code int} Tensor whose elements are indices into the * flattened version of an array of dimensions dims. * @param dims An 1-D {@code int} Tensor. The shape of the array to use for unraveling @@ -8859,7 +8764,6 @@ public UnravelIndex unravelIndex(Operand indices, Oper * Etc. *

    This is the opposite of {@code pack}. * - * @param data type for {@code output} output * @param value 1-D or higher, with {@code axis} dimension size equal to {@code num}. * @param num The value of the num attribute * @param options carries optional attribute values @@ -8900,7 +8804,6 @@ public Unstage unstage(List> dtypes, Unstage.Options... o *

    result == [[1, 2, 4], * [0, 2, 5]] * - * @param data type for {@code output} output * @param sortedInputs 2-D Tensor where each row is ordered. * @param values 2-D Tensor with the same numbers of rows as {@code sorted_search_values}. Contains * the values that will be searched for in {@code sorted_search_values}. @@ -8928,7 +8831,6 @@ public UpperBound upperBound(Operand sortedInputs, *

    result == [[1, 2, 4], * [0, 2, 5]] * - * @param data type for {@code output} output * @param sortedInputs 2-D Tensor where each row is ordered. * @param values 2-D Tensor with the same numbers of rows as {@code sorted_search_values}. Contains * the values that will be searched for in {@code sorted_search_values}. @@ -8988,7 +8890,6 @@ public Variable variable(Operand init, Variable.Options. * TODO(zhifengc/mrry): Adds a pointer to a more detail document * about sharing states in tensorflow. * - * @param data type for {@code ref} output * @param shape The shape of the variable tensor. * @param dtype The type of elements in the variable tensor. * @param options carries optional attribute values @@ -9009,7 +8910,6 @@ public Variable variable(Shape shape, Class dtype, * shape(t) ==> [2, 2, 3] * * - * @param data type for {@code output} output * @param input The input value * @return a new instance of VariableShape, with default output types */ @@ -9026,7 +8926,6 @@ public VariableShape variableShape(Operand input) { * shape(t) ==> [2, 2, 3] * * - * @param data type for {@code output} output * @param input The input value * @param outType The value of the outType attribute * @param data type for {@code VariableShape} output and operands @@ -9147,7 +9046,6 @@ public Zeros zeros(Operand dims, Class data type for {@code y} output * @param x a tensor of type T. * @param data type for {@code ZerosLike} output and operands * @return a new instance of ZerosLike diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java index 99f3648ea27..8bd174ba427 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java @@ -107,7 +107,6 @@ public final class QuantizationOps { * max_range / max_expected_T); * * - * @param data type for {@code output} output * @param input The input value * @param minRange The minimum scalar value possibly produced for the input. * @param maxRange The maximum scalar value possibly produced for the input. @@ -165,7 +164,6 @@ public Dequantize dequantize(Operand input, * max_range / max_expected_T); * * - * @param data type for {@code output} output * @param input The input value * @param minRange The minimum scalar value possibly produced for the input. * @param maxRange The maximum scalar value possibly produced for the input. @@ -275,6 +273,28 @@ public FakeQuantWithMinMaxArgsGradient fakeQuantWithMinMaxArgsGradient( *

*

This operation has a gradient and thus allows for training {@code min} and {@code max} * values. + *

+ *
+ *
+ *

constant_input = tf.constant([[1.2, -0.3, 0.7], [2.1, 0.5, -1.0]], dtype=tf.float32) + *

min_val = -0.5 + * max_val = 0.8 + * num_bits = 8 + * narrow_range = False #False:for the quantization range [0; 2^num_bits - 1] + *

quantized_data = tf.quantization.fake_quant_with_min_max_vars( + * ... inputs=constant_input, min=min_val, max=max_val, num_bits=num_bits, narrow_range=narrow_range + * ... ) + *

print("Input:\n", constant_input.numpy()) + * Input: + * [[ 1.2 -0.3 0.7] + * [ 2.1 0.5 -1. ]] + * print("Output:\n", quantized_data.numpy()) + * Output: + * [[ 0.8003921 -0.3007843 0.6984313] + * [ 0.8003921 0.4996078 -0.4996078]] + *

+ *
+ *
* * @param inputs The inputs value * @param min The min value @@ -456,7 +476,6 @@ public FakeQuantWithMinMaxVarsPerChannelGradient fakeQuantWithMinMaxVarsPerChann * The legacy default value for this is 0.01, but it is strongly suggested to * set it to 0 for new uses. * - * @param data type for {@code output} output * @param input The input value * @param minRange The minimum value of the quantization range. This value may be adjusted by the * op depending on other parameters. The adjusted value is written to {@code output_min}. @@ -482,7 +501,6 @@ public Quantize quantize(Operand input, * This is almost identical to QuantizeAndDequantizeV2, except that num_bits is a * tensor, so its value can change during training. * - * @param data type for {@code output} output * @param input The input value * @param inputMin The inputMin value * @param inputMax The inputMax value @@ -502,7 +520,6 @@ public QuantizeAndDequantize quantizeAndDequantize(Operan * This is almost identical to QuantizeAndDequantizeV2, except that num_bits is a * tensor, so its value can change during training. * - * @param data type for {@code output} output * @param input The input value * @param inputMin The inputMin value * @param inputMax The inputMax value @@ -522,7 +539,6 @@ public QuantizeAndDequantizeV3 quantizeAndDequantizeV3(Op * This is almost identical to QuantizeAndDequantizeV2, except that it returns a * gradient of 1 for inputs that are within the quantization range, or 0 otherwise. * - * @param data type for {@code output} output * @param input Tensor to quantize and then dequantize. * @param inputMin If {@code range_given == True}, this specifies the minimum input value that needs to * be represented, otherwise it is determined from the min value of the {@code input} @@ -544,7 +560,6 @@ public QuantizeAndDequantizeV4 quantizeAndDequantizeV4(Op * Returns a gradient of 1 for inputs that are within the quantization range, * or 0 otherwise. * - * @param data type for {@code input_backprop} output * @param gradients The gradients value * @param input The input value * @param inputMin The inputMin value @@ -581,7 +596,6 @@ public QuantizeAndDequantizeV4Grad quantizeAndDequantizeV * that output into this operator, we can reduce it from 32 bits down to 8 with * minimal loss of accuracy. * - * @param data type for {@code output} output * @param input The input value * @param inputMin The float value that the minimum quantized input value represents. * @param inputMax The float value that the maximum quantized input value represents. @@ -598,7 +612,6 @@ public QuantizeDownAndShrinkRange quantizeDownAndShrinkRa /** * Concatenates quantized tensors along one dimension. * - * @param data type for {@code output} output * @param concatDim 0-D. The dimension along which to concatenate. Must be in the * range [0, rank(values)). * @param values The {@code N} Tensors to concatenate. Their ranks and types must match, @@ -617,7 +630,6 @@ public QuantizedConcat quantizedConcat(Operand conc /** * The QuantizedMatMulWithBiasAndDequantize operation * - * @param data type for {@code out} output * @param a The a value * @param b The b value * @param bias The bias value @@ -644,7 +656,6 @@ public QuantizedMatMulWithBiasAndDequantize quantizedMatM /** * The QuantizedMatMulWithBiasAndRequantize operation * - * @param data type for {@code out} output * @param a The a value * @param b The b value * @param bias The bias value @@ -694,7 +705,6 @@ public RequantizationRange requantizationRange(Operand input, * {@code input_max} is 1.0f, and we are dealing with {@code quint16} quantized data, then a 0 * value in the 16-bit data should be interpreted as -1.0f, and a 65535 means 1.0f. * - * @param data type for {@code output} output * @param input The input value * @param inputMin The float value that the minimum quantized input value represents. * @param inputMax The float value that the maximum quantized input value represents. @@ -715,7 +725,6 @@ public Requantize requantize(Operand i * Given quantized {@code input} which was quantized using {@code scales} and {@code zero_points}, performs dequantization using the formula: * dequantized_data = (quantized_data - zero_point) * scale. * - * @param data type for {@code output} output * @param input Must be a Tensor of Tin. * @param scales The float value(s) used as scale(s) when quantizing original data that input represents. * Must be a scalar Tensor if quantization_axis is -1 (per-tensor quantization), otherwise 1D Tensor of size (input.dim_size(quantization_axis),) (per-axis quantization). @@ -746,7 +755,6 @@ public UniformDequantize uniformDequantize( * Given {@code input}, {@code scales} and {@code zero_points}, performs quantization using the formula: * quantized_data = floor(input_data * (1.0f / scale) + 0.5f) + zero_point * - * @param data type for {@code output} output * @param input Must be a Tensor of Tin. * @param scales The float value(s) to use as scale(s) to quantize {@code input}. * Must be a scalar Tensor if quantization_axis is -1 (per-tensor quantization), otherwise 1D Tensor of size (input.dim_size(quantization_axis),) (per-axis quantization). @@ -780,7 +788,6 @@ public UniformQuantize uniformQuantize(Operand data type for {@code output} output * @param lhs Must be a 2D Tensor of Tin. * @param rhs Must be a 2D Tensor of Tin. * @param lhsScales The float value(s) used as scale when quantizing original data that lhs represents. @@ -833,7 +840,6 @@ public UniformQuantizedDot uniformQuan * {@code rhs} must be quantized Tensor, where its data value is quantized using the formula: * quantized_data = clip(original_data / scale + zero_point, quantization_min_val, quantization_max_val). * - * @param data type for {@code output} output * @param lhs Must be a 2D Tensor of Tlhs. * @param rhs Must be a 2D Tensor of Trhs. * @param rhsScales The float value(s) used as scale when quantizing original data that rhs represents. @@ -873,7 +879,6 @@ public UniformQuantizedDotHybrid uniformQuantizedDotHybri * i.e. At least one among input_quantization_axis and output_quantization_axis must be -1, or two must be equal. * * - * @param data type for {@code output} output * @param input Must be a Tensor of Tin. * @param inputScales The float value(s) used as scale(s) when quantizing original data that {@code input} represents. * Must be a scalar Tensor if quantization_axis is -1 (per-tensor quantization), otherwise 1D Tensor of size (input.dim_size(quantization_axis),) (per-axis quantization). diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RaggedOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RaggedOps.java index 83bf63f461f..43b18f0cf57 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RaggedOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RaggedOps.java @@ -60,7 +60,6 @@ public final class RaggedOps { * {@code i}. *

Values in {@code arr} outside of the range [0, size) are ignored. * - * @param data type for {@code output} output * @param splits 1D int64 {@code Tensor}. * @param values 2D int {@code Tensor}. * @param sizeOutput non-negative int scalar {@code Tensor}. @@ -82,7 +81,6 @@ public RaggedBincount raggedBincount( * Performs sparse-output bin counting for a ragged tensor input. * Counts the number of times each value occurs in the input. * - * @param data type for {@code output_values} output * @param splits Tensor containing the row splits of the ragged tensor to count. * @param values Tensor containing values of the sparse tensor to count. * @param weights A Tensor of the same shape as indices containing per-index weight values. @@ -102,8 +100,6 @@ public RaggedCountSparseOutput raggedCountSparseOutput( * Generates a feature cross from a list of tensors, and returns it as a * RaggedTensor. See {@code tf.ragged.cross} for more details. * - * @param data type for {@code output_values} output - * @param data type for {@code output_row_splits} output * @param raggedValues The values tensor for each RaggedTensor input. * @param raggedRowSplits The row_splits tensor for each RaggedTensor input. * @param sparseIndices The indices tensor for each SparseTensor input. @@ -135,7 +131,6 @@ public RaggedCross raggedCross( /** * The RaggedFillEmptyRows operation * - * @param data type for {@code output_values} output * @param valueRowids The valueRowids value * @param values The values value * @param nrows The nrows value @@ -151,7 +146,6 @@ public RaggedFillEmptyRows raggedFillEmptyRows(Operand data type for {@code d_values} output * @param reverseIndexMap The reverseIndexMap value * @param gradValues The gradValues value * @param data type for {@code RaggedFillEmptyRowsGrad} output and operands @@ -183,8 +177,6 @@ public RaggedFillEmptyRowsGrad raggedFillEmptyRowsGrad( *

(Note: This c++ op is used to implement the higher-level python * {@code tf.ragged.gather} op, which also supports ragged indices.) * - * @param data type for {@code output_nested_splits} output - * @param data type for {@code output_dense_values} output * @param paramsNestedSplits The {@code nested_row_splits} tensors that define the row-partitioning for the * {@code params} RaggedTensor input. * @param paramsDenseValues The {@code flat_values} for the {@code params} RaggedTensor. There was a terminology change @@ -221,8 +213,6 @@ public RaggedGather raggedGather( * The vector inputs must all have the same size. Scalar inputs are broadcast * to match the size of the vector inputs. * - * @param data type for {@code rt_nested_splits} output - * @param data type for {@code rt_dense_values} output * @param starts The starts of each range. * @param limits The limits of each range. * @param deltas The deltas of each range. @@ -250,8 +240,6 @@ public RaggedRange raggedRange(Operand starts, * The vector inputs must all have the same size. Scalar inputs are broadcast * to match the size of the vector inputs. * - * @param data type for {@code rt_nested_splits} output - * @param data type for {@code rt_dense_values} output * @param starts The starts of each range. * @param limits The limits of each range. * @param deltas The deltas of each range. @@ -279,8 +267,6 @@ public RaggedRange raggedRange(Oper * inferred as {@code output_ragged_rank} - {@code rank(encoded_ragged)}. See * {@code RaggedTensorToVariant} for the corresponding encoding logic. * - * @param data type for {@code output_nested_splits} output - * @param data type for {@code output_dense_values} output * @param encodedRagged A {@code variant} Tensor containing encoded {@code RaggedTensor}s. * @param inputRaggedRank The ragged rank of each encoded {@code RaggedTensor} component in the input. If set to * -1, this is inferred as {@code output_ragged_rank} - {@code rank(encoded_ragged)} @@ -310,8 +296,6 @@ public RaggedTensorFromVariant raggedTensorFromVari * inferred as {@code output_ragged_rank} - {@code rank(encoded_ragged)}. See * {@code RaggedTensorToVariant} for the corresponding encoding logic. * - * @param data type for {@code output_nested_splits} output - * @param data type for {@code output_dense_values} output * @param encodedRagged A {@code variant} Tensor containing encoded {@code RaggedTensor}s. * @param inputRaggedRank The ragged rank of each encoded {@code RaggedTensor} component in the input. If set to * -1, this is inferred as {@code output_ragged_rank} - {@code rank(encoded_ragged)} @@ -335,7 +319,6 @@ public RaggedTensorFromVariant ragged * output=SparseTensor(indices=sparse_indices, values=sparse_values, * dense_shape=sparse_dense_shape) * - * @param data type for {@code sparse_values} output * @param rtNestedSplits The {@code row_splits} for the {@code RaggedTensor}. * @param rtDenseValues The {@code flat_values} for the {@code RaggedTensor}. * @param data type for {@code RaggedTensorToSparse} output and operands @@ -365,7 +348,6 @@ public RaggedTensorToSparse raggedTensorToSparse( * is preceded by "FIRST_DIM_SIZE". * * - * @param data type for {@code result} output * @param shape The desired shape of the output tensor. If left unspecified (empty), * the minimal shape required to contain all the elements in the ragged tensor * (the natural shape) will be used. If some dimensions are left unspecified, then @@ -438,7 +420,6 @@ public RaggedTensorToVariant raggedTensorToVariant( * the outer row-splits and the shape of the dense-values that were provided as * inputs to the RaggedTensorToVariant op. * - * @param data type for {@code dense_values_grad} output * @param encodedRaggedGrad A {@code variant} Tensor containing encoded {@code RaggedTensor} gradients. * @param rowSplits Outermost row-splits that were used as input to the RaggedTensorToVariant op. * @param denseValuesShape Shape of the dense_values that was used as an input to the diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomExperimentalOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomExperimentalOps.java index 09a2b385b6f..34d3585f270 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomExperimentalOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomExperimentalOps.java @@ -49,7 +49,6 @@ public final class RandomExperimentalOps { * *

The outputs are a deterministic function of {@code value}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param value The tensor to be shuffled. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java index 3c62a3b57a1..c5ff9a489a0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java @@ -203,7 +203,6 @@ public LogUniformCandidateSampler logUniformCandidateSampler(Operand tru /** * Draws samples from a multinomial distribution. * - * @param data type for {@code output} output * @param logits 2-D Tensor with shape {@code [batch_size, num_classes]}. Each slice {@code [i, :]} * represents the unnormalized log probabilities for all classes. * @param numSamples 0-D. Number of independent samples to draw for each row slice. @@ -218,7 +217,6 @@ public Multinomial multinomial(Operand logits, /** * Draws samples from a multinomial distribution. * - * @param data type for {@code output} output * @param logits 2-D Tensor with shape {@code [batch_size, num_classes]}. Each slice {@code [i, :]} * represents the unnormalized log probabilities for all classes. * @param numSamples 0-D. Number of independent samples to draw for each row slice. @@ -236,7 +234,6 @@ public Multinomial multinomial(Operand * Non-deterministically generates some integers. * This op may use some OS-provided source of non-determinism (e.g. an RNG), so each execution will give different results. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @return a new instance of NonDeterministicInts, with default output types */ @@ -248,7 +245,6 @@ public NonDeterministicInts nonDeterministicInts(Operand data type for {@code output} output * @param shape The shape of the output tensor. * @param dtype The type of the output. * @param data type for {@code NonDeterministicInts} output and operands @@ -264,7 +260,6 @@ public NonDeterministicInts nonDeterministicInts( * scalar which applies to the entire output, or a vector of length shape[0] which * stores the parameters for each batch. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. Batches are indexed by the 0th dimension. * @param means The mean parameter of each batch. * @param stdevs The standard deviation parameter of each batch. Must be greater than 0. @@ -287,7 +282,6 @@ public ParameterizedTruncatedNormal parameterizedTruncate * transformation-rejection from pairs of uniform and normal random variables. * See http://dl.acm.org/citation.cfm?id=358414 * - * @param data type for {@code output} output * @param shape 1-D integer tensor. Shape of independent samples to draw from each * distribution described by the shape parameters given in alpha. * @param alpha A tensor in which each scalar is a "shape" parameter describing the @@ -304,7 +298,6 @@ public RandomGamma randomGamma(Operand /** * Computes the derivative of a Gamma random sample w.r.t. {@code alpha}. * - * @param data type for {@code output} output * @param alpha The alpha value * @param sample The sample value * @param data type for {@code RandomGammaGrad} output and operands @@ -326,7 +319,6 @@ public RandomGammaGrad randomGammaGrad(Operand alpha, * See Donald E. Knuth (1969). Seminumerical Algorithms. The Art of Computer * Programming, Volume 2. Addison Wesley * - * @param data type for {@code output} output * @param shape 1-D integer tensor. Shape of independent samples to draw from each * distribution described by the shape parameters given in rate. * @param rate A tensor in which each scalar is a "rate" parameter describing the @@ -350,7 +342,6 @@ public RandomPoisson randomPoisson(Operand shape, * See Donald E. Knuth (1969). Seminumerical Algorithms. The Art of Computer * Programming, Volume 2. Addison Wesley * - * @param data type for {@code output} output * @param shape 1-D integer tensor. Shape of independent samples to draw from each * distribution described by the shape parameters given in rate. * @param rate A tensor in which each scalar is a "rate" parameter describing the @@ -376,7 +367,6 @@ public RandomPoisson randomPoisson(Operand * - * @param data type for {@code output} output * @param value The tensor to be shuffled. * @param options carries optional attribute values * @param data type for {@code RandomShuffle} output and operands @@ -391,7 +381,6 @@ public RandomShuffle randomShuffle(Operand value, * Outputs random values from a normal distribution. * The generated values will have mean 0 and standard deviation 1. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param dtype The type of the output. * @param options carries optional attribute values @@ -408,7 +397,6 @@ public RandomStandardNormal randomStandardNormal( * The generated values follow a uniform distribution in the range {@code [0, 1)}. The * lower bound 0 is included in the range, while the upper bound 1 is excluded. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param dtype The type of the output. * @param options carries optional attribute values @@ -429,7 +417,6 @@ public RandomUniform randomUniform(Operand data type for {@code output} output * @param shape The shape of the output tensor. * @param minval 0-D. Inclusive lower bound on the generated integers. * @param maxval 0-D. Exclusive upper bound on the generated integers. @@ -491,7 +478,6 @@ public RngSkip rngSkip(Operand resource, Operand algori /** * The StatefulRandomBinomial operation * - * @param data type for {@code output} output * @param resource The resource value * @param algorithm The algorithm value * @param shape The shape value @@ -509,7 +495,6 @@ public StatefulRandomBinomial statefulRandomBinomial /** * The StatefulRandomBinomial operation * - * @param data type for {@code output} output * @param resource The resource value * @param algorithm The algorithm value * @param shape The shape value @@ -530,7 +515,6 @@ public StatefulRandomBinomial stateful * Outputs random values from a normal distribution. * The generated values will have mean 0 and standard deviation 1. * - * @param data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -545,7 +529,6 @@ public StatefulStandardNormal statefulStandardNormal(Operand data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -565,7 +548,6 @@ public StatefulStandardNormal statefulStandardNormal( * deviation 1, except that values whose magnitude is more than 2 standard * deviations from the mean are dropped and re-picked. * - * @param data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -583,7 +565,6 @@ public StatefulTruncatedNormal statefulTruncatedNormal( * deviation 1, except that values whose magnitude is more than 2 standard * deviations from the mean are dropped and re-picked. * - * @param data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -602,7 +583,6 @@ public StatefulTruncatedNormal statefulTruncatedNormal( * The generated values follow a uniform distribution in the range {@code [0, 1)}. The * lower bound 0 is included in the range, while the upper bound 1 is excluded. * - * @param data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -618,7 +598,6 @@ public StatefulUniform statefulUniform(Operand resour * The generated values follow a uniform distribution in the range {@code [0, 1)}. The * lower bound 0 is included in the range, while the upper bound 1 is excluded. * - * @param data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -635,7 +614,6 @@ public StatefulUniform statefulUniform(Operand data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -658,7 +636,6 @@ public StatefulUniformFullInt statefulUniformFullInt( * power of two. The bias is small for values of {@code maxval - minval} significantly * smaller than the range of the output (either {@code 2^32} or {@code 2^64}). * - * @param data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -676,7 +653,6 @@ public StatefulUniformInt statefulUniformInt( /** * Draws samples from a multinomial distribution. * - * @param data type for {@code output} output * @param logits 2-D Tensor with shape {@code [batch_size, num_classes]}. Each slice {@code [i, :]} * represents the unnormalized log probabilities for all classes. * @param numSamples 0-D. Number of independent samples to draw for each row slice. @@ -691,7 +667,6 @@ public StatelessMultinomial statelessMultinomial(Operand data type for {@code output} output * @param logits 2-D Tensor with shape {@code [batch_size, num_classes]}. Each slice {@code [i, :]} * represents the unnormalized log probabilities for all classes. * @param numSamples 0-D. Number of independent samples to draw for each row slice. @@ -709,7 +684,6 @@ public StatelessMultinomial statelessMultinomial( /** * The StatelessParameterizedTruncatedNormal operation * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param means The mean parameter of each batch. @@ -731,7 +705,6 @@ public StatelessParameterizedTruncatedNormal statelessPar * Outputs random values from a binomial distribution. *

The outputs are a deterministic function of {@code shape}, {@code seed}, {@code counts}, and {@code probs}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param counts The counts of the binomial distribution. Must be broadcastable with {@code probs}, @@ -752,7 +725,6 @@ public StatelessRandomBinomial statelessRandomBinomi * Outputs random values from a binomial distribution. *

The outputs are a deterministic function of {@code shape}, {@code seed}, {@code counts}, and {@code probs}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param counts The counts of the binomial distribution. Must be broadcastable with {@code probs}, @@ -775,7 +747,6 @@ public StatelessRandomBinomial statele * Outputs random values from a gamma distribution. *

The outputs are a deterministic function of the inputs. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -830,7 +801,6 @@ public StatelessRandomGetKeyCounterAlg statelessRandomGetKeyCounterAlg( * The generated values will have mean 0 and standard deviation 1. *

The outputs are a deterministic function of {@code shape} and {@code seed}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @return a new instance of StatelessRandomNormal, with default output types @@ -845,7 +815,6 @@ public StatelessRandomNormal statelessRandomNormal(OperandThe outputs are a deterministic function of {@code shape} and {@code seed}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param dtype The type of the output. @@ -862,7 +831,6 @@ public StatelessRandomNormal statelessRandomNormal( * The generated values will have mean 0 and standard deviation 1. *

The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -879,7 +847,6 @@ public StatelessRandomNormalV2 statelessRandomNormalV2(OperandThe outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -899,7 +866,6 @@ public StatelessRandomNormalV2 statelessRandomNormalV2( * Outputs random values from a Poisson distribution. *

The outputs are a deterministic function of {@code shape}, {@code seed}, and {@code lam}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param lam The rate of the Poisson distribution. Shape must match the rightmost dimensions @@ -920,7 +886,6 @@ public StatelessRandomPoisson statelessRandomPoisson( * lower bound 0 is included in the range, while the upper bound 1 is excluded. *

The outputs are a deterministic function of {@code shape} and {@code seed}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @return a new instance of StatelessRandomUniform, with default output types @@ -936,7 +901,6 @@ public StatelessRandomUniform statelessRandomUniform(OperandThe outputs are a deterministic function of {@code shape} and {@code seed}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param dtype The type of the output. @@ -953,7 +917,6 @@ public StatelessRandomUniform statelessRandomUniform( * The generated values are uniform integers covering the whole range of {@code dtype}. *

The outputs are a deterministic function of {@code shape} and {@code seed}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param dtype The type of the output. @@ -970,7 +933,6 @@ public StatelessRandomUniformFullInt statelessRandomUnifo * The generated values are uniform integers covering the whole range of {@code dtype}. *

The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -990,7 +952,6 @@ public StatelessRandomUniformFullIntV2 statelessRandomUni * The generated values follow a uniform distribution in the range {@code [minval, maxval)}. *

The outputs are a deterministic function of {@code shape}, {@code seed}, {@code minval}, and {@code maxval}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param minval Minimum value (inclusive, scalar). @@ -1009,7 +970,6 @@ public StatelessRandomUniformInt statelessRandomUniformIn * The generated values follow a uniform distribution in the range {@code [minval, maxval)}. *

The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter}, {@code alg}, {@code minval} and {@code maxval}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -1031,7 +991,6 @@ public StatelessRandomUniformIntV2 statelessRandomUniform * lower bound 0 is included in the range, while the upper bound 1 is excluded. *

The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -1050,7 +1009,6 @@ public StatelessRandomUniformV2 statelessRandomUniformV2( * lower bound 0 is included in the range, while the upper bound 1 is excluded. *

The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -1072,7 +1030,6 @@ public StatelessRandomUniformV2 statelessRandomUniformV2( * deviations from the mean are dropped and re-picked. *

The outputs are a deterministic function of {@code shape} and {@code seed}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @return a new instance of StatelessTruncatedNormal, with default output types @@ -1089,7 +1046,6 @@ public StatelessTruncatedNormal statelessTruncatedNormal( * deviations from the mean are dropped and re-picked. *

The outputs are a deterministic function of {@code shape} and {@code seed}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param dtype The type of the output. @@ -1108,7 +1064,6 @@ public StatelessTruncatedNormal statelessTruncatedNormal( * deviations from the mean are dropped and re-picked. *

The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -1128,7 +1083,6 @@ public StatelessTruncatedNormalV2 statelessTruncatedNormalV2( * deviations from the mean are dropped and re-picked. *

The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -1176,7 +1130,6 @@ public ThreadUnsafeUnigramCandidateSampler threadUnsafeUnigramCandidateSampler( * deviation 1, except that values whose magnitude is more than 2 standard * deviations from the mean are dropped and re-picked. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param dtype The type of the output. * @param options carries optional attribute values diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ShapeOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ShapeOps.java index c9cdae676a4..68cb802f86d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ShapeOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ShapeOps.java @@ -388,7 +388,8 @@ public Operand tail(Shape shape, Class type) { * shape. * * @param shape the TensorFlow shape - * @param n the number of leading dimensions to get, must be <= than the shape's numDimensions() + * @param n the number of leading dimensions to get, must be less than or equal to the shape's + * numDimensions() * @return a 1-dimensional operand with the dimensions matching the first n dimensions of the * shape */ @@ -401,7 +402,8 @@ public Operand take(Shape shape, Operand n) { * shape. * * @param shape the TensorFlow shape - * @param n the number of leading dimensions to get, must be <= than the shape's numDimensions() + * @param n the number of leading dimensions to get, must be less than or equal to the shape's + * numDimensions() * @param type the shape datatype. * @param the shape datatype. * @return a 1-dimensional operand with the dimensions matching * the first n dimensions of the @@ -416,7 +418,8 @@ public Operand take(Shape shape, Operand n, Class Operand takeLast(Shape shape, Operand * shape. * * @param shape the TensorFlow shape - * @param n the number of leading dimensions to get, must be <= than the shape's numDimensions() + * @param n the number of leading dimensions to get, must be less than or equal to the shape's + * numDimensions() * @param type the shape datatype. * @param the shape datatype. * @return a 1-dimensional operand containing the dimensions matching the last n dimensions of the diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java index 33e2cd4d920..ac5703c264a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java @@ -125,7 +125,6 @@ public BatchIfft3d batchIfft3d(Operand input) { * Computes the 1-dimensional discrete Fourier transform over the inner-most * dimension of {@code input}. * - * @param data type for {@code output} output * @param input A complex tensor. * @param data type for {@code FFT} output and operands * @return a new instance of Fft @@ -139,7 +138,6 @@ public Fft fft(Operand input) { * Computes the 2-dimensional discrete Fourier transform over the inner-most * 2 dimensions of {@code input}. * - * @param data type for {@code output} output * @param input A complex tensor. * @param data type for {@code FFT2D} output and operands * @return a new instance of Fft2d @@ -153,7 +151,6 @@ public Fft2d fft2d(Operand input) { * Computes the 3-dimensional discrete Fourier transform over the inner-most 3 * dimensions of {@code input}. * - * @param data type for {@code output} output * @param input A complex tensor. * @param data type for {@code FFT3D} output and operands * @return a new instance of Fft3d @@ -173,7 +170,6 @@ public Fft3d fft3d(Operand input) { *

Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor. The FFT length for each dimension. * @param axes An int32 tensor with a same shape as fft_length. Axes to perform the transform. @@ -190,7 +186,6 @@ public FftNd fftNd(Operand input, Operand fftLen * Computes the inverse 1-dimensional discrete Fourier transform over the * inner-most dimension of {@code input}. * - * @param data type for {@code output} output * @param input A complex tensor. * @param data type for {@code IFFT} output and operands * @return a new instance of Ifft @@ -204,7 +199,6 @@ public Ifft ifft(Operand input) { * Computes the inverse 2-dimensional discrete Fourier transform over the * inner-most 2 dimensions of {@code input}. * - * @param data type for {@code output} output * @param input A complex tensor. * @param data type for {@code IFFT2D} output and operands * @return a new instance of Ifft2d @@ -218,7 +212,6 @@ public Ifft2d ifft2d(Operand input) { * Computes the inverse 3-dimensional discrete Fourier transform over the * inner-most 3 dimensions of {@code input}. * - * @param data type for {@code output} output * @param input A complex tensor. * @param data type for {@code IFFT3D} output and operands * @return a new instance of Ifft3d @@ -238,7 +231,6 @@ public Ifft3d ifft3d(Operand input) { *

Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor. The FFT length for each dimension. * @param axes An int32 tensor with a same shape as fft_length. Axes to perform the transform. @@ -264,7 +256,6 @@ public IfftNd ifftNd(Operand input, Operand fftL * than the corresponding dimension of {@code input}, the dimension is cropped. If it is * larger, the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor of shape [1]. The FFT length. * @return a new instance of Irfft, with default output types @@ -287,7 +278,6 @@ public Irfft irfft(Operand input, Operand fft * than the corresponding dimension of {@code input}, the dimension is cropped. If it is * larger, the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor of shape [1]. The FFT length. * @param Treal The value of the Treal attribute @@ -314,7 +304,6 @@ public Irfft irfft(Operand input, * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor of shape [2]. The FFT length for each dimension. * @return a new instance of Irfft2d, with default output types @@ -338,7 +327,6 @@ public Irfft2d irfft2d(Operand input, Operand * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor of shape [2]. The FFT length for each dimension. * @param Treal The value of the Treal attribute @@ -365,7 +353,6 @@ public Irfft2d irfft2d(Operand input, * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor of shape [3]. The FFT length for each dimension. * @return a new instance of Irfft3d, with default output types @@ -389,7 +376,6 @@ public Irfft3d irfft3d(Operand input, Operand * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor of shape [3]. The FFT length for each dimension. * @param Treal The value of the Treal attribute @@ -413,7 +399,6 @@ public Irfft3d irfft3d(Operand input, *

Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor. The FFT length for each dimension. * @param axes An int32 tensor with a same shape as fft_length. Axes to perform the transform. @@ -436,7 +421,6 @@ public IrfftNd irfftNd(Operand input, Operand *

Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor. The FFT length for each dimension. * @param axes An int32 tensor with a same shape as fft_length. Axes to perform the transform. @@ -460,7 +444,6 @@ public IrfftNd irfftNd(Operand input, * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A float32 tensor. * @param fftLength An int32 tensor of shape [1]. The FFT length. * @param Tcomplex The value of the Tcomplex attribute @@ -484,7 +467,6 @@ public Rfft rfft(Operand input, Operand< * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A float32 tensor. * @param fftLength An int32 tensor of shape [2]. The FFT length for each dimension. * @param Tcomplex The value of the Tcomplex attribute @@ -508,7 +490,6 @@ public Rfft2d rfft2d(Operand input, * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A float32 tensor. * @param fftLength An int32 tensor of shape [3]. The FFT length for each dimension. * @param Tcomplex The value of the Tcomplex attribute @@ -532,7 +513,6 @@ public Rfft3d rfft3d(Operand input, *

Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor. The FFT length for each dimension. * @param axes An int32 tensor with a same shape as fft_length. Axes to perform the transform. diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java index 91726a9a693..f6f83acce58 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java @@ -17,14 +17,18 @@ // package org.tensorflow.op; +import java.util.List; import org.tensorflow.Operand; import org.tensorflow.ndarray.Shape; import org.tensorflow.op.sparse.AddManySparseToTensorsMap; import org.tensorflow.op.sparse.AddSparseToTensorsMap; +import org.tensorflow.op.sparse.ConvertToListOfSparseCoreCooTensors; +import org.tensorflow.op.sparse.ConvertToSparseCoreCsrWrappedCooTensor; import org.tensorflow.op.sparse.DenseCountSparseOutput; import org.tensorflow.op.sparse.DenseToDenseSetOperation; import org.tensorflow.op.sparse.DenseToSparseSetOperation; import org.tensorflow.op.sparse.DeserializeSparse; +import org.tensorflow.op.sparse.GetStatsFromListOfSparseCoreCooTensors; import org.tensorflow.op.sparse.SparseAccumulatorApplyGradient; import org.tensorflow.op.sparse.SparseAccumulatorTakeGradient; import org.tensorflow.op.sparse.SparseAdd; @@ -68,6 +72,7 @@ import org.tensorflow.op.sparse.SparseToSparseSetOperation; import org.tensorflow.op.sparse.TakeManySparseFromTensorsMap; import org.tensorflow.types.TBool; +import org.tensorflow.types.TFloat32; import org.tensorflow.types.TInt32; import org.tensorflow.types.TInt64; import org.tensorflow.types.TString; @@ -151,11 +156,60 @@ public AddSparseToTensorsMap addSparseToTensorsMap(Operand sparseIndices return AddSparseToTensorsMap.create(scope, sparseIndices, sparseValues, sparseShape, options); } + /** + * The ConvertToListOfSparseCoreCooTensors operation + * + * @param indicesOrRowSplits The indicesOrRowSplits value + * @param values The values value + * @param weights The weights value + * @param sampleCount The value of the sampleCount attribute + * @param numScPerChip The value of the numScPerChip attribute + * @param rowOffset The value of the rowOffset attribute + * @param colOffset The value of the colOffset attribute + * @param colShift The value of the colShift attribute + * @param numScShards The value of the numScShards attribute + * @param stackedTableSampleCount The value of the stackedTableSampleCount attribute + * @param combiner The value of the combiner attribute + * @return a new instance of ConvertToListOfSparseCoreCooTensors + */ + public ConvertToListOfSparseCoreCooTensors convertToListOfSparseCoreCooTensors( + Operand indicesOrRowSplits, Operand values, Operand weights, + Long sampleCount, Long numScPerChip, Long rowOffset, Long colOffset, Long colShift, + Long numScShards, Long stackedTableSampleCount, String combiner) { + return ConvertToListOfSparseCoreCooTensors.create(scope, indicesOrRowSplits, values, weights, sampleCount, numScPerChip, rowOffset, colOffset, colShift, numScShards, stackedTableSampleCount, combiner); + } + + /** + * The ConvertToSparseCoreCsrWrappedCooTensor operation + * + * @param sortedRowIdsList The sortedRowIdsList value + * @param sortedColIdsList The sortedColIdsList value + * @param sortedGainsList The sortedGainsList value + * @param idCountsList The idCountsList value + * @param splits The splits value + * @param sampleCountPerSc The value of the sampleCountPerSc attribute + * @param numReplica The value of the numReplica attribute + * @param maxMinibatchesPerSc The value of the maxMinibatchesPerSc attribute + * @param maxIdsPerChipPerSample The value of the maxIdsPerChipPerSample attribute + * @param tableVocabSize The value of the tableVocabSize attribute + * @param featureWidth The value of the featureWidth attribute + * @param tableName The value of the tableName attribute + * @param allowIdDropping The value of the allowIdDropping attribute + * @return a new instance of ConvertToSparseCoreCsrWrappedCooTensor + */ + public ConvertToSparseCoreCsrWrappedCooTensor convertToSparseCoreCsrWrappedCooTensor( + Iterable> sortedRowIdsList, Iterable> sortedColIdsList, + Iterable> sortedGainsList, Iterable> idCountsList, + Operand splits, Long sampleCountPerSc, Long numReplica, Long maxMinibatchesPerSc, + Long maxIdsPerChipPerSample, Long tableVocabSize, Long featureWidth, String tableName, + Boolean allowIdDropping) { + return ConvertToSparseCoreCsrWrappedCooTensor.create(scope, sortedRowIdsList, sortedColIdsList, sortedGainsList, idCountsList, splits, sampleCountPerSc, numReplica, maxMinibatchesPerSc, maxIdsPerChipPerSample, tableVocabSize, featureWidth, tableName, allowIdDropping); + } + /** * Performs sparse-output bin counting for a tf.tensor input. * Counts the number of times each value occurs in the input. * - * @param data type for {@code output_values} output * @param values Tensor containing data to count. * @param weights A Tensor of the same shape as indices containing per-index weight values. May * also be the empty tensor if no weights are used. @@ -179,7 +233,6 @@ public DenseCountSparseOutput denseCountSparseOutput( * dimension contains the result of {@code set_operation} applied to the corresponding * {@code [0...n-1]} dimension of {@code set}. * - * @param data type for {@code result_values} output * @param set1 {@code Tensor} with rank {@code n}. 1st {@code n-1} dimensions must be the same as {@code set2}. * Dimension {@code n} contains values in a set, duplicates are allowed but ignored. * @param set2 {@code Tensor} with rank {@code n}. 1st {@code n-1} dimensions must be the same as {@code set1}. @@ -209,7 +262,6 @@ public DenseToDenseSetOperation denseToDenseSetOperation(Op * dimension contains the result of {@code set_operation} applied to the corresponding * {@code [0...n-1]} dimension of {@code set}. * - * @param data type for {@code result_values} output * @param set1 {@code Tensor} with rank {@code n}. 1st {@code n-1} dimensions must be the same as {@code set2}. * Dimension {@code n} contains values in a set, duplicates are allowed but ignored. * @param set2Indices 2D {@code Tensor}, indices of a {@code SparseTensor}. Must be in row-major @@ -272,7 +324,6 @@ public DenseToSparseSetOperation denseToSparseSetOperation( * shape = [2 50] * * - * @param data type for {@code sparse_values} output * @param serializedSparse The serialized {@code SparseTensor} objects. The last dimension * must have 3 columns. * @param dtype The {@code dtype} of the serialized {@code SparseTensor} objects. @@ -284,6 +335,29 @@ public DeserializeSparse deserializeSparse( return DeserializeSparse.create(scope, serializedSparse, dtype); } + /** + * The GetStatsFromListOfSparseCoreCooTensors operation + * + * @param rowIdsList The rowIdsList value + * @param colIdsList The colIdsList value + * @param gainsList The gainsList value + * @param sampleCountList The value of the sampleCountList attribute + * @param colOffsetList The value of the colOffsetList attribute + * @param numReplica The value of the numReplica attribute + * @param tableVocabSize The value of the tableVocabSize attribute + * @param featureWidth The value of the featureWidth attribute + * @param numScPerChip The value of the numScPerChip attribute + * @param tableName The value of the tableName attribute + * @return a new instance of GetStatsFromListOfSparseCoreCooTensors + */ + public GetStatsFromListOfSparseCoreCooTensors getStatsFromListOfSparseCoreCooTensors( + Iterable> rowIdsList, Iterable> colIdsList, + Iterable> gainsList, List sampleCountList, List colOffsetList, + Long numReplica, Long tableVocabSize, Long featureWidth, Long numScPerChip, + String tableName) { + return GetStatsFromListOfSparseCoreCooTensors.create(scope, rowIdsList, colIdsList, gainsList, sampleCountList, colOffsetList, numReplica, tableVocabSize, featureWidth, numScPerChip, tableName); + } + /** * Applies a sparse gradient to a given accumulator. * Does not add if local_step is smaller than the accumulator's @@ -317,7 +391,6 @@ public SparseAccumulatorApplyGradient sparseAccumulatorApplyGradient(Operand data type for {@code values} output * @param handle The handle to a SparseConditionalAccumulator. * @param numRequired Number of gradients required before we return an aggregate. * @param dtype The data type of accumulated gradients. Needs to correspond to the type @@ -344,7 +417,6 @@ public SparseAccumulatorTakeGradient sparseAccumulatorTakeG * only for a positive value. *

In the following shapes, {@code nnz} is the count after taking {@code thresh} into account. * - * @param data type for {@code sum_values} output * @param aIndices 2-D. The {@code indices} of the first {@code SparseTensor}, size {@code [nnz, ndims]} Matrix. * @param aValues 1-D. The {@code values} of the first {@code SparseTensor}, size {@code [nnz]} Vector. * @param aShape 1-D. The {@code shape} of the first {@code SparseTensor}, size {@code [ndims]} Vector. @@ -369,7 +441,6 @@ public SparseAdd sparseAdd(Operand aIndices, Operan * non-empty values of the sum, and outputs the gradients w.r.t. the non-empty * values of A and B. * - * @param data type for {@code a_val_grad} output * @param backpropValGrad 1-D with shape {@code [nnz(sum)]}. The gradient with respect to * the non-empty values of the sum. * @param aIndices 2-D. The {@code indices} of the {@code SparseTensor} A, size {@code [nnz(A), ndims]}. @@ -393,7 +464,6 @@ public SparseAddGrad sparseAddGrad(Operand backpropValGr * {@code i}. *

Values in {@code arr} outside of the range [0, size) are ignored. * - * @param data type for {@code output} output * @param indices 2D int64 {@code Tensor}. * @param values 1D int {@code Tensor}. * @param denseShape 1D int64 {@code Tensor}. @@ -452,7 +522,6 @@ public SparseBincount sparseBincount( * [b c ] [ ] [b c ] * * - * @param data type for {@code output_values} output * @param indices 2-D. Indices of each input {@code SparseTensor}. * @param values 1-D. Non-empty values of each {@code SparseTensor}. * @param shapes 1-D. Shapes of each {@code SparseTensor}. @@ -490,7 +559,6 @@ public SparseConditionalAccumulator sparseConditionalAccumulat * Performs sparse-output bin counting for a sparse tensor input. * Counts the number of times each value occurs in the input. * - * @param data type for {@code output_values} output * @param indices Tensor containing the indices of the sparse tensor to count. * @param values Tensor containing values of the sparse tensor to count. * @param denseShape Tensor containing the dense shape of the sparse tensor to count. @@ -624,7 +692,6 @@ public SparseCrossHashed sparseCrossHashed(Iterable> indices, * indices and shape, but possibly with different non-zero values. The output of * this Op is the resultant non-zero values. * - * @param data type for {@code output} output * @param spIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param spValues 1-D. {@code N} non-empty values corresponding to {@code sp_indices}. @@ -643,7 +710,6 @@ public SparseDenseCwiseAdd sparseDenseCwiseAdd(OperandLimitation: this Op only broadcasts the dense side to the sparse side, but not * the other direction. * - * @param data type for {@code output} output * @param spIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param spValues 1-D. {@code N} non-empty values corresponding to {@code sp_indices}. @@ -665,7 +731,6 @@ public SparseDenseCwiseDiv sparseDenseCwiseDiv(OperandLimitation: this Op only broadcasts the dense side to the sparse side, but not * the other direction. * - * @param data type for {@code output} output * @param spIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param spValues 1-D. {@code N} non-empty values corresponding to {@code sp_indices}. @@ -716,7 +781,6 @@ public SparseDenseCwiseMul sparseDenseCwiseMul(Operand * - * @param data type for {@code output_values} output * @param indices 2-D. the indices of the sparse tensor. * @param values 1-D. the values of the sparse tensor. * @param denseShape 1-D. the shape of the sparse tensor. @@ -741,7 +805,6 @@ public SparseFillEmptyRows sparseFillEmptyRows(Operand data type for {@code d_values} output * @param reverseIndexMap 1-D. The reverse index map from SparseFillEmptyRows. * @param gradValues 1-D. The gradients from backprop. * @param data type for {@code SparseFillEmptyRowsGrad} output and operands @@ -786,7 +849,6 @@ public SparseMatMul sparseMatMul(Operand a, Operand data type for {@code output} output * @param inputIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param inputValues 1-D. {@code N} non-empty values corresponding to {@code input_indices}. @@ -815,7 +877,6 @@ public SparseReduceMax sparseReduceMax(Operand in * with a single element is returned. Additionally, the axes can be negative, * which are interpreted according to the indexing rules in Python. * - * @param data type for {@code output_values} output * @param inputIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param inputValues 1-D. {@code N} non-empty values corresponding to {@code input_indices}. @@ -844,7 +905,6 @@ public SparseReduceMaxSparse sparseReduceMaxSparse( * with a single element is returned. Additionally, the axes can be negative, * which are interpreted according to the indexing rules in Python. * - * @param data type for {@code output} output * @param inputIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param inputValues 1-D. {@code N} non-empty values corresponding to {@code input_indices}. @@ -873,7 +933,6 @@ public SparseReduceSum sparseReduceSum(Operand inpu * with a single element is returned. Additionally, the axes can be negative, * which are interpreted according to the indexing rules in Python. * - * @param data type for {@code output_values} output * @param inputIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param inputValues 1-D. {@code N} non-empty values corresponding to {@code input_indices}. @@ -898,7 +957,6 @@ public SparseReduceSumSparse sparseReduceSumSparse( *

If the tensor has rank {@code R} and {@code N} non-empty values, {@code input_indices} has * shape {@code [N, R]}, input_values has length {@code N}, and input_shape has length {@code R}. * - * @param data type for {@code output_values} output * @param inputIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param inputValues 1-D. {@code N} non-empty values corresponding to {@code input_indices}. @@ -943,7 +1001,6 @@ public SparseReshape sparseReshape(Operand inputIndices, Operand *

Like {@code SegmentMean}, but {@code segment_ids} can have rank less than {@code data}'s first * dimension, selecting a subset of dimension 0, specified by {@code indices}. * - * @param data type for {@code output} output * @param data The data value * @param indices A 1-D tensor. Has same rank as {@code segment_ids}. * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated. @@ -963,8 +1020,6 @@ public SparseSegmentMean sparseSegmentMean(Operand dat * value is the number of unique indexes in "indices". Also returns vector * "sorted_unique_indices" containing the corresponding indexes from "indices". * - * @param data type for {@code output} output - * @param data type for {@code sorted_unique_indices} output * @param grad gradient propagated to the SparseSegmentMean op. * @param indices indices passed to the corresponding SparseSegmentMean op. * @param segmentIds segment_ids passed to the corresponding SparseSegmentMean op. @@ -987,7 +1042,6 @@ public SparseSegmentMeanGrad sparse * the section on segmentation * for an explanation of segments. * - * @param data type for {@code output} output * @param data The data value * @param indices A 1-D tensor. Has same rank as {@code segment_ids}. * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated. @@ -1007,7 +1061,6 @@ public SparseSegmentMeanWithNumSegments sparseSegmentMean * N is the size of the segment being reduced. *

See {@code tf.sparse.segment_sum} for usage examples. * - * @param data type for {@code output} output * @param data The data value * @param indices A 1-D tensor. Has same rank as {@code segment_ids}. * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated. @@ -1027,8 +1080,6 @@ public SparseSegmentSqrtN sparseSegmentSqrtN(Operand d * value is the number of unique indexes in "indices". Also returns vector * "sorted_unique_indices" containing the corresponding indexes from "indices". * - * @param data type for {@code output} output - * @param data type for {@code sorted_unique_indices} output * @param grad gradient propagated to the SparseSegmentSqrtN op. * @param indices indices passed to the corresponding SparseSegmentSqrtN op. * @param segmentIds segment_ids passed to the corresponding SparseSegmentSqrtN op. @@ -1052,7 +1103,6 @@ public SparseSegmentSqrtNGrad spars * the section on segmentation * for an explanation of segments. * - * @param data type for {@code output} output * @param data The data value * @param indices A 1-D tensor. Has same rank as {@code segment_ids}. * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated. @@ -1097,7 +1147,6 @@ public SparseSegmentSqrtNWithNumSegments sparseSegmentSqr * tf.segment_sum(c, tf.constant([0, 0, 1])) * * - * @param data type for {@code output} output * @param data The data value * @param indices A 1-D tensor. Has same rank as {@code segment_ids}. * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated. @@ -1117,8 +1166,6 @@ public SparseSegmentSum sparseSegmentSum(Operand data, * value is the number of unique indexes in "indices". Also returns vector * "sorted_unique_indices" containing the corresponding indexes from "indices". * - * @param data type for {@code output} output - * @param data type for {@code sorted_unique_indices} output * @param grad gradient propagated to the SparseSegmentSum op. * @param indices indices passed to the corresponding SparseSegmentSum op. * @param segmentIds segment_ids passed to the corresponding SparseSegmentSum op. @@ -1160,7 +1207,6 @@ public SparseSegmentSumGrad sparseS * # [ 0 0 0 0]] * * - * @param data type for {@code output} output * @param data The data value * @param indices A 1-D tensor. Has same rank as {@code segment_ids}. * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated. @@ -1194,7 +1240,6 @@ public SparseSegmentSumWithNumSegments sparseSegmentSumWi * [ ] * * - * @param data type for {@code output_values} output * @param indices 2-D tensor represents the indices of the sparse tensor. * @param values 1-D tensor represents the values of the sparse tensor. * @param shape 1-D. tensor represents the shape of the sparse tensor. @@ -1216,7 +1261,6 @@ public SparseSlice sparseSlice(Operand indices, Ope * the sliced {@code SparseTensor}, and outputs the gradients w.r.t. * the non-empty values of input {@code SparseTensor}. * - * @param data type for {@code val_grad} output * @param backpropValGrad 1-D. The gradient with respect to * the non-empty values of the sliced {@code SparseTensor}. * @param inputIndices 2-D. The {@code indices} of the input {@code SparseTensor}. @@ -1245,7 +1289,6 @@ public SparseSliceGrad sparseSliceGrad(Operand backpropV *

Hence, the {@code SparseTensor} result has exactly the same non-zero indices and * shape. * - * @param data type for {@code output} output * @param spIndices 2-D. {@code NNZ x R} matrix with the indices of non-empty values in a * SparseTensor, in canonical ordering. * @param spValues 1-D. {@code NNZ} non-empty values corresponding to {@code sp_indices}. @@ -1262,7 +1305,6 @@ public SparseSoftmax sparseSoftmax(Operand spIndi * Returns the element-wise max of two SparseTensors. * Assumes the two SparseTensors have the same shape, i.e., no broadcasting. * - * @param data type for {@code output_values} output * @param aIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, in the canonical lexicographic ordering. * @param aValues 1-D. {@code N} non-empty values corresponding to {@code a_indices}. @@ -1283,7 +1325,6 @@ public SparseSparseMaximum sparseSparseMaximum(Operand data type for {@code output_values} output * @param aIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, in the canonical lexicographic ordering. * @param aValues 1-D. {@code N} non-empty values corresponding to {@code a_indices}. @@ -1321,7 +1362,6 @@ public SparseSparseMinimum sparseSparseMinimum(Operand * - * @param data type for {@code output_values} output * @param splitDim 0-D. The dimension along which to split. Must be in the range * {@code [0, rank(shape))}. * @param indices 2-D tensor represents the indices of the sparse tensor. @@ -1342,7 +1382,6 @@ public SparseSplit sparseSplit(Operand splitDim, * Adds up a {@code SparseTensor} and a dense {@code Tensor}, producing a dense {@code Tensor}. * This Op does not require {@code a_indices} be sorted in standard lexicographic order. * - * @param data type for {@code output} output * @param aIndices 2-D. The {@code indices} of the {@code SparseTensor}, with shape {@code [nnz, ndims]}. * @param aValues 1-D. The {@code values} of the {@code SparseTensor}, with shape {@code [nnz]}. * @param aShape 1-D. The {@code shape} of the {@code SparseTensor}, with shape {@code [ndims]}. @@ -1367,7 +1406,6 @@ public SparseTensorDenseAdd sparseTensor * A should be sorted in order of increasing dimension 1 (i.e., "column major" * order instead of "row major" order). * - * @param data type for {@code product} output * @param aIndices 2-D. The {@code indices} of the {@code SparseTensor}, size {@code [nnz, 2]} Matrix. * @param aValues 1-D. The {@code values} of the {@code SparseTensor}, size {@code [nnz]} Vector. * @param aShape 1-D. The {@code shape} of the {@code SparseTensor}, size {@code [2]} Vector. @@ -1401,7 +1439,6 @@ public SparseTensorDenseMatMul sparseTensorDenseMatMul( * contain any repeats. If {@code validate_indices} is true, these properties * are checked during execution. * - * @param data type for {@code dense} output * @param sparseIndices 0-D, 1-D, or 2-D. {@code sparse_indices[i]} contains the complete * index where {@code sparse_values[i]} will be placed. * @param outputShape 1-D. Shape of the dense output tensor. @@ -1441,7 +1478,6 @@ public SparseToDense sparseToDense( * dimension contains the result of {@code set_operation} applied to the corresponding * {@code [0...n-1]} dimension of {@code set}. * - * @param data type for {@code result_values} output * @param set1Indices 2D {@code Tensor}, indices of a {@code SparseTensor}. Must be in row-major * order. * @param set1Values 1D {@code Tensor}, values of a {@code SparseTensor}. Must be in row-major @@ -1511,7 +1547,6 @@ public SparseToSparseSetOperation sparseToSparseSetOperatio * shape = [2 50] * * - * @param data type for {@code sparse_values} output * @param sparseHandles 1-D, The {@code N} serialized {@code SparseTensor} objects. * Shape: {@code [N]}. * @param dtype The {@code dtype} of the {@code SparseTensor} objects stored in the diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java index b7d38d58553..56a82c2dbf6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java @@ -260,7 +260,6 @@ public StringLength stringLength(Operand input, StringLength.Options... * strings and outputs a ragged tensor with 1 ragged dimension containing ngrams * of that string, joined along the innermost axis. * - * @param data type for {@code ngrams_splits} output * @param data The values tensor of the ragged string tensor to make ngrams out of. Must be a * 1D string tensor. * @param dataSplits The splits tensor of the ragged string tensor to make ngrams out of. @@ -510,7 +509,6 @@ public ToHashBucketStrong toHashBucketStrong(Operand input, Long numBuc * * * - * @param data type for {@code output} output * @param stringTensor The stringTensor value * @return a new instance of ToNumber, with default output types */ @@ -533,7 +531,6 @@ public ToNumber toNumber(Operand stringTensor) { * * * - * @param data type for {@code output} output * @param stringTensor The stringTensor value * @param outType The numeric type to interpret each string in {@code string_tensor} as. * @param data type for {@code StringToNumber} output and operands @@ -559,7 +556,6 @@ public ToNumber toNumber(Operand stringTensor, C * string (in row-major order). * * - * @param data type for {@code row_splits} output * @param input The text to be decoded. Can have any shape. Note that the output is flattened * to a vector of char values. * @param inputEncoding Text encoding of the input strings. This is any of the encodings supported @@ -588,7 +584,6 @@ public UnicodeDecode unicodeDecode(Operand input, String inputE * string (in row-major order). * * - * @param data type for {@code row_splits} output * @param input The text to be decoded. Can have any shape. Note that the output is flattened * to a vector of char values. * @param inputEncoding Text encoding of the input strings. This is any of the encodings supported @@ -623,7 +618,6 @@ public UnicodeDecode unicodeDecode(Operand input * string (in row-major order). * * - * @param data type for {@code row_splits} output * @param input The text to be decoded. Can have any shape. Note that the output is flattened * to a vector of char values. * @param inputEncoding Text encoding of the input strings. This is any of the encodings supported @@ -656,7 +650,6 @@ public UnicodeDecodeWithOffsets unicodeDecodeWithOffsets(Operand * * - * @param data type for {@code row_splits} output * @param input The text to be decoded. Can have any shape. Note that the output is flattened * to a vector of char values. * @param inputEncoding Text encoding of the input strings. This is any of the encodings supported diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TpuOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TpuOps.java index 59a9f973858..f6ea8e12178 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TpuOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TpuOps.java @@ -26,8 +26,6 @@ import org.tensorflow.op.tpu.CompilationResult; import org.tensorflow.op.tpu.Compile; import org.tensorflow.op.tpu.CompileSucceededAssert; -import org.tensorflow.op.tpu.ComputeDedupDataSize; -import org.tensorflow.op.tpu.ComputeDedupDataTupleMask; import org.tensorflow.op.tpu.ConfigureAndInitializeGlobalTPU; import org.tensorflow.op.tpu.ConfigureDistributedTPU; import org.tensorflow.op.tpu.ConfigureTPUEmbedding; @@ -52,6 +50,7 @@ import org.tensorflow.op.tpu.FinalizeTPUEmbedding; import org.tensorflow.op.tpu.GetMinibatchSplitsWithPhysicalReplica; import org.tensorflow.op.tpu.GetMinibatchesInCsrWithPhysicalReplica; +import org.tensorflow.op.tpu.GetTpuTaskId; import org.tensorflow.op.tpu.GlobalIterId; import org.tensorflow.op.tpu.InfeedDequeue; import org.tensorflow.op.tpu.InfeedDequeueTuple; @@ -158,7 +157,6 @@ public final class TpuOps { *

replica 0's output: {@code [[A], [C]]} * replica 1's output: {@code [[B], [D]]} * - * @param data type for {@code output} output * @param input The local input to the sum. * @param groupAssignment An int32 tensor with shape * [num_groups, num_replicas_per_group]. {@code group_assignment[i]} represents the @@ -242,32 +240,6 @@ public CompileSucceededAssert compileSucceededAssert(Operand compilatio return CompileSucceededAssert.create(scope, compilationStatus); } - /** - * An op computes the size of the deduplication data from embedding core and returns the updated config. - * This op is to compute size of the deduplication data so to provide this - * information to the op that computes the tuple mask of deduplication data can - * have static output shape. - * - * @param config Serialized TPUEmbeddingConfiguration proto. - * @return a new instance of ComputeDedupDataSize - */ - public ComputeDedupDataSize computeDedupDataSize(String config) { - return ComputeDedupDataSize.create(scope, config); - } - - /** - * An op computes tuple mask of deduplication data from embedding core. - * The deduplication data receiving from embedding core is a Tensor with - * type=DT_VARIANT. The tensor itself is an XLA nested tuple, whose elements are - * rank 1 tensors. This op is to represents types and length of these elements. - * - * @param config Serialized TPUEmbeddingConfiguration proto. - * @return a new instance of ComputeDedupDataTupleMask - */ - public ComputeDedupDataTupleMask computeDedupDataTupleMask(String config) { - return ComputeDedupDataTupleMask.create(scope, config); - } - /** * An op that sets up the centralized structures for a distributed TPU system. * @@ -365,7 +337,6 @@ public ConvertToCooTensor convertToCooTensor(Operand indicesOrRowSplits, * and {@code B, D, F, H} as group 1. Thus we get the outputs: * {@code [A+C+E+G, B+D+F+H, A+C+E+G, B+D+F+H, A+C+E+G, B+D+F+H, A+C+E+G, B+D+F+H]}. * - * @param data type for {@code output} output * @param input The local input to the sum. * @param groupAssignment An int32 tensor with shape * [num_groups, num_replicas_per_group]. {@code group_assignment[i]} represents the @@ -789,6 +760,16 @@ public GetMinibatchesInCsrWithPhysicalReplica getMinibatchesInCsrWithPhysicalRep return GetMinibatchesInCsrWithPhysicalReplica.create(scope, programKey, rowIds, colIds, gains, splits, idCounts, sampleCount, numReplica, maxMinibatchesPerSc, maxIdsPerChipPerSample, tableVocabSize, featureWidth, numScPerChip, tableName, miniBatchInCsr); } + /** + * An op returns the TPU task ID from TPU topology. + * This op is to return the TPU task ID from TPU topology. + * + * @return a new instance of GetTpuTaskId + */ + public GetTpuTaskId getTpuTaskId() { + return GetTpuTaskId.create(scope); + } + /** * The GlobalIterId operation * @@ -801,7 +782,6 @@ public GlobalIterId globalIterId() { /** * A placeholder op for a value that will be fed into the computation. * - * @param data type for {@code output} output * @param dtype The type of elements in the tensor. * @param shape The shape of the tensor. * @param data type for {@code InfeedDequeue} output and operands @@ -1252,7 +1232,6 @@ public OrdinalSelector ordinalSelector() { * Retrieves a single tensor from the computation outfeed. * This operation will block indefinitely until data is available. * - * @param data type for {@code output} output * @param dtype The type of elements in the tensor. * @param shape The shape of the tensor. * @param options carries optional attribute values @@ -1302,7 +1281,6 @@ public OutfeedDequeueTupleV2 outfeedDequeueTupleV2(Operand deviceOrdinal * tensor allowing dynamic outfeed. * This operation will block indefinitely until data is available. * - * @param data type for {@code output} output * @param deviceOrdinal An int scalar tensor, representing the TPU device to use. This should be -1 when * the Op is running on a TPU device, and >= 0 when the Op is running on the CPU * device. @@ -1355,7 +1333,6 @@ public PartitionedCall partitionedCall(Iterable> args, Operand data type for {@code output} output * @param inputs A list of partitioned inputs which must have the same shape. * @param partitionDims A list of integers describing how each dimension is partitioned. Emptiness * indicates the inputs are replicated. @@ -1372,7 +1349,6 @@ public PartitionedInput partitionedInput(Iterable data type for {@code output} output * @param inputs A tensor which represents the full shape of partitioned tensors. * @param numSplits The value of the numSplits attribute * @param partitionDims A list of integers describing how each dimension is partitioned. Emptiness @@ -1454,7 +1430,6 @@ public ReplicateMetadata replicateMetadata(Long numReplicas, * *

The above computation has a replicated input of two replicas. * - * @param data type for {@code output} output * @param inputs The inputs value * @param options carries optional attribute values * @param data type for {@code TPUReplicatedInput} output and operands @@ -1476,7 +1451,6 @@ public ReplicatedInput replicatedInput(Iterable> * *

The above computation has a replicated output of two replicas. * - * @param data type for {@code outputs} output * @param input The input value * @param numReplicas The value of the numReplicas attribute * @param data type for {@code TPUReplicatedOutput} output and operands @@ -1784,8 +1758,6 @@ public ShutdownTPUSystem shutdownTPUSystem() { * values. This op is to split these values into two groups for two types, and * construct each group as one tensor to return. * - * @param data type for {@code integer_tensor} output - * @param data type for {@code float_tensor} output * @param input An XLA tuple including integer and float elements as deduplication data tuple. * @param integerType integer_tensor type. Allowed types: int32, int64, uint32, uint64. * @param floatType float_tensor type. Allowed types: half, bfloat16, float. @@ -1913,7 +1885,6 @@ public TPUReplicateMetadata tPUReplicateMetadata(Long numReplicas, * *

The above computation has a replicated input of two replicas. * - * @param data type for {@code output} output * @deprecated use {@link org.tensorflow.op.tpu.ReplicatedInput} instead * @param inputs The inputs value * @param options carries optional attribute values @@ -1937,7 +1908,6 @@ public TPUReplicatedInput tPUReplicatedInput(Iterable *

The above computation has a replicated output of two replicas. * - * @param data type for {@code outputs} output * @deprecated use {@link org.tensorflow.op.tpu.ReplicatedOutput} instead * @param input The input value * @param numReplicas The value of the numReplicas attribute diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java index 0442b896828..3ee5b8de813 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java @@ -166,7 +166,6 @@ public AccumulatorSetGlobalStep accumulatorSetGlobalStep(Operand handle * the accumulated gradients. Also automatically increments the recorded * global_step in the accumulator by 1, and resets the aggregate to 0. * - * @param data type for {@code average} output * @param handle The handle to an accumulator. * @param numRequired Number of gradients required before we return an aggregate. * @param dtype The data type of accumulated gradients. Needs to correspond to the type @@ -185,7 +184,6 @@ public AccumulatorTakeGradient accumulatorTakeGradient( * v_t <- max(beta2 * v_{t-1}, abs(g)) * variable <- variable - learning_rate / (1 - beta1^t) * m_t / (v_t + epsilon) * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param m Should be from a Variable(). * @param v Should be from a Variable(). @@ -212,7 +210,6 @@ public ApplyAdaMax applyAdaMax(Operand var, Operand m * update_accum = rho() * update_accum + (1 - rho()) * update.square(); * var -= update; * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param accumUpdate Should be from a Variable(). @@ -235,7 +232,6 @@ public ApplyAdadelta applyAdadelta(Operand var, Operand< * accum += grad * grad * var -= lr * grad * (1 / sqrt(accum)) * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param lr Scaling factor. Must be a scalar. @@ -252,7 +248,6 @@ public ApplyAdagrad applyAdagrad(Operand var, Operand /** * Update '*var' according to the proximal adagrad scheme. * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param gradientAccumulator Should be from a Variable(). * @param gradientSquaredAccumulator Should be from a Variable(). @@ -277,7 +272,6 @@ public ApplyAdagradDa applyAdagradDa(Operand var, * accum += grad * grad * var -= lr * grad * (1 / sqrt(accum)) * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param lr Scaling factor. Must be a scalar. @@ -299,7 +293,6 @@ public ApplyAdagradV2 applyAdagradV2(Operand var, Operan * $$v_t := \beta_2 \cdot v_{t-1} + (1 - \beta_2) \cdot g^2$$ * $$\text{var} := \begin{cases} \text{var} - (m_t \beta_1 + g \cdot (1 - \beta_1))\cdot\text{lr}_t/(\sqrt{v_t} + \epsilon), &\text{if use_nesterov}\\ \text{var} - m_t \cdot \text{lr}_t /(\sqrt{v_t} + \epsilon), &\text{otherwise} \end{cases}$$ * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param m Should be from a Variable(). * @param v Should be from a Variable(). @@ -326,7 +319,6 @@ public ApplyAdam applyAdam(Operand var, Operand m, Op * update <- (alpha + sign_decay * sign(g) *sign(m)) * g * variable <- variable - lr_t * update * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param m Should be from a Variable(). * @param lr Scaling factor. Must be a scalar. @@ -361,7 +353,6 @@ public ApplyAddSign applyAddSign(Operand var, Operand * mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms - mg * mg + epsilon) * var <- var - mom * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param mg Should be from a Variable(). * @param ms Should be from a Variable(). @@ -392,7 +383,6 @@ public ApplyCenteredRmsProp applyCenteredRmsProp(Operand * var = (sign(linear) * l1 - linear) / quadratic if |linear| > l1 else 0.0 * accum = accum_new * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param linear Should be from a Variable(). @@ -415,7 +405,6 @@ public ApplyFtrl applyFtrl(Operand var, Operand accum /** * Update '*var' by subtracting 'alpha' * 'delta' from it. * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param alpha Scaling factor. Must be a scalar. * @param delta The change. @@ -434,7 +423,6 @@ public ApplyGradientDescent applyGradientDescent(Operand *

accum = accum * momentum + grad * var -= lr * accum * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param lr Scaling factor. Must be a scalar. @@ -455,7 +443,6 @@ public ApplyMomentum applyMomentum(Operand var, Operand< * update <- exp(logbase * sign_decay * sign(g) * sign(m_t)) * g * variable <- variable - lr_t * update * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param m Should be from a Variable(). * @param lr Scaling factor. Must be a scalar. @@ -479,7 +466,6 @@ public ApplyPowerSign applyPowerSign(Operand var, Operan * prox_v = var - lr * grad * (1 / sqrt(accum)) * var = sign(prox_v)/(1+lrl2) * max{|prox_v|-lrl1,0} * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param lr Scaling factor. Must be a scalar. @@ -501,7 +487,6 @@ public ApplyProximalAdagrad applyProximalAdagrad(Operand * prox_v = var - alpha * delta * var = sign(prox_v)/(1+alphal2) * max{|prox_v|-alphal1,0} * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param alpha Scaling factor. Must be a scalar. * @param l1 L1 regularization. Must be a scalar. @@ -528,7 +513,6 @@ public ApplyProximalGradientDescent applyProximalGradientDe * mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon) * var <- var - mom * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param ms Should be from a Variable(). * @param mom Should be from a Variable(). @@ -570,7 +554,6 @@ public ApplyRmsProp applyRmsProp(Operand var, Operand * about broadcasting * here . * - * @param data type for {@code output} output * @param x 2-D or higher with shape {@code [..., r_x, c_x]}. * @param y 2-D or higher with shape {@code [..., r_y, c_y]}. * @param Tout If not spcified, Tout is the same type to input type. @@ -717,7 +700,6 @@ public NegTrain negTrain(Operand wIn, Operand wOut, Operand< * op exists to prevent subtle bugs from silently returning unimplemented * gradients in some corner cases. * - * @param data type for {@code output} output * @param input any tensor. * @param options carries optional attribute values * @param data type for {@code PreventGradient} output and operands @@ -776,7 +758,6 @@ public ResourceAccumulatorSetGlobalStep resourceAccumulatorSetGlobalStep( * the accumulated gradients. Also automatically increments the recorded * global_step in the accumulator by 1, and resets the aggregate to 0. * - * @param data type for {@code average} output * @param handle The handle to an accumulator. * @param numRequired Number of gradients required before we return an aggregate. * @param dtype The data type of accumulated gradients. Needs to correspond to the type @@ -1535,7 +1516,6 @@ public Restore restore(Operand prefix, Operand tensorNames, *

The {@code shape_and_slice} input has the same format as the * elements of the {@code shapes_and_slices} input of the {@code SaveSlices} op. * - * @param data type for {@code tensor} output * @param filePattern Must have a single element. The pattern of the files from * which we read the tensor. * @param tensorName Must have a single element. The name of the tensor to be @@ -1687,7 +1667,6 @@ public SdcaShrinkL1 sdcaShrinkL1(Iterable> weights, Float l1, /** * var: Should be from a Variable(). * - * @param data type for {@code out} output * @param var The var value * @param accum Should be from a Variable(). * @param accumUpdate : Should be from a Variable(). @@ -1712,7 +1691,6 @@ public SparseApplyAdadelta sparseApplyAdadelta(Operand v * $$accum += grad * grad$$ * $$var -= lr * grad * (1 / sqrt(accum))$$ * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param lr Learning rate. Must be a scalar. @@ -1732,7 +1710,6 @@ public SparseApplyAdagrad sparseApplyAdagrad(Operand var /** * Update entries in '*var' and '*accum' according to the proximal adagrad scheme. * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param gradientAccumulator Should be from a Variable(). * @param gradientSquaredAccumulator Should be from a Variable(). @@ -1769,7 +1746,6 @@ public SparseApplyAdagradDa sparseApplyAdagradDa(Operand * $$mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)$$ * $$var <- var - mom$$ * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param mg Should be from a Variable(). * @param ms Should be from a Variable(). @@ -1802,7 +1778,6 @@ public SparseApplyCenteredRmsProp sparseApplyCenteredRmsPro * var = (sign(linear) * l1 - linear) / quadratic if |linear| > l1 else 0.0 * accum = accum_new * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param linear Should be from a Variable(). @@ -1831,7 +1806,6 @@ public SparseApplyFtrl sparseApplyFtrl(Operand var, Oper *

$$accum = accum * momentum + grad$$ * $$var -= lr * accum$$ * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param lr Learning rate. Must be a scalar. @@ -1856,7 +1830,6 @@ public SparseApplyMomentum sparseApplyMomentum(Operand v * $$prox_v -= lr * grad * (1 / sqrt(accum))$$ * $$var = sign(prox_v)/(1+lrl2) * max{|prox_v|-lrl1,0}$$ * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param lr Learning rate. Must be a scalar. @@ -1880,7 +1853,6 @@ public SparseApplyProximalAdagrad sparseApplyProximalAdagra * $$prox_v = var - alpha * grad$$ * $$var = sign(prox_v)/(1+alphal2) * max{|prox_v|-alphal1,0}$$ * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param alpha Scaling factor. Must be a scalar. * @param l1 L1 regularization. Must be a scalar. @@ -1908,7 +1880,6 @@ public SparseApplyProximalGradientDescent sparseApplyProxim * $$mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)$$ * $$var <- var - mom$$ * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param ms Should be from a Variable(). * @param mom Should be from a Variable(). @@ -1960,7 +1931,6 @@ public SymbolicGradient symbolicGradient(Iterable> input, * along each dimension, {@code train.TileGrad} takes in {@code multiples} and aggregates * each repeated tile of {@code input} into {@code output}. * - * @param data type for {@code output} output * @param input The input value * @param multiples The multiples value * @param data type for {@code TileGrad} output and operands diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java index 75f9104ce4b..22a2ef5ae85 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java @@ -27,9 +27,6 @@ import org.tensorflow.op.xla.SplitND; import org.tensorflow.op.xla.XlaHostCompute; import org.tensorflow.op.xla.XlaRecvFromHost; -import org.tensorflow.op.xla.XlaRecvTPUEmbeddingActivations; -import org.tensorflow.op.xla.XlaRecvTPUEmbeddingDeduplicationData; -import org.tensorflow.op.xla.XlaSendTPUEmbeddingGradients; import org.tensorflow.op.xla.XlaSendToHost; import org.tensorflow.op.xla.XlaSparseCoreAdagrad; import org.tensorflow.op.xla.XlaSparseCoreAdagradMomentum; @@ -95,18 +92,8 @@ public final class XlaOps { * * * @param resource Resource variable for concatenated input tensors across all dimensions. - * } - * in_arg { - * name: "inputs" - * description: <<END - * Input tensor slices in row-major order to merge across all dimensions. All + * @param inputs Input tensor slices in row-major order to merge across all dimensions. All * inputs must have the same shape. - * } - * out_arg { - * name: "output" - * description: <<END - * Output tensor formed from merging input slices based on num_concats defined. - * @param inputs The inputs value * @param numConcats Number of ways to merge per dimension. * @param options carries optional attribute values * @return a new instance of AssignVariableConcatND @@ -149,14 +136,8 @@ public AssignVariableConcatND assignVariableConcatND(Operand re * [8, 9, 10]] * * - * @param data type for {@code output} output * @param inputs Input tensor slices in row-major order to merge across all dimensions. All * inputs must have the same shape. - * } - * out_arg { - * name: "output" - * description: <<END - * Output tensor formed from merging input slices based on num_concats defined. * @param numConcats Number of ways to merge per dimension. * @param options carries optional attribute values * @param data type for {@code XlaConcatND} output and operands @@ -199,13 +180,7 @@ public ConcatND concatND(Iterable> inputs, List< * [0, 0]] * * - * @param data type for {@code outputs} output * @param resource Resource variable of input tensor to split across all dimensions. - * } - * out_arg { - * name: "outputs" - * description: <<END - * Output slices based on input and num_splits defined, in row-major order. * @param T The value of the T attribute * @param N The value of the N attribute * @param numSplits Number of ways to split per dimension. Shape dimensions must be evenly @@ -252,13 +227,7 @@ public ReadVariableSplitND readVariableSplitND( * [0, 0]] * * - * @param data type for {@code outputs} output * @param input Input tensor to split across all dimensions. - * } - * out_arg { - * name: "outputs" - * description: <<END - * Output slices based on input and num_splits defined, in row-major order. * @param N The value of the N attribute * @param numSplits Number of ways to split per dimension. Shape dimensions must be evenly * divisible. @@ -298,7 +267,6 @@ public XlaHostCompute xlaHostCompute(Iterable> inputs, * shape: shape for output. * key: A unique identifier for this region used to match up host transfers. * - * @param data type for {@code output} output * @param Toutput The value of the Toutput attribute * @param shape The value of the shape attribute * @param key The value of the key attribute @@ -310,76 +278,6 @@ public XlaRecvFromHost xlaRecvFromHost(Class Toutput, Sh return XlaRecvFromHost.create(scope, Toutput, shape, key); } - /** - * An op that receives embedding activations on the TPU. - * The TPU system performs the embedding lookups and aggregations. The results of - * these aggregations are visible to the Tensorflow Graph as the outputs of a - * XlaRecvTPUEmbeddingActivations Op. This op returns a list containing one - * Tensor of activations per table specified in the model. - * - * @param deduplicationData A Tensor with type=DT_VARIANT containing the deduplication - * data. The tensor is an XLA nested tuple containing N elements (where N is - * the ratio of the number of embedding to tensor cores per TPU chip). Each - * element of the nested tuple is a tuple of rank 1 tensors. Each tensor either - * contains indices (DT_UINT32) for embedding lookup on the TensorCore or - * weights (DT_FLOAT) to apply to the output of the embedding lookup operation. - * @param numTables The number of output activation tensors. If feature descriptor is - * present in the tpu embedding config, it is equal to the number of features - * otherwise equal to number of embedding tables in the model. - * @param config Serialized TPUEmbeddingConfiguration proto. - * @return a new instance of XlaRecvTPUEmbeddingActivations - */ - public XlaRecvTPUEmbeddingActivations xlaRecvTPUEmbeddingActivations( - Operand deduplicationData, Long numTables, String config) { - return XlaRecvTPUEmbeddingActivations.create(scope, deduplicationData, numTables, config); - } - - /** - * Receives deduplication data (indices and weights) from the embedding core. - * The deduplication data is a Tensor with type=DT_VARIANT. The tensor itself is an - * XLA nested tuple containing N elements (where N is the ratio of the number of - * embedding to tensor cores per TPU chip). Each element of the nested tuple is a - * tuple of rank 1 tensors. Each tensor either contains indices (DT_UINT32) for - * embedding lookup on the TensorCore or weights (DT_FLOAT) to apply to the output - * of the embedding lookup operation. - * - * @param config Serialized TPUEmbeddingConfiguration proto. - * @return a new instance of XlaRecvTPUEmbeddingDeduplicationData - */ - public XlaRecvTPUEmbeddingDeduplicationData xlaRecvTPUEmbeddingDeduplicationData(String config) { - return XlaRecvTPUEmbeddingDeduplicationData.create(scope, config); - } - - /** - * An op that performs gradient updates of embedding tables. - * The gradients argument is a TensorList having the same length and shapes as the - * return value of XlaRecvTPUEmbeddingActivations, but contains gradients of the - * model's loss with respect to the embedding activations. The embedding tables are - * updated from these gradients via the optimizer specified in the - * TPUEmbeddingConfiguration proto given to tpu.initialize_system. - * - * @param gradients A TensorList of gradients with which to update embedding tables. - * @param learningRates A TensorList of learning rates used for updating the embedding - * tables via the optimizer. The length of the TensorList must be equal to the - * number of dynamic learning rate tags specified in the - * TPUEmbeddingConfiguration proto. - * @param deduplicationData A Tensor with type=DT_VARIANT containing the deduplication - * data. The tensor is an XLA nested tuple containing N elements (where N is - * the ratio of the number of embedding to tensor cores per TPU chip). Each - * element of the nested tuple is a tuple of rank 1 tensors. Each tensor either - * contains indices (DT_UINT32) for embedding lookup on the TensorCore or - * weights (DT_FLOAT) to apply to the output of the embedding lookup operation. - * @param config Serialized TPUEmbeddingConfiguration proto. - * @param options carries optional attribute values - * @return a new instance of XlaSendTPUEmbeddingGradients - */ - public XlaSendTPUEmbeddingGradients xlaSendTPUEmbeddingGradients( - Iterable> gradients, Iterable> learningRates, - Operand deduplicationData, String config, - XlaSendTPUEmbeddingGradients.Options... options) { - return XlaSendTPUEmbeddingGradients.create(scope, gradients, learningRates, deduplicationData, config, options); - } - /** * An op to send a tensor to the host. * input: the tensor that will be sent to the host. diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java index 34789dce80c..7fea36a03b3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java @@ -52,8 +52,6 @@ * res = bitwise_ops.bitwise_and(lhs, rhs) * tf.assert_equal(tf.cast(res, tf.float32), exp) # TRUE * - * - * @param data type for {@code z} output */ @OpMetadata( opType = BitwiseAnd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java index afa384f6e38..1e57451698b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java @@ -52,8 +52,6 @@ * res = bitwise_ops.bitwise_or(lhs, rhs) * tf.assert_equal(tf.cast(res, tf.float32), exp) # TRUE * - * - * @param data type for {@code z} output */ @OpMetadata( opType = BitwiseOr.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java index dc26dc145aa..52953422482 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java @@ -52,8 +52,6 @@ * res = bitwise_ops.bitwise_xor(lhs, rhs) * tf.assert_equal(tf.cast(res, tf.float32), exp) # TRUE * - * - * @param data type for {@code z} output */ @OpMetadata( opType = BitwiseXor.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java index a2d9a985bae..8dcb5a72de7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java @@ -73,8 +73,6 @@ * expected = tf.constant([dtype.max - x for x in inputs], dtype=tf.float32) * tf.assert_equal(tf.cast(inverted, tf.float32), tf.cast(expected, tf.float32)) * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Invert.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java index 5874dc12979..ccf41c473f8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java @@ -63,8 +63,6 @@ * bitwise_ops.left_shift(lhs, rhs) * # <tf.Tensor: shape=(4,), dtype=int8, numpy=array([ -2, 64, 101, 32], dtype=int8)> * - * - * @param data type for {@code z} output */ @OpMetadata( opType = LeftShift.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java index 22c95c81136..6c1407b9d19 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java @@ -65,8 +65,6 @@ * bitwise_ops.right_shift(lhs, rhs) * # <tf.Tensor: shape=(4,), dtype=int8, numpy=array([ -2, 64, 101, 32], dtype=int8)> * - * - * @param data type for {@code z} output */ @OpMetadata( opType = RightShift.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveAllToAll.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveAllToAll.java index 99ccff79289..9c513486b9b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveAllToAll.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveAllToAll.java @@ -37,8 +37,6 @@ /** * Mutually exchanges multiple tensors of identical type and shape. - * - * @param data type for {@code data} output */ @OpMetadata( opType = CollectiveAllToAll.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastRecv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastRecv.java index 332b5dcf9ab..a66995e4d4e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastRecv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastRecv.java @@ -38,8 +38,6 @@ /** * Receives a tensor value broadcast from another device. - * - * @param data type for {@code data} output */ @OpMetadata( opType = CollectiveBcastRecv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastSend.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastSend.java index ee495b56951..df7a315413f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastSend.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastSend.java @@ -36,8 +36,6 @@ /** * Broadcasts a tensor value to one or more other devices. - * - * @param data type for {@code data} output */ @OpMetadata( opType = CollectiveBcastSend.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveGather.java index d3997e8743f..57a2b134ff6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveGather.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveGather.java @@ -41,8 +41,6 @@ * {@code is_stateless} means each op does not need control dependencies to other * collective ops. In this case, keys that are unique at runtime * (e.g. {@code instance_key}) should be used to distinguish collective groups. - * - * @param data type for {@code data} output */ @OpMetadata( opType = CollectiveGather.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectivePermute.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectivePermute.java index 9fd029facf3..380a949a664 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectivePermute.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectivePermute.java @@ -40,8 +40,6 @@ *

For example, suppose there are 4 TPU instances: {@code [A, B, C, D]}. Passing * source_target_pairs={@code [[0,1],[1,2],[2,3],[3,0]]} gets the outputs: * {@code [D, A, B, C]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CollectivePermute.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduce.java index 7eab3bb0f17..8f6c26778e1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduce.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduce.java @@ -37,8 +37,6 @@ /** * Mutually reduces multiple tensors of identical type and shape. - * - * @param data type for {@code data} output */ @OpMetadata( opType = CollectiveReduce.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduceScatter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduceScatter.java index 5ab06edf273..8b89dbaf183 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduceScatter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduceScatter.java @@ -41,8 +41,6 @@ * {@code is_stateless} means each op does not need control dependencies to other * collective ops. In this case, keys that are unique at runtime * (e.g. {@code instance_key}) should be used to distinguish collective groups. - * - * @param data type for {@code data} output */ @OpMetadata( opType = CollectiveReduceScatter.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ApproxTopK.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ApproxTopK.java index 1daca9f077e..48f4f94315b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ApproxTopK.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ApproxTopK.java @@ -38,8 +38,6 @@ * Returns min/max k values and their indices of the input operand in an approximate manner. * See https://arxiv.org/abs/2206.14286 for the algorithm details. * This op is only optimized on TPU currently. - * - * @param data type for {@code values} output */ @OpMetadata( opType = ApproxTopK.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Assign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Assign.java index a8001c6103a..e49f3eafacc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Assign.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Assign.java @@ -37,8 +37,6 @@ * Update 'ref' by assigning 'value' to it. * This operation outputs "ref" after the assignment is done. * This makes it easier to chain operations that need to use the reset value. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = Assign.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAdd.java index 2b6f78046ca..848231d569a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAdd.java @@ -37,8 +37,6 @@ * Update 'ref' by adding 'value' to it. * This operation outputs "ref" after the update is done. * This makes it easier to chain operations that need to use the reset value. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = AssignAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSub.java index 162fc069e92..cc96d634945 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSub.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSub.java @@ -37,8 +37,6 @@ * Update 'ref' by subtracting 'value' from it. * This operation outputs "ref" after the update is done. * This makes it easier to chain operations that need to use the reset value. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = AssignSub.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchFunction.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchFunction.java index d544fdeca5a..577f213f47d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchFunction.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchFunction.java @@ -163,6 +163,12 @@ public static BatchFunction create(Scope scope, Iterable> inTensors, if (opts.lowPriorityMaxEnqueuedBatches != null) { opBuilder.setAttr("low_priority_max_enqueued_batches", opts.lowPriorityMaxEnqueuedBatches); } + if (opts.mixedPriorityPolicy != null) { + opBuilder.setAttr("mixed_priority_policy", opts.mixedPriorityPolicy); + } + if (opts.batchPaddingPolicy != null) { + opBuilder.setAttr("batch_padding_policy", opts.batchPaddingPolicy); + } if (opts.enableLargeBatchSplitting != null) { opBuilder.setAttr("enable_large_batch_splitting", opts.enableLargeBatchSplitting); } @@ -291,6 +297,26 @@ public static Options lowPriorityMaxEnqueuedBatches(Long lowPriorityMaxEnqueuedB return new Options().lowPriorityMaxEnqueuedBatches(lowPriorityMaxEnqueuedBatches); } + /** + * Sets the mixedPriorityPolicy option. + * + * @param mixedPriorityPolicy the mixedPriorityPolicy option + * @return this Options instance. + */ + public static Options mixedPriorityPolicy(String mixedPriorityPolicy) { + return new Options().mixedPriorityPolicy(mixedPriorityPolicy); + } + + /** + * Sets the batchPaddingPolicy option. + * + * @param batchPaddingPolicy the batchPaddingPolicy option + * @return this Options instance. + */ + public static Options batchPaddingPolicy(String batchPaddingPolicy) { + return new Options().batchPaddingPolicy(batchPaddingPolicy); + } + /** * Sets the enableLargeBatchSplitting option. * @@ -339,6 +365,10 @@ public static class Options { private Long lowPriorityMaxEnqueuedBatches; + private String mixedPriorityPolicy; + + private String batchPaddingPolicy; + private Boolean enableLargeBatchSplitting; private Options() { @@ -475,6 +505,28 @@ public Options lowPriorityMaxEnqueuedBatches(Long lowPriorityMaxEnqueuedBatches) return this; } + /** + * Sets the mixedPriorityPolicy option. + * + * @param mixedPriorityPolicy the mixedPriorityPolicy option + * @return this Options instance. + */ + public Options mixedPriorityPolicy(String mixedPriorityPolicy) { + this.mixedPriorityPolicy = mixedPriorityPolicy; + return this; + } + + /** + * Sets the batchPaddingPolicy option. + * + * @param batchPaddingPolicy the batchPaddingPolicy option + * @return this Options instance. + */ + public Options batchPaddingPolicy(String batchPaddingPolicy) { + this.batchPaddingPolicy = batchPaddingPolicy; + return this; + } + /** * Sets the enableLargeBatchSplitting option. * @@ -571,6 +623,16 @@ public static class Inputs extends RawOpInputs { */ public final long lowPriorityMaxEnqueuedBatches; + /** + * The mixedPriorityPolicy attribute + */ + public final String mixedPriorityPolicy; + + /** + * The batchPaddingPolicy attribute + */ + public final String batchPaddingPolicy; + /** * the types of tensors to be batched. */ @@ -593,7 +655,7 @@ public static class Inputs extends RawOpInputs { public final boolean enableLargeBatchSplitting; public Inputs(GraphOperation op) { - super(new BatchFunction(op), op, Arrays.asList("num_batch_threads", "max_batch_size", "batch_timeout_micros", "max_enqueued_batches", "allowed_batch_sizes", "container", "shared_name", "batching_queue", "low_priority_max_batch_size", "low_priority_batch_timeout_micros", "low_priority_allowed_batch_sizes", "low_priority_max_enqueued_batches", "Tin", "Tcaptured", "Tout", "enable_large_batch_splitting")); + super(new BatchFunction(op), op, Arrays.asList("num_batch_threads", "max_batch_size", "batch_timeout_micros", "max_enqueued_batches", "allowed_batch_sizes", "container", "shared_name", "batching_queue", "low_priority_max_batch_size", "low_priority_batch_timeout_micros", "low_priority_allowed_batch_sizes", "low_priority_max_enqueued_batches", "mixed_priority_policy", "batch_padding_policy", "Tin", "Tcaptured", "Tout", "enable_large_batch_splitting")); int inputIndex = 0; int inTensorsLength = op.inputListLength("in_tensors"); inTensors = Arrays.asList((Operand[]) op.inputList(inputIndex, inTensorsLength)); @@ -613,6 +675,8 @@ public Inputs(GraphOperation op) { lowPriorityBatchTimeoutMicros = op.attributes().getAttrInt("low_priority_batch_timeout_micros"); lowPriorityAllowedBatchSizes = op.attributes().getAttrIntList("low_priority_allowed_batch_sizes"); lowPriorityMaxEnqueuedBatches = op.attributes().getAttrInt("low_priority_max_enqueued_batches"); + mixedPriorityPolicy = op.attributes().getAttrString("mixed_priority_policy"); + batchPaddingPolicy = op.attributes().getAttrString("batch_padding_policy"); Tin = op.attributes().getAttrTypeList("Tin"); Tcaptured = op.attributes().getAttrTypeList("Tcaptured"); Tout = op.attributes().getAttrTypeList("Tout"); diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpace.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpace.java index 889bd521e0d..09fa1d49bcb 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpace.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpace.java @@ -42,8 +42,6 @@ * this op outputs a copy of the input tensor where values from the {@code batch} * dimension are moved in spatial blocks to the {@code height} and {@code width} dimensions, * followed by cropping along the {@code height} and {@code width} dimensions. - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchToSpace.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpaceNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpaceNd.java index c7cf592d517..65a98188342 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpaceNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpaceNd.java @@ -42,8 +42,6 @@ * the input. The spatial dimensions of this intermediate result are then * optionally cropped according to {@code crops} to produce the output. This is the * reverse of SpaceToBatch. See below for a precise description. - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchToSpaceNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java index c1bd2421b15..82a2a99d295 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java @@ -96,8 +96,6 @@ * endian orderings will give different results. A copy from input buffer to output * buffer is made on BE machines when types are of different sizes in order to get * the same casting results as on LE machines. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Bitcast.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java index 96cfa009842..165e7e12b9a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java @@ -37,8 +37,6 @@ * Return the shape of s0 op s1 with broadcast. * Given {@code s0} and {@code s1}, tensors that represent shapes, compute {@code r0}, the * broadcasted shape. {@code s0}, {@code s1} and {@code r0} are all integer vectors. - * - * @param data type for {@code r0} output */ @OpMetadata( opType = BroadcastDynamicShape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java index fe9cf0e7039..f29d66c8de6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java @@ -36,8 +36,6 @@ /** * Return the reduction indices for computing gradients of s0 op s1 with broadcast. * This is typically used by gradient computations for a broadcasting operation. - * - * @param data type for {@code r0} output */ @OpMetadata( opType = BroadcastGradientArgs.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastTo.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastTo.java index d9ada9ae323..f27247cd37a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastTo.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastTo.java @@ -72,8 +72,6 @@ * The newly-created tensor takes the full memory of the broadcasted * shape. (In a graph context, {@code broadcast_to} might be fused to * subsequent operation and then be optimized away, however.) - * - * @param data type for {@code output} output */ @OpMetadata( opType = BroadcastTo.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CheckPinned.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CheckPinned.java new file mode 100644 index 00000000000..2708bcad2bf --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CheckPinned.java @@ -0,0 +1,115 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.core; + +import java.util.Arrays; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.op.annotation.Operator; +import org.tensorflow.proto.DataType; +import org.tensorflow.types.family.TType; + +/** + * Checks whether a tensor is located in host memory pinned for GPU. + * When run: + *

    + *
  • Reports an {@code InvalidArgument} error if {@code tensor} is not in pinned memory.
    • + *
  • Reports a {@code FailedPrecondition} error if not built with CUDA.
    • + *
+ */ +@OpMetadata( + opType = CheckPinned.OP_NAME, + inputsClass = CheckPinned.Inputs.class +) +@Operator +public final class CheckPinned extends RawOp implements Operand { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "CheckPinned"; + + private Output output; + + public CheckPinned(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + output = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new CheckPinned operation. + * + * @param scope current scope + * @param tensor The tensor value + * @param data type for {@code CheckPinned} output and operands + * @return a new instance of CheckPinned + */ + @Endpoint( + describeByClass = true + ) + public static CheckPinned create(Scope scope, Operand tensor) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "CheckPinned"); + opBuilder.addInput(tensor.asOutput()); + return new CheckPinned<>(opBuilder.build()); + } + + /** + * Gets output. + * + * @return output. + */ + public Output output() { + return output; + } + + @Override + public Output asOutput() { + return output; + } + + @OpInputsMetadata( + outputsClass = CheckPinned.class + ) + public static class Inputs extends RawOpInputs> { + /** + * The tensor input + */ + public final Operand tensor; + + /** + * The T attribute + */ + public final DataType T; + + public Inputs(GraphOperation op) { + super(new CheckPinned<>(op), op, Arrays.asList("T")); + int inputIndex = 0; + tensor = (Operand) op.input(inputIndex++); + T = op.attributes().getAttrType("T"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ClipByValue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ClipByValue.java index 4477b0d4924..2ae7185a7e5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ClipByValue.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ClipByValue.java @@ -39,8 +39,6 @@ * shape as {@code t} with its values clipped to {@code clip_value_min} and {@code clip_value_max}. * Any values less than {@code clip_value_min} are set to {@code clip_value_min}. Any values * greater than {@code clip_value_max} are set to {@code clip_value_max}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ClipByValue.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Concat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Concat.java index 894b3a574be..cf3b735f4be 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Concat.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Concat.java @@ -37,8 +37,6 @@ /** * Concatenates tensors along one dimension. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Concat.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ConcatOffset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ConcatOffset.java index df14b30a11b..9b9a8d813c3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ConcatOffset.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ConcatOffset.java @@ -47,14 +47,12 @@ * y = [2, 3, 7] * z = [2, 9, 7] * offsets = concat_offset(1, [x, y, z]) - * [list(off.numpy()) for off in offsets] + * [[a.item() for a in list(off.numpy())] for off in offsets] * [[0, 0, 0], [0, 2, 0], [0, 5, 0]] * * * *

This is typically used by gradient computations for a concat operation. - * - * @param data type for {@code offset} output */ @OpMetadata( opType = ConcatOffset.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Copy.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Copy.java index 9b55fac9069..a04de48877b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Copy.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Copy.java @@ -42,8 +42,6 @@ * deep-copying. See the documentation of Debug* ops for more details. *

Unlike the CopyHost Op, this op does not have HostMemory constraint on its * input or output. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Copy.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyHost.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyHost.java index 59af18c8b33..055c9d878bf 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyHost.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyHost.java @@ -40,8 +40,6 @@ * gRPC gating status, the output will simply forward the input tensor without * deep-copying. See the documentation of Debug* ops for more details. *

Unlike the Copy Op, this op has HostMemory constraint on its input or output. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CopyHost.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMesh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMesh.java index f83d6c6ad61..166d4613d54 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMesh.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMesh.java @@ -35,8 +35,6 @@ /** * The CopyToMesh operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = CopyToMesh.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMeshGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMeshGrad.java index fa3467cd849..095d5b5d7ce 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMeshGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMeshGrad.java @@ -35,8 +35,6 @@ /** * The CopyToMeshGrad operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = CopyToMeshGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java index 7a81a4419e6..0f404fa1419 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java @@ -35,8 +35,6 @@ /** * Increments 'ref' until it reaches 'limit'. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CountUpTo.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeepCopy.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeepCopy.java index ca15dbb9a55..f0b9b3927a8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeepCopy.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeepCopy.java @@ -35,8 +35,6 @@ /** * Makes a copy of {@code x}. - * - * @param data type for {@code y} output */ @OpMetadata( opType = DeepCopy.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyTemporaryVariable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyTemporaryVariable.java index cc8f2bafb2f..876a1e46ee5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyTemporaryVariable.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyTemporaryVariable.java @@ -41,8 +41,6 @@ * This is typically achieved by chaining the ref through each assign op, or by * using control dependencies. *

Outputs the final value of the tensor pointed to by 'ref'. - * - * @param data type for {@code value} output */ @OpMetadata( opType = DestroyTemporaryVariable.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicPartition.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicPartition.java index b851e0cccdf..d7d7bf7c328 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicPartition.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicPartition.java @@ -78,8 +78,6 @@ * * * - * - * @param data type for {@code outputs} output */ @OpMetadata( opType = DynamicPartition.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicStitch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicStitch.java index 9aba2968627..d160ab8255c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicStitch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicStitch.java @@ -90,8 +90,6 @@ *

* *
- * - * @param data type for {@code merged} output */ @OpMetadata( opType = DynamicStitch.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java index 02c76780ba2..6f7d74d94e5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java @@ -38,8 +38,6 @@ /** * Creates a tensor with the given shape. *

This operation creates a tensor of {@code shape} and {@code dtype}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Empty.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EnsureShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EnsureShape.java index 131285dc0e6..bbada3714ac 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EnsureShape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EnsureShape.java @@ -38,8 +38,6 @@ * Ensures that the tensor's shape matches the expected shape. * Raises an error if the input tensor's shape does not match the specified shape. * Returns the input tensor otherwise. - * - * @param data type for {@code output} output */ @OpMetadata( opType = EnsureShape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Enter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Enter.java index baed3b18053..309e5700eb1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Enter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Enter.java @@ -40,8 +40,6 @@ * {@code is_constant} is true, {@code output} is a constant in the child frame; otherwise * it may be changed in the child frame. At most {@code parallel_iterations} iterations * are run in parallel in the child frame. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Enter.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Exit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Exit.java index c1535016b59..8dea6a66fe6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Exit.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Exit.java @@ -36,8 +36,6 @@ /** * Exits the current frame to its parent frame. * Exit makes its input {@code data} available to the parent frame. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Exit.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExpandDims.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExpandDims.java index bf17427d228..0f0e030b71d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExpandDims.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExpandDims.java @@ -59,8 +59,6 @@ *

{@code -1-input.dims() <= dim <= input.dims()} *

This operation is related to {@code squeeze()}, which removes dimensions of * size 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ExpandDims.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java index 12afb6060b3..350c416e235 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java @@ -36,8 +36,6 @@ /** * Extract {@code patches} from {@code input} and put them in the {@code "depth"} output dimension. 3D extension of {@code extract_image_patches}. - * - * @param data type for {@code patches} output */ @OpMetadata( opType = ExtractVolumePatches.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/FakeParam.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/FakeParam.java index ee07de5268d..79e63958dda 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/FakeParam.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/FakeParam.java @@ -40,8 +40,6 @@ * valid output when run, so must either be removed (e.g. replaced with a * function input) or guaranteed not to be used (e.g. if mirroring an * intermediate output needed for the gradient computation of the other branch). - * - * @param data type for {@code output} output */ @OpMetadata( opType = FakeParam.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fill.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fill.java index 5ba5931795e..8634981f57c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fill.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fill.java @@ -53,8 +53,6 @@ *

  • Because {@code tf.fill} evaluates at graph runtime, it supports dynamic shapes * based on other runtime Tensors, unlike {@code tf.constant}.
    • * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Fill.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Gather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Gather.java index 1b1e3f888ee..43e09807b66 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Gather.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Gather.java @@ -57,9 +57,10 @@ *

    Note that on CPU, if an out of bound index is found, an error is returned. * On GPU, if an out of bound index is found, a 0 is stored in the * corresponding output value. + *

    Note that on TPU, if any dimension of {@code params} is of size 0 then the output will + * be the expected shape filled with zeros. On CPU and GPU an error will be + * returned. *

    See also {@code tf.batch_gather} and {@code tf.gather_nd}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Gather.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GatherNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GatherNd.java index b1a05118129..755bf4e7905 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GatherNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GatherNd.java @@ -57,9 +57,17 @@ * 

      * indices.shape[:-1] + params.shape[indices.shape[-1]:]
  *
    - *

    Note that on CPU, if an out of bound index is found, an error is returned. - * On GPU, if an out of bound index is found, a 0 is stored in the - * corresponding output value. + *

    If {@code indices} contains any out-of-bound indices, depending on + * {@code bad_indices_policy}, the op will either return an error or ignore the + * out-of-bound indices. {@code bad_indices_policy} can be one of the following values: + *

      + *
    1. "" or "DEFAULT": raises on CPU and ignore on GPU. This is because + * historically on CPU and GPU we handle errors in different ways, and for + * backward compatibility we keep the default behavior.
      2. + *
    2. "ERROR": raises error; GPU does not support this value.
      3. + *
    3. "IGNORE": ignore error and set the corresponding output to 0; + * supported on both CPU and GPU.
      4. + *
    *

    Some examples below. *

    Simple indexing into a matrix: * 

    @@ -125,8 +133,6 @@
  *     output = [['b0', 'b1'], ['d0', 'c1']]
  *
    *

    See also {@code tf.gather} and {@code tf.batch_gather}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = GatherNd.OP_NAME, @@ -153,6 +159,7 @@ public GatherNd(Operation operation) { * @param scope current scope * @param params The tensor from which to gather values. * @param indices Index tensor. + * @param options carries optional attribute values * @param data type for {@code GatherNd} output and operands * @return a new instance of GatherNd */ @@ -160,13 +167,30 @@ public GatherNd(Operation operation) { describeByClass = true ) public static GatherNd create(Scope scope, Operand params, - Operand indices) { + Operand indices, Options... options) { OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "GatherNd"); opBuilder.addInput(params.asOutput()); opBuilder.addInput(indices.asOutput()); + if (options != null) { + for (Options opts : options) { + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } + } + } return new GatherNd<>(opBuilder.build()); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Gets output. * Values from {@code params} gathered from indices given by {@code indices}, with @@ -182,6 +206,27 @@ public Output asOutput() { return output; } + /** + * Optional attributes for {@link org.tensorflow.op.core.GatherNd} + */ + public static class Options { + private String badIndicesPolicy; + + private Options() { + } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } + } + @OpInputsMetadata( outputsClass = GatherNd.class ) @@ -206,13 +251,19 @@ public static class Inputs extends RawOpInputs> { */ public final DataType Tindices; + /** + * The badIndicesPolicy attribute + */ + public final String badIndicesPolicy; + public Inputs(GraphOperation op) { - super(new GatherNd<>(op), op, Arrays.asList("Tparams", "Tindices")); + super(new GatherNd<>(op), op, Arrays.asList("Tparams", "Tindices", "bad_indices_policy")); int inputIndex = 0; params = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); Tparams = op.attributes().getAttrType("Tparams"); Tindices = op.attributes().getAttrType("Tindices"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java index a2445004e6d..0cccfb42045 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java @@ -37,8 +37,6 @@ /** * Get the value of the tensor specified by its handle. - * - * @param data type for {@code value} output */ @OpMetadata( opType = GetSessionTensor.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GuaranteeConst.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GuaranteeConst.java index 8839f77471f..c4235de8ff2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GuaranteeConst.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GuaranteeConst.java @@ -39,8 +39,6 @@ *

    Only accepts value typed tensors as inputs and rejects resource variable handles * as input. *

    Returns the input tensor without modification. - * - * @param data type for {@code output} output */ @OpMetadata( opType = GuaranteeConst.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java index 0846ac056c0..782cfc69f05 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java @@ -51,8 +51,6 @@ * variables.global_variables_initializer().run() * sess.run(hist) => [2, 1, 1, 0, 2] * - * - * @param data type for {@code out} output */ @OpMetadata( opType = HistogramFixedWidth.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HostConst.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HostConst.java index 8aa7bf2e13c..82f5ef8f295 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HostConst.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HostConst.java @@ -37,8 +37,6 @@ /** * Returns a constant tensor on the host. Only for writing C++ tests. - * - * @param data type for {@code output} output */ @OpMetadata( opType = HostConst.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Identity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Identity.java index 12c84344373..d0729ab93da 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Identity.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Identity.java @@ -35,8 +35,6 @@ /** * Return a tensor with the same shape and contents as the input tensor or value. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Identity.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java index 47cbe749ee9..12d647268ba 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java @@ -38,8 +38,6 @@ /** * Returns immutable tensor from memory region. * The current implementation memmaps the tensor from a file. - * - * @param data type for {@code tensor} output */ @OpMetadata( opType = ImmutableConst.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceAdd.java index c42388fc55c..78f37851589 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceAdd.java @@ -39,8 +39,6 @@ * 

      * Computes y = x; y[i, :] += v; return y.
  *
    - * - * @param data type for {@code y} output */ @OpMetadata( opType = InplaceAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceSub.java index a39bf6d741b..31d0287aab2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceSub.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceSub.java @@ -40,8 +40,6 @@ * * Computes y = x; y[i, :] -= v; return y. * - * - * @param data type for {@code y} output */ @OpMetadata( opType = InplaceSub.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceUpdate.java index 8aecb6edf8c..d34e0f15011 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceUpdate.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceUpdate.java @@ -39,8 +39,6 @@ * Computes {@code x[i, :] = v; return x}. *

    Originally this function is mutative however for compilation we make this * operation create / operate on a copy of {@code x}. - * - * @param data type for {@code y} output */ @OpMetadata( opType = InplaceUpdate.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java index 3473ddf487e..317eb054e29 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java @@ -42,8 +42,6 @@ * 

      * tf.linspace(10.0, 12.0, 3, name="linspace") => [ 10.0  11.0  12.0]
  *
    - * - * @param data type for {@code output} output */ @OpMetadata( opType = LinSpace.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java index 7406671423c..7546b26f8f4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java @@ -36,10 +36,6 @@ /** * Outputs all keys and values in the table. - * - * @param data type for {@code keys} output - * - * @param data type for {@code values} output */ @OpMetadata( opType = LookupTableExport.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableFind.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableFind.java index b097f2ee81d..1155c94662f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableFind.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableFind.java @@ -39,8 +39,6 @@ * The output {@code values} is of the type of the table values. *

    The scalar {@code default_value} is the value output for keys not present in the * table. It must also be of the same type as the table values. - * - * @param data type for {@code values} output */ @OpMetadata( opType = LookupTableFind.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java index 8cf633e2d7f..2a4b761a8fd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java @@ -51,8 +51,6 @@ *

    result = LowerBound(sorted_sequence, values) *

    result == [[1, 2, 2], * [0, 1, 5]] - * - * @param data type for {@code output} output */ @OpMetadata( opType = LowerBound.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Max.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Max.java index fb03ee5c942..04c4f1481d3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Max.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Max.java @@ -39,8 +39,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Max.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Merge.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Merge.java index 7e4c77434b9..f5a189c9c58 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Merge.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Merge.java @@ -41,8 +41,6 @@ * It is usually combined with {@code Switch} to implement branching. *

    {@code Merge} forwards the first tensor to become available to {@code output}, and sets * {@code value_index} to its index in {@code inputs}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Merge.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Min.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Min.java index f3db8fedac0..89ac31b5854 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Min.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Min.java @@ -39,8 +39,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Min.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPad.java index e63036ec117..751bec8fd66 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPad.java @@ -57,8 +57,6 @@ * [5, 4, 4, 5, 6, 6, 5] * [5, 4, 4, 5, 6, 6, 5]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = MirrorPad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPadGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPadGrad.java index 64235a34e0a..d1286e4bd89 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPadGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPadGrad.java @@ -50,8 +50,6 @@ * pad(t, paddings) ==> [[ 1, 5] * [11, 28]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = MirrorPadGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java index d49045a1bad..5e8f5709b65 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java @@ -46,8 +46,6 @@ * num_devices: The number of devices participating in this reduction. * shared_name: Identifier that shared between ops of the same reduction. * - * @param data type for {@code data} output - * * @deprecated use {@link org.tensorflow.op.distribute.NcclAllReduce} instead */ @OpMetadata( diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java index 4d5c2d771de..5e6c2a583ef 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java @@ -43,8 +43,6 @@ * output: The same as input. * shape: The shape of the input tensor. * - * @param data type for {@code output} output - * * @deprecated use {@link org.tensorflow.op.distribute.NcclBroadcast} instead */ @OpMetadata( diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java index 8b050aba7e3..cd3dea3af6f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java @@ -43,8 +43,6 @@ * data: the value of the reduction across all {@code num_devices} devices. * reduction: the reduction operation to perform. * - * @param data type for {@code data} output - * * @deprecated use {@link org.tensorflow.op.distribute.NcclReduce} instead */ @OpMetadata( diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NextIteration.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NextIteration.java index 33e50ce1b5d..1f0f73c672f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NextIteration.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NextIteration.java @@ -35,8 +35,6 @@ /** * Makes its input available to the next iteration. - * - * @param data type for {@code output} output */ @OpMetadata( opType = NextIteration.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OneHot.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OneHot.java index 09f55f7eaff..8ed3c25bd8e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OneHot.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OneHot.java @@ -111,8 +111,6 @@ * [0.0, 0.0, 0.0] // one_hot(-1) * ] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = OneHot.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OnesLike.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OnesLike.java index b69df0d0952..51178e062f4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OnesLike.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OnesLike.java @@ -35,8 +35,6 @@ /** * Returns a tensor of ones with the same shape and type as x. - * - * @param data type for {@code y} output */ @OpMetadata( opType = OnesLike.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Pad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Pad.java index d80e87f0f2d..60ddbcf6817 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Pad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Pad.java @@ -56,8 +56,6 @@ * [0, 0, 2, 2, 0, 0] * [0, 0, 0, 0, 0, 0]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Pad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelConcat.java index c5cbde1618c..b12c3b896aa 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelConcat.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelConcat.java @@ -50,8 +50,6 @@ * that the input shapes be known during graph construction. Parallel concat * will copy pieces of the input into the output as they become available, in * some situations this can provide a performance benefit. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ParallelConcat.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelDynamicStitch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelDynamicStitch.java index a23c3d135a8..c9fd16880ca 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelDynamicStitch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelDynamicStitch.java @@ -89,8 +89,6 @@ *

    * *
    - * - * @param data type for {@code merged} output */ @OpMetadata( opType = ParallelDynamicStitch.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java index 634500dcfc0..f4c450973da 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java @@ -40,8 +40,6 @@ * N.B. This operation will fail with an error if it is executed. It is * intended as a way to represent a value that will always be fed, and to * provide attrs that enable the fed value to be checked at runtime. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Placeholder.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/PlaceholderWithDefault.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/PlaceholderWithDefault.java index 9604ea0a92a..202d4cc476c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/PlaceholderWithDefault.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/PlaceholderWithDefault.java @@ -36,8 +36,6 @@ /** * A placeholder op that passes through {@code input} when its output is not fed. - * - * @param data type for {@code output} output */ @OpMetadata( opType = PlaceholderWithDefault.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Prod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Prod.java index 71c7f986eb6..3f1c696a0bc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Prod.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Prod.java @@ -40,8 +40,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Prod.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/QuantizedReshape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/QuantizedReshape.java index 6e92b83bf89..84816c6893f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/QuantizedReshape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/QuantizedReshape.java @@ -37,8 +37,6 @@ /** * Reshapes a quantized tensor as per the Reshape op. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedReshape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RandomIndexShuffle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RandomIndexShuffle.java index 68cd7f9f0eb..76538abf9cb 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RandomIndexShuffle.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RandomIndexShuffle.java @@ -39,8 +39,6 @@ *

    If multiple inputs are vectors (matrix in case of seed) then the size of the * first dimension must match. *

    The outputs are deterministic. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomIndexShuffle.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Range.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Range.java index 0699bd59b09..702214095a5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Range.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Range.java @@ -44,8 +44,6 @@ * # 'delta' is 3 * tf.range(start, limit, delta) ==> [3, 6, 9, 12, 15] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Range.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java index 236991942ee..f57c2781c3f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java @@ -41,8 +41,6 @@ * writes on which this operation depends directly or indirectly, and to not be * influenced by any of the writes which depend directly or indirectly on this * operation. - * - * @param data type for {@code value} output */ @OpMetadata( opType = ReadVariableOp.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java index 1853328543d..5b3caab37b8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java @@ -36,8 +36,6 @@ /** * Receives the named tensor from send_device on recv_device. - * - * @param data type for {@code tensor} output */ @OpMetadata( opType = Recv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMax.java index 529841fd5fa..dca6c6a5ffc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMax.java @@ -39,8 +39,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ReduceMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMin.java index f349357096b..a7e544cfaab 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMin.java @@ -39,8 +39,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ReduceMin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceProd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceProd.java index 49008ad1a36..3dc53ad9c58 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceProd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceProd.java @@ -40,8 +40,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ReduceProd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceSum.java index 05851e60764..bbe161f9210 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceSum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceSum.java @@ -40,8 +40,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ReduceSum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefEnter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefEnter.java index 888c0ee977b..218092a2563 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefEnter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefEnter.java @@ -39,8 +39,6 @@ * {@code is_constant} is true, {@code output} is a constant in the child frame; otherwise * it may be changed in the child frame. At most {@code parallel_iterations} iterations * are run in parallel in the child frame. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RefEnter.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefExit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefExit.java index c23ff2d03d7..9a840da2c3d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefExit.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefExit.java @@ -36,8 +36,6 @@ /** * Exits the current frame to its parent frame. * Exit makes its input {@code data} available to the parent frame. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RefExit.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefIdentity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefIdentity.java index 53d515be8e1..c3bb004b548 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefIdentity.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefIdentity.java @@ -35,8 +35,6 @@ /** * Return the same ref tensor as the input ref tensor. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RefIdentity.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefMerge.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefMerge.java index 9354cb2847b..4baf6cc6260 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefMerge.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefMerge.java @@ -41,8 +41,6 @@ * It is usually combined with {@code Switch} to implement branching. *

    {@code Merge} forwards the first tensor for become available to {@code output}, and sets * {@code value_index} to its index in {@code inputs}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RefMerge.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefNextIteration.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefNextIteration.java index 5c7f1d2c4b7..ef647c70cd6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefNextIteration.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefNextIteration.java @@ -35,8 +35,6 @@ /** * Makes its input available to the next iteration. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RefNextIteration.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSelect.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSelect.java index 02c6ddc8e2f..d7ffa33956e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSelect.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSelect.java @@ -37,8 +37,6 @@ /** * Forwards the {@code index}th element of {@code inputs} to {@code output}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RefSelect.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSwitch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSwitch.java index 04a2d4811ab..2e97b2bbcad 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSwitch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSwitch.java @@ -39,8 +39,6 @@ * If {@code pred} is true, the {@code data} input is forwarded to {@code output_true}. Otherwise, * the data goes to {@code output_false}. *

    See also {@code Switch} and {@code Merge}. - * - * @param data type for {@code output_false} output */ @OpMetadata( opType = RefSwitch.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Relayout.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Relayout.java index 959987e6200..503d3cfe42a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Relayout.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Relayout.java @@ -35,8 +35,6 @@ /** * The Relayout operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = Relayout.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RelayoutLike.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RelayoutLike.java index 7fd8a91fb8b..499cb8d6c72 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RelayoutLike.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RelayoutLike.java @@ -35,8 +35,6 @@ /** * The RelayoutLike operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = RelayoutLike.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reshape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reshape.java index 4b1ce466a7d..54c0aba057e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reshape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reshape.java @@ -90,8 +90,6 @@ * # shape `[]` reshapes to a scalar * reshape(t, []) ==> 7 * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Reshape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java index f8e5cf5abef..0ca0faa179e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java @@ -37,8 +37,6 @@ /** * Increments variable pointed to by 'resource' until it reaches 'limit'. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ResourceCountUpTo.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java index 5dff2d95dc2..c458bacea4c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java @@ -49,8 +49,6 @@ * # Higher rank indices * output[i, ..., j, :, ... :] = params[indices[i, ..., j], :, ..., :] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = ResourceGather.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java index 1a86a282ab9..f9c6b72b544 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java @@ -37,8 +37,6 @@ /** * The ResourceGatherNd operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = ResourceGatherNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdAdd.java index 4c1d9d3820c..ee6c1cf7d61 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdAdd.java @@ -103,6 +103,9 @@ public static ResourceScatterNdAdd create(Scope scope, Operand if (opts.useLocking != null) { opBuilder.setAttr("use_locking", opts.useLocking); } + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } } } return new ResourceScatterNdAdd(opBuilder.build()); @@ -120,12 +123,24 @@ public static Options useLocking(Boolean useLocking) { return new Options().useLocking(useLocking); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Optional attributes for {@link org.tensorflow.op.core.ResourceScatterNdAdd} */ public static class Options { private Boolean useLocking; + private String badIndicesPolicy; + private Options() { } @@ -141,6 +156,17 @@ public Options useLocking(Boolean useLocking) { this.useLocking = useLocking; return this; } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } } @OpInputsMetadata( @@ -181,8 +207,13 @@ public static class Inputs extends RawOpInputs { */ public final boolean useLocking; + /** + * The badIndicesPolicy attribute + */ + public final String badIndicesPolicy; + public Inputs(GraphOperation op) { - super(new ResourceScatterNdAdd(op), op, Arrays.asList("T", "Tindices", "use_locking")); + super(new ResourceScatterNdAdd(op), op, Arrays.asList("T", "Tindices", "use_locking", "bad_indices_policy")); int inputIndex = 0; ref = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); @@ -190,6 +221,7 @@ public Inputs(GraphOperation op) { T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); useLocking = op.attributes().getAttrBool("use_locking"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMax.java index 193d4c7dfda..379843a67c7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMax.java @@ -77,6 +77,9 @@ public static ResourceScatterNdMax create(Scope scope, Operand if (opts.useLocking != null) { opBuilder.setAttr("use_locking", opts.useLocking); } + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } } } return new ResourceScatterNdMax(opBuilder.build()); @@ -94,12 +97,24 @@ public static Options useLocking(Boolean useLocking) { return new Options().useLocking(useLocking); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Optional attributes for {@link org.tensorflow.op.core.ResourceScatterNdMax} */ public static class Options { private Boolean useLocking; + private String badIndicesPolicy; + private Options() { } @@ -115,6 +130,17 @@ public Options useLocking(Boolean useLocking) { this.useLocking = useLocking; return this; } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } } @OpInputsMetadata( @@ -155,8 +181,13 @@ public static class Inputs extends RawOpInputs { */ public final boolean useLocking; + /** + * The badIndicesPolicy attribute + */ + public final String badIndicesPolicy; + public Inputs(GraphOperation op) { - super(new ResourceScatterNdMax(op), op, Arrays.asList("T", "Tindices", "use_locking")); + super(new ResourceScatterNdMax(op), op, Arrays.asList("T", "Tindices", "use_locking", "bad_indices_policy")); int inputIndex = 0; ref = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); @@ -164,6 +195,7 @@ public Inputs(GraphOperation op) { T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); useLocking = op.attributes().getAttrBool("use_locking"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMin.java index 9a1023916fd..ba46417abba 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMin.java @@ -77,6 +77,9 @@ public static ResourceScatterNdMin create(Scope scope, Operand if (opts.useLocking != null) { opBuilder.setAttr("use_locking", opts.useLocking); } + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } } } return new ResourceScatterNdMin(opBuilder.build()); @@ -94,12 +97,24 @@ public static Options useLocking(Boolean useLocking) { return new Options().useLocking(useLocking); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Optional attributes for {@link org.tensorflow.op.core.ResourceScatterNdMin} */ public static class Options { private Boolean useLocking; + private String badIndicesPolicy; + private Options() { } @@ -115,6 +130,17 @@ public Options useLocking(Boolean useLocking) { this.useLocking = useLocking; return this; } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } } @OpInputsMetadata( @@ -155,8 +181,13 @@ public static class Inputs extends RawOpInputs { */ public final boolean useLocking; + /** + * The badIndicesPolicy attribute + */ + public final String badIndicesPolicy; + public Inputs(GraphOperation op) { - super(new ResourceScatterNdMin(op), op, Arrays.asList("T", "Tindices", "use_locking")); + super(new ResourceScatterNdMin(op), op, Arrays.asList("T", "Tindices", "use_locking", "bad_indices_policy")); int inputIndex = 0; ref = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); @@ -164,6 +195,7 @@ public Inputs(GraphOperation op) { T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); useLocking = op.attributes().getAttrBool("use_locking"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdSub.java index 4c321416231..f39e42e742b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdSub.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdSub.java @@ -103,6 +103,9 @@ public static ResourceScatterNdSub create(Scope scope, Operand if (opts.useLocking != null) { opBuilder.setAttr("use_locking", opts.useLocking); } + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } } } return new ResourceScatterNdSub(opBuilder.build()); @@ -120,12 +123,24 @@ public static Options useLocking(Boolean useLocking) { return new Options().useLocking(useLocking); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Optional attributes for {@link org.tensorflow.op.core.ResourceScatterNdSub} */ public static class Options { private Boolean useLocking; + private String badIndicesPolicy; + private Options() { } @@ -141,6 +156,17 @@ public Options useLocking(Boolean useLocking) { this.useLocking = useLocking; return this; } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } } @OpInputsMetadata( @@ -181,8 +207,13 @@ public static class Inputs extends RawOpInputs { */ public final boolean useLocking; + /** + * The badIndicesPolicy attribute + */ + public final String badIndicesPolicy; + public Inputs(GraphOperation op) { - super(new ResourceScatterNdSub(op), op, Arrays.asList("T", "Tindices", "use_locking")); + super(new ResourceScatterNdSub(op), op, Arrays.asList("T", "Tindices", "use_locking", "bad_indices_policy")); int inputIndex = 0; ref = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); @@ -190,6 +221,7 @@ public Inputs(GraphOperation op) { T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); useLocking = op.attributes().getAttrBool("use_locking"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdUpdate.java index 1a21fa30916..588d923c05a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdUpdate.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdUpdate.java @@ -104,6 +104,9 @@ public static ResourceScatterNdUpdate create(Scope scope, Operand { */ public final boolean useLocking; + /** + * The badIndicesPolicy attribute + */ + public final String badIndicesPolicy; + public Inputs(GraphOperation op) { - super(new ResourceScatterNdUpdate(op), op, Arrays.asList("T", "Tindices", "use_locking")); + super(new ResourceScatterNdUpdate(op), op, Arrays.asList("T", "Tindices", "use_locking", "bad_indices_policy")); int inputIndex = 0; ref = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); @@ -191,6 +222,7 @@ public Inputs(GraphOperation op) { T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); useLocking = op.attributes().getAttrBool("use_locking"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reverse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reverse.java index 65a6ac9ab0c..711b7148209 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reverse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reverse.java @@ -76,8 +76,6 @@ * [16, 17, 18, 19], * [12, 13, 14, 15]]]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Reverse.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReverseSequence.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReverseSequence.java index b7eb3fb25a2..e18f16874f0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReverseSequence.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReverseSequence.java @@ -84,8 +84,6 @@ * output[3:, :, 2, :, ...] = input[3:, :, 2, :, ...] * output[2:, :, 3, :, ...] = input[2:, :, 3, :, ...] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = ReverseSequence.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Roll.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Roll.java index a2f04750d53..e190730b970 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Roll.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Roll.java @@ -54,8 +54,6 @@ * # 't' is [[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]] * roll(t, shift=[2, -3], axis=[1, 1]) ==> [[1, 2, 3, 4, 0], [6, 7, 8, 9, 5]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Roll.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterAdd.java index bc66b56b3d1..9f0bc6a526f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterAdd.java @@ -55,8 +55,6 @@ *

    * *
    - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterDiv.java index 083f4de2a81..902d11400e5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterDiv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterDiv.java @@ -52,8 +52,6 @@ *

    Duplicate entries are handled correctly: if multiple {@code indices} reference * the same location, their contributions divide. *

    Requires {@code updates.shape = indices.shape + ref.shape[1:]} or {@code updates.shape = []}. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterDiv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java index 162556fb11c..9b761e52419 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java @@ -54,8 +54,6 @@ *

    * *
    - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java index 4264f92bc7e..7f725ad19d0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java @@ -54,8 +54,6 @@ *
    * *
    - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterMin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMul.java index 7fb20e9d36e..ae8bbca9670 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMul.java @@ -52,8 +52,6 @@ *

    Duplicate entries are handled correctly: if multiple {@code indices} reference * the same location, their contributions multiply. *

    Requires {@code updates.shape = indices.shape + ref.shape[1:]} or {@code updates.shape = []}. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterMul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNd.java index 34487ebf9d7..ad6bcd00a16 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNd.java @@ -107,10 +107,16 @@ * [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]], * [[5, 5, 5, 5], [6, 6, 6, 6], [7, 7, 7, 7], [8, 8, 8, 8]]] * - *

    Note that on CPU, if an out of bound index is found, an error is returned. - * On GPU, if an out of bound index is found, the index is ignored. - * - * @param data type for {@code output} output + *

    If {@code indices} contains any out-of-bound indices, depending on + * {@code bad_indices_policy}, the op will either return an error or ignore the + * out-of-bound indices. {@code bad_indices_policy} can be one of the following values: + *

      + *
    1. "" or "DEFAULT": raises on CPU and ignore on GPU. This is because + * historically on CPU and GPU we handle errors in different ways, and for + * backward compatibility we keep the default behavior.
      2. + *
    2. "ERROR": raises error; GPU does not support this value.
      3. + *
    3. "IGNORE": ignore the bad indices; supported on both CPU and GPU.
      4. + *
    */ @OpMetadata( opType = ScatterNd.OP_NAME, @@ -138,6 +144,7 @@ public ScatterNd(Operation operation) { * @param indices Tensor of indices. * @param updates Values to scatter into the output tensor. * @param shape 1-D. The shape of the output tensor. + * @param options carries optional attribute values * @param data type for {@code ScatterNd} output and operands * @param data type for {@code ScatterNd} output and operands * @return a new instance of ScatterNd @@ -146,14 +153,31 @@ public ScatterNd(Operation operation) { describeByClass = true ) public static ScatterNd create(Scope scope, - Operand indices, Operand updates, Operand shape) { + Operand indices, Operand updates, Operand shape, Options... options) { OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "ScatterNd"); opBuilder.addInput(indices.asOutput()); opBuilder.addInput(updates.asOutput()); opBuilder.addInput(shape.asOutput()); + if (options != null) { + for (Options opts : options) { + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } + } + } return new ScatterNd<>(opBuilder.build()); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Gets output. * A new tensor with the given shape and updates applied according @@ -169,6 +193,27 @@ public Output asOutput() { return output; } + /** + * Optional attributes for {@link org.tensorflow.op.core.ScatterNd} + */ + public static class Options { + private String badIndicesPolicy; + + private Options() { + } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } + } + @OpInputsMetadata( outputsClass = ScatterNd.class ) @@ -198,14 +243,20 @@ public static class Inputs extends RawOpInpu */ public final DataType Tindices; + /** + * The badIndicesPolicy attribute + */ + public final String badIndicesPolicy; + public Inputs(GraphOperation op) { - super(new ScatterNd<>(op), op, Arrays.asList("T", "Tindices")); + super(new ScatterNd<>(op), op, Arrays.asList("T", "Tindices", "bad_indices_policy")); int inputIndex = 0; indices = (Operand) op.input(inputIndex++); updates = (Operand) op.input(inputIndex++); shape = (Operand) op.input(inputIndex++); T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdAdd.java index aef9eed4a32..257dce25682 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdAdd.java @@ -62,8 +62,6 @@ * *

    See {@code tf.scatter_nd} for more details about how to make updates to * slices. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterNdAdd.OP_NAME, @@ -111,6 +109,9 @@ public static ScatterNdAdd create(Scope scope, Operand r if (opts.useLocking != null) { opBuilder.setAttr("use_locking", opts.useLocking); } + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } } } return new ScatterNdAdd<>(opBuilder.build()); @@ -128,6 +129,16 @@ public static Options useLocking(Boolean useLocking) { return new Options().useLocking(useLocking); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Gets outputRef. * Same as ref. Returned as a convenience for operations that want @@ -149,6 +160,8 @@ public Output asOutput() { public static class Options { private Boolean useLocking; + private String badIndicesPolicy; + private Options() { } @@ -164,6 +177,17 @@ public Options useLocking(Boolean useLocking) { this.useLocking = useLocking; return this; } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } } @OpInputsMetadata( @@ -204,8 +228,13 @@ public static class Inputs extends RawOpInputs> */ public final boolean useLocking; + /** + * The badIndicesPolicy attribute + */ + public final String badIndicesPolicy; + public Inputs(GraphOperation op) { - super(new ScatterNdAdd<>(op), op, Arrays.asList("T", "Tindices", "use_locking")); + super(new ScatterNdAdd<>(op), op, Arrays.asList("T", "Tindices", "use_locking", "bad_indices_policy")); int inputIndex = 0; ref = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); @@ -213,6 +242,7 @@ public Inputs(GraphOperation op) { T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); useLocking = op.attributes().getAttrBool("use_locking"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMax.java index 0adccafee2a..a7ebdf162d6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMax.java @@ -36,8 +36,6 @@ /** * Computes element-wise maximum. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterNdMax.OP_NAME, @@ -85,6 +83,9 @@ public static ScatterNdMax create(Scope scope, Operand r if (opts.useLocking != null) { opBuilder.setAttr("use_locking", opts.useLocking); } + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } } } return new ScatterNdMax<>(opBuilder.build()); @@ -102,6 +103,16 @@ public static Options useLocking(Boolean useLocking) { return new Options().useLocking(useLocking); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Gets outputRef. * Same as ref. Returned as a convenience for operations that want @@ -123,6 +134,8 @@ public Output asOutput() { public static class Options { private Boolean useLocking; + private String badIndicesPolicy; + private Options() { } @@ -138,6 +151,17 @@ public Options useLocking(Boolean useLocking) { this.useLocking = useLocking; return this; } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } } @OpInputsMetadata( @@ -178,8 +202,13 @@ public static class Inputs extends RawOpInputs> */ public final boolean useLocking; + /** + * The badIndicesPolicy attribute + */ + public final String badIndicesPolicy; + public Inputs(GraphOperation op) { - super(new ScatterNdMax<>(op), op, Arrays.asList("T", "Tindices", "use_locking")); + super(new ScatterNdMax<>(op), op, Arrays.asList("T", "Tindices", "use_locking", "bad_indices_policy")); int inputIndex = 0; ref = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); @@ -187,6 +216,7 @@ public Inputs(GraphOperation op) { T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); useLocking = op.attributes().getAttrBool("use_locking"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMin.java index d2780381fcb..3ade02671ed 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMin.java @@ -36,8 +36,6 @@ /** * Computes element-wise minimum. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterNdMin.OP_NAME, @@ -85,6 +83,9 @@ public static ScatterNdMin create(Scope scope, Operand r if (opts.useLocking != null) { opBuilder.setAttr("use_locking", opts.useLocking); } + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } } } return new ScatterNdMin<>(opBuilder.build()); @@ -102,6 +103,16 @@ public static Options useLocking(Boolean useLocking) { return new Options().useLocking(useLocking); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Gets outputRef. * Same as ref. Returned as a convenience for operations that want @@ -123,6 +134,8 @@ public Output asOutput() { public static class Options { private Boolean useLocking; + private String badIndicesPolicy; + private Options() { } @@ -138,6 +151,17 @@ public Options useLocking(Boolean useLocking) { this.useLocking = useLocking; return this; } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } } @OpInputsMetadata( @@ -178,8 +202,13 @@ public static class Inputs extends RawOpInputs> */ public final boolean useLocking; + /** + * The badIndicesPolicy attribute + */ + public final String badIndicesPolicy; + public Inputs(GraphOperation op) { - super(new ScatterNdMin<>(op), op, Arrays.asList("T", "Tindices", "use_locking")); + super(new ScatterNdMin<>(op), op, Arrays.asList("T", "Tindices", "use_locking", "bad_indices_policy")); int inputIndex = 0; ref = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); @@ -187,6 +216,7 @@ public Inputs(GraphOperation op) { T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); useLocking = op.attributes().getAttrBool("use_locking"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdNonAliasingAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdNonAliasingAdd.java index 4d29ef748d8..c152dadc35e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdNonAliasingAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdNonAliasingAdd.java @@ -63,8 +63,6 @@ * [1, 13, 3, 14, 14, 6, 7, 20] * *

    See {@code tf.scatter_nd} for more details about how to make updates to slices. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ScatterNdNonAliasingAdd.OP_NAME, @@ -94,6 +92,7 @@ public ScatterNdNonAliasingAdd(Operation operation) { * A tensor of indices into {@code input}. * @param updates A Tensor. Must have the same type as ref. A tensor of updated values * to add to {@code input}. + * @param options carries optional attribute values * @param data type for {@code ScatterNdNonAliasingAdd} output and operands * @return a new instance of ScatterNdNonAliasingAdd */ @@ -101,14 +100,31 @@ public ScatterNdNonAliasingAdd(Operation operation) { describeByClass = true ) public static ScatterNdNonAliasingAdd create(Scope scope, Operand input, - Operand indices, Operand updates) { + Operand indices, Operand updates, Options... options) { OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "ScatterNdNonAliasingAdd"); opBuilder.addInput(input.asOutput()); opBuilder.addInput(indices.asOutput()); opBuilder.addInput(updates.asOutput()); + if (options != null) { + for (Options opts : options) { + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } + } + } return new ScatterNdNonAliasingAdd<>(opBuilder.build()); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Gets output. * A {@code Tensor} with the same shape as {@code input}, containing values of {@code input} @@ -124,6 +140,27 @@ public Output asOutput() { return output; } + /** + * Optional attributes for {@link org.tensorflow.op.core.ScatterNdNonAliasingAdd} + */ + public static class Options { + private String badIndicesPolicy; + + private Options() { + } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } + } + @OpInputsMetadata( outputsClass = ScatterNdNonAliasingAdd.class ) @@ -155,14 +192,20 @@ public static class Inputs extends RawOpInputs(op), op, Arrays.asList("T", "Tindices")); + super(new ScatterNdNonAliasingAdd<>(op), op, Arrays.asList("T", "Tindices", "bad_indices_policy")); int inputIndex = 0; input = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); updates = (Operand) op.input(inputIndex++); T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdSub.java index b2018d27511..21654611e88 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdSub.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdSub.java @@ -63,8 +63,6 @@ * *

    See {@code tf.scatter_nd} for more details about how to make updates to * slices. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterNdSub.OP_NAME, @@ -112,6 +110,9 @@ public static ScatterNdSub create(Scope scope, Operand r if (opts.useLocking != null) { opBuilder.setAttr("use_locking", opts.useLocking); } + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } } } return new ScatterNdSub<>(opBuilder.build()); @@ -129,6 +130,16 @@ public static Options useLocking(Boolean useLocking) { return new Options().useLocking(useLocking); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Gets outputRef. * Same as ref. Returned as a convenience for operations that want @@ -150,6 +161,8 @@ public Output asOutput() { public static class Options { private Boolean useLocking; + private String badIndicesPolicy; + private Options() { } @@ -165,6 +178,17 @@ public Options useLocking(Boolean useLocking) { this.useLocking = useLocking; return this; } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } } @OpInputsMetadata( @@ -205,8 +229,13 @@ public static class Inputs extends RawOpInputs> */ public final boolean useLocking; + /** + * The badIndicesPolicy attribute + */ + public final String badIndicesPolicy; + public Inputs(GraphOperation op) { - super(new ScatterNdSub<>(op), op, Arrays.asList("T", "Tindices", "use_locking")); + super(new ScatterNdSub<>(op), op, Arrays.asList("T", "Tindices", "use_locking", "bad_indices_policy")); int inputIndex = 0; ref = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); @@ -214,6 +243,7 @@ public Inputs(GraphOperation op) { T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); useLocking = op.attributes().getAttrBool("use_locking"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdUpdate.java index 56427f20fac..5bf1e30fe35 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdUpdate.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdUpdate.java @@ -62,8 +62,6 @@ *

    See {@code tf.scatter_nd} for more details about how to make updates to * slices. *

    See also {@code tf.scatter_update} and {@code tf.batch_scatter_update}. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterNdUpdate.OP_NAME, @@ -111,6 +109,9 @@ public static ScatterNdUpdate create(Scope scope, Operand(opBuilder.build()); @@ -128,6 +129,16 @@ public static Options useLocking(Boolean useLocking) { return new Options().useLocking(useLocking); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Gets outputRef. * Same as ref. Returned as a convenience for operations that want to @@ -149,6 +160,8 @@ public Output asOutput() { public static class Options { private Boolean useLocking; + private String badIndicesPolicy; + private Options() { } @@ -164,6 +177,17 @@ public Options useLocking(Boolean useLocking) { this.useLocking = useLocking; return this; } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } } @OpInputsMetadata( @@ -204,8 +228,13 @@ public static class Inputs extends RawOpInputs(op), op, Arrays.asList("T", "Tindices", "use_locking")); + super(new ScatterNdUpdate<>(op), op, Arrays.asList("T", "Tindices", "use_locking", "bad_indices_policy")); int inputIndex = 0; ref = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); @@ -213,6 +242,7 @@ public Inputs(GraphOperation op) { T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); useLocking = op.attributes().getAttrBool("use_locking"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterSub.java index 06d274ff356..4686a81470f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterSub.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterSub.java @@ -54,8 +54,6 @@ *

    * *
    - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterSub.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterUpdate.java index 711cbf7485f..60e22039589 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterUpdate.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterUpdate.java @@ -57,8 +57,6 @@ * * *

    See also {@code tf.batch_scatter_update} and {@code tf.scatter_nd_update}. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterUpdate.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Select.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Select.java index 71caff86d14..c88ea468f39 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Select.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Select.java @@ -36,8 +36,6 @@ /** * The SelectV2 operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = Select.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java index 61af8e762a2..562b2088b93 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java @@ -54,10 +54,6 @@ * out ==> [2, 4, 6] * idx ==> [1, 3, 5] * - * - * @param data type for {@code out} output - * - * @param data type for {@code idx} output */ @OpMetadata( opType = SetDiff1d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java index 4f9f9115847..2f7592fbc03 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java @@ -44,8 +44,6 @@ * # 't' is [[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]] * shape(t) ==> [2, 2, 3] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Shape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java index b56a39452d5..b53a00a1a82 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java @@ -41,8 +41,6 @@ /** * Returns shape of tensors. * This operation returns N 1-D integer tensors representing shape of {@code input[i]s}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ShapeN.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java index 1ad02bc0f9b..2be90850900 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java @@ -45,8 +45,6 @@ * # 't' is [[[1, 1,, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]]] * size(t) ==> 12 * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Size.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Slice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Slice.java index b53cae539a0..37a168fb6f7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Slice.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Slice.java @@ -41,8 +41,6 @@ * 'begin'. *

    Requirements: * 0 <= begin[i] <= begin[i] + size[i] <= Di for i in [0, n) - * - * @param data type for {@code output} output */ @OpMetadata( opType = Slice.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Snapshot.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Snapshot.java index d8b1ed563d9..bafca31221f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Snapshot.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Snapshot.java @@ -35,8 +35,6 @@ /** * Returns a copy of the input tensor. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Snapshot.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SpaceToBatchNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SpaceToBatchNd.java index d56e6ef8709..2a366e46641 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SpaceToBatchNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SpaceToBatchNd.java @@ -132,8 +132,6 @@ * *

    Among others, this operation is useful for reducing atrous convolution into * regular convolution. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SpaceToBatchNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Split.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Split.java index f6a01ed1950..dc4fad88677 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Split.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Split.java @@ -38,8 +38,6 @@ /** * Splits a tensor into {@code num_split} tensors along one dimension. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Split.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SplitV.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SplitV.java index 8d1beb3fc5b..cc0525e9645 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SplitV.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SplitV.java @@ -39,8 +39,6 @@ /** * Splits a tensor into {@code num_split} tensors along one dimension. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SplitV.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Squeeze.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Squeeze.java index 3ccc9dff638..52155b47d43 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Squeeze.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Squeeze.java @@ -50,8 +50,6 @@ * # 't' is a tensor of shape [1, 2, 1, 3, 1, 1] * shape(squeeze(t, [2, 4])) ==> [1, 2, 3, 1] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Squeeze.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stack.java index 0022997321a..976a86955b3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stack.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stack.java @@ -51,8 +51,6 @@ * pack([x, y, z], axis=1) => [[1, 2, 3], [4, 5, 6]] * *

    This is the opposite of {@code unpack}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Stack.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPop.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPop.java index a6a3021ce14..502cfcc8c06 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPop.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPop.java @@ -36,8 +36,6 @@ /** * Pop the element at the top of the stack. - * - * @param data type for {@code elem} output */ @OpMetadata( opType = StackPop.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPush.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPush.java index c43aa1de30e..f9f05ff1912 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPush.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPush.java @@ -35,8 +35,6 @@ /** * Push an element onto the stack. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StackPush.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StochasticCastToInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StochasticCastToInt.java index 29da2cb9a53..a06a2c8017d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StochasticCastToInt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StochasticCastToInt.java @@ -40,8 +40,6 @@ * Stochastically cast a given tensor from floats to ints. * The values are cast with a deterministic pseudo-random tensor from a uniform distribution generated from user given key, counter, algorithm. Values will saturate if out of the specified integer type range, and will become zero if inputs are NaN. *

    The outputs are a deterministic function of {@code input}, {@code key}, {@code counter}, {@code alg}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StochasticCastToInt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StopGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StopGradient.java index c2086cb3e92..fb486c42253 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StopGradient.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StopGradient.java @@ -85,8 +85,6 @@ *

  • Adversarial training, where no backprop should happen through the adversarial * example generation process.
    • * - * - * @param data type for {@code output} output */ @OpMetadata( opType = StopGradient.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSlice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSlice.java index 6b8953f7995..ec55dae1c24 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSlice.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSlice.java @@ -133,8 +133,6 @@ *

    Requirements: * {@code 0 != strides[i] for i in [0, m)} * {@code ellipsis_mask must be a power of two (only one ellipsis)} - * - * @param data type for {@code output} output */ @OpMetadata( opType = StridedSlice.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceAssign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceAssign.java index b2ab8d606e2..2911a675905 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceAssign.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceAssign.java @@ -41,8 +41,6 @@ * {@code begin}, {@code end}, {@code strides}, etc. work exactly as in {@code StridedSlice}. *

    NOTE this op currently does not support broadcasting and so {@code value}'s * shape must be exactly the shape produced by the slice of {@code ref}. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = StridedSliceAssign.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceGrad.java index 2a234c9ab7a..fcd7518dd87 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceGrad.java @@ -43,8 +43,6 @@ *

    Arguments are the same as StridedSliceGrad with the exception that * {@code dy} is the input gradient to be propagated and {@code shape} is the * shape of {@code StridedSlice}'s {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StridedSliceGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Sum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Sum.java index 15957ea2189..abcdb1ee9ef 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Sum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Sum.java @@ -40,8 +40,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Sum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SwitchCond.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SwitchCond.java index c6a8f810467..c6842c9ab87 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SwitchCond.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SwitchCond.java @@ -39,8 +39,6 @@ * If {@code pred} is true, the {@code data} input is forwarded to {@code output_true}. Otherwise, * the data goes to {@code output_false}. *

    See also {@code RefSwitch} and {@code Merge}. - * - * @param data type for {@code output_false} output */ @OpMetadata( opType = SwitchCond.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java index 3e8c8a70ec8..d66021bb728 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java @@ -48,8 +48,6 @@ * var = state_ops.assign(var, [[4.0, 5.0]]) * var = state_ops.assign_add(var, [[6.0, 7.0]]) * final = state_ops._destroy_temporary_variable(var, var_name=var_name) - * - * @param data type for {@code ref} output */ @OpMetadata( opType = TemporaryVariable.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java index b3dbc08ef3e..75ba48a0102 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java @@ -48,8 +48,6 @@ * (n0 + n1 + ... + n(T-1) x d0 x d1 x ...) * *

    All elements must have the same shape (excepting the first dimension). - * - * @param data type for {@code value} output */ @OpMetadata( opType = TensorArrayConcat.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java index 0f7fd351089..60d8b437b00 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java @@ -40,8 +40,6 @@ /** * Gather specific elements from the TensorArray into output {@code value}. * All elements selected by {@code indices} must have the same shape. - * - * @param data type for {@code value} output */ @OpMetadata( opType = TensorArrayGather.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java index 6e52e6ef906..d1cf5c89e65 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java @@ -39,8 +39,6 @@ /** * The TensorArrayPack operation - * - * @param data type for {@code value} output */ @OpMetadata( opType = TensorArrayPack.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java index 6765205c463..f5a0aa073a7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java @@ -38,8 +38,6 @@ /** * Read an element from the TensorArray into output {@code value}. - * - * @param data type for {@code value} output */ @OpMetadata( opType = TensorArrayRead.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java index 664783a09c5..70ef65f9314 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java @@ -48,8 +48,6 @@ * is not already set. * tensor: The concated result. * lengths: Output tensor containing sizes of the 0th dimension of tensors in the list, used for computing the gradient. - * - * @param data type for {@code tensor} output */ @OpMetadata( opType = TensorListConcat.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java index d955a6a636d..6190f9c1c01 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java @@ -39,8 +39,6 @@ * The shape of the elements of the given list, as a tensor. * input_handle: the list * element_shape: the shape of elements of the list - * - * @param data type for {@code element_shape} output */ @OpMetadata( opType = TensorListElementShape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java index 27a627b4759..ac725c72b97 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java @@ -42,8 +42,6 @@ *

    input_handle: The input tensor list. * indices: The indices used to index into the list. * values: The tensor. - * - * @param data type for {@code values} output */ @OpMetadata( opType = TensorListGather.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java index 1ea76d2101e..244704b5754 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java @@ -40,8 +40,6 @@ * input_handle: the list * index: the position in the list from which an element will be retrieved * item: the element at that position - * - * @param data type for {@code item} output */ @OpMetadata( opType = TensorListGetItem.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java index ee7a5cde1c9..af805e71f9b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java @@ -42,8 +42,6 @@ * tensor: the withdrawn last element of the list * element_dtype: the type of elements in the list * element_shape: the shape of the output tensor - * - * @param data type for {@code tensor} output */ @OpMetadata( opType = TensorListPopBack.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java index fec4f942658..2d058b8e00d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java @@ -41,8 +41,6 @@ *

    input_handle: the input list * tensor: the gathered result * num_elements: optional. If not -1, the number of elements in the list. - * - * @param data type for {@code tensor} output */ @OpMetadata( opType = TensorListStack.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapLookup.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapLookup.java index dccdc1ee996..a3e8b54e888 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapLookup.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapLookup.java @@ -39,8 +39,6 @@ * input_handle: the input map * key: the key to be looked up * value: the value found from the given key - * - * @param data type for {@code value} output */ @OpMetadata( opType = TensorMapLookup.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapStackKeys.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapStackKeys.java index b2a217c98e6..8942b2f9f8b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapStackKeys.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapStackKeys.java @@ -38,8 +38,6 @@ * Returns a Tensor stack of all keys in a tensor map. * input_handle: the input map * keys: the returned Tensor of all keys in the map - * - * @param data type for {@code keys} output */ @OpMetadata( opType = TensorMapStackKeys.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdAdd.java index a72a1defde1..77d1dd111d5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdAdd.java @@ -94,10 +94,16 @@ * * * - *

    Note: on CPU, if an out of bound index is found, an error is returned. - * On GPU, if an out of bound index is found, the index is ignored. - * - * @param data type for {@code output} output + *

    If {@code indices} contains any out-of-bound indices, depending on + * {@code bad_indices_policy}, the op will either return an error or ignore the + * out-of-bound indices. {@code bad_indices_policy} can be one of the following values: + *

      + *
    1. "" or "DEFAULT": raises on CPU and ignore on GPU. This is because + * historically on CPU and GPU we handle errors in different ways, and for + * backward compatibility we keep the default behavior.
      2. + *
    2. "ERROR": raises error; GPU does not support this value.
      3. + *
    3. "IGNORE": ignore the bad indices; supported on both CPU and GPU.
      4. + *
    */ @OpMetadata( opType = TensorScatterNdAdd.OP_NAME, @@ -125,6 +131,7 @@ public TensorScatterNdAdd(Operation operation) { * @param tensor Tensor to copy/update. * @param indices Index tensor. * @param updates Updates to scatter into output. + * @param options carries optional attribute values * @param data type for {@code TensorScatterAdd} output and operands * @return a new instance of TensorScatterNdAdd */ @@ -132,14 +139,31 @@ public TensorScatterNdAdd(Operation operation) { describeByClass = true ) public static TensorScatterNdAdd create(Scope scope, Operand tensor, - Operand indices, Operand updates) { + Operand indices, Operand updates, Options... options) { OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "TensorScatterNdAdd"); opBuilder.addInput(tensor.asOutput()); opBuilder.addInput(indices.asOutput()); opBuilder.addInput(updates.asOutput()); + if (options != null) { + for (Options opts : options) { + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } + } + } return new TensorScatterNdAdd<>(opBuilder.build()); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Gets output. * A new tensor copied from tensor and updates added according to the indices. @@ -154,6 +178,27 @@ public Output asOutput() { return output; } + /** + * Optional attributes for {@link org.tensorflow.op.core.TensorScatterNdAdd} + */ + public static class Options { + private String badIndicesPolicy; + + private Options() { + } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } + } + @OpInputsMetadata( outputsClass = TensorScatterNdAdd.class ) @@ -183,14 +228,20 @@ public static class Inputs extends RawOpInputs(op), op, Arrays.asList("T", "Tindices")); + super(new TensorScatterNdAdd<>(op), op, Arrays.asList("T", "Tindices", "bad_indices_policy")); int inputIndex = 0; tensor = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); updates = (Operand) op.input(inputIndex++); T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMax.java index ceddda24a20..cbf9b2dd471 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMax.java @@ -50,8 +50,6 @@ * * *

    Refer to {@code tf.tensor_scatter_nd_update} for more details. - * - * @param data type for {@code output} output */ @OpMetadata( opType = TensorScatterNdMax.OP_NAME, @@ -79,6 +77,7 @@ public TensorScatterNdMax(Operation operation) { * @param tensor Tensor to update. * @param indices Index tensor. * @param updates Updates to scatter into output. + * @param options carries optional attribute values * @param data type for {@code TensorScatterMax} output and operands * @return a new instance of TensorScatterNdMax */ @@ -86,14 +85,31 @@ public TensorScatterNdMax(Operation operation) { describeByClass = true ) public static TensorScatterNdMax create(Scope scope, Operand tensor, - Operand indices, Operand updates) { + Operand indices, Operand updates, Options... options) { OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "TensorScatterNdMax"); opBuilder.addInput(tensor.asOutput()); opBuilder.addInput(indices.asOutput()); opBuilder.addInput(updates.asOutput()); + if (options != null) { + for (Options opts : options) { + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } + } + } return new TensorScatterNdMax<>(opBuilder.build()); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Gets output. * A new tensor copied from tensor whose values are element-wise maximum between tensor and updates according to the indices. @@ -108,6 +124,27 @@ public Output asOutput() { return output; } + /** + * Optional attributes for {@link org.tensorflow.op.core.TensorScatterNdMax} + */ + public static class Options { + private String badIndicesPolicy; + + private Options() { + } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } + } + @OpInputsMetadata( outputsClass = TensorScatterNdMax.class ) @@ -137,14 +174,20 @@ public static class Inputs extends RawOpInputs(op), op, Arrays.asList("T", "Tindices")); + super(new TensorScatterNdMax<>(op), op, Arrays.asList("T", "Tindices", "bad_indices_policy")); int inputIndex = 0; tensor = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); updates = (Operand) op.input(inputIndex++); T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMin.java index b6da07b4c31..7db99c551d1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMin.java @@ -36,8 +36,6 @@ /** * The TensorScatterMin operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = TensorScatterNdMin.OP_NAME, @@ -65,6 +63,7 @@ public TensorScatterNdMin(Operation operation) { * @param tensor Tensor to update. * @param indices Index tensor. * @param updates Updates to scatter into output. + * @param options carries optional attribute values * @param data type for {@code TensorScatterMin} output and operands * @return a new instance of TensorScatterNdMin */ @@ -72,14 +71,31 @@ public TensorScatterNdMin(Operation operation) { describeByClass = true ) public static TensorScatterNdMin create(Scope scope, Operand tensor, - Operand indices, Operand updates) { + Operand indices, Operand updates, Options... options) { OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "TensorScatterNdMin"); opBuilder.addInput(tensor.asOutput()); opBuilder.addInput(indices.asOutput()); opBuilder.addInput(updates.asOutput()); + if (options != null) { + for (Options opts : options) { + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } + } + } return new TensorScatterNdMin<>(opBuilder.build()); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Gets output. * A new tensor copied from tensor whose values are element-wise minimum between tensor and updates according to the indices. @@ -94,6 +110,27 @@ public Output asOutput() { return output; } + /** + * Optional attributes for {@link org.tensorflow.op.core.TensorScatterNdMin} + */ + public static class Options { + private String badIndicesPolicy; + + private Options() { + } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } + } + @OpInputsMetadata( outputsClass = TensorScatterNdMin.class ) @@ -123,14 +160,20 @@ public static class Inputs extends RawOpInputs(op), op, Arrays.asList("T", "Tindices")); + super(new TensorScatterNdMin<>(op), op, Arrays.asList("T", "Tindices", "bad_indices_policy")); int inputIndex = 0; tensor = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); updates = (Operand) op.input(inputIndex++); T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdSub.java index 3623707e77e..095e0428962 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdSub.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdSub.java @@ -91,8 +91,6 @@ * *

    Note that on CPU, if an out of bound index is found, an error is returned. * On GPU, if an out of bound index is found, the index is ignored. - * - * @param data type for {@code output} output */ @OpMetadata( opType = TensorScatterNdSub.OP_NAME, @@ -120,6 +118,7 @@ public TensorScatterNdSub(Operation operation) { * @param tensor Tensor to copy/update. * @param indices Index tensor. * @param updates Updates to scatter into output. + * @param options carries optional attribute values * @param data type for {@code TensorScatterSub} output and operands * @return a new instance of TensorScatterNdSub */ @@ -127,14 +126,31 @@ public TensorScatterNdSub(Operation operation) { describeByClass = true ) public static TensorScatterNdSub create(Scope scope, Operand tensor, - Operand indices, Operand updates) { + Operand indices, Operand updates, Options... options) { OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "TensorScatterNdSub"); opBuilder.addInput(tensor.asOutput()); opBuilder.addInput(indices.asOutput()); opBuilder.addInput(updates.asOutput()); + if (options != null) { + for (Options opts : options) { + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } + } + } return new TensorScatterNdSub<>(opBuilder.build()); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Gets output. * A new tensor copied from tensor and updates subtracted according to the indices. @@ -149,6 +165,27 @@ public Output asOutput() { return output; } + /** + * Optional attributes for {@link org.tensorflow.op.core.TensorScatterNdSub} + */ + public static class Options { + private String badIndicesPolicy; + + private Options() { + } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } + } + @OpInputsMetadata( outputsClass = TensorScatterNdSub.class ) @@ -178,14 +215,20 @@ public static class Inputs extends RawOpInputs(op), op, Arrays.asList("T", "Tindices")); + super(new TensorScatterNdSub<>(op), op, Arrays.asList("T", "Tindices", "bad_indices_policy")); int inputIndex = 0; tensor = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); updates = (Operand) op.input(inputIndex++); T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdUpdate.java index 3c53fca7eab..96323c0db29 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdUpdate.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdUpdate.java @@ -42,7 +42,6 @@ * scattered onto an existing tensor (as opposed to a zero-tensor). If the memory * for the existing tensor cannot be re-used, a copy is made and updated. *

    If {@code indices} contains duplicates, then we pick the last update for the index. - *

    If an out of bound index is found on CPU, an error is returned. *

    WARNING: There are some GPU specific semantics for this operation. *

      *
    • If an out of bound index is found, the index is ignored.
      • @@ -64,9 +63,17 @@ * 
        * indices.shape[:-1] + tensor.shape[indices.shape[-1]:]
  *
      + *

      If {@code indices} contains any out-of-bound indices, depending on + * {@code bad_indices_policy}, the op will either return an error or ignore the + * out-of-bound indices. {@code bad_indices_policy} can be one of the following values: + *

        + *
      1. "" or "DEFAULT": raises on CPU and ignore on GPU. This is because + * historically on CPU and GPU we handle errors in different ways, and for + * backward compatibility we keep the default behavior.
        2. + *
      2. "ERROR": raises error; GPU does not support this value.
        3. + *
      3. "IGNORE": ignore the bad indices; supported on both CPU and GPU.
        4. + *
      *

      For usage examples see the python tf.tensor_scatter_nd_update {@link org.tensorflow.op.Ops#tensorScatterNdUpdate} function - * - * @param data type for {@code output} output */ @OpMetadata( opType = TensorScatterNdUpdate.OP_NAME, @@ -94,6 +101,7 @@ public TensorScatterNdUpdate(Operation operation) { * @param tensor Tensor to copy/update. * @param indices Index tensor. * @param updates Updates to scatter into output. + * @param options carries optional attribute values * @param data type for {@code TensorScatterUpdate} output and operands * @return a new instance of TensorScatterNdUpdate */ @@ -101,14 +109,31 @@ public TensorScatterNdUpdate(Operation operation) { describeByClass = true ) public static TensorScatterNdUpdate create(Scope scope, Operand tensor, - Operand indices, Operand updates) { + Operand indices, Operand updates, Options... options) { OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "TensorScatterNdUpdate"); opBuilder.addInput(tensor.asOutput()); opBuilder.addInput(indices.asOutput()); opBuilder.addInput(updates.asOutput()); + if (options != null) { + for (Options opts : options) { + if (opts.badIndicesPolicy != null) { + opBuilder.setAttr("bad_indices_policy", opts.badIndicesPolicy); + } + } + } return new TensorScatterNdUpdate<>(opBuilder.build()); } + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public static Options badIndicesPolicy(String badIndicesPolicy) { + return new Options().badIndicesPolicy(badIndicesPolicy); + } + /** * Gets output. * A new tensor with the given shape and updates applied according @@ -124,6 +149,27 @@ public Output asOutput() { return output; } + /** + * Optional attributes for {@link org.tensorflow.op.core.TensorScatterNdUpdate} + */ + public static class Options { + private String badIndicesPolicy; + + private Options() { + } + + /** + * Sets the badIndicesPolicy option. + * + * @param badIndicesPolicy the badIndicesPolicy option + * @return this Options instance. + */ + public Options badIndicesPolicy(String badIndicesPolicy) { + this.badIndicesPolicy = badIndicesPolicy; + return this; + } + } + @OpInputsMetadata( outputsClass = TensorScatterNdUpdate.class ) @@ -153,14 +199,20 @@ public static class Inputs extends RawOpInputs(op), op, Arrays.asList("T", "Tindices")); + super(new TensorScatterNdUpdate<>(op), op, Arrays.asList("T", "Tindices", "bad_indices_policy")); int inputIndex = 0; tensor = (Operand) op.input(inputIndex++); indices = (Operand) op.input(inputIndex++); updates = (Operand) op.input(inputIndex++); T = op.attributes().getAttrType("T"); Tindices = op.attributes().getAttrType("Tindices"); + badIndicesPolicy = op.attributes().getAttrString("bad_indices_policy"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorStridedSliceUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorStridedSliceUpdate.java index 23b2d386a05..de80c141d72 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorStridedSliceUpdate.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorStridedSliceUpdate.java @@ -41,8 +41,6 @@ * {@code strides} etc. work exactly as in {@code StridedSlice}. *

      NOTE this op currently does not support broadcasting and so {@code value}'s shape * must be exactly the shape produced by the slice of {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = TensorStridedSliceUpdate.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Tile.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Tile.java index c9a58b9158c..7339fdbb3de 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Tile.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Tile.java @@ -67,8 +67,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Tile.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unbatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unbatch.java index a49747c48ca..fa4c04f3c27 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unbatch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unbatch.java @@ -53,8 +53,6 @@ * shared_name: Instances of Unbatch with the same container and shared_name are * assumed to possibly belong to the same batch. If left empty, the op name will * be used as the shared name. - * - * @param data type for {@code unbatched_tensor} output */ @OpMetadata( opType = Unbatch.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnbatchGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnbatchGrad.java index 912e08c3a6b..25418f3986f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnbatchGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnbatchGrad.java @@ -49,8 +49,6 @@ * shared_name: Instances of UnbatchGrad with the same container and shared_name * are assumed to possibly belong to the same batch. If left empty, the op name * will be used as the shared name. - * - * @param data type for {@code batched_grad} output */ @OpMetadata( opType = UnbatchGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniformQuantizedClipByValue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniformQuantizedClipByValue.java index ca3c5dfdd14..f1a4eb739d1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniformQuantizedClipByValue.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniformQuantizedClipByValue.java @@ -40,8 +40,6 @@ * Given quantized {@code operand} which was quantized using {@code scales} and {@code zero_points}, performs clip by value using {@code min} and {@code max} values. * If quantization_axis is -1 (per-tensor quantized), the entire operand is clipped using scalar min, max. * Otherwise (per-channel quantized), the clipping is also done per-channel. - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformQuantizedClipByValue.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java index c4324a9f324..4d17cf9f141 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java @@ -74,10 +74,6 @@ * [2, 0]] * idx ==> [0, 1, 1] * - * - * @param data type for {@code y} output - * - * @param data type for {@code idx} output */ @OpMetadata( opType = Unique.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java index 80a1804887f..8046082f95b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java @@ -78,10 +78,6 @@ * idx ==> [0, 1, 1] * count ==> [1, 2] * - * - * @param data type for {@code y} output - * - * @param data type for {@code idx} output */ @OpMetadata( opType = UniqueWithCounts.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java index 5393635bc69..ec7c8f8c6e9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java @@ -52,8 +52,6 @@ *

      {@literal @}compatibility(numpy)
      * Equivalent to np.unravel_index *
      {@literal @}end_compatibility - * - * @param data type for {@code output} output */ @OpMetadata( opType = UnravelIndex.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstack.java index fd20a76940d..64c8de23911 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstack.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstack.java @@ -46,8 +46,6 @@ * and each tensor in {@code output} will have shape {@code (A, C, D)}. * Etc. *

      This is the opposite of {@code pack}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Unstack.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java index d5e939ffde6..78e45391c8a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java @@ -51,8 +51,6 @@ *

      result = UpperBound(sorted_sequence, values) *

      result == [[1, 2, 4], * [0, 2, 5]] - * - * @param data type for {@code output} output */ @OpMetadata( opType = UpperBound.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java index a0febf9c223..d8b09bfddde 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java @@ -40,8 +40,6 @@ * Outputs a ref to the tensor state so it may be read or modified. * TODO(zhifengc/mrry): Adds a pointer to a more detail document * about sharing states in tensorflow. - * - * @param data type for {@code ref} output */ @OpMetadata( opType = Variable.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java index 3f94b9efbd6..abfd8d7c504 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java @@ -44,8 +44,6 @@ * # 't' is [[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]] * shape(t) ==> [2, 2, 3] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = VariableShape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ZerosLike.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ZerosLike.java index 792a37d112c..497cf5128b8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ZerosLike.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ZerosLike.java @@ -35,8 +35,6 @@ /** * Returns a tensor of zeros with the same shape and type as x. - * - * @param data type for {@code y} output */ @OpMetadata( opType = ZerosLike.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GlobalShuffleDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GlobalShuffleDataset.java new file mode 100644 index 00000000000..19ec4cd2e96 --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GlobalShuffleDataset.java @@ -0,0 +1,230 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.data; + +import java.util.Arrays; +import java.util.List; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Operands; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.proto.DataType; +import org.tensorflow.types.TInt64; +import org.tensorflow.types.family.TType; + +/** + * The GlobalShuffleDataset operation + */ +@OpMetadata( + opType = GlobalShuffleDataset.OP_NAME, + inputsClass = GlobalShuffleDataset.Inputs.class +) +public final class GlobalShuffleDataset extends RawOp implements Operand { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "GlobalShuffleDataset"; + + private Output handle; + + @SuppressWarnings("unchecked") + public GlobalShuffleDataset(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + handle = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new GlobalShuffleDataset operation. + * + * @param scope current scope + * @param inputDataset The inputDataset value + * @param seed The seed value + * @param seed2 The seed2 value + * @param seedGenerator The seedGenerator value + * @param outputTypes The value of the outputTypes attribute + * @param outputShapes The value of the outputShapes attribute + * @param options carries optional attribute values + * @return a new instance of GlobalShuffleDataset + */ + @Endpoint( + describeByClass = true + ) + public static GlobalShuffleDataset create(Scope scope, Operand inputDataset, + Operand seed, Operand seed2, Operand seedGenerator, + List> outputTypes, List outputShapes, Options... options) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "GlobalShuffleDataset"); + opBuilder.addInput(inputDataset.asOutput()); + opBuilder.addInput(seed.asOutput()); + opBuilder.addInput(seed2.asOutput()); + opBuilder.addInput(seedGenerator.asOutput()); + opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes)); + Shape[] outputShapesArray = new Shape[outputShapes.size()]; + for (int i = 0 ; i < outputShapesArray.length ; i++) { + outputShapesArray[i] = outputShapes.get(i); + } + opBuilder.setAttr("output_shapes", outputShapesArray); + if (options != null) { + for (Options opts : options) { + if (opts.reshuffleEachIteration != null) { + opBuilder.setAttr("reshuffle_each_iteration", opts.reshuffleEachIteration); + } + if (opts.metadata != null) { + opBuilder.setAttr("metadata", opts.metadata); + } + } + } + return new GlobalShuffleDataset(opBuilder.build()); + } + + /** + * Sets the reshuffleEachIteration option. + * + * @param reshuffleEachIteration the reshuffleEachIteration option + * @return this Options instance. + */ + public static Options reshuffleEachIteration(Boolean reshuffleEachIteration) { + return new Options().reshuffleEachIteration(reshuffleEachIteration); + } + + /** + * Sets the metadata option. + * + * @param metadata the metadata option + * @return this Options instance. + */ + public static Options metadata(String metadata) { + return new Options().metadata(metadata); + } + + /** + * Gets handle. + * + * @return handle. + */ + public Output handle() { + return handle; + } + + @Override + @SuppressWarnings("unchecked") + public Output asOutput() { + return (Output) handle; + } + + /** + * Optional attributes for {@link org.tensorflow.op.data.GlobalShuffleDataset} + */ + public static class Options { + private Boolean reshuffleEachIteration; + + private String metadata; + + private Options() { + } + + /** + * Sets the reshuffleEachIteration option. + * + * @param reshuffleEachIteration the reshuffleEachIteration option + * @return this Options instance. + */ + public Options reshuffleEachIteration(Boolean reshuffleEachIteration) { + this.reshuffleEachIteration = reshuffleEachIteration; + return this; + } + + /** + * Sets the metadata option. + * + * @param metadata the metadata option + * @return this Options instance. + */ + public Options metadata(String metadata) { + this.metadata = metadata; + return this; + } + } + + @OpInputsMetadata( + outputsClass = GlobalShuffleDataset.class + ) + public static class Inputs extends RawOpInputs { + /** + * The inputDataset input + */ + public final Operand inputDataset; + + /** + * The seed input + */ + public final Operand seed; + + /** + * The seed2 input + */ + public final Operand seed2; + + /** + * The seedGenerator input + */ + public final Operand seedGenerator; + + /** + * The reshuffleEachIteration attribute + */ + public final boolean reshuffleEachIteration; + + /** + * The outputTypes attribute + */ + public final DataType[] outputTypes; + + /** + * The outputShapes attribute + */ + public final Shape[] outputShapes; + + /** + * The metadata attribute + */ + public final String metadata; + + public Inputs(GraphOperation op) { + super(new GlobalShuffleDataset(op), op, Arrays.asList("reshuffle_each_iteration", "output_types", "output_shapes", "metadata")); + int inputIndex = 0; + inputDataset = (Operand) op.input(inputIndex++); + seed = (Operand) op.input(inputIndex++); + seed2 = (Operand) op.input(inputIndex++); + seedGenerator = (Operand) op.input(inputIndex++); + reshuffleEachIteration = op.attributes().getAttrBool("reshuffle_each_iteration"); + outputTypes = op.attributes().getAttrTypeList("output_types"); + outputShapes = op.attributes().getAttrShapeList("output_shapes"); + metadata = op.attributes().getAttrString("metadata"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IndexFlatMapDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IndexFlatMapDataset.java new file mode 100644 index 00000000000..b5d3f116ad5 --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IndexFlatMapDataset.java @@ -0,0 +1,224 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.data; + +import java.util.Arrays; +import java.util.List; +import org.tensorflow.ConcreteFunction; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Operands; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.op.annotation.Operator; +import org.tensorflow.proto.DataType; +import org.tensorflow.types.TInt64; +import org.tensorflow.types.family.TType; + +/** + * The IndexFlatMapDataset operation + */ +@OpMetadata( + opType = IndexFlatMapDataset.OP_NAME, + inputsClass = IndexFlatMapDataset.Inputs.class +) +@Operator( + group = "data" +) +public final class IndexFlatMapDataset extends RawOp implements Operand { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "IndexFlatMapDataset"; + + private Output handle; + + @SuppressWarnings("unchecked") + public IndexFlatMapDataset(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + handle = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new IndexFlatMapDataset operation. + * + * @param scope current scope + * @param inputDataset The inputDataset value + * @param mapFuncOtherArgs The mapFuncOtherArgs value + * @param indexMapFuncOtherArgs The indexMapFuncOtherArgs value + * @param outputCardinality The outputCardinality value + * @param mapFunc The value of the mapFunc attribute + * @param indexMapFunc The value of the indexMapFunc attribute + * @param outputTypes The value of the outputTypes attribute + * @param outputShapes The value of the outputShapes attribute + * @param options carries optional attribute values + * @return a new instance of IndexFlatMapDataset + */ + @Endpoint( + describeByClass = true + ) + public static IndexFlatMapDataset create(Scope scope, Operand inputDataset, + Iterable> mapFuncOtherArgs, Iterable> indexMapFuncOtherArgs, + Operand outputCardinality, ConcreteFunction mapFunc, ConcreteFunction indexMapFunc, + List> outputTypes, List outputShapes, Options... options) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "IndexFlatMapDataset"); + opBuilder.addInput(inputDataset.asOutput()); + opBuilder.addInputList(Operands.asOutputs(mapFuncOtherArgs)); + opBuilder.addInputList(Operands.asOutputs(indexMapFuncOtherArgs)); + opBuilder.addInput(outputCardinality.asOutput()); + opBuilder.setAttr("map_func", mapFunc); + opBuilder.setAttr("index_map_func", indexMapFunc); + opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes)); + Shape[] outputShapesArray = new Shape[outputShapes.size()]; + for (int i = 0 ; i < outputShapesArray.length ; i++) { + outputShapesArray[i] = outputShapes.get(i); + } + opBuilder.setAttr("output_shapes", outputShapesArray); + if (options != null) { + for (Options opts : options) { + if (opts.metadata != null) { + opBuilder.setAttr("metadata", opts.metadata); + } + } + } + return new IndexFlatMapDataset(opBuilder.build()); + } + + /** + * Sets the metadata option. + * + * @param metadata the metadata option + * @return this Options instance. + */ + public static Options metadata(String metadata) { + return new Options().metadata(metadata); + } + + /** + * Gets handle. + * + * @return handle. + */ + public Output handle() { + return handle; + } + + @Override + @SuppressWarnings("unchecked") + public Output asOutput() { + return (Output) handle; + } + + /** + * Optional attributes for {@link org.tensorflow.op.data.IndexFlatMapDataset} + */ + public static class Options { + private String metadata; + + private Options() { + } + + /** + * Sets the metadata option. + * + * @param metadata the metadata option + * @return this Options instance. + */ + public Options metadata(String metadata) { + this.metadata = metadata; + return this; + } + } + + @OpInputsMetadata( + outputsClass = IndexFlatMapDataset.class + ) + public static class Inputs extends RawOpInputs { + /** + * The inputDataset input + */ + public final Operand inputDataset; + + /** + * The mapFuncOtherArgs input + */ + public final Iterable> mapFuncOtherArgs; + + /** + * The indexMapFuncOtherArgs input + */ + public final Iterable> indexMapFuncOtherArgs; + + /** + * The outputCardinality input + */ + public final Operand outputCardinality; + + /** + * The TmapFuncArgs attribute + */ + public final DataType[] TmapFuncArgs; + + /** + * The TindexMapFuncArgs attribute + */ + public final DataType[] TindexMapFuncArgs; + + /** + * The outputTypes attribute + */ + public final DataType[] outputTypes; + + /** + * The outputShapes attribute + */ + public final Shape[] outputShapes; + + /** + * The metadata attribute + */ + public final String metadata; + + public Inputs(GraphOperation op) { + super(new IndexFlatMapDataset(op), op, Arrays.asList("Tmap_func_args", "Tindex_map_func_args", "output_types", "output_shapes", "metadata")); + int inputIndex = 0; + inputDataset = (Operand) op.input(inputIndex++); + int mapFuncOtherArgsLength = op.inputListLength("map_func_other_args"); + mapFuncOtherArgs = Arrays.asList((Operand[]) op.inputList(inputIndex, mapFuncOtherArgsLength)); + inputIndex += mapFuncOtherArgsLength; + int indexMapFuncOtherArgsLength = op.inputListLength("index_map_func_other_args"); + indexMapFuncOtherArgs = Arrays.asList((Operand[]) op.inputList(inputIndex, indexMapFuncOtherArgsLength)); + inputIndex += indexMapFuncOtherArgsLength; + outputCardinality = (Operand) op.input(inputIndex++); + TmapFuncArgs = op.attributes().getAttrTypeList("Tmap_func_args"); + TindexMapFuncArgs = op.attributes().getAttrTypeList("Tindex_map_func_args"); + outputTypes = op.attributes().getAttrTypeList("output_types"); + outputShapes = op.attributes().getAttrShapeList("output_shapes"); + metadata = op.attributes().getAttrString("metadata"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetModelProto.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetModelProto.java new file mode 100644 index 00000000000..1ad0de4c183 --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetModelProto.java @@ -0,0 +1,102 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.data; + +import java.util.Arrays; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.types.TString; +import org.tensorflow.types.family.TType; + +/** + * Returns the serialized model proto of an iterator resource. + * Returns the serialized model proto of an iterator resource. + */ +@OpMetadata( + opType = IteratorGetModelProto.OP_NAME, + inputsClass = IteratorGetModelProto.Inputs.class +) +public final class IteratorGetModelProto extends RawOp implements Operand { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "IteratorGetModelProto"; + + private Output modelProto; + + public IteratorGetModelProto(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + modelProto = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new IteratorGetModelProto operation. + * + * @param scope current scope + * @param iterator An resource from an dataset iterator. + * @return a new instance of IteratorGetModelProto + */ + @Endpoint( + describeByClass = true + ) + public static IteratorGetModelProto create(Scope scope, Operand iterator) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "IteratorGetModelProto"); + opBuilder.addInput(iterator.asOutput()); + return new IteratorGetModelProto(opBuilder.build()); + } + + /** + * Gets modelProto. + * A serialized model proto. + * @return modelProto. + */ + public Output modelProto() { + return modelProto; + } + + @Override + public Output asOutput() { + return modelProto; + } + + @OpInputsMetadata( + outputsClass = IteratorGetModelProto.class + ) + public static class Inputs extends RawOpInputs { + /** + * An resource from an dataset iterator. + */ + public final Operand iterator; + + public Inputs(GraphOperation op) { + super(new IteratorGetModelProto(op), op, Arrays.asList()); + int inputIndex = 0; + iterator = (Operand) op.input(inputIndex++); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java index a42cc0f51d2..131903f2fc1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java @@ -35,8 +35,6 @@ /** * Computes rectified linear gradients for a LeakyRelu operation. - * - * @param data type for {@code backprops} output */ @OpMetadata( opType = LeakyReluGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MapDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MapDataset.java index 6e8ca298f38..4b6e7355a51 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MapDataset.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MapDataset.java @@ -98,6 +98,9 @@ public static MapDataset create(Scope scope, Operand inputDatas if (opts.preserveCardinality != null) { opBuilder.setAttr("preserve_cardinality", opts.preserveCardinality); } + if (opts.forceSynchronous != null) { + opBuilder.setAttr("force_synchronous", opts.forceSynchronous); + } if (opts.metadata != null) { opBuilder.setAttr("metadata", opts.metadata); } @@ -126,6 +129,16 @@ public static Options preserveCardinality(Boolean preserveCardinality) { return new Options().preserveCardinality(preserveCardinality); } + /** + * Sets the forceSynchronous option. + * + * @param forceSynchronous the forceSynchronous option + * @return this Options instance. + */ + public static Options forceSynchronous(Boolean forceSynchronous) { + return new Options().forceSynchronous(forceSynchronous); + } + /** * Sets the metadata option. * @@ -159,6 +172,8 @@ public static class Options { private Boolean preserveCardinality; + private Boolean forceSynchronous; + private String metadata; private Options() { @@ -186,6 +201,17 @@ public Options preserveCardinality(Boolean preserveCardinality) { return this; } + /** + * Sets the forceSynchronous option. + * + * @param forceSynchronous the forceSynchronous option + * @return this Options instance. + */ + public Options forceSynchronous(Boolean forceSynchronous) { + this.forceSynchronous = forceSynchronous; + return this; + } + /** * Sets the metadata option. * @@ -237,13 +263,18 @@ public static class Inputs extends RawOpInputs { */ public final boolean preserveCardinality; + /** + * The forceSynchronous attribute + */ + public final boolean forceSynchronous; + /** * The metadata attribute */ public final String metadata; public Inputs(GraphOperation op) { - super(new MapDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes", "use_inter_op_parallelism", "preserve_cardinality", "metadata")); + super(new MapDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes", "use_inter_op_parallelism", "preserve_cardinality", "force_synchronous", "metadata")); int inputIndex = 0; inputDataset = (Operand) op.input(inputIndex++); int otherArgumentsLength = op.inputListLength("other_arguments"); @@ -254,6 +285,7 @@ public Inputs(GraphOperation op) { outputShapes = op.attributes().getAttrShapeList("output_shapes"); useInterOpParallelism = op.attributes().getAttrBool("use_inter_op_parallelism"); preserveCardinality = op.attributes().getAttrBool("preserve_cardinality"); + forceSynchronous = op.attributes().getAttrBool("force_synchronous"); metadata = op.attributes().getAttrString("metadata"); } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelMapDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelMapDataset.java index 68e97058b5c..6b783929411 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelMapDataset.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelMapDataset.java @@ -107,6 +107,9 @@ public static ParallelMapDataset create(Scope scope, Operand in if (opts.preserveCardinality != null) { opBuilder.setAttr("preserve_cardinality", opts.preserveCardinality); } + if (opts.useUnboundedThreadpool != null) { + opBuilder.setAttr("use_unbounded_threadpool", opts.useUnboundedThreadpool); + } if (opts.metadata != null) { opBuilder.setAttr("metadata", opts.metadata); } @@ -145,6 +148,16 @@ public static Options preserveCardinality(Boolean preserveCardinality) { return new Options().preserveCardinality(preserveCardinality); } + /** + * Sets the useUnboundedThreadpool option. + * + * @param useUnboundedThreadpool the useUnboundedThreadpool option + * @return this Options instance. + */ + public static Options useUnboundedThreadpool(Boolean useUnboundedThreadpool) { + return new Options().useUnboundedThreadpool(useUnboundedThreadpool); + } + /** * Sets the metadata option. * @@ -180,6 +193,8 @@ public static class Options { private Boolean preserveCardinality; + private Boolean useUnboundedThreadpool; + private String metadata; private Options() { @@ -218,6 +233,17 @@ public Options preserveCardinality(Boolean preserveCardinality) { return this; } + /** + * Sets the useUnboundedThreadpool option. + * + * @param useUnboundedThreadpool the useUnboundedThreadpool option + * @return this Options instance. + */ + public Options useUnboundedThreadpool(Boolean useUnboundedThreadpool) { + this.useUnboundedThreadpool = useUnboundedThreadpool; + return this; + } + /** * Sets the metadata option. * @@ -280,13 +306,18 @@ public static class Inputs extends RawOpInputs { */ public final boolean preserveCardinality; + /** + * The useUnboundedThreadpool attribute + */ + public final boolean useUnboundedThreadpool; + /** * The metadata attribute */ public final String metadata; public Inputs(GraphOperation op) { - super(new ParallelMapDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes", "use_inter_op_parallelism", "deterministic", "preserve_cardinality", "metadata")); + super(new ParallelMapDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes", "use_inter_op_parallelism", "deterministic", "preserve_cardinality", "use_unbounded_threadpool", "metadata")); int inputIndex = 0; inputDataset = (Operand) op.input(inputIndex++); int otherArgumentsLength = op.inputListLength("other_arguments"); @@ -299,6 +330,7 @@ public Inputs(GraphOperation op) { useInterOpParallelism = op.attributes().getAttrBool("use_inter_op_parallelism"); deterministic = op.attributes().getAttrString("deterministic"); preserveCardinality = op.attributes().getAttrBool("preserve_cardinality"); + useUnboundedThreadpool = op.attributes().getAttrBool("use_unbounded_threadpool"); metadata = op.attributes().getAttrString("metadata"); } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WeightedFlatMapDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WeightedFlatMapDataset.java new file mode 100644 index 00000000000..2f97c1e168c --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WeightedFlatMapDataset.java @@ -0,0 +1,186 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.data; + +import java.util.Arrays; +import java.util.List; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Operands; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.proto.DataType; +import org.tensorflow.types.TFloat64; +import org.tensorflow.types.family.TType; + +/** + * The WeightedFlatMapDataset operation + */ +@OpMetadata( + opType = WeightedFlatMapDataset.OP_NAME, + inputsClass = WeightedFlatMapDataset.Inputs.class +) +public final class WeightedFlatMapDataset extends RawOp implements Operand { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "WeightedFlatMapDataset"; + + private Output handle; + + @SuppressWarnings("unchecked") + public WeightedFlatMapDataset(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + handle = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new WeightedFlatMapDataset operation. + * + * @param scope current scope + * @param inputDatasets The inputDatasets value + * @param weights The weights value + * @param outputTypes The value of the outputTypes attribute + * @param outputShapes The value of the outputShapes attribute + * @param options carries optional attribute values + * @return a new instance of WeightedFlatMapDataset + */ + @Endpoint( + describeByClass = true + ) + public static WeightedFlatMapDataset create(Scope scope, + Iterable> inputDatasets, Iterable> weights, + List> outputTypes, List outputShapes, Options... options) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "WeightedFlatMapDataset"); + opBuilder.addInputList(Operands.asOutputs(inputDatasets)); + opBuilder.addInputList(Operands.asOutputs(weights)); + opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes)); + Shape[] outputShapesArray = new Shape[outputShapes.size()]; + for (int i = 0 ; i < outputShapesArray.length ; i++) { + outputShapesArray[i] = outputShapes.get(i); + } + opBuilder.setAttr("output_shapes", outputShapesArray); + if (options != null) { + for (Options opts : options) { + if (opts.metadata != null) { + opBuilder.setAttr("metadata", opts.metadata); + } + } + } + return new WeightedFlatMapDataset(opBuilder.build()); + } + + /** + * Sets the metadata option. + * + * @param metadata the metadata option + * @return this Options instance. + */ + public static Options metadata(String metadata) { + return new Options().metadata(metadata); + } + + /** + * Gets handle. + * + * @return handle. + */ + public Output handle() { + return handle; + } + + @Override + @SuppressWarnings("unchecked") + public Output asOutput() { + return (Output) handle; + } + + /** + * Optional attributes for {@link org.tensorflow.op.data.WeightedFlatMapDataset} + */ + public static class Options { + private String metadata; + + private Options() { + } + + /** + * Sets the metadata option. + * + * @param metadata the metadata option + * @return this Options instance. + */ + public Options metadata(String metadata) { + this.metadata = metadata; + return this; + } + } + + @OpInputsMetadata( + outputsClass = WeightedFlatMapDataset.class + ) + public static class Inputs extends RawOpInputs { + /** + * The inputDatasets input + */ + public final Iterable> inputDatasets; + + /** + * The weights input + */ + public final Iterable> weights; + + /** + * The outputTypes attribute + */ + public final DataType[] outputTypes; + + /** + * The outputShapes attribute + */ + public final Shape[] outputShapes; + + /** + * The metadata attribute + */ + public final String metadata; + + public Inputs(GraphOperation op) { + super(new WeightedFlatMapDataset(op), op, Arrays.asList("output_types", "output_shapes", "metadata")); + int inputIndex = 0; + int inputDatasetsLength = op.inputListLength("input_datasets"); + inputDatasets = Arrays.asList((Operand[]) op.inputList(inputIndex, inputDatasetsLength)); + inputIndex += inputDatasetsLength; + int weightsLength = op.inputListLength("weights"); + weights = Arrays.asList((Operand[]) op.inputList(inputIndex, weightsLength)); + inputIndex += weightsLength; + outputTypes = op.attributes().getAttrTypeList("output_types"); + outputShapes = op.attributes().getAttrShapeList("output_shapes"); + metadata = op.attributes().getAttrString("metadata"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MapDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MapDataset.java index f02bba6e46a..7c8cfafc8f4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MapDataset.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MapDataset.java @@ -98,6 +98,9 @@ public static MapDataset create(Scope scope, Operand inputDatas if (opts.preserveCardinality != null) { opBuilder.setAttr("preserve_cardinality", opts.preserveCardinality); } + if (opts.forceSynchronous != null) { + opBuilder.setAttr("force_synchronous", opts.forceSynchronous); + } } } return new MapDataset(opBuilder.build()); @@ -123,6 +126,16 @@ public static Options preserveCardinality(Boolean preserveCardinality) { return new Options().preserveCardinality(preserveCardinality); } + /** + * Sets the forceSynchronous option. + * + * @param forceSynchronous the forceSynchronous option + * @return this Options instance. + */ + public static Options forceSynchronous(Boolean forceSynchronous) { + return new Options().forceSynchronous(forceSynchronous); + } + /** * Gets handle. * @@ -146,6 +159,8 @@ public static class Options { private Boolean preserveCardinality; + private Boolean forceSynchronous; + private Options() { } @@ -170,6 +185,17 @@ public Options preserveCardinality(Boolean preserveCardinality) { this.preserveCardinality = preserveCardinality; return this; } + + /** + * Sets the forceSynchronous option. + * + * @param forceSynchronous the forceSynchronous option + * @return this Options instance. + */ + public Options forceSynchronous(Boolean forceSynchronous) { + this.forceSynchronous = forceSynchronous; + return this; + } } @OpInputsMetadata( @@ -211,8 +237,13 @@ public static class Inputs extends RawOpInputs { */ public final boolean preserveCardinality; + /** + * The forceSynchronous attribute + */ + public final boolean forceSynchronous; + public Inputs(GraphOperation op) { - super(new MapDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes", "use_inter_op_parallelism", "preserve_cardinality")); + super(new MapDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes", "use_inter_op_parallelism", "preserve_cardinality", "force_synchronous")); int inputIndex = 0; inputDataset = (Operand) op.input(inputIndex++); int otherArgumentsLength = op.inputListLength("other_arguments"); @@ -223,6 +254,7 @@ public Inputs(GraphOperation op) { outputShapes = op.attributes().getAttrShapeList("output_shapes"); useInterOpParallelism = op.attributes().getAttrBool("use_inter_op_parallelism"); preserveCardinality = op.attributes().getAttrBool("preserve_cardinality"); + forceSynchronous = op.attributes().getAttrBool("force_synchronous"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java index d1aae3e74ad..86215fa9a9c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java @@ -39,8 +39,6 @@ * that are not a number (NaN) or infinity (Inf). Otherwise, returns the input * tensor. Unlike CheckNumerics (V1), CheckNumericsV2 distinguishes -Inf and +Inf * in the errors it throws. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CheckNumerics.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientIdentity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientIdentity.java index 37f2fec7d91..776a971ef27 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientIdentity.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientIdentity.java @@ -37,8 +37,6 @@ * This op is hidden from public in Python. It is used by TensorFlow Debugger to * register gradient tensors for gradient debugging. * This op operates on non-reference-type tensors. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DebugGradientIdentity.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientRefIdentity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientRefIdentity.java index 5071299a66a..76a9e9029ca 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientRefIdentity.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientRefIdentity.java @@ -37,8 +37,6 @@ * This op is hidden from public in Python. It is used by TensorFlow Debugger to * register gradient tensors for gradient debugging. * This op operates on reference-type tensors. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DebugGradientRefIdentity.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugIdentity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugIdentity.java index 63c7105e3c8..10edd71d4b1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugIdentity.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugIdentity.java @@ -36,8 +36,6 @@ /** * Provides an identity mapping of the non-Ref type input tensor for debugging. * Provides an identity mapping of the non-Ref type input tensor for debugging. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DebugIdentity.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java index ec63e9da708..4ff0f11c7bc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java @@ -40,8 +40,6 @@ * Computes a numeric summary of the input tensor. The shape of the output * depends on the tensor_debug_mode attribute. * This op is used internally by TensorFlow Debugger (tfdbg) v2. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DebugNumericsSummary.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclAllReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclAllReduce.java index c5416746198..7cc17dd9d36 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclAllReduce.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclAllReduce.java @@ -45,8 +45,6 @@ * reduction: the reduction operation to perform. * num_devices: The number of devices participating in this reduction. * shared_name: Identifier that shared between ops of the same reduction. - * - * @param data type for {@code data} output */ @OpMetadata( opType = NcclAllReduce.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclBroadcast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclBroadcast.java index 3824d6a10dd..41a2050e44f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclBroadcast.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclBroadcast.java @@ -42,8 +42,6 @@ *

      input: The input to the broadcast. * output: The same as input. * shape: The shape of the input tensor. - * - * @param data type for {@code output} output */ @OpMetadata( opType = NcclBroadcast.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclReduce.java index 2a80593be6c..8fcf62bf4cc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclReduce.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclReduce.java @@ -42,8 +42,6 @@ *

      input: The input to the reduction. * data: the value of the reduction across all {@code num_devices} devices. * reduction: the reduction operation to perform. - * - * @param data type for {@code data} output */ @OpMetadata( opType = NcclReduce.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java index 806ad99e2ea..af516490d88 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java @@ -36,8 +36,6 @@ /** * Cast x of type SrcT to y of DstT. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Cast.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java index 6b0a717157c..0da2678549f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java @@ -48,8 +48,6 @@ * # tensor `imag` is [4.75, 5.75] * tf.complex(real, imag) ==> [[2.25 + 4.75j], [3.25 + 5.75j]] * - * - * @param data type for {@code out} output */ @OpMetadata( opType = Complex.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java index 0a6a141c036..123c74afd50 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java @@ -43,8 +43,6 @@ *

      For each channel, the Op first computes the mean of the image pixels in the * channel and then adjusts each component of each pixel to * {@code (x - mean) * contrast_factor + mean}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = AdjustContrast.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java index 45fe50175c4..b0001085638 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java @@ -41,8 +41,6 @@ *

      The input image is considered in the RGB colorspace. Conceptually, the RGB * colors are first mapped into HSV. A delta is then applied all the hue values, * and then remapped back to RGB colorspace. - * - * @param data type for {@code output} output */ @OpMetadata( opType = AdjustHue.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java index a7fea42d8fb..5f0c063dc1d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java @@ -41,8 +41,6 @@ *

      The input image is considered in the RGB colorspace. Conceptually, the RGB * colors are first mapped into HSV. A scale is then applied all the saturation * values, and then remapped back to RGB colorspace. - * - * @param data type for {@code output} output */ @OpMetadata( opType = AdjustSaturation.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java index 59e98a3252d..e639b0f2cb7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java @@ -38,8 +38,6 @@ /** * Computes the gradient of the crop_and_resize op wrt the input image tensor. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CropAndResizeGradImage.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java index ae91e89973a..a5c7ee7845e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java @@ -53,8 +53,6 @@ * unoccupied areas (in the first frame) with zeros (black). For frames after the * first frame that does not occupy the entire canvas, it uses the previous * frame to fill the unoccupied areas. - * - * @param data type for {@code image} output */ @OpMetadata( opType = DecodeImage.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java index db44c3b3146..dd6384caf7c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java @@ -51,8 +51,6 @@ * of color channels. *

      This op also supports decoding JPEGs and non-animated GIFs since the interface * is the same, though it is cleaner to use {@code tf.io.decode_image}. - * - * @param data type for {@code image} output */ @OpMetadata( opType = DecodePng.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java index 8033cecb4c9..56c64a5e50c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java @@ -45,8 +45,6 @@ * box is {@code [0.1, 0.2, 0.5, 0.9]}, the upper-left and bottom-right coordinates of * the bounding box will be {@code (40, 10)} to {@code (100, 50)} (in (x,y) coordinates). *

      Parts of the bounding box may fall outside the image. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DrawBoundingBoxes.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractImagePatches.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractImagePatches.java index 69492ac2873..54395a44acc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractImagePatches.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractImagePatches.java @@ -36,8 +36,6 @@ /** * Extract {@code patches} from {@code images} and put them in the "depth" output dimension. - * - * @param data type for {@code patches} output */ @OpMetadata( opType = ExtractImagePatches.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java index 368fe5cfd02..4ca887e7e72 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java @@ -39,8 +39,6 @@ /** * Extract the shape information of a JPEG-encoded image. * This op only parses the image header, so it is much faster than DecodeJpeg. - * - * @param data type for {@code image_shape} output */ @OpMetadata( opType = ExtractJpegShape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java index 6e32b95ca11..abd3d53d884 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java @@ -39,8 +39,6 @@ * value of the pixels. The output is only well defined if the value in {@code images} * are in {@code [0,1]}. *

      See {@code rgb_to_hsv} for a description of the HSV encoding. - * - * @param data type for {@code output} output */ @OpMetadata( opType = HsvToRgb.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java index 572b3e59d16..cef590ad519 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java @@ -42,8 +42,6 @@ * {@code (x', y') = ((a0 x + a1 y + a2) / k, (b0 x + b1 y + b2) / k)}, where * {@code k = c0 x + c1 y + 1}. If the transformed point lays outside of the input * image, the output pixel is set to 0. - * - * @param data type for {@code transformed_images} output */ @OpMetadata( opType = ImageProjectiveTransformV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV3.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV3.java index 2c448fc9397..59f06c2b982 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV3.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV3.java @@ -42,8 +42,6 @@ * {@code (x', y') = ((a0 x + a1 y + a2) / k, (b0 x + b1 y + b2) / k)}, where * {@code k = c0 x + c1 y + 1}. If the transformed point lays outside of the input * image, the output pixel is set to fill_value. - * - * @param data type for {@code transformed_images} output */ @OpMetadata( opType = ImageProjectiveTransformV3.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppression.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppression.java index 65c6f7f7f2a..f682bfd1f5a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppression.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppression.java @@ -58,8 +58,6 @@ * of other overlapping boxes instead of directly causing them to be pruned. * To enable this Soft-NMS mode, set the {@code soft_nms_sigma} parameter to be * larger than 0. - * - * @param data type for {@code selected_scores} output */ @OpMetadata( opType = NonMaxSuppression.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/QuantizedResizeBilinear.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/QuantizedResizeBilinear.java index def6ca5246e..94b4e077416 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/QuantizedResizeBilinear.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/QuantizedResizeBilinear.java @@ -38,8 +38,6 @@ /** * Resize quantized {@code images} to {@code size} using quantized bilinear interpolation. * Input images and output images must be quantized types. - * - * @param data type for {@code resized_images} output */ @OpMetadata( opType = QuantizedResizeBilinear.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java index 966401d271c..063b7b8f529 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java @@ -41,8 +41,6 @@ *

      This Op picks a random location in {@code image} and crops a {@code height} by {@code width} * rectangle from that location. The random location is picked so the cropped * area will fit inside the original image. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomCrop.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java index 16d5af61802..c04fe6d13e0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java @@ -36,8 +36,6 @@ /** * Computes the gradient of bicubic interpolation. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ResizeBicubicGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java index dbd172bfbf2..166d6b46de6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java @@ -36,8 +36,6 @@ /** * Computes the gradient of bilinear interpolation. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ResizeBilinearGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java index 1fc40174782..355ac564de1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java @@ -36,8 +36,6 @@ /** * Resize {@code images} to {@code size} using nearest neighbor interpolation. - * - * @param data type for {@code resized_images} output */ @OpMetadata( opType = ResizeNearestNeighbor.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java index 485aa4ba63b..36df9e12b2d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java @@ -36,8 +36,6 @@ /** * Computes the gradient of nearest neighbor interpolation. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ResizeNearestNeighborGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java index 3709f0bd4f7..be3c84d9b66 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java @@ -56,8 +56,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = RgbToHsv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java index 152f96ce75f..a7378278309 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java @@ -70,8 +70,6 @@ * {@code use_image_if_no_bounding_boxes = true} will assume there is a single implicit * bounding box covering the whole image. If {@code use_image_if_no_bounding_boxes} is * false and no bounding boxes are supplied, an error is raised. - * - * @param data type for {@code begin} output */ @OpMetadata( opType = SampleDistortedBoundingBox.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslateGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslateGrad.java index 55dae2a4ae8..1749d046b37 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslateGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslateGrad.java @@ -36,8 +36,6 @@ /** * The ScaleAndTranslateGrad operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = ScaleAndTranslateGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/StatelessSampleDistortedBoundingBox.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/StatelessSampleDistortedBoundingBox.java index ac9dfdfe74d..31c4de5388d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/StatelessSampleDistortedBoundingBox.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/StatelessSampleDistortedBoundingBox.java @@ -95,8 +95,6 @@ * {@code use_image_if_no_bounding_boxes = true} will assume there is a single implicit * bounding box covering the whole image. If {@code use_image_if_no_bounding_boxes} is * false and no bounding boxes are supplied, an error is raised. - * - * @param data type for {@code begin} output */ @OpMetadata( opType = StatelessSampleDistortedBoundingBox.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java index 0ef81b9eff2..07eac6679d4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java @@ -38,8 +38,6 @@ /** * Reinterpret the bytes of a string as a vector of numbers. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DecodePaddedRaw.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java index 068d203c2b0..217c843796f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java @@ -37,8 +37,6 @@ /** * Reinterpret the bytes of a string as a vector of numbers. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DecodeRaw.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java index 1ff234ea6b6..9704bd78d15 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java @@ -77,8 +77,6 @@ * values = [1, 2, 3, 4, 5] * shape = [2 50] * - * - * @param data type for {@code sparse_values} output */ @OpMetadata( opType = DeserializeManySparse.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java index 66a64b13c0b..039ff1546f0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java @@ -37,8 +37,6 @@ /** * Transforms a serialized tensorflow.TensorProto proto into a Tensor. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ParseTensor.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java index b0e447608f3..70f9327d112 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java @@ -44,8 +44,6 @@ * {@code SparseTensor} objects going into each row of {@code serialized_sparse} will have * rank {@code R-1}. *

      The minibatch size {@code N} is extracted from {@code sparse_shape[0]}. - * - * @param data type for {@code serialized_sparse} output */ @OpMetadata( opType = SerializeManySparse.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java index 2f450dcf3bd..b0c2b5935bf 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java @@ -38,8 +38,6 @@ /** * Serialize a {@code SparseTensor} into a {@code [3]} {@code Tensor} object. - * - * @param data type for {@code serialized_sparse} output */ @OpMetadata( opType = SerializeSparse.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandPart.java index 34f179ed2b0..a521e77b040 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandPart.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandPart.java @@ -65,8 +65,6 @@ * tf.linalg.band_part(input, -1, 0) ==> Lower triangular part. * tf.linalg.band_part(input, 0, 0) ==> Diagonal. * - * - * @param data type for {@code band} output */ @OpMetadata( opType = BandPart.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandedTriangularSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandedTriangularSolve.java index 9dc6dba4348..532d4fe148b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandedTriangularSolve.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandedTriangularSolve.java @@ -35,8 +35,6 @@ /** * The BandedTriangularSolve operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BandedTriangularSolve.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java index 0016839b211..b43cf15b48e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java @@ -35,8 +35,6 @@ /** * The BatchCholesky operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchCholesky.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java index d9ce332f7e2..5e917e740b8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java @@ -35,8 +35,6 @@ /** * The BatchCholeskyGrad operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchCholeskyGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixBandPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixBandPart.java index 55e8a0d6a75..99cb57ff97f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixBandPart.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixBandPart.java @@ -36,8 +36,6 @@ /** * The BatchMatrixBandPart operation - * - * @param data type for {@code band} output */ @OpMetadata( opType = BatchMatrixBandPart.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDeterminant.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDeterminant.java index c50a706e073..7f1bd32a749 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDeterminant.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDeterminant.java @@ -35,8 +35,6 @@ /** * The BatchMatrixDeterminant operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatrixDeterminant.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiag.java index bba3cae6292..edc731b1f36 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiag.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiag.java @@ -35,8 +35,6 @@ /** * The BatchMatrixDiag operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatrixDiag.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiagPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiagPart.java index 63e7e0e3026..ac379b960aa 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiagPart.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiagPart.java @@ -35,8 +35,6 @@ /** * The BatchMatrixDiagPart operation - * - * @param data type for {@code diagonal} output */ @OpMetadata( opType = BatchMatrixDiagPart.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java index 081dab67e8b..009deec3658 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java @@ -35,8 +35,10 @@ /** * The BatchMatrixInverse operation - * - * @param data type for {@code output} output + * DEPRECATED: This operation is deprecated and will be removed in a future version. + * Use tf.linalg.inv instead. + *

      Computes the inverse of one or more square invertible matrices or their + * adjoints (conjugate transposes). */ @OpMetadata( opType = BatchMatrixInverse.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSetDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSetDiag.java index 67a97a485c0..eaea0c7db31 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSetDiag.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSetDiag.java @@ -35,8 +35,6 @@ /** * The BatchMatrixSetDiag operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatrixSetDiag.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java index dc65bb1dce1..5b6749c53e4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java @@ -35,8 +35,6 @@ /** * The BatchMatrixSolve operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatrixSolve.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java index 801c5262946..7cb6714696f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java @@ -36,8 +36,6 @@ /** * The BatchMatrixSolveLs operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatrixSolveLs.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java index ae63e405dd7..d7b326bae21 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java @@ -35,8 +35,6 @@ /** * The BatchMatrixTriangularSolve operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatrixTriangularSolve.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java index 1d6588ac785..637625bd5db 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java @@ -35,8 +35,6 @@ /** * The BatchSelfAdjointEigV2 operation - * - * @param data type for {@code e} output */ @OpMetadata( opType = BatchSelfAdjointEig.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSvd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSvd.java index cf723ceeedc..a2411601e63 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSvd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSvd.java @@ -35,8 +35,6 @@ /** * The BatchSvd operation - * - * @param data type for {@code s} output */ @OpMetadata( opType = BatchSvd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cholesky.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cholesky.java index 294a41889da..ef6d0ca1a3d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cholesky.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cholesky.java @@ -45,8 +45,6 @@ *

      Note: The gradient computation on GPU is faster for large matrices but * not for large batch dimensions when the submatrices are small. In this * case it might be faster to use the CPU. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Cholesky.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java index f2529b61318..ce7975bbb29 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java @@ -37,8 +37,6 @@ * Computes the reverse mode backpropagated gradient of the Cholesky algorithm. * For an explanation see "Differentiation of the Cholesky algorithm" by * Iain Murray http://arxiv.org/abs/1602.07527. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CholeskyGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/ConjugateTranspose.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/ConjugateTranspose.java index e14f2e71ef9..561e4fecbf1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/ConjugateTranspose.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/ConjugateTranspose.java @@ -39,8 +39,6 @@ * The output {@code y} has the same rank as {@code x}. The shapes of {@code x} and {@code y} satisfy: * {@code y.shape[i] == x.shape[perm[i]] for i in [0, 1, ..., rank(x) - 1]} * {@code y[i,j,k,...,s,t,u] == conj(x[perm[i], perm[j], perm[k],...,perm[s], perm[t], perm[u]])} - * - * @param data type for {@code y} output */ @OpMetadata( opType = ConjugateTranspose.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java index 68ee2a65439..5c942c1e41b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java @@ -38,8 +38,6 @@ * {@code a} and {@code b} must be the same shape; they can either be simple 3-element vectors, * or any shape where the innermost dimension is 3. In the latter case, each pair * of corresponding 3-element vectors is cross-multiplied independently. - * - * @param data type for {@code product} output */ @OpMetadata( opType = Cross.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Det.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Det.java index 62aafcde736..d63118c9f73 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Det.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Det.java @@ -38,8 +38,6 @@ * The input is a tensor of shape {@code [..., M, M]} whose inner-most 2 dimensions * form square matrices. The output is a tensor containing the determinants * for all input submatrices {@code [..., :, :]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Det.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java index 783950dfde9..3276bbb78fe 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java @@ -46,8 +46,6 @@ * e, v = eig(a) * e = eig(a, compute_v=False) * - * - * @param data type for {@code e} output */ @OpMetadata( opType = Eig.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Einsum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Einsum.java index 51d3eeb3fa6..5b57bad8aa4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Einsum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Einsum.java @@ -99,8 +99,6 @@ * supported by {@code numpy.einsum}. *
      {@literal @}end_compatibility *

    - * - * @param data type for {@code output} output */ @OpMetadata( opType = Einsum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/EuclideanNorm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/EuclideanNorm.java index ab6f58f4885..f544381e1a7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/EuclideanNorm.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/EuclideanNorm.java @@ -40,8 +40,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = EuclideanNorm.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Inv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Inv.java index 6b02bc2a059..93338f1df07 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Inv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Inv.java @@ -42,8 +42,6 @@ *

    If a matrix is not invertible there is no guarantee what the op does. It * may detect the condition and raise an exception or it may simply return a * garbage result. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Inv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LogMatrixDeterminant.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LogMatrixDeterminant.java index 298e01306db..a144ac2d31c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LogMatrixDeterminant.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LogMatrixDeterminant.java @@ -43,8 +43,6 @@ * The {@code log_abs_determinant} is computed as {@code det(P)*sum(log(diag(LU)))} where {@code LU} * is the {@code LU} decomposition of the input and {@code P} is the corresponding * permutation matrix. - * - * @param data type for {@code sign} output */ @OpMetadata( opType = LogMatrixDeterminant.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java index 480ed23e696..9063fab1875 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java @@ -51,10 +51,6 @@ *

    P represents a permutation matrix encoded as a list of indices each between {@code 0} * and {@code M-1}, inclusive. If P_mat denotes the permutation matrix corresponding to * P, then the L, U and P satisfies P_mat * input = L * U. - * - * @param data type for {@code lu} output - * - * @param data type for {@code p} output */ @OpMetadata( opType = Lu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatMul.java index a592a65396a..c817cbc9037 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatMul.java @@ -41,8 +41,6 @@ * true). *

    Note: The default kernel implementation for MatMul on GPUs uses * cublas. - * - * @param data type for {@code product} output */ @OpMetadata( opType = MatMul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiag.java index 0a292c9d1b1..5241708f71a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiag.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiag.java @@ -116,8 +116,6 @@ * [1, 9], * [9, 2]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = MatrixDiag.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPart.java index 084c946193e..a818b134cbe 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPart.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPart.java @@ -96,8 +96,6 @@ * [3, 4, 9], * [4, 3, 8]]] * - * - * @param data type for {@code diagonal} output */ @OpMetadata( opType = MatrixDiagPart.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPartV3.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPartV3.java index d4794ab7571..c6ecab46bab 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPartV3.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPartV3.java @@ -126,8 +126,6 @@ * [4, 3, 8]]] * * - * - * @param data type for {@code diagonal} output */ @OpMetadata( opType = MatrixDiagPartV3.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagV3.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagV3.java index 943b92e2c95..67b5b3b74b0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagV3.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagV3.java @@ -144,8 +144,6 @@ * [9, 2]] * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = MatrixDiagV3.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixExponential.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixExponential.java index 961f57037f4..9332cd02b3e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixExponential.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixExponential.java @@ -35,8 +35,6 @@ /** * Deprecated, use python implementation tf.linalg.matrix_exponential. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MatrixExponential.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixLogarithm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixLogarithm.java index b3876d3a572..f1529a1c264 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixLogarithm.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixLogarithm.java @@ -46,8 +46,6 @@ *

    The input is a tensor of shape {@code [..., M, M]} whose inner-most 2 dimensions * form square matrices. The output is a tensor of the same shape as the input * containing the exponential for all input submatrices {@code [..., :, :]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MatrixLogarithm.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSetDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSetDiag.java index 0ae2c206569..1ec3a1444f5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSetDiag.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSetDiag.java @@ -132,8 +132,6 @@ * [7, 4, 2, 4]]] * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = MatrixSetDiag.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSolveLs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSolveLs.java index 3b340034827..d0601c6ee57 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSolveLs.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSolveLs.java @@ -66,8 +66,6 @@ * least-squares solution, even when \(A\) is rank deficient. This path is * typically 6-7 times slower than the fast path. If {@code fast} is {@code False} then * {@code l2_regularizer} is ignored. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MatrixSolveLs.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Qr.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Qr.java index 9e73edaf6b8..037f024d04b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Qr.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Qr.java @@ -47,8 +47,6 @@ * q, r = qr(a) * q_full, r_full = qr(a, full_matrices=True) * - * - * @param data type for {@code q} output */ @OpMetadata( opType = Qr.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java index 93ca4112092..d3136668a39 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java @@ -41,8 +41,6 @@ * {@code a} (after being transposed if {@code transpose_a} is non-zero) must match the * outer dimension of {@code b} (after being transposed if {@code transposed_b} is * non-zero). - * - * @param data type for {@code out} output */ @OpMetadata( opType = QuantizedMatMul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java index 4ff470d2594..0cc43361bf4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java @@ -43,8 +43,6 @@ * match the outer dimension of {@code b} (after being transposed if {@code transposed_b} is * non-zero). Then do broadcast add operation with bias values on the matrix * multiplication result. The bias size must match inner dimension of {@code b}. - * - * @param data type for {@code out} output */ @OpMetadata( opType = QuantizedMatMulWithBias.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java index ad1182c50de..eee116597b9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java @@ -44,8 +44,6 @@ * non-zero). Then do broadcast add operation with bias values on the matrix * multiplication result. The bias size must match inner dimension of {@code b}. Then do * relu activation to get non-negative result. - * - * @param data type for {@code out} output */ @OpMetadata( opType = QuantizedMatMulWithBiasAndRelu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java index 91eefc72f1b..82bdde439f1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java @@ -45,8 +45,6 @@ * multiplication result. The bias size must match inner dimension of {@code b}. Then do * relu activation to get non-negative result. Then do requantize operation to get * final uint8 result. - * - * @param data type for {@code out} output */ @OpMetadata( opType = QuantizedMatMulWithBiasAndReluAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/SelfAdjointEig.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/SelfAdjointEig.java index 2d64ddb4dda..75c06a99f2a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/SelfAdjointEig.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/SelfAdjointEig.java @@ -45,8 +45,6 @@ * e, v = self_adjoint_eig(a) * e = self_adjoint_eig(a, compute_v=False) * - * - * @param data type for {@code e} output */ @OpMetadata( opType = SelfAdjointEig.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Solve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Solve.java index a0f41eda3f5..d1057183227 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Solve.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Solve.java @@ -41,8 +41,6 @@ * satisfies {@code matrix[..., :, :] * output[..., :, :] = rhs[..., :, :]}. * If {@code adjoint} is {@code True} then each output matrix satisfies * {@code adjoint(matrix[..., :, :]) * output[..., :, :] = rhs[..., :, :]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Solve.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Sqrtm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Sqrtm.java index 224688c8e1d..cf48c52605a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Sqrtm.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Sqrtm.java @@ -47,8 +47,6 @@ *

    The input is a tensor of shape {@code [..., M, M]} whose inner-most 2 dimensions * form square matrices. The output is a tensor of the same shape as the input * containing the matrix square root for all input submatrices {@code [..., :, :]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Sqrtm.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Svd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Svd.java index b17b01cf88e..b11eafdccfc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Svd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Svd.java @@ -45,8 +45,6 @@ * s, u, v = svd(a) * s, _, _ = svd(a, compute_uv=False) * - * - * @param data type for {@code s} output */ @OpMetadata( opType = Svd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiag.java index 6292194a118..69ee9258392 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiag.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiag.java @@ -48,8 +48,6 @@ * [0, 0, 3, 0] * [0, 0, 0, 4]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = TensorDiag.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiagPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiagPart.java index ae21a73b071..838a036f84b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiagPart.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiagPart.java @@ -49,8 +49,6 @@ * * tf.diag_part(input) ==> [1, 2, 3, 4] * - * - * @param data type for {@code diagonal} output */ @OpMetadata( opType = TensorDiagPart.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Transpose.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Transpose.java index 65f22dfe32b..712576c0989 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Transpose.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Transpose.java @@ -38,8 +38,6 @@ * Shuffle dimensions of x according to a permutation. * The output {@code y} has the same rank as {@code x}. The shapes of {@code x} and {@code y} satisfy: * {@code y.shape[i] == x.shape[perm[i]] for i in [0, 1, ..., rank(x) - 1]} - * - * @param data type for {@code y} output */ @OpMetadata( opType = Transpose.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TriangularSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TriangularSolve.java index 891f4e1f608..026fbfb70bf 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TriangularSolve.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TriangularSolve.java @@ -77,8 +77,6 @@ * # [4. ], * # [1.9999999]], dtype=float32)> * - * - * @param data type for {@code output} output */ @OpMetadata( opType = TriangularSolve.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalMatMul.java index bd69ed483e4..a6122dabc83 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalMatMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalMatMul.java @@ -36,8 +36,6 @@ /** * Calculate product with tridiagonal matrix. * Calculates product of two matrices, where left matrix is a tridiagonal matrix. - * - * @param data type for {@code output} output */ @OpMetadata( opType = TridiagonalMatMul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalSolve.java index 57c0864ef7d..6b0a890d12e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalSolve.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalSolve.java @@ -42,8 +42,6 @@ * pivoting, depending on {@code partial_pivoting} attribute. On GPU, Nvidia's cuSPARSE * library is used: https://docs.nvidia.com/cuda/cusparse/index.html#gtsv * Partial pivoting is not yet supported by XLA backends. - * - * @param data type for {@code output} output */ @OpMetadata( opType = TridiagonalSolve.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java index 27d77557bfb..7fd47c7c6f5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java @@ -39,8 +39,6 @@ * Reads out the CSR components at batch {@code index}. * This op is meant only for debugging / testing, and its interface is not expected * to be stable. - * - * @param data type for {@code values} output */ @OpMetadata( opType = CSRSparseMatrixComponents.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java index 51bed06f6ba..97fb87d7250 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java @@ -36,8 +36,6 @@ /** * Convert a (possibly batched) CSRSparseMatrix to dense. - * - * @param data type for {@code dense_output} output */ @OpMetadata( opType = CSRSparseMatrixToDense.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java index 5c111887894..ad365783cea 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java @@ -37,8 +37,6 @@ /** * Converts a (possibly batched) CSRSparesMatrix to a SparseTensor. - * - * @param data type for {@code values} output */ @OpMetadata( opType = CSRSparseMatrixToSparseTensor.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMatMul.java index 2de2e93ec3b..5d9ed9bbbf2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMatMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMatMul.java @@ -56,8 +56,6 @@ * C = conjugate(transpose(A . B)) = conjugate(transpose(B)) . * conjugate(transpose(A)) * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseMatrixMatMul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java index ef53c5f5693..0f4ee840704 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java @@ -38,8 +38,6 @@ * Given a tensor {@code x}, this operation returns a tensor containing the absolute * value of each element in {@code x}. For example, if x is an input element and y is * an output element, this operation computes \(y = |x|\). - * - * @param data type for {@code y} output */ @OpMetadata( opType = Abs.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AccumulateN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AccumulateN.java index 61d1df63943..3a0e466e8cd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AccumulateN.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AccumulateN.java @@ -43,8 +43,6 @@ * storage is proportional to the output size rather than the inputs size. *

    Unlike the original {@code accumulate_n}, {@code accumulate_n_v2} is differentiable. *

    Returns a {@code Tensor} of same shape and type as the elements of {@code inputs}. - * - * @param data type for {@code sum} output */ @OpMetadata( opType = AccumulateN.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acos.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acos.java index 078326e1891..915e5b98b63 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acos.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acos.java @@ -37,8 +37,6 @@ * Computes acos of x element-wise. * Provided an input tensor, the {@code tf.math.acos} operation returns the inverse cosine of each element of the tensor. If {@code y = tf.math.cos(x)} then, {@code x = tf.math.acos(y)}. *

    Input range is {@code [-1, 1]} and the output has a range of {@code [0, pi]}. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Acos.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acosh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acosh.java index 60edbd7880f..8ade37b1990 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acosh.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acosh.java @@ -41,8 +41,6 @@ * x = tf.constant([-2, -0.5, 1, 1.2, 200, 10000, float("inf")]) * tf.math.acosh(x) ==> [nan nan 0. 0.62236255 5.9914584 9.903487 inf] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Acosh.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Add.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Add.java index 4f32acd9ee1..61db4d2e4ec 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Add.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Add.java @@ -39,8 +39,6 @@ * here *

    Given two input tensors, the {@code tf.add} operation computes the sum for every element in the tensor. *

    Both input and output have a range {@code (-inf, inf)}. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Add.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AddN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AddN.java index 6cd47212eef..f2ef9209796 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AddN.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AddN.java @@ -41,8 +41,6 @@ * x = [9, 7, 10] * tf.math.add_n(x) ==> 26 * - * - * @param data type for {@code sum} output */ @OpMetadata( opType = AddN.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java index a9c7814636f..6ad1ff84bba 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java @@ -51,8 +51,6 @@ *

    {@literal @}compatibility(numpy)
    * Equivalent to np.angle. *
    {@literal @}end_compatibility - * - * @param data type for {@code output} output */ @OpMetadata( opType = Angle.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java index 5a7b5adec69..c222f3d54d5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java @@ -48,8 +48,6 @@ * # c = 4 * # here a[4] = 166.32 which is the largest element of a across axis 0 * - * - * @param data type for {@code output} output */ @OpMetadata( opType = ArgMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java index ff138655b1f..41aa45a10ad 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java @@ -48,8 +48,6 @@ * # c = 0 * # here a[0] = 1 which is the smallest element of a across axis 0 * - * - * @param data type for {@code output} output */ @OpMetadata( opType = ArgMin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asin.java index 050107db969..810aeb5fa3b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asin.java @@ -47,8 +47,6 @@ * * tf.math.asin(y) # [1.047, 0.785] = x * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Asin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asinh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asinh.java index d4170db292a..918518f2b82 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asinh.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asinh.java @@ -42,8 +42,6 @@ * x = tf.constant([-float("inf"), -2, -0.5, 1, 1.2, 200, 10000, float("inf")]) * tf.math.asinh(x) ==> [-inf -1.4436355 -0.4812118 0.8813736 1.0159732 5.991471 9.903487 inf] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Asinh.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan.java index aab73783c10..8979ab75d9e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan.java @@ -47,8 +47,6 @@ * * tf.math.atan(y) # [1.047, 0.785] = x * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Atan.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java index dfff4a48676..2d566d3cc22 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java @@ -51,8 +51,6 @@ * * * - * - * @param data type for {@code z} output */ @OpMetadata( opType = Atan2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atanh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atanh.java index ea5729193bf..c4dd0f1ead2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atanh.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atanh.java @@ -44,8 +44,6 @@ * x = tf.constant([-float("inf"), -1, -0.5, 1, 0, 0.5, 10, float("inf")]) * tf.math.atanh(x) ==> [nan -inf -0.54930615 inf 0. 0.54930615 nan nan] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Atanh.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java index d3782706f20..945d2107a39 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java @@ -35,8 +35,6 @@ /** * The BesselI0 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselI0.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java index eec8b3281a3..7e27d3e4263 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java @@ -35,8 +35,6 @@ /** * The BesselI0e operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselI0e.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java index bb59dc19f5c..28304567e86 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java @@ -35,8 +35,6 @@ /** * The BesselI1 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselI1.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java index fe929e32eb1..df3b3f937e8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java @@ -35,8 +35,6 @@ /** * The BesselI1e operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselI1e.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java index f7b9904c100..1a895c89f00 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java @@ -41,8 +41,6 @@ *

    \(B(x; a, b) = \int_0^x t^{a-1} (1 - t)^{b-1} dt\) *

    is the incomplete beta function and \(B(a, b)\) is the complete * beta function. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Betainc.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java index 6e78f0799fc..463dc277eae 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java @@ -42,8 +42,6 @@ * the value in {@code weights} at each index where the corresponding value in {@code arr} is * {@code i}. *

    Values in {@code arr} outside of the range [0, size) are ignored. - * - * @param data type for {@code bins} output */ @OpMetadata( opType = Bincount.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java index 3db46461d7c..1a69b94a8e4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java @@ -35,8 +35,6 @@ /** * Returns element-wise smallest integer not less than x. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Ceil.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java index 798b2a9cb1a..9461d599888 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java @@ -52,8 +52,6 @@ * * * - * - * @param data type for {@code y} output */ @OpMetadata( opType = ComplexAbs.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Conj.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Conj.java index 266da810658..d46b7f2ae5b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Conj.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Conj.java @@ -45,8 +45,6 @@ * # tensor 'input' is [-2.25 + 4.75j, 3.25 + 5.75j] * tf.conj(input) ==> [-2.25 - 4.75j, 3.25 - 5.75j] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conj.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cos.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cos.java index 0ab0152ff02..b6b5b9595c5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cos.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cos.java @@ -43,8 +43,6 @@ * x = tf.constant([-float("inf"), -9, -0.5, 1, 1.2, 200, 10000, float("inf")]) * tf.math.cos(x) ==> [nan -0.91113025 0.87758255 0.5403023 0.36235774 0.48718765 -0.95215535 nan] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Cos.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cosh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cosh.java index 76a98abe533..391d2efd7ab 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cosh.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cosh.java @@ -42,8 +42,6 @@ * x = tf.constant([-float("inf"), -9, -0.5, 1, 1.2, 2, 10, float("inf")]) * tf.math.cosh(x) ==> [inf 4.0515420e+03 1.1276259e+00 1.5430807e+00 1.8106556e+00 3.7621956e+00 1.1013233e+04 inf] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Cosh.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumprod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumprod.java index 3e901959c5d..90bdcdc0038 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumprod.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumprod.java @@ -56,8 +56,6 @@ * 

      * tf.cumprod([a, b, c], exclusive=True, reverse=True)  # => [b * c, c, 1]
  *
    - * - * @param data type for {@code out} output */ @OpMetadata( opType = Cumprod.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumsum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumsum.java index 12b3346db25..ff8dca235c9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumsum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumsum.java @@ -56,8 +56,6 @@ * 
      * tf.cumsum([a, b, c], exclusive=True, reverse=True)  # => [b + c, c, 0]
  *
    - * - * @param data type for {@code out} output */ @OpMetadata( opType = Cumsum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java index 52595f56eea..f7367703a41 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java @@ -51,8 +51,6 @@ * floating point type is used instead. *

    By setting the {@code reverse} kwarg to {@code True}, the cumulative log-sum-exp is performed in the * opposite direction. - * - * @param data type for {@code out} output */ @OpMetadata( opType = CumulativeLogsumexp.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java index ff9a38ba24d..808be372c5f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java @@ -41,8 +41,6 @@ * the value in {@code weights} at each index where the corresponding value in {@code arr} is * {@code i}. *

    Values in {@code arr} outside of the range [0, size) are ignored. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DenseBincount.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java index 37117f4e1b8..3a48d548bd4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java @@ -36,8 +36,6 @@ /** * Computes Psi, the derivative of Lgamma (the log of the absolute value of * {@code Gamma(x)}), element-wise. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Digamma.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Div.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Div.java index 62a15f37da7..8ad37113d3f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Div.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Div.java @@ -37,8 +37,6 @@ * Returns x / y element-wise. * NOTE: {@code math.Div} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = Div.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DivNoNan.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DivNoNan.java index bb098cfdf14..43047bad3c6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DivNoNan.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DivNoNan.java @@ -37,8 +37,6 @@ * Returns 0 if the denominator is zero. * NOTE: {@code math.DivNoNan} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = DivNoNan.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java index 1e2046e2892..ef607d7778b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java @@ -35,8 +35,6 @@ /** * Computes the Gauss error function of {@code x} element-wise. In statistics, for non-negative values of $x$, the error function has the following interpretation: for a random variable $Y$ that is normally distributed with mean 0 and variance $1/\sqrt{2}$, $erf(x)$ is the probability that $Y$ falls in the range $[−x, x]$. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Erf.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java index b8d11327b94..25fdbcd648c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java @@ -35,8 +35,6 @@ /** * Computes the complementary error function of {@code x} element-wise. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Erfc.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Exp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Exp.java index 1a5c7456b51..fe1d6ed1515 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Exp.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Exp.java @@ -56,8 +56,6 @@ * x = tf.constant(1 + 1j) * tf.math.exp(x) ==> 1.4686939399158851+2.2873552871788423j * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Exp.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Expm1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Expm1.java index a6f8f64ab43..b9c80edf84b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Expm1.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Expm1.java @@ -47,8 +47,6 @@ * x = tf.constant(1 + 1j) * tf.math.expm1(x) ==> (0.46869393991588515+2.2873552871788423j) * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Expm1.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java index bb9dbc4aa32..27ed6af66ac 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java @@ -35,8 +35,6 @@ /** * Returns element-wise largest integer not greater than x. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Floor.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorDiv.java index 47887e1a4dd..61d57ac8c4f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorDiv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorDiv.java @@ -37,8 +37,6 @@ * Returns x // y element-wise. * NOTE: {@code math.FloorDiv} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = FloorDiv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java index 58c90f87123..b41e5d112b2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java @@ -40,8 +40,6 @@ * {@code floor(x / y) * y + floormod(x, y) = x}, regardless of the signs of x and y. *

    NOTE: {@code math.FloorMod} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = FloorMod.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java index 4f116ba6e63..224c434af9f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java @@ -42,8 +42,6 @@ *

    is the lower incomplete Gamma function. *

    Note, above {@code Q(a, x)} ({@code Igammac}) is the upper regularized complete * Gamma function. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Igamma.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java index f9e7aced432..a3c6c4f20ad 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java @@ -35,8 +35,6 @@ /** * Computes the gradient of {@code igamma(a, x)} wrt {@code a}. - * - * @param data type for {@code z} output */ @OpMetadata( opType = IgammaGradA.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java index 1cc0549ad00..80f2545ce69 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java @@ -42,8 +42,6 @@ *

    is the upper incomplete Gamma function. *

    Note, above {@code P(a, x)} ({@code Igamma}) is the lower regularized complete * Gamma function. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Igammac.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java index fe04cd17336..509de2b8c7b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java @@ -47,8 +47,6 @@ * # tensor 'input' is [-2.25 + 4.75j, 3.25 + 5.75j] * tf.imag(input) ==> [4.75, 5.75] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Imag.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java index 3035d46e60c..a466109898c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java @@ -46,8 +46,6 @@ * # tensor `x` is [3, 4, 0, 2, 1] * invert_permutation(x) ==> [2, 4, 3, 0, 1] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = InvertPermutation.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java index d8c6b4889a2..4c5aea1de84 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java @@ -42,8 +42,6 @@ * x = tf.constant([0, 0.5, 1, 4.5, -4, -5.6]) * tf.math.lgamma(x) ==> [inf, 0.5723649, 0., 2.4537368, inf, -4.6477685] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Lgamma.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log.java index 32ee589536a..911ab61ff0c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log.java @@ -41,8 +41,6 @@ * x = tf.constant([0, 0.5, 1, 5]) * tf.math.log(x) ==> [-inf, -0.6931472, 0. , 1.609438] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Log.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log1p.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log1p.java index f280d8b0062..05fe31ad376 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log1p.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log1p.java @@ -41,8 +41,6 @@ * x = tf.constant([0, 0.5, 1, 5]) * tf.math.log1p(x) ==> [0., 0.4054651, 0.6931472, 1.7917595] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Log1p.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java index c46c8c6e384..0c864b79f5e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java @@ -37,8 +37,6 @@ * Returns the max of x and y (i.e. x > y ? x : y) element-wise. * NOTE: {@code math.Maximum} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = Maximum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mean.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mean.java index 94de9fc5bd4..9018aa2bd6d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mean.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mean.java @@ -40,8 +40,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Mean.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java index 588bcb3328b..b516ee5c302 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java @@ -37,8 +37,6 @@ * Returns the min of x and y (i.e. x < y ? x : y) element-wise. * NOTE: {@code math.Minimum} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = Minimum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java index d318de97c9c..60ccc32e855 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java @@ -39,8 +39,6 @@ * {@code tf.truncatediv(x, y) * y + truncate_mod(x, y) = x}. *

    NOTE: {@code math.Mod} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = Mod.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mul.java index d7466085ada..d18a48a6472 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mul.java @@ -37,8 +37,6 @@ * Returns x * y element-wise. * NOTE: {@code math.Mul} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = Mul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/MulNoNan.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/MulNoNan.java index 85429b70ca1..7e85f94c31d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/MulNoNan.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/MulNoNan.java @@ -37,8 +37,6 @@ * Returns x * y element-wise. Returns zero if y is zero, even if x if infinite or NaN. * NOTE: {@code math.MulNoNan} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = MulNoNan.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java index 37d1ffb8fc9..2c9b4f4719f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java @@ -35,8 +35,6 @@ /** * The Ndtri operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = Ndtri.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Neg.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Neg.java index e0ec5783144..e11b274470a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Neg.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Neg.java @@ -36,8 +36,6 @@ /** * Computes numerical negative value element-wise. * I.e., \(y = -x\). - * - * @param data type for {@code y} output */ @OpMetadata( opType = Neg.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java index 45ff3a179ca..fef32810db3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java @@ -40,8 +40,6 @@ *

    {@literal @}compatibility(cpp)
    * Equivalent to C++ std::nextafter function. *
    {@literal @}end_compatibility - * - * @param data type for {@code output} output */ @OpMetadata( opType = NextAfter.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java index b2fb442489b..f391fef2335 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java @@ -39,8 +39,6 @@ *

    \(\psi^{(a)}(x) = \frac{d^a}{dx^a} \psi(x)\) *

    where \(\psi(x)\) is the digamma function. * The polygamma function is defined only for non-negative integer orders \a\. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Polygamma.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Pow.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Pow.java index f50532e8d62..3a8f8acbb7a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Pow.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Pow.java @@ -42,8 +42,6 @@ * # tensor 'y' is [[8, 16], [2, 3]] * tf.pow(x, y) ==> [[256, 65536], [9, 27]] * - * - * @param data type for {@code z} output */ @OpMetadata( opType = Pow.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java index ad59711dca9..cf02c4ad713 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java @@ -37,8 +37,6 @@ /** * Returns x + y element-wise, working on quantized buffers. - * - * @param data type for {@code z} output */ @OpMetadata( opType = QuantizedAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java index 6b5c3d05579..b9f1e5b062c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java @@ -37,8 +37,6 @@ /** * Returns x * y element-wise, working on quantized buffers. - * - * @param data type for {@code z} output */ @OpMetadata( opType = QuantizedMul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java index 6217269b474..c85e0d73861 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java @@ -47,8 +47,6 @@ * # tensor 'input' is [-2.25 + 4.75j, 3.25 + 5.75j] * tf.real(input) ==> [-2.25, 3.25] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Real.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RealDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RealDiv.java index c1aceba76d3..fb2e7e77d33 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RealDiv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RealDiv.java @@ -38,8 +38,6 @@ * If {@code x} and {@code y} are reals, this will return the floating-point division. *

    NOTE: {@code Div} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = RealDiv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Reciprocal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Reciprocal.java index 97ae15f6015..c0e6b9c573a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Reciprocal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Reciprocal.java @@ -36,8 +36,6 @@ /** * Computes the reciprocal of x element-wise. * I.e., \(y = 1 / x\). - * - * @param data type for {@code y} output */ @OpMetadata( opType = Reciprocal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ReciprocalGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ReciprocalGrad.java index 13b7b7592ab..9d1c672629f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ReciprocalGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ReciprocalGrad.java @@ -37,8 +37,6 @@ * Computes the gradient for the inverse of {@code x} wrt its input. * Specifically, {@code grad = -dy * y*y}, where {@code y = 1/x}, and {@code dy} * is the corresponding input gradient. - * - * @param data type for {@code z} output */ @OpMetadata( opType = ReciprocalGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java index c2a71d1d594..f6dcf220ade 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java @@ -37,8 +37,6 @@ /** * Requantizes input with min and max values known per channel. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RequantizePerChannel.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java index 716bc8be07b..62a48d4ecd0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java @@ -43,8 +43,6 @@ * rint(0.5000001) ==> 1.0 * rint([-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0]) ==> [-2., -2., -0., 0., 2., 2., 2.] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Rint.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Round.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Round.java index d8a5aff3d2d..0e7441efeb1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Round.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Round.java @@ -37,8 +37,6 @@ * Rounds the values of a tensor to the nearest integer, element-wise. * Rounds half to even. Also known as bankers rounding. If you want to round * according to the current system rounding mode use std::cint. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Round.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rsqrt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rsqrt.java index 12ce75ef035..3d438f10f12 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rsqrt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rsqrt.java @@ -36,8 +36,6 @@ /** * Computes reciprocal of square root of x element-wise. * I.e., \(y = 1 / \sqrt{x}\). - * - * @param data type for {@code y} output */ @OpMetadata( opType = Rsqrt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RsqrtGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RsqrtGrad.java index f92da40a82b..90fc4892083 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RsqrtGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RsqrtGrad.java @@ -37,8 +37,6 @@ * Computes the gradient for the rsqrt of {@code x} wrt its input. * Specifically, {@code grad = dy * -0.5 * y^3}, where {@code y = rsqrt(x)}, and {@code dy} * is the corresponding input gradient. - * - * @param data type for {@code z} output */ @OpMetadata( opType = RsqrtGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java index 1939c7a4d3a..44ec468eaf4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java @@ -73,8 +73,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SegmentMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMean.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMean.java index 7d0e2af1606..2e69b2bb8b5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMean.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMean.java @@ -64,8 +64,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SegmentMean.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java index cb5a312d3ff..9dce52fceed 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java @@ -73,8 +73,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SegmentMin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentProd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentProd.java index 87738a1ac3a..77fd53d92a0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentProd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentProd.java @@ -66,8 +66,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SegmentProd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentSum.java index 578d159e289..c47c3acd24f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentSum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentSum.java @@ -44,9 +44,6 @@ * that {@code segment_ids[j] == i}. *

    If the sum is empty for a given segment ID {@code i}, {@code output[i] = 0}. *

    Note that this op is currently only supported with jit_compile=True. - * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SegmentSum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sigmoid.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sigmoid.java index bd93a0303eb..8e71006a2c0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sigmoid.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sigmoid.java @@ -36,8 +36,6 @@ /** * Computes sigmoid of {@code x} element-wise. * Specifically, {@code y = 1 / (1 + exp(-x))}. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Sigmoid.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SigmoidGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SigmoidGrad.java index 8f4b7cfe45c..a85b754cc61 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SigmoidGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SigmoidGrad.java @@ -37,8 +37,6 @@ * Computes the gradient of the sigmoid of {@code x} wrt its input. * Specifically, {@code grad = dy * y * (1 - y)}, where {@code y = sigmoid(x)}, and * {@code dy} is the corresponding input gradient. - * - * @param data type for {@code z} output */ @OpMetadata( opType = SigmoidGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sign.java index 15f5e07b597..ee9d2d65154 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sign.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sign.java @@ -46,8 +46,6 @@ * * * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Sign.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sin.java index 06269cb6278..1a13ada1838 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sin.java @@ -42,8 +42,6 @@ * x = tf.constant([-float("inf"), -9, -0.5, 1, 1.2, 200, 10, float("inf")]) * tf.math.sin(x) ==> [nan -0.4121185 -0.47942555 0.84147096 0.9320391 -0.87329733 -0.54402107 nan] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Sin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sinh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sinh.java index 9e1a692df76..b4af201ab99 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sinh.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sinh.java @@ -42,8 +42,6 @@ * x = tf.constant([-float("inf"), -9, -0.5, 1, 1.2, 2, 10, float("inf")]) * tf.math.sinh(x) ==> [-inf -4.0515420e+03 -5.2109528e-01 1.1752012e+00 1.5094614e+00 3.6268604e+00 1.1013232e+04 inf] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Sinh.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java index 95f33401f0b..5989ca78f57 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java @@ -40,8 +40,6 @@ * Generates points from the Sobol sequence. * Creates a Sobol sequence with {@code num_results} samples. Each sample has dimension * {@code dim}. Skips the first {@code skip} samples. - * - * @param data type for {@code samples} output */ @OpMetadata( opType = SobolSample.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java index aa80f8d0840..cdb0aea4f9f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java @@ -35,8 +35,6 @@ /** * The Softplus operation - * - * @param data type for {@code activations} output */ @OpMetadata( opType = Softplus.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java index 5a8445dad45..3f2901810ce 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java @@ -35,8 +35,6 @@ /** * Computes softplus gradients for a softplus operation. - * - * @param data type for {@code backprops} output */ @OpMetadata( opType = SoftplusGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sqrt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sqrt.java index ac6cd68b529..8c6edfc6e89 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sqrt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sqrt.java @@ -36,8 +36,6 @@ /** * Computes square root of x element-wise. * I.e., \(y = \sqrt{x} = x^{1/2}\). - * - * @param data type for {@code y} output */ @OpMetadata( opType = Sqrt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SqrtGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SqrtGrad.java index 451143c16e4..eed0209152b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SqrtGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SqrtGrad.java @@ -37,8 +37,6 @@ * Computes the gradient for the sqrt of {@code x} wrt its input. * Specifically, {@code grad = dy * 0.5 / y}, where {@code y = sqrt(x)}, and {@code dy} * is the corresponding input gradient. - * - * @param data type for {@code z} output */ @OpMetadata( opType = SqrtGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Square.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Square.java index d5811d17c2a..2952af307d2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Square.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Square.java @@ -36,8 +36,6 @@ /** * Computes square of x element-wise. * I.e., \(y = x * x = x^2\). - * - * @param data type for {@code y} output */ @OpMetadata( opType = Square.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SquaredDifference.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SquaredDifference.java index 2af6fe083e3..4d880a79baa 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SquaredDifference.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SquaredDifference.java @@ -37,8 +37,6 @@ * Returns conj(x - y)(x - y) element-wise. * NOTE: {@code math.SquaredDifference} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = SquaredDifference.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sub.java index 6313555f9f1..b48b311d80e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sub.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sub.java @@ -37,8 +37,6 @@ * Returns x - y element-wise. * NOTE: {@code math.Sub} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = Sub.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tan.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tan.java index 566b7d2b03f..c1073f8a5bb 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tan.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tan.java @@ -43,8 +43,6 @@ * x = tf.constant([-float("inf"), -9, -0.5, 1, 1.2, 200, 10000, float("inf")]) * tf.math.tan(x) ==> [nan 0.45231566 -0.5463025 1.5574077 2.572152 -1.7925274 0.32097113 nan] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Tan.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tanh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tanh.java index ee24b4085df..706a8d90cd0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tanh.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tanh.java @@ -49,8 +49,6 @@ * * * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Tanh.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TanhGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TanhGrad.java index c638f78b3fe..273adcf20a6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TanhGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TanhGrad.java @@ -37,8 +37,6 @@ * Computes the gradient for the tanh of {@code x} wrt its input. * Specifically, {@code grad = dy * (1 - y*y)}, where {@code y = tanh(x)}, and {@code dy} * is the corresponding input gradient. - * - * @param data type for {@code z} output */ @OpMetadata( opType = TanhGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateDiv.java index 377eb5848d8..7857bd6221b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateDiv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateDiv.java @@ -41,8 +41,6 @@ * Python Semantics. *

    NOTE: {@code math.TruncateDiv} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = TruncateDiv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java index e80c75e5709..bd7a41fafd2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java @@ -38,8 +38,6 @@ * the result here is consistent with a truncating divide. E.g. {@code truncate(x / y) * y + truncate_mod(x, y) = x}. *

    NOTE: {@code math.TruncateMod} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = TruncateMod.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UniformQuantizedAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UniformQuantizedAdd.java index 535d432dcca..312c712b44e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UniformQuantizedAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UniformQuantizedAdd.java @@ -52,8 +52,6 @@ * i.e. For both operands {@code lhs} and {@code rhs}, * if {@code operand.quantization_axis} >= 0 and {@code output.quantization_axis} >= 0, * {@code operand.dims} - {@code operand.quantization_axis} must be equal to {@code output.dims} - {@code output.quantization_axis}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformQuantizedAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMax.java index 50d32494e80..27888d7f1f5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMax.java @@ -67,8 +67,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = UnsortedSegmentMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java index db83daaead7..af919665a56 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java @@ -64,8 +64,6 @@ * result in safe but unspecified behavior, which may include ignoring * out-of-bound indices or outputting a tensor with a 0 stored in the first * dimension of its shape if {@code num_segments} is 0. - * - * @param data type for {@code output} output */ @OpMetadata( opType = UnsortedSegmentMin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentProd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentProd.java index a36c653ef2a..fd3f76bc1e7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentProd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentProd.java @@ -64,8 +64,6 @@ * result in safe but unspecified behavior, which may include ignoring * out-of-bound indices or outputting a tensor with a 0 stored in the first * dimension of its shape if {@code num_segments} is 0. - * - * @param data type for {@code output} output */ @OpMetadata( opType = UnsortedSegmentProd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentSum.java index 14c0bef2293..af4dd57e39f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentSum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentSum.java @@ -67,8 +67,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = UnsortedSegmentSum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xdivy.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xdivy.java index 8be3546a9f0..0ba35ba8a83 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xdivy.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xdivy.java @@ -35,8 +35,6 @@ /** * Returns 0 if x == 0, and x / y otherwise, elementwise. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Xdivy.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlog1py.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlog1py.java index b798c8ef598..c6e6184bed0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlog1py.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlog1py.java @@ -35,8 +35,6 @@ /** * Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Xlog1py.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlogy.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlogy.java index b4ad543093f..e27ef9a210c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlogy.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlogy.java @@ -35,8 +35,6 @@ /** * Returns 0 if x == 0, and x * log(y) otherwise, elementwise. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Xlogy.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java index 887fb1af711..593507c4340 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java @@ -37,8 +37,6 @@ * Compute the Hurwitz zeta function \(\zeta(x, q)\). * The Hurwitz zeta function is defined as: *

    \(\zeta(x, q) = \sum_{n=0}^{\infty} (q + n)^{-x}\) - * - * @param data type for {@code z} output */ @OpMetadata( opType = Zeta.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java index a4b68423646..a208c49973f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java @@ -35,8 +35,6 @@ /** * The Erfinv operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = erfinv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java index 6ef1d289c7d..839ca6179b3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java @@ -35,8 +35,6 @@ /** * The BesselJ0 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselJ0.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java index 5e7718f4144..6e125a29821 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java @@ -35,8 +35,6 @@ /** * The BesselJ1 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselJ1.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java index 338b5759a10..8ec9f528212 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java @@ -35,8 +35,6 @@ /** * The BesselK0 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselK0.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java index f2a01b68ba8..69d5995c59d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java @@ -35,8 +35,6 @@ /** * The BesselK0e operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselK0e.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java index 8143c8107d5..f26b95a8c53 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java @@ -35,8 +35,6 @@ /** * The BesselK1 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselK1.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java index 08ea2073dab..995eaccd9dd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java @@ -35,8 +35,6 @@ /** * The BesselK1e operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselK1e.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java index c82e15022db..1beae63d61f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java @@ -35,8 +35,6 @@ /** * The BesselY0 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselY0.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java index 5b86f1987e3..3985dee42d0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java @@ -35,8 +35,6 @@ /** * The BesselY1 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselY1.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java index 045ffc0d94c..e34e0376249 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java @@ -35,8 +35,6 @@ /** * The Dawsn operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = Dawsn.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java index bcdff92cb07..9b61e0fcb90 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java @@ -35,8 +35,6 @@ /** * The Expint operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = Expint.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java index 790daad9115..dffb6bda0f0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java @@ -35,8 +35,6 @@ /** * The FresnelCos operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = FresnelCos.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java index a148cb42bff..23e7e1d4bbd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java @@ -35,8 +35,6 @@ /** * The FresnelSin operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = FresnelSin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java index 7835a2fca79..0a012a3be6c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java @@ -35,8 +35,6 @@ /** * The Spence operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = Spence.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java index aa583ae8174..3d6355679c8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java @@ -38,8 +38,6 @@ * Performs average pooling on the input. * Each entry in {@code output} is the mean of the corresponding size {@code ksize} * window in {@code value}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = AvgPool.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java index b7b61a50351..5f5410d91d5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java @@ -38,8 +38,6 @@ * Performs 3D average pooling on the input. * Each entry in {@code output} is the mean of the corresponding size {@code ksize} window in * {@code value}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = AvgPool3d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java index 6acc17b69ae..4b41a0338b3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java @@ -37,8 +37,6 @@ /** * Computes gradients of average pooling function. - * - * @param data type for {@code output} output */ @OpMetadata( opType = AvgPool3dGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPoolGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPoolGrad.java index 74acc456c92..9a2c1511bba 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPoolGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPoolGrad.java @@ -37,8 +37,6 @@ /** * Computes gradients of the average pooling function. - * - * @param data type for {@code output} output */ @OpMetadata( opType = AvgPoolGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalization.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalization.java index deaec7bdd3d..ef7ead8115e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalization.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalization.java @@ -36,8 +36,6 @@ /** * Batch normalization. * This op is deprecated. Prefer {@code tf.nn.batch_normalization}. - * - * @param data type for {@code result} output */ @OpMetadata( opType = BatchNormWithGlobalNormalization.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalizationGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalizationGrad.java index f75aebb0e4c..03e84d778c4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalizationGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalizationGrad.java @@ -36,8 +36,6 @@ /** * Gradients for batch normalization. * This op is deprecated. See {@code tf.nn.batch_normalization}. - * - * @param data type for {@code dx} output */ @OpMetadata( opType = BatchNormWithGlobalNormalizationGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAdd.java index c228699e9cb..5f826546b07 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAdd.java @@ -37,8 +37,6 @@ * Adds {@code bias} to {@code value}. * This is a special case of {@code tf.add} where {@code bias} is restricted to be 1-D. * Broadcasting is supported, so {@code value} may have any number of dimensions. - * - * @param data type for {@code output} output */ @OpMetadata( opType = BiasAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAddGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAddGrad.java index 01c90a2fd49..33c2829c271 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAddGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAddGrad.java @@ -38,8 +38,6 @@ * It accumulates all the values from out_backprop into the feature dimension. * For NHWC data format, the feature dimension is the last. For NCHW data format, * the feature dimension is the third-to-last. - * - * @param data type for {@code output} output */ @OpMetadata( opType = BiasAddGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java index 3363a371d20..ef303c35efc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java @@ -56,8 +56,6 @@ * this op uses IFCO. So in order for the following snippet to be equivalent * all gate-related outputs should be reordered. * - * - * @param data type for {@code i} output */ @OpMetadata( opType = BlockLSTM.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java index 2684ae60017..85bc08f38b6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java @@ -37,8 +37,6 @@ /** * Computes the LSTM cell backward propagation for the entire time sequence. * This implementation is to be used in conjunction of BlockLSTMV2. - * - * @param data type for {@code x_grad} output */ @OpMetadata( opType = BlockLSTMGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv.java index 7e352a1ff76..096c8a3719f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv.java @@ -38,8 +38,6 @@ * Computes a N-D convolution given (N+1+batch_dims)-D {@code input} and (N+2)-D {@code filter} tensors. * General function for computing a N-D convolution. It is required that * {@code 1 <= N <= 3}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java index 9fef633fefd..6d7eb6e004e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java @@ -56,8 +56,6 @@ * *

    Must have {@code strides[0] = strides[3] = 1}. For the most common case of the same * horizontal and vertices strides, {@code strides = [1, stride, stride, 1]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv2d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java index 9d09ebaa1df..2d5af50d5e6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java @@ -37,8 +37,6 @@ /** * Computes the gradients of convolution with respect to the filter. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv2dBackpropFilter.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilterV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilterV2.java index 901d2a50f72..1b8a95c8728 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilterV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilterV2.java @@ -35,8 +35,6 @@ /** * Computes the gradients of convolution with respect to the filter. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv2dBackpropFilterV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java index 9e44c7170cb..fc0f5f296e1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java @@ -37,8 +37,6 @@ /** * Computes the gradients of convolution with respect to the input. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv2dBackpropInput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInputV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInputV2.java index 1fa123e14b2..04941640016 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInputV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInputV2.java @@ -35,8 +35,6 @@ /** * Computes the gradients of convolution with respect to the input. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv2dBackpropInputV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java index 5d3d0925894..7de4f93716d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java @@ -40,8 +40,6 @@ * two waveforms as a function of a time-lag applied to one of them. This * is also known as a sliding dot product or sliding inner-product. *

    Our Conv3D implements a form of cross-correlation. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv3d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java index 2cc01b0dfe0..79970ac4d15 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java @@ -37,8 +37,6 @@ /** * Computes the gradients of 3-D convolution with respect to the filter. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv3dBackpropFilter.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java index 651f027ac42..d60306ab96d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java @@ -36,8 +36,6 @@ /** * Computes the gradients of 3-D convolution with respect to the input. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv3dBackpropInput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java index 59cde61eb54..f270607bb50 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java @@ -43,8 +43,6 @@ * the first of these is emitted. That is, when the top path is "A B B B B", * "A B" is returned if merge_repeated = True but "A B B B B" is * returned if merge_repeated = False. - * - * @param data type for {@code log_probability} output */ @OpMetadata( opType = CtcBeamSearchDecoder.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java index de01c874c33..688f60ab28e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java @@ -45,8 +45,6 @@ *

    Regardless of the value of merge_repeated, if the maximum index of a given * time and batch corresponds to the blank, index {@code (num_classes - 1)}, no new * element is emitted. - * - * @param data type for {@code log_probability} output */ @OpMetadata( opType = CtcGreedyDecoder.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java index d2dd09549fa..8369dae6c75 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java @@ -39,8 +39,6 @@ * Calculates the CTC Loss (log probability) for each batch entry. Also calculates * the gradient. This class performs the softmax operation for you, so inputs * should be e.g. linear projections of outputs by an LSTM. - * - * @param data type for {@code loss} output */ @OpMetadata( opType = CtcLoss.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java index 0525df86f45..8845090aa6e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java @@ -73,8 +73,6 @@ * major. * reserve_space: An opaque tensor that can be used in backprop calculation. It * is only produced if is_training is true. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CudnnRNN.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java index d76dd629918..a1e09f597ac 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java @@ -83,8 +83,6 @@ * shape as input_c. * params_backprop: The backprop to the params buffer in the forward pass. Has the * same shape as params. - * - * @param data type for {@code input_backprop} output */ @OpMetadata( opType = CudnnRNNBackprop.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java index a513cf67d66..0c38a68a23e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java @@ -65,8 +65,6 @@ * seed2: the 2nd part of a seed to initialize dropout. * num_proj: The output dimensionality for the projection matrices. If None or 0, * no projection is performed. - * - * @param data type for {@code params} output */ @OpMetadata( opType = CudnnRNNCanonicalToParams.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java index 6a1e55f34e2..b85a3568412 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java @@ -65,8 +65,6 @@ * seed2: the 2nd part of a seed to initialize dropout. * num_proj: The output dimensionality for the projection matrices. If None or 0, * no projection is performed. - * - * @param data type for {@code weights} output */ @OpMetadata( opType = CudnnRNNParamsToCanonical.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java index 051c792e878..1dbc4d48ad8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java @@ -57,8 +57,6 @@ * compatible across GPUs. Please use CudnnRNNParamsWeights and * CudnnRNNParamsBiases to save and restore them in a way that is compatible * across different runs. - * - * @param data type for {@code params_size} output */ @OpMetadata( opType = CudnnRnnParamsSize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java index 3376ad9ed6e..6e83cd0c867 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java @@ -36,8 +36,6 @@ /** * Returns the dimension index in the destination data format given the one in * the source data format. - * - * @param data type for {@code y} output */ @OpMetadata( opType = DataFormatDimMap.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java index e02890a40ce..f719f7cc7ce 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java @@ -64,8 +64,6 @@ * 

      * [1, 2]
  *
    - * - * @param data type for {@code y} output */ @OpMetadata( opType = DataFormatVecPermute.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthToSpace.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthToSpace.java index cceb78d27d1..2f1880cda02 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthToSpace.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthToSpace.java @@ -109,8 +109,6 @@ * [ [11], [12], [15], [16]]]] * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = DepthToSpace.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java index e3f7f02ac33..93a0b744513 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java @@ -52,8 +52,6 @@ * *

    Must have {@code strides[0] = strides[3] = 1}. For the most common case of the same * horizontal and vertices strides, {@code strides = [1, stride, stride, 1]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DepthwiseConv2dNative.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java index 6c55468131b..66eb190debf 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java @@ -37,8 +37,6 @@ /** * Computes the gradients of depthwise convolution with respect to the filter. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DepthwiseConv2dNativeBackpropFilter.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java index 0f1a70bb566..287b29abba1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java @@ -37,8 +37,6 @@ /** * Computes the gradients of depthwise convolution with respect to the input. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DepthwiseConv2dNativeBackpropInput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java index f213e685ab6..019c786873c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java @@ -57,8 +57,6 @@ * kernel size and contains all zeros. *

    Note on duality: The dilation of {@code input} by the {@code filter} is equal to the * negation of the erosion of {@code -input} by the reflected {@code filter}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Dilation2d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java index 93381ee22cf..cae841aee0d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java @@ -36,8 +36,6 @@ /** * Computes the gradient of morphological 2-D dilation with respect to the filter. - * - * @param data type for {@code filter_backprop} output */ @OpMetadata( opType = Dilation2dBackpropFilter.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropInput.java index 7747bc57c64..8204785ae02 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropInput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropInput.java @@ -36,8 +36,6 @@ /** * Computes the gradient of morphological 2-D dilation with respect to the input. - * - * @param data type for {@code in_backprop} output */ @OpMetadata( opType = Dilation2dBackpropInput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Elu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Elu.java index 6119dd0dec2..253baee2601 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Elu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Elu.java @@ -55,8 +55,6 @@ * *

    See Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) * - * - * @param data type for {@code activations} output */ @OpMetadata( opType = Elu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java index 2df99ce5c8f..4d32b6d365f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java @@ -35,8 +35,6 @@ /** * Computes gradients for the exponential linear (Elu) operation. - * - * @param data type for {@code backprops} output */ @OpMetadata( opType = EluGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java index 04cfd0e3cd9..bb525aac295 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java @@ -41,8 +41,6 @@ * region generation step. The only difference is that after pooling regions are * generated, a mean operation is performed instead of a max operation in each * pooling region. - * - * @param data type for {@code output} output */ @OpMetadata( opType = FractionalAvgPool.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java index 71b1e624c55..eee42886ab1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java @@ -41,8 +41,6 @@ * out_backprop to those indices that form the same pooling cell. Therefore, we * just need to know the shape of original input tensor, instead of the whole * tensor. - * - * @param data type for {@code output} output */ @OpMetadata( opType = FractionalAvgPoolGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java index d4c2cb5cf15..08bcbd1a63d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java @@ -63,8 +63,6 @@ * *

    For more details on fractional max pooling, see this paper: * Benjamin Graham, Fractional Max-Pooling - * - * @param data type for {@code output} output */ @OpMetadata( opType = FractionalMaxPool.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java index 432d6bbfdb7..d44e062ccf7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java @@ -36,8 +36,6 @@ /** * Computes gradient of the FractionalMaxPool function. - * - * @param data type for {@code output} output */ @OpMetadata( opType = FractionalMaxPoolGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java index 41e62263399..f5cede8855e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java @@ -37,10 +37,6 @@ * Batch normalization. * Note that the size of 4D Tensors are defined by either "NHWC" or "NCHW". * The size of 1D Tensors matches the dimension C of the 4D Tensors. - * - * @param data type for {@code y} output - * - * @param data type for {@code batch_mean} output */ @OpMetadata( opType = FusedBatchNorm.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java index efc751554d2..985249a19fe 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java @@ -38,10 +38,6 @@ * Gradient for batch normalization. * Note that the size of 4D Tensors are defined by either "NHWC" or "NCHW". * The size of 1D Tensors matches the dimension C of the 4D Tensors. - * - * @param data type for {@code x_backprop} output - * - * @param data type for {@code scale_backprop} output */ @OpMetadata( opType = FusedBatchNormGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java index 1a11cf9c722..336419f92ad 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java @@ -48,8 +48,6 @@ * Internally this op uses a single per-graph scratch buffer, which means that it * will block if multiple versions are being run in parallel. This is because this * operator is primarily an optimization to minimize memory usage. - * - * @param data type for {@code output} output */ @OpMetadata( opType = FusedPadConv2d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedResizeAndPadConv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedResizeAndPadConv2d.java index 69b33a7ffee..8491feba1d7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedResizeAndPadConv2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedResizeAndPadConv2d.java @@ -47,8 +47,6 @@ * Internally this op uses a single per-graph scratch buffer, which means that it * will block if multiple versions are being run in parallel. This is because this * operator is primarily an optimization to minimize memory usage. - * - * @param data type for {@code output} output */ @OpMetadata( opType = FusedResizeAndPadConv2d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCell.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCell.java index 413c9db45cf..0db7843bced 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCell.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCell.java @@ -73,8 +73,6 @@ * * h = (1-u) \circ c + u \circ h_prev * - * - * @param data type for {@code r} output */ @OpMetadata( opType = GRUBlockCell.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java index 108aa910427..7379a2790ba 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java @@ -108,8 +108,6 @@ * * d_b_c = sum of d_c_bar along axis = 0 * - * - * @param data type for {@code d_x} output */ @OpMetadata( opType = GRUBlockCellGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InvGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InvGrad.java index 37f66b92878..5f178f53e50 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InvGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InvGrad.java @@ -37,8 +37,6 @@ * Computes the gradient for the inverse of {@code x} wrt its input. * Specifically, {@code grad = -dy * y*y}, where {@code y = 1/x}, and {@code dy} * is the corresponding input gradient. - * - * @param data type for {@code z} output */ @OpMetadata( opType = InvGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/IsotonicRegression.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/IsotonicRegression.java index 8936770d8b7..ecd511253e8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/IsotonicRegression.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/IsotonicRegression.java @@ -38,8 +38,6 @@ /** * Solves a batch of isotonic regression problems. - * - * @param data type for {@code output} output */ @OpMetadata( opType = IsotonicRegression.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java index e3b179e440c..9cc952c05cb 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java @@ -39,8 +39,6 @@ * 

      * output = sum(t ** 2) / 2
  *
    - * - * @param data type for {@code output} output */ @OpMetadata( opType = L2Loss.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java index 12d4402e70f..5b1e38d3fbe 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java @@ -57,8 +57,6 @@ * co = tanh(cs) * h = co .* o * - * - * @param data type for {@code i} output */ @OpMetadata( opType = LSTMBlockCell.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java index e22e2241718..931e4bf2381 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java @@ -36,8 +36,6 @@ /** * Computes the LSTM cell backward propagation for 1 timestep. * This implementation is to be used in conjunction of LSTMBlockCell. - * - * @param data type for {@code cs_prev_grad} output */ @OpMetadata( opType = LSTMBlockCellGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java index 022b81f82da..a0f088f9a03 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java @@ -35,8 +35,6 @@ /** * Computes rectified linear: {@code max(features, features * alpha)}. - * - * @param data type for {@code activations} output */ @OpMetadata( opType = LeakyRelu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java index f0bb2b5017b..17c1e5c0d04 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java @@ -46,8 +46,6 @@ * *

    For details, see Krizhevsky et al., ImageNet classification with deep * convolutional neural networks (NIPS 2012) . - * - * @param data type for {@code output} output */ @OpMetadata( opType = LocalResponseNormalization.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java index 041837b7871..c0b795094aa 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java @@ -35,8 +35,6 @@ /** * Gradients for Local Response Normalization. - * - * @param data type for {@code output} output */ @OpMetadata( opType = LocalResponseNormalizationGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java index 1f9ee440140..1e19b56c19f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java @@ -39,8 +39,6 @@ * 

      * logsoftmax[i, j] = logits[i, j] - log(sum(exp(logits[i])))
  *
    - * - * @param data type for {@code logsoftmax} output */ @OpMetadata( opType = LogSoftmax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool.java index 427b3c92bb2..75b432b8ba3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool.java @@ -36,8 +36,6 @@ /** * Performs max pooling on the input. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MaxPool.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java index d9cace3d967..d701189d5e1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java @@ -36,8 +36,6 @@ /** * Performs 3D max pooling on the input. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MaxPool3d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java index 6ac95b8a978..932399be80b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java @@ -36,8 +36,6 @@ /** * Computes gradients of 3D max pooling function. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MaxPool3dGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java index 5efa05dec89..74dbc598b35 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java @@ -36,8 +36,6 @@ /** * Computes second-order gradients of the maxpooling function. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MaxPool3dGradGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGrad.java index 214b0b0d31c..a329757270c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGrad.java @@ -36,8 +36,6 @@ /** * Computes gradients of the maxpooling function. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MaxPoolGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java index a33ba6642b8..0b0f0f616b7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java @@ -36,8 +36,6 @@ /** * Computes second-order gradients of the maxpooling function. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MaxPoolGradGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGradWithArgmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGradWithArgmax.java index 35f1ffeb6dd..9dedc6014b8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGradWithArgmax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGradWithArgmax.java @@ -36,8 +36,6 @@ /** * Computes second-order gradients of the maxpooling function. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MaxPoolGradGradWithArgmax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradWithArgmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradWithArgmax.java index 0edd2ca5adc..60d7e7de94c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradWithArgmax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradWithArgmax.java @@ -36,8 +36,6 @@ /** * Computes gradients of the maxpooling function. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MaxPoolGradWithArgmax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java index bcfba861e1e..bd19af1b703 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java @@ -46,10 +46,6 @@ * even if padding is involved and the mathematically correct answer is outside * (either negative or too large). This is a bug, but fixing it is difficult to do * in a safe backwards compatible way, especially due to flattening. - * - * @param data type for {@code output} output - * - * @param data type for {@code argmax} output */ @OpMetadata( opType = MaxPoolWithArgmax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/NthElement.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/NthElement.java index 383dbfc3b22..57754316380 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/NthElement.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/NthElement.java @@ -43,8 +43,6 @@ * 
      * values.shape = input.shape[:-1]
  *
    - * - * @param data type for {@code values} output */ @OpMetadata( opType = NthElement.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedAvgPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedAvgPool.java index 2e27d649947..8987fcd7d55 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedAvgPool.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedAvgPool.java @@ -37,8 +37,6 @@ /** * Produces the average pool of the input tensor for quantized types. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedAvgPool.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java index 0b9e3b27b55..7f22995509c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java @@ -39,8 +39,6 @@ * Quantized Batch normalization. * This op is deprecated and will be removed in the future. Prefer * {@code tf.nn.batch_normalization}. - * - * @param data type for {@code result} output */ @OpMetadata( opType = QuantizedBatchNormWithGlobalNormalization.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java index c95300fa493..744eb1397eb 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java @@ -38,8 +38,6 @@ /** * Adds Tensor 'bias' to Tensor 'input' for Quantized types. * Broadcasts the values of bias on dimensions 0..N-2 of 'input'. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedBiasAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java index 4594e0401cc..9226b7b697e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DAndRelu operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DAndRelu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java index 0104cbf9908..f02eba09012 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DAndReluAndRequantize operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DAndReluAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java index 5fe5999adab..66344508160 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DAndRequantize operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java index 134449aba91..bfd108c34d3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java @@ -38,8 +38,6 @@ /** * Computes QuantizedConv2D per channel. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DPerChannel.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java index 27f5343c6ff..fe5566ac7e9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DWithBias operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DWithBias.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java index 61c9bb31b45..ff7d157a846 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DWithBiasAndRelu operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DWithBiasAndRelu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java index 081b8ac3863..b68080cc72c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DWithBiasAndReluAndRequantize operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DWithBiasAndReluAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java index 21f4eef7826..5301017e666 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DWithBiasAndRequantize operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DWithBiasAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java index afdd8b87219..687e41485d4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DWithBiasSignedSumAndReluAndRequantize operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java index d92782f88bb..34ceb6e7898 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DWithBiasSumAndRelu operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DWithBiasSumAndRelu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java index 0d9c4fab0f6..021873d6885 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DWithBiasSumAndReluAndRequantize operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DWithBiasSumAndReluAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java index 88482fc869f..77d21ba9794 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java @@ -42,8 +42,6 @@ * number of the associated minimum, and the highest represents the maximum. * This means that you can only interpret the quantized output in the same way, by * taking the returned minimum and maximum values into account. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java index 19c05799f1f..3281b31698b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java @@ -38,8 +38,6 @@ /** * Computes quantized depthwise Conv2D. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedDepthwiseConv2D.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java index 9414fd9e015..70314ace0b0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java @@ -38,8 +38,6 @@ /** * Computes quantized depthwise Conv2D with Bias. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedDepthwiseConv2DWithBias.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java index c8d6a30445b..76b0917f709 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java @@ -38,8 +38,6 @@ /** * Computes quantized depthwise Conv2D with Bias and Relu. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedDepthwiseConv2DWithBiasAndRelu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java index b23311716d2..55dfdecdb39 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java @@ -38,8 +38,6 @@ /** * Computes quantized depthwise Conv2D with Bias, Relu and Requantize. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedInstanceNorm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedInstanceNorm.java index 54bd27c1705..48aedde6806 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedInstanceNorm.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedInstanceNorm.java @@ -36,8 +36,6 @@ /** * Quantized Instance normalization. - * - * @param data type for {@code y} output */ @OpMetadata( opType = QuantizedInstanceNorm.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedMaxPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedMaxPool.java index b1323bb3b42..e57d4e945b4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedMaxPool.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedMaxPool.java @@ -37,8 +37,6 @@ /** * Produces the max pool of the input tensor for quantized types. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedMaxPool.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java index b80e07346d9..ad55085ab6f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java @@ -37,8 +37,6 @@ /** * Computes Quantized Rectified Linear: {@code max(features, 0)} - * - * @param data type for {@code activations} output */ @OpMetadata( opType = QuantizedRelu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java index d820e51188a..2b2f21a6b45 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java @@ -37,8 +37,6 @@ /** * Computes Quantized Rectified Linear 6: {@code min(max(features, 0), 6)} - * - * @param data type for {@code activations} output */ @OpMetadata( opType = QuantizedRelu6.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java index 577df61b8dd..41daae389b6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java @@ -37,8 +37,6 @@ /** * Computes Quantized Rectified Linear X: {@code min(max(features, 0), max_value)} - * - * @param data type for {@code activations} output */ @OpMetadata( opType = QuantizedReluX.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu.java index 218fee4f3d2..126eb0c4c56 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu.java @@ -45,8 +45,6 @@ * * * - * - * @param data type for {@code activations} output */ @OpMetadata( opType = Relu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java index 19de03d7f8e..5500229b21c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java @@ -35,8 +35,6 @@ /** * Computes rectified linear 6: {@code min(max(features, 0), 6)}. - * - * @param data type for {@code activations} output */ @OpMetadata( opType = Relu6.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java index 48ec9cb7037..9af8b816d87 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java @@ -35,8 +35,6 @@ /** * Computes rectified linear 6 gradients for a Relu6 operation. - * - * @param data type for {@code backprops} output */ @OpMetadata( opType = Relu6Grad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java index 5e7103853f3..b15132dd583 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java @@ -35,8 +35,6 @@ /** * Computes rectified linear gradients for a Relu operation. - * - * @param data type for {@code backprops} output */ @OpMetadata( opType = ReluGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java index d382a2f5a75..33d504105ec 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java @@ -40,8 +40,6 @@ * {@code initializer = tf.variance_scaling_initializer(factor=1.0, mode='FAN_IN')}. * For correct dropout, use {@code tf.contrib.nn.alpha_dropout}. *

    See Self-Normalizing Neural Networks - * - * @param data type for {@code activations} output */ @OpMetadata( opType = Selu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java index 7a2e0656275..bd2d2203f69 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java @@ -35,8 +35,6 @@ /** * Computes gradients for the scaled exponential linear (Selu) operation. - * - * @param data type for {@code backprops} output */ @OpMetadata( opType = SeluGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java index 36ef20f21fd..dd6b9ecb2b5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java @@ -39,8 +39,6 @@ * 

      * $$softmax[i, j] = exp(logits[i, j]) / sum_j(exp(logits[i, j]))$$
  *
    - * - * @param data type for {@code softmax} output */ @OpMetadata( opType = Softmax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java index 9a17188c048..a7836f24051 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java @@ -36,8 +36,6 @@ /** * Computes softmax cross entropy cost and gradients to backpropagate. * Inputs are the logits, not probabilities. - * - * @param data type for {@code loss} output */ @OpMetadata( opType = SoftmaxCrossEntropyWithLogits.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java index 1345a1ffd11..1144c4c21be 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java @@ -35,8 +35,6 @@ /** * Computes softsign: {@code features / (abs(features) + 1)}. - * - * @param data type for {@code activations} output */ @OpMetadata( opType = Softsign.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java index b16c933ffe0..3ebe407b08e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java @@ -35,8 +35,6 @@ /** * Computes softsign gradients for a softsign operation. - * - * @param data type for {@code backprops} output */ @OpMetadata( opType = SoftsignGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToBatch.java index 050a12e7f98..e35f65ee574 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToBatch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToBatch.java @@ -100,8 +100,6 @@ * *

    Among others, this operation is useful for reducing atrous convolution into * regular convolution. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SpaceToBatch.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToDepth.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToDepth.java index 18449c4627c..aaaddf55663 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToDepth.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToDepth.java @@ -103,8 +103,6 @@ * [[9, 10, 11, 12], * [13, 14, 15, 16]]]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SpaceToDepth.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java index 043587de9b5..1b7c99a694e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java @@ -40,8 +40,6 @@ * of features. This label is considered to have probability 1.0 for the * given row. *

    Inputs are the logits, not probabilities. - * - * @param data type for {@code loss} output */ @OpMetadata( opType = SparseSoftmaxCrossEntropyWithLogits.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java index b752c40666b..189f0434054 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java @@ -46,10 +46,6 @@ * values.shape = indices.shape = input.shape[:-1] + [k] * *

    If two elements are equal, the lower-index element appears first. - * - * @param data type for {@code values} output - * - * @param data type for {@code indices} output */ @OpMetadata( opType = TopK.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolution.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolution.java index 9b4715c3a21..124c2b062f0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolution.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolution.java @@ -55,8 +55,6 @@ * *

    {@code output} is also quantized, using the same formula. * If {@code rhs} is per-tensor quantized, {@code output} must be also per-tensor quantized. - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformQuantizedConvolution.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolutionHybrid.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolutionHybrid.java index 02b51c0dfe4..8510272759e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolutionHybrid.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolutionHybrid.java @@ -55,8 +55,6 @@ * *

    {@code rhs} must be quantized Tensor, where its data value is quantized using the formula: * quantized_data = clip(original_data / scale + zero_point, quantization_min_val, quantization_max_val). - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformQuantizedConvolutionHybrid.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Dequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Dequantize.java index 743b6c81d93..a062ee1db29 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Dequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Dequantize.java @@ -80,8 +80,6 @@ * : std::max(min_range / min_expected_T, * max_range / max_expected_T); * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Dequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxArgsGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxArgsGradient.java index 4f3b11ce977..87007c73d6b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxArgsGradient.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxArgsGradient.java @@ -136,6 +136,38 @@ public static Options narrowRange(Boolean narrowRange) { * Gets backprops. * Backpropagated gradients below the FakeQuantWithMinMaxArgs operation: * {@code gradients * (inputs >= min && inputs <= max)}. + * 

    +   * import tensorflow as tf
+   *
+   * # Define some sample data
+   * gradients = tf.random.uniform((2, 3), minval=-5.0, maxval=5.0, dtype=tf.float32)
+   * inputs = tf.random.uniform((2, 3), minval=-10.0, maxval=10.0, dtype=tf.float32)
+   *
+   * # Define quantization parameters (adjust as needed)
+   * min_val = -2.0
+   * max_val = 8.0
+   * num_bits = 4  # Number of bits for quantization
+   *
+   * # Calculate gradients for fake quantization with specified parameters
+   * output_gradients = tf.quantization.fake_quant_with_min_max_args_gradient(
+   *     gradients=gradients, inputs=inputs, min=min_val, max=max_val, num_bits=num_bits, narrow_range = False, name=None
+   * )
+   *
+   * # Print the original gradients and the gradients after the fake-quant operation
+   * print("Original Gradients:")
+   * print(gradients)
+   * print("\nGradients after Fake-Quantization:")
+   * print(output_gradients)
+   *
+   *
    + *

    #Original Gradients: + * #tf.Tensor( + * #[[ 1.242547 3.217492 3.568469 ] + * #[-0.55371046 0.23130894 2.608243 ]], shape=(2, 3), dtype=float32) + *

    #Gradients after Fake-Quantization: + * #tf.Tensor( + * #[[ 0. 3.217492 3.568469 ] + * [-0.55371046 0.23130894 2.608243 ]], shape=(2, 3), dtype=float32)
    * @return backprops. */ public Output backprops() { diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVars.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVars.java index faa38bb0585..e78b22ca6d5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVars.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVars.java @@ -57,6 +57,28 @@ * *

    This operation has a gradient and thus allows for training {@code min} and {@code max} * values. + *

    + *
    + *
    + *

    constant_input = tf.constant([[1.2, -0.3, 0.7], [2.1, 0.5, -1.0]], dtype=tf.float32) + *

    min_val = -0.5 + * max_val = 0.8 + * num_bits = 8 + * narrow_range = False #False:for the quantization range [0; 2^num_bits - 1] + *

    quantized_data = tf.quantization.fake_quant_with_min_max_vars( + * ... inputs=constant_input, min=min_val, max=max_val, num_bits=num_bits, narrow_range=narrow_range + * ... ) + *

    print("Input:\n", constant_input.numpy()) + * Input: + * [[ 1.2 -0.3 0.7] + * [ 2.1 0.5 -1. ]] + * print("Output:\n", quantized_data.numpy()) + * Output: + * [[ 0.8003921 -0.3007843 0.6984313] + * [ 0.8003921 0.4996078 -0.4996078]] + *

    + *
    + *
    */ @OpMetadata( opType = FakeQuantWithMinMaxVars.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java index a6a5df07a8a..ed34d301ec7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java @@ -128,8 +128,6 @@ *

    Ensures the minimum quantization range is at least this value. * The legacy default value for this is 0.01, but it is strongly suggested to * set it to 0 for new uses. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Quantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java index b6552257828..eeb9f05536c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java @@ -38,8 +38,6 @@ * Quantizes then dequantizes a tensor. * This is almost identical to QuantizeAndDequantizeV2, except that num_bits is a * tensor, so its value can change during training. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizeAndDequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV3.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV3.java index a715ecdb8e5..e1de6cd2ab7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV3.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV3.java @@ -38,8 +38,6 @@ * Quantizes then dequantizes a tensor. * This is almost identical to QuantizeAndDequantizeV2, except that num_bits is a * tensor, so its value can change during training. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizeAndDequantizeV3.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4.java index 75b47a7f0f9..7de2e59c64b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4.java @@ -37,8 +37,6 @@ * Quantizes then dequantizes a tensor. * This is almost identical to QuantizeAndDequantizeV2, except that it returns a * gradient of 1 for inputs that are within the quantization range, or 0 otherwise. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizeAndDequantizeV4.OP_NAME, @@ -114,7 +112,7 @@ public static QuantizeAndDequantizeV4 create(Scope scope, * Sets the signedInput option. * * @param signedInput Whether the quantization is signed or unsigned. (actually this parameter should - * have been called {@code signed_output}</b>) + * have been called {@code signed_output}) * @return this Options instance. */ public static Options signedInput(Boolean signedInput) { @@ -218,7 +216,7 @@ private Options() { * Sets the signedInput option. * * @param signedInput Whether the quantization is signed or unsigned. (actually this parameter should - * have been called {@code signed_output}</b>) + * have been called {@code signed_output}) * @return this Options instance. */ public Options signedInput(Boolean signedInput) { @@ -317,7 +315,7 @@ public static class Inputs extends RawOpInputs{@code signed_output}</b>) + * have been called {@code signed_output}) */ public final boolean signedInput; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4Grad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4Grad.java index d2d9d9e6035..65cf77c43ca 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4Grad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4Grad.java @@ -37,8 +37,6 @@ * Returns the gradient of {@code QuantizeAndDequantizeV4}. * Returns a gradient of 1 for inputs that are within the quantization range, * or 0 otherwise. - * - * @param data type for {@code input_backprop} output */ @OpMetadata( opType = QuantizeAndDequantizeV4Grad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java index d8aee82efb2..77aaa257758 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java @@ -56,8 +56,6 @@ * input values that only uses a small fraction of the possible range. By feeding * that output into this operator, we can reduce it from 32 bits down to 8 with * minimal loss of accuracy. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizeDownAndShrinkRange.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedConcat.java index cae65990d35..a52e49b8080 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedConcat.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedConcat.java @@ -38,8 +38,6 @@ /** * Concatenates quantized tensors along one dimension. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConcat.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java index 69827ccd019..c03a82caf5c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java @@ -37,8 +37,6 @@ /** * The QuantizedMatMulWithBiasAndDequantize operation - * - * @param data type for {@code out} output */ @OpMetadata( opType = QuantizedMatMulWithBiasAndDequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java index cd48b07ac48..b848d068a15 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java @@ -37,8 +37,6 @@ /** * The QuantizedMatMulWithBiasAndRequantize operation - * - * @param data type for {@code out} output */ @OpMetadata( opType = QuantizedMatMulWithBiasAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java index 48bfa78ab74..0ebd2ce0e3a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java @@ -43,8 +43,6 @@ * interpretation of the {@code input} data. For example, if {@code input_min} is -1.0f and * {@code input_max} is 1.0f, and we are dealing with {@code quint16} quantized data, then a 0 * value in the 16-bit data should be interpreted as -1.0f, and a 65535 means 1.0f. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Requantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformDequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformDequantize.java index 97dad1321da..8f5d44bf663 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformDequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformDequantize.java @@ -40,8 +40,6 @@ * Perform dequantization on the quantized Tensor {@code input}. * Given quantized {@code input} which was quantized using {@code scales} and {@code zero_points}, performs dequantization using the formula: * dequantized_data = (quantized_data - zero_point) * scale. - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformDequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantize.java index 43fed90b7cc..390ceb83d8a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantize.java @@ -40,8 +40,6 @@ * Perform quantization on Tensor {@code input}. * Given {@code input}, {@code scales} and {@code zero_points}, performs quantization using the formula: * quantized_data = floor(input_data * (1.0f / scale) + 0.5f) + zero_point - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformQuantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDot.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDot.java index 16768a99b22..eff33c22ce7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDot.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDot.java @@ -44,8 +44,6 @@ * quantized_data = clip(original_data / scale + zero_point, quantization_min_val, quantization_max_val). * {@code output} is also quantized, using the same formula. * If {@code rhs} is per-tensor quantized, {@code output} must be also per-tensor quantized. - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformQuantizedDot.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDotHybrid.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDotHybrid.java index ed8c67f9a53..1f30f7a1a4c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDotHybrid.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDotHybrid.java @@ -43,8 +43,6 @@ * {@code lhs} and {@code rhs} must be 2D Tensors and the lhs.dim_size(1) must match rhs.dim_size(0). * {@code rhs} must be quantized Tensor, where its data value is quantized using the formula: * quantized_data = clip(original_data / scale + zero_point, quantization_min_val, quantization_max_val). - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformQuantizedDotHybrid.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformRequantize.java index 85f81e8f202..eb4c511b567 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformRequantize.java @@ -52,8 +52,6 @@ *

  • per-axis -> per-axis where input_quantization_axis equals output_quantization_axis. * i.e. At least one among input_quantization_axis and output_quantization_axis must be -1, or two must be equal.
    • * - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java index 2607b8e0fcf..0aadded3990 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java @@ -42,8 +42,6 @@ * the value in {@code weights} at each index where the corresponding value in {@code arr} is * {@code i}. *

    Values in {@code arr} outside of the range [0, size) are ignored. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RaggedBincount.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java index 1e654d1665b..720919e6873 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java @@ -37,8 +37,6 @@ /** * Performs sparse-output bin counting for a ragged tensor input. * Counts the number of times each value occurs in the input. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = RaggedCountSparseOutput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java index 1d5cc361a5f..3b356804b4f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java @@ -39,10 +39,6 @@ /** * Generates a feature cross from a list of tensors, and returns it as a * RaggedTensor. See {@code tf.ragged.cross} for more details. - * - * @param data type for {@code output_values} output - * - * @param data type for {@code output_row_splits} output */ @OpMetadata( opType = RaggedCross.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRows.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRows.java index 5f1b9cf66ec..d8414fd1ae3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRows.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRows.java @@ -37,8 +37,6 @@ /** * The RaggedFillEmptyRows operation - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = RaggedFillEmptyRows.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRowsGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRowsGrad.java index 9ea15d1320a..314e4a689af 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRowsGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRowsGrad.java @@ -36,8 +36,6 @@ /** * The RaggedFillEmptyRowsGrad operation - * - * @param data type for {@code d_values} output */ @OpMetadata( opType = RaggedFillEmptyRowsGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedGather.java index 059c102f6ed..3c71b9987c4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedGather.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedGather.java @@ -56,10 +56,6 @@ * *

    (Note: This c++ op is used to implement the higher-level python * {@code tf.ragged.gather} op, which also supports ragged indices.) - * - * @param data type for {@code output_nested_splits} output - * - * @param data type for {@code output_dense_values} output */ @OpMetadata( opType = RaggedGather.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java index 52d8d2d66b9..39a6487398e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java @@ -50,10 +50,6 @@ *

    The input tensors {@code starts}, {@code limits}, and {@code deltas} may be scalars or vectors. * The vector inputs must all have the same size. Scalar inputs are broadcast * to match the size of the vector inputs. - * - * @param data type for {@code rt_nested_splits} output - * - * @param data type for {@code rt_dense_values} output */ @OpMetadata( opType = RaggedRange.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java index 9223acdcd39..5e9e6cae9a7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java @@ -50,10 +50,6 @@ * values of the decoded {@code RaggedTensor}. If {@code input_ragged_rank} is -1, then it is * inferred as {@code output_ragged_rank} - {@code rank(encoded_ragged)}. See * {@code RaggedTensorToVariant} for the corresponding encoding logic. - * - * @param data type for {@code output_nested_splits} output - * - * @param data type for {@code output_dense_values} output */ @OpMetadata( opType = RaggedTensorFromVariant.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToSparse.java index 510cab39924..e765d995332 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToSparse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToSparse.java @@ -41,8 +41,6 @@ * input=ragged.from_nested_row_splits(rt_dense_values, rt_nested_splits) * output=SparseTensor(indices=sparse_indices, values=sparse_values, * dense_shape=sparse_dense_shape) - * - * @param data type for {@code sparse_values} output */ @OpMetadata( opType = RaggedTensorToSparse.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToTensor.java index 127c85e9f72..1bbb93a9327 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToTensor.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToTensor.java @@ -54,8 +54,6 @@ *

  • "FIRST_DIM_SIZE": if value_rowids is used for the first dimension, then it * is preceded by "FIRST_DIM_SIZE".
    • * - * - * @param data type for {@code result} output */ @OpMetadata( opType = RaggedTensorToTensor.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariantGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariantGradient.java index d8e57336a0e..ca254cd1cf5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariantGradient.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariantGradient.java @@ -42,8 +42,6 @@ * op, given the variant-encoded ragged gradients of the outputs, along with * the outer row-splits and the shape of the dense-values that were provided as * inputs to the RaggedTensorToVariant op. - * - * @param data type for {@code dense_values_grad} output */ @OpMetadata( opType = RaggedTensorToVariantGradient.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java index 6412651e6ac..a213609fca6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java @@ -38,8 +38,6 @@ /** * Draws samples from a multinomial distribution. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Multinomial.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java index 6008cd03718..83f81ee6c51 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java @@ -38,8 +38,6 @@ /** * Non-deterministically generates some integers. * This op may use some OS-provided source of non-determinism (e.g. an RNG), so each execution will give different results. - * - * @param data type for {@code output} output */ @OpMetadata( opType = NonDeterministicInts.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java index e2a12f2a3c9..4bc87b4da51 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java @@ -37,8 +37,6 @@ * Outputs random values from a normal distribution. The parameters may each be a * scalar which applies to the entire output, or a vector of length shape[0] which * stores the parameters for each batch. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ParameterizedTruncatedNormal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java index 5558b534e66..cc1a0ab9ba6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java @@ -38,8 +38,6 @@ * This op uses the algorithm by Marsaglia et al. to acquire samples via * transformation-rejection from pairs of uniform and normal random variables. * See http://dl.acm.org/citation.cfm?id=358414 - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomGamma.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java index 7baaab08ee4..4ab62242717 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java @@ -35,8 +35,6 @@ /** * Computes the derivative of a Gamma random sample w.r.t. {@code alpha}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomGammaGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java index d26081bd288..3e5fc40fc2f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java @@ -45,8 +45,6 @@ * random variables. * See Donald E. Knuth (1969). Seminumerical Algorithms. The Art of Computer * Programming, Volume 2. Addison Wesley - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomPoisson.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomShuffle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomShuffle.java index 8c52e218fc8..517900e7df1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomShuffle.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomShuffle.java @@ -43,8 +43,6 @@ * [3, 4], ==> [1, 2], * [5, 6]] [3, 4]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomShuffle.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java index 3addc74b9bb..322fe10883c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java @@ -37,8 +37,6 @@ /** * Outputs random values from a normal distribution. * The generated values will have mean 0 and standard deviation 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomStandardNormal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java index 74487b121aa..5940994392c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java @@ -38,8 +38,6 @@ * Outputs random values from a uniform distribution. * The generated values follow a uniform distribution in the range {@code [0, 1)}. The * lower bound 0 is included in the range, while the upper bound 1 is excluded. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomUniform.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java index 243fd44c671..6eba6a6c8b8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java @@ -41,8 +41,6 @@ *

    The random integers are slightly biased unless {@code maxval - minval} is an exact * power of two. The bias is small for values of {@code maxval - minval} significantly * smaller than the range of the output (either {@code 2^32} or {@code 2^64}). - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomUniformInt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java index fc03e7feddb..67bc6bf1167 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java @@ -38,8 +38,6 @@ /** * The StatefulRandomBinomial operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatefulRandomBinomial.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java index 8330a9f4b49..ff905308114 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java @@ -39,8 +39,6 @@ /** * Outputs random values from a normal distribution. * The generated values will have mean 0 and standard deviation 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatefulStandardNormal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java index e623baabf5c..409dff36de6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java @@ -41,8 +41,6 @@ * The generated values follow a normal distribution with mean 0 and standard * deviation 1, except that values whose magnitude is more than 2 standard * deviations from the mean are dropped and re-picked. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatefulTruncatedNormal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java index a0e85b0458f..65f86463b06 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java @@ -40,8 +40,6 @@ * Outputs random values from a uniform distribution. * The generated values follow a uniform distribution in the range {@code [0, 1)}. The * lower bound 0 is included in the range, while the upper bound 1 is excluded. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatefulUniform.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java index a43b26418ea..80f425ff575 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java @@ -38,8 +38,6 @@ /** * Outputs random integers from a uniform distribution. * The generated values are uniform integers covering the whole range of {@code dtype}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatefulUniformFullInt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformInt.java index 154f3bd2841..d2854aea992 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformInt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformInt.java @@ -42,8 +42,6 @@ *

    The random integers are slightly biased unless {@code maxval - minval} is an exact * power of two. The bias is small for values of {@code maxval - minval} significantly * smaller than the range of the output (either {@code 2^32} or {@code 2^64}). - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatefulUniformInt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java index 1c306047fd5..45a902b2da8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java @@ -38,8 +38,6 @@ /** * Draws samples from a multinomial distribution. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessMultinomial.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java index b10e961aab2..64f85682701 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java @@ -35,8 +35,6 @@ /** * The StatelessParameterizedTruncatedNormal operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessParameterizedTruncatedNormal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java index 71a3cb24cf9..ebd295592eb 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java @@ -39,8 +39,6 @@ * Outputs deterministic pseudorandom random numbers from a binomial distribution. * Outputs random values from a binomial distribution. *

    The outputs are a deterministic function of {@code shape}, {@code seed}, {@code counts}, and {@code probs}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomBinomial.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java index e57dfcf90f6..69bd0d03ddd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java @@ -39,8 +39,6 @@ * Outputs deterministic pseudorandom random numbers from a gamma distribution. * Outputs random values from a gamma distribution. *

    The outputs are a deterministic function of the inputs. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomGamma.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java index 7081e980beb..bf0fa718d0e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java @@ -39,8 +39,6 @@ * Outputs deterministic pseudorandom values from a normal distribution. * The generated values will have mean 0 and standard deviation 1. *

    The outputs are a deterministic function of {@code shape} and {@code seed}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomNormal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormalV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormalV2.java index b1e9dcb4439..ef4f9aafee6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormalV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormalV2.java @@ -41,8 +41,6 @@ * Outputs deterministic pseudorandom values from a normal distribution. * The generated values will have mean 0 and standard deviation 1. *

    The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomNormalV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java index 3a55731c32d..c617e49f652 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java @@ -38,8 +38,6 @@ * Outputs deterministic pseudorandom random numbers from a Poisson distribution. * Outputs random values from a Poisson distribution. *

    The outputs are a deterministic function of {@code shape}, {@code seed}, and {@code lam}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomPoisson.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java index 6e18ceffb6f..86c24f1e171 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java @@ -40,8 +40,6 @@ * The generated values follow a uniform distribution in the range {@code [0, 1)}. The * lower bound 0 is included in the range, while the upper bound 1 is excluded. *

    The outputs are a deterministic function of {@code shape} and {@code seed}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomUniform.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java index ef2bf5e7884..41e703d9ddf 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java @@ -38,8 +38,6 @@ * Outputs deterministic pseudorandom random integers from a uniform distribution. * The generated values are uniform integers covering the whole range of {@code dtype}. *

    The outputs are a deterministic function of {@code shape} and {@code seed}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomUniformFullInt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullIntV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullIntV2.java index 50fb67d6fe1..7a910d86feb 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullIntV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullIntV2.java @@ -40,8 +40,6 @@ * Outputs deterministic pseudorandom random integers from a uniform distribution. * The generated values are uniform integers covering the whole range of {@code dtype}. *

    The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomUniformFullIntV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java index 8bce8bc129e..5c792f75e51 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java @@ -37,8 +37,6 @@ * Outputs deterministic pseudorandom random integers from a uniform distribution. * The generated values follow a uniform distribution in the range {@code [minval, maxval)}. *

    The outputs are a deterministic function of {@code shape}, {@code seed}, {@code minval}, and {@code maxval}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomUniformInt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformIntV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformIntV2.java index aa3e3d0de83..ae538d14050 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformIntV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformIntV2.java @@ -39,8 +39,6 @@ * Outputs deterministic pseudorandom random integers from a uniform distribution. * The generated values follow a uniform distribution in the range {@code [minval, maxval)}. *

    The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter}, {@code alg}, {@code minval} and {@code maxval}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomUniformIntV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformV2.java index 8b0e106cb95..86bb5202639 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformV2.java @@ -42,8 +42,6 @@ * The generated values follow a uniform distribution in the range {@code [0, 1)}. The * lower bound 0 is included in the range, while the upper bound 1 is excluded. *

    The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomUniformV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java index 2ddedee0436..83c4ebdab9c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java @@ -41,8 +41,6 @@ * deviation 1, except that values whose magnitude is more than 2 standard * deviations from the mean are dropped and re-picked. *

    The outputs are a deterministic function of {@code shape} and {@code seed}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessTruncatedNormal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormalV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormalV2.java index 6505cd06561..ae8b00ae1df 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormalV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormalV2.java @@ -43,8 +43,6 @@ * deviation 1, except that values whose magnitude is more than 2 standard * deviations from the mean are dropped and re-picked. *

    The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessTruncatedNormalV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java index ee3e12c25e3..36fbe8a2a05 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java @@ -39,8 +39,6 @@ * The generated values follow a normal distribution with mean 0 and standard * deviation 1, except that values whose magnitude is more than 2 standard * deviations from the mean are dropped and re-picked. - * - * @param data type for {@code output} output */ @OpMetadata( opType = TruncatedNormal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/experimental/StatelessShuffle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/experimental/StatelessShuffle.java index 5100d0ef8c6..dc17294084b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/experimental/StatelessShuffle.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/experimental/StatelessShuffle.java @@ -45,8 +45,6 @@ * [5, 6]] [3, 4]] * *

    The outputs are a deterministic function of {@code value}, {@code key}, {@code counter} and {@code alg}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessShuffle.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft.java index 42ef1e6bdf9..220c72d1723 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft.java @@ -37,8 +37,6 @@ * Fast Fourier transform. * Computes the 1-dimensional discrete Fourier transform over the inner-most * dimension of {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Fft.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft2d.java index 118d2db63e0..4f78086027b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft2d.java @@ -37,8 +37,6 @@ * 2D fast Fourier transform. * Computes the 2-dimensional discrete Fourier transform over the inner-most * 2 dimensions of {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Fft2d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft3d.java index 6195de0eae8..7f5478e228a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft3d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft3d.java @@ -37,8 +37,6 @@ * 3D fast Fourier transform. * Computes the 3-dimensional discrete Fourier transform over the inner-most 3 * dimensions of {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Fft3d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/FftNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/FftNd.java index b7f4268150c..8f530229379 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/FftNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/FftNd.java @@ -44,8 +44,6 @@ * is not given, the default shape(input) is used. *

    Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. - * - * @param data type for {@code output} output */ @OpMetadata( opType = FftNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft.java index 3a313a6f23e..6b1f6fa6d8c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft.java @@ -37,8 +37,6 @@ * Inverse fast Fourier transform. * Computes the inverse 1-dimensional discrete Fourier transform over the * inner-most dimension of {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Ifft.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft2d.java index ad0902bf3a1..2c4c19b2ead 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft2d.java @@ -37,8 +37,6 @@ * Inverse 2D fast Fourier transform. * Computes the inverse 2-dimensional discrete Fourier transform over the * inner-most 2 dimensions of {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Ifft2d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft3d.java index 82251ed232c..efcb06fafcd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft3d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft3d.java @@ -37,8 +37,6 @@ * Inverse 3D fast Fourier transform. * Computes the inverse 3-dimensional discrete Fourier transform over the * inner-most 3 dimensions of {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Ifft3d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IfftNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IfftNd.java index 82855d2bab4..181e3756015 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IfftNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IfftNd.java @@ -44,8 +44,6 @@ * is not given, the default shape(input) is used. *

    Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. - * - * @param data type for {@code output} output */ @OpMetadata( opType = IfftNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java index ecf2703b6e8..50f6daef0a0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java @@ -50,8 +50,6 @@ *

    Along the axis {@code signal.Irfft} is computed on, if {@code fft_length / 2 + 1} is smaller * than the corresponding dimension of {@code input}, the dimension is cropped. If it is * larger, the dimension is padded with zeros. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Irfft.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java index 8a448fd2a52..01214bfec41 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java @@ -51,8 +51,6 @@ * {@code fft_length / 2 + 1} for the inner-most dimension) is smaller than the * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Irfft2d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java index a336791cb83..c83389668b4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java @@ -51,8 +51,6 @@ * {@code fft_length / 2 + 1} for the inner-most dimension) is smaller than the * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Irfft3d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IrfftNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IrfftNd.java index 93006aea156..5e83c9f4dc3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IrfftNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IrfftNd.java @@ -48,8 +48,6 @@ * is not given, the default shape(input) is used. *

    Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. - * - * @param data type for {@code output} output */ @OpMetadata( opType = IrfftNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java index f5c14f6eec7..c4d7b74e39a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java @@ -46,8 +46,6 @@ *

    Along the axis {@code signal.Rfft} is computed on, if {@code fft_length} is smaller than the * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Rfft.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java index 6587b7378c1..314d16f4eec 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java @@ -47,8 +47,6 @@ *

    Along each axis {@code signal.Rfft2d} is computed on, if {@code fft_length} is smaller than the * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Rfft2d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java index 35746c0f93b..282c4b7386e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java @@ -47,8 +47,6 @@ *

    Along each axis {@code signal.Rfft3d} is computed on, if {@code fft_length} is smaller than the * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Rfft3d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/RfftNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/RfftNd.java index 85e48957ee4..17bf1368600 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/RfftNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/RfftNd.java @@ -47,8 +47,6 @@ * is not given, the default shape(input) is used. *

    Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RfftNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/ConvertToListOfSparseCoreCooTensors.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/ConvertToListOfSparseCoreCooTensors.java new file mode 100644 index 00000000000..7ed71c4c316 --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/ConvertToListOfSparseCoreCooTensors.java @@ -0,0 +1,209 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.sparse; + +import java.util.Arrays; +import java.util.List; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.op.annotation.Operator; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TInt32; + +/** + * The ConvertToListOfSparseCoreCooTensors operation + */ +@OpMetadata( + opType = ConvertToListOfSparseCoreCooTensors.OP_NAME, + inputsClass = ConvertToListOfSparseCoreCooTensors.Inputs.class +) +@Operator( + group = "sparse" +) +public final class ConvertToListOfSparseCoreCooTensors extends RawOp { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "ConvertToListOfSparseCoreCooTensors"; + + private List> rowIdsList; + + private List> colIdsList; + + private List> gainsList; + + @SuppressWarnings("unchecked") + public ConvertToListOfSparseCoreCooTensors(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + int rowIdsListLength = operation.outputListLength("row_ids_list"); + rowIdsList = Arrays.asList((Output[]) operation.outputList(outputIdx, rowIdsListLength)); + outputIdx += rowIdsListLength; + int colIdsListLength = operation.outputListLength("col_ids_list"); + colIdsList = Arrays.asList((Output[]) operation.outputList(outputIdx, colIdsListLength)); + outputIdx += colIdsListLength; + int gainsListLength = operation.outputListLength("gains_list"); + gainsList = Arrays.asList((Output[]) operation.outputList(outputIdx, gainsListLength)); + outputIdx += gainsListLength; + } + + /** + * Factory method to create a class wrapping a new ConvertToListOfSparseCoreCooTensors operation. + * + * @param scope current scope + * @param indicesOrRowSplits The indicesOrRowSplits value + * @param values The values value + * @param weights The weights value + * @param sampleCount The value of the sampleCount attribute + * @param numScPerChip The value of the numScPerChip attribute + * @param rowOffset The value of the rowOffset attribute + * @param colOffset The value of the colOffset attribute + * @param colShift The value of the colShift attribute + * @param numScShards The value of the numScShards attribute + * @param stackedTableSampleCount The value of the stackedTableSampleCount attribute + * @param combiner The value of the combiner attribute + * @return a new instance of ConvertToListOfSparseCoreCooTensors + */ + @Endpoint( + describeByClass = true + ) + public static ConvertToListOfSparseCoreCooTensors create(Scope scope, + Operand indicesOrRowSplits, Operand values, Operand weights, + Long sampleCount, Long numScPerChip, Long rowOffset, Long colOffset, Long colShift, + Long numScShards, Long stackedTableSampleCount, String combiner) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "ConvertToListOfSparseCoreCooTensors"); + opBuilder.addInput(indicesOrRowSplits.asOutput()); + opBuilder.addInput(values.asOutput()); + opBuilder.addInput(weights.asOutput()); + opBuilder.setAttr("sample_count", sampleCount); + opBuilder.setAttr("num_sc_per_chip", numScPerChip); + opBuilder.setAttr("row_offset", rowOffset); + opBuilder.setAttr("col_offset", colOffset); + opBuilder.setAttr("col_shift", colShift); + opBuilder.setAttr("num_sc_shards", numScShards); + opBuilder.setAttr("stacked_table_sample_count", stackedTableSampleCount); + opBuilder.setAttr("combiner", combiner); + return new ConvertToListOfSparseCoreCooTensors(opBuilder.build()); + } + + /** + * Gets rowIdsList. + * + * @return rowIdsList. + */ + public List> rowIdsList() { + return rowIdsList; + } + + /** + * Gets colIdsList. + * + * @return colIdsList. + */ + public List> colIdsList() { + return colIdsList; + } + + /** + * Gets gainsList. + * + * @return gainsList. + */ + public List> gainsList() { + return gainsList; + } + + @OpInputsMetadata( + outputsClass = ConvertToListOfSparseCoreCooTensors.class + ) + public static class Inputs extends RawOpInputs { + /** + * The indicesOrRowSplits input + */ + public final Operand indicesOrRowSplits; + + /** + * The values input + */ + public final Operand values; + + /** + * The weights input + */ + public final Operand weights; + + /** + * The sampleCount attribute + */ + public final long sampleCount; + + /** + * The rowOffset attribute + */ + public final long rowOffset; + + /** + * The colOffset attribute + */ + public final long colOffset; + + /** + * The colShift attribute + */ + public final long colShift; + + /** + * The numScShards attribute + */ + public final long numScShards; + + /** + * The stackedTableSampleCount attribute + */ + public final long stackedTableSampleCount; + + /** + * The combiner attribute + */ + public final String combiner; + + public Inputs(GraphOperation op) { + super(new ConvertToListOfSparseCoreCooTensors(op), op, Arrays.asList("sample_count", "row_offset", "col_offset", "col_shift", "num_sc_shards", "stacked_table_sample_count", "combiner")); + int inputIndex = 0; + indicesOrRowSplits = (Operand) op.input(inputIndex++); + values = (Operand) op.input(inputIndex++); + weights = (Operand) op.input(inputIndex++); + sampleCount = op.attributes().getAttrInt("sample_count"); + rowOffset = op.attributes().getAttrInt("row_offset"); + colOffset = op.attributes().getAttrInt("col_offset"); + colShift = op.attributes().getAttrInt("col_shift"); + numScShards = op.attributes().getAttrInt("num_sc_shards"); + stackedTableSampleCount = op.attributes().getAttrInt("stacked_table_sample_count"); + combiner = op.attributes().getAttrString("combiner"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/ConvertToSparseCoreCsrWrappedCooTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/ConvertToSparseCoreCsrWrappedCooTensor.java new file mode 100644 index 00000000000..6590a927699 --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/ConvertToSparseCoreCsrWrappedCooTensor.java @@ -0,0 +1,283 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.sparse; + +import java.util.Arrays; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.op.Operands; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.op.annotation.Operator; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TInt32; +import org.tensorflow.types.TInt64; + +/** + * The ConvertToSparseCoreCsrWrappedCooTensor operation + */ +@OpMetadata( + opType = ConvertToSparseCoreCsrWrappedCooTensor.OP_NAME, + inputsClass = ConvertToSparseCoreCsrWrappedCooTensor.Inputs.class +) +@Operator( + group = "sparse" +) +public final class ConvertToSparseCoreCsrWrappedCooTensor extends RawOp { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "ConvertToSparseCoreCsrWrappedCooTensor"; + + private Output rowPointers; + + private Output sortedSampleIds; + + private Output sortedTokenIds; + + private Output sortedGains; + + private Output rowPointersUnpaddedSize; + + private Output idsUnpaddedSize; + + private Output numMinibatchesPerSc; + + public ConvertToSparseCoreCsrWrappedCooTensor(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + rowPointers = operation.output(outputIdx++); + sortedSampleIds = operation.output(outputIdx++); + sortedTokenIds = operation.output(outputIdx++); + sortedGains = operation.output(outputIdx++); + rowPointersUnpaddedSize = operation.output(outputIdx++); + idsUnpaddedSize = operation.output(outputIdx++); + numMinibatchesPerSc = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new ConvertToSparseCoreCsrWrappedCooTensor operation. + * + * @param scope current scope + * @param sortedRowIdsList The sortedRowIdsList value + * @param sortedColIdsList The sortedColIdsList value + * @param sortedGainsList The sortedGainsList value + * @param idCountsList The idCountsList value + * @param splits The splits value + * @param sampleCountPerSc The value of the sampleCountPerSc attribute + * @param numReplica The value of the numReplica attribute + * @param maxMinibatchesPerSc The value of the maxMinibatchesPerSc attribute + * @param maxIdsPerChipPerSample The value of the maxIdsPerChipPerSample attribute + * @param tableVocabSize The value of the tableVocabSize attribute + * @param featureWidth The value of the featureWidth attribute + * @param tableName The value of the tableName attribute + * @param allowIdDropping The value of the allowIdDropping attribute + * @return a new instance of ConvertToSparseCoreCsrWrappedCooTensor + */ + @Endpoint( + describeByClass = true + ) + public static ConvertToSparseCoreCsrWrappedCooTensor create(Scope scope, + Iterable> sortedRowIdsList, Iterable> sortedColIdsList, + Iterable> sortedGainsList, Iterable> idCountsList, + Operand splits, Long sampleCountPerSc, Long numReplica, Long maxMinibatchesPerSc, + Long maxIdsPerChipPerSample, Long tableVocabSize, Long featureWidth, String tableName, + Boolean allowIdDropping) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "ConvertToSparseCoreCsrWrappedCooTensor"); + opBuilder.addInputList(Operands.asOutputs(sortedRowIdsList)); + opBuilder.addInputList(Operands.asOutputs(sortedColIdsList)); + opBuilder.addInputList(Operands.asOutputs(sortedGainsList)); + opBuilder.addInputList(Operands.asOutputs(idCountsList)); + opBuilder.addInput(splits.asOutput()); + opBuilder.setAttr("sample_count_per_sc", sampleCountPerSc); + opBuilder.setAttr("num_replica", numReplica); + opBuilder.setAttr("max_minibatches_per_sc", maxMinibatchesPerSc); + opBuilder.setAttr("max_ids_per_chip_per_sample", maxIdsPerChipPerSample); + opBuilder.setAttr("table_vocab_size", tableVocabSize); + opBuilder.setAttr("feature_width", featureWidth); + opBuilder.setAttr("table_name", tableName); + opBuilder.setAttr("allow_id_dropping", allowIdDropping); + return new ConvertToSparseCoreCsrWrappedCooTensor(opBuilder.build()); + } + + /** + * Gets rowPointers. + * + * @return rowPointers. + */ + public Output rowPointers() { + return rowPointers; + } + + /** + * Gets sortedSampleIds. + * + * @return sortedSampleIds. + */ + public Output sortedSampleIds() { + return sortedSampleIds; + } + + /** + * Gets sortedTokenIds. + * + * @return sortedTokenIds. + */ + public Output sortedTokenIds() { + return sortedTokenIds; + } + + /** + * Gets sortedGains. + * + * @return sortedGains. + */ + public Output sortedGains() { + return sortedGains; + } + + /** + * Gets rowPointersUnpaddedSize. + * + * @return rowPointersUnpaddedSize. + */ + public Output rowPointersUnpaddedSize() { + return rowPointersUnpaddedSize; + } + + /** + * Gets idsUnpaddedSize. + * + * @return idsUnpaddedSize. + */ + public Output idsUnpaddedSize() { + return idsUnpaddedSize; + } + + /** + * Gets numMinibatchesPerSc. + * + * @return numMinibatchesPerSc. + */ + public Output numMinibatchesPerSc() { + return numMinibatchesPerSc; + } + + @OpInputsMetadata( + outputsClass = ConvertToSparseCoreCsrWrappedCooTensor.class + ) + public static class Inputs extends RawOpInputs { + /** + * The sortedRowIdsList input + */ + public final Iterable> sortedRowIdsList; + + /** + * The sortedColIdsList input + */ + public final Iterable> sortedColIdsList; + + /** + * The sortedGainsList input + */ + public final Iterable> sortedGainsList; + + /** + * The idCountsList input + */ + public final Iterable> idCountsList; + + /** + * The splits input + */ + public final Operand splits; + + /** + * The sampleCountPerSc attribute + */ + public final long sampleCountPerSc; + + /** + * The numReplica attribute + */ + public final long numReplica; + + /** + * The maxMinibatchesPerSc attribute + */ + public final long maxMinibatchesPerSc; + + /** + * The maxIdsPerChipPerSample attribute + */ + public final long maxIdsPerChipPerSample; + + /** + * The tableVocabSize attribute + */ + public final long tableVocabSize; + + /** + * The featureWidth attribute + */ + public final long featureWidth; + + /** + * The tableName attribute + */ + public final String tableName; + + /** + * The allowIdDropping attribute + */ + public final boolean allowIdDropping; + + public Inputs(GraphOperation op) { + super(new ConvertToSparseCoreCsrWrappedCooTensor(op), op, Arrays.asList("sample_count_per_sc", "num_replica", "max_minibatches_per_sc", "max_ids_per_chip_per_sample", "table_vocab_size", "feature_width", "table_name", "allow_id_dropping")); + int inputIndex = 0; + int sortedRowIdsListLength = op.inputListLength("sorted_row_ids_list"); + sortedRowIdsList = Arrays.asList((Operand[]) op.inputList(inputIndex, sortedRowIdsListLength)); + inputIndex += sortedRowIdsListLength; + int sortedColIdsListLength = op.inputListLength("sorted_col_ids_list"); + sortedColIdsList = Arrays.asList((Operand[]) op.inputList(inputIndex, sortedColIdsListLength)); + inputIndex += sortedColIdsListLength; + int sortedGainsListLength = op.inputListLength("sorted_gains_list"); + sortedGainsList = Arrays.asList((Operand[]) op.inputList(inputIndex, sortedGainsListLength)); + inputIndex += sortedGainsListLength; + int idCountsListLength = op.inputListLength("id_counts_list"); + idCountsList = Arrays.asList((Operand[]) op.inputList(inputIndex, idCountsListLength)); + inputIndex += idCountsListLength; + splits = (Operand) op.input(inputIndex++); + sampleCountPerSc = op.attributes().getAttrInt("sample_count_per_sc"); + numReplica = op.attributes().getAttrInt("num_replica"); + maxMinibatchesPerSc = op.attributes().getAttrInt("max_minibatches_per_sc"); + maxIdsPerChipPerSample = op.attributes().getAttrInt("max_ids_per_chip_per_sample"); + tableVocabSize = op.attributes().getAttrInt("table_vocab_size"); + featureWidth = op.attributes().getAttrInt("feature_width"); + tableName = op.attributes().getAttrString("table_name"); + allowIdDropping = op.attributes().getAttrBool("allow_id_dropping"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java index 49d78c0517c..5cf78a2a0a6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java @@ -37,8 +37,6 @@ /** * Performs sparse-output bin counting for a tf.tensor input. * Counts the number of times each value occurs in the input. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = DenseCountSparseOutput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToDenseSetOperation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToDenseSetOperation.java index 2ea6aa671d1..546adba1a9d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToDenseSetOperation.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToDenseSetOperation.java @@ -42,8 +42,6 @@ * has rank {@code n} and the same 1st {@code n-1} dimensions as {@code set1} and {@code set2}. The {@code nth} * dimension contains the result of {@code set_operation} applied to the corresponding * {@code [0...n-1]} dimension of {@code set}. - * - * @param data type for {@code result_values} output */ @OpMetadata( opType = DenseToDenseSetOperation.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToSparseSetOperation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToSparseSetOperation.java index bb75893bfd4..1b8cbcaee50 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToSparseSetOperation.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToSparseSetOperation.java @@ -48,8 +48,6 @@ * has rank {@code n} and the same 1st {@code n-1} dimensions as {@code set1} and {@code set2}. The {@code nth} * dimension contains the result of {@code set_operation} applied to the corresponding * {@code [0...n-1]} dimension of {@code set}. - * - * @param data type for {@code result_values} output */ @OpMetadata( opType = DenseToSparseSetOperation.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java index 697249eca81..ba0c51f9a1e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java @@ -76,8 +76,6 @@ * values = [1, 2, 3, 4, 5] * shape = [2 50] * - * - * @param data type for {@code sparse_values} output */ @OpMetadata( opType = DeserializeSparse.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/GetStatsFromListOfSparseCoreCooTensors.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/GetStatsFromListOfSparseCoreCooTensors.java new file mode 100644 index 00000000000..51f5c33d66b --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/GetStatsFromListOfSparseCoreCooTensors.java @@ -0,0 +1,204 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.sparse; + +import java.util.Arrays; +import java.util.List; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.op.Operands; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.op.annotation.Operator; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TInt32; + +/** + * The GetStatsFromListOfSparseCoreCooTensors operation + */ +@OpMetadata( + opType = GetStatsFromListOfSparseCoreCooTensors.OP_NAME, + inputsClass = GetStatsFromListOfSparseCoreCooTensors.Inputs.class +) +@Operator( + group = "sparse" +) +public final class GetStatsFromListOfSparseCoreCooTensors extends RawOp { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "GetStatsFromListOfSparseCoreCooTensors"; + + private Output maxIdsPerSparseCore; + + private Output maxUniqueIdsPerSparseCore; + + public GetStatsFromListOfSparseCoreCooTensors(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + maxIdsPerSparseCore = operation.output(outputIdx++); + maxUniqueIdsPerSparseCore = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new GetStatsFromListOfSparseCoreCooTensors operation. + * + * @param scope current scope + * @param rowIdsList The rowIdsList value + * @param colIdsList The colIdsList value + * @param gainsList The gainsList value + * @param sampleCountList The value of the sampleCountList attribute + * @param colOffsetList The value of the colOffsetList attribute + * @param numReplica The value of the numReplica attribute + * @param tableVocabSize The value of the tableVocabSize attribute + * @param featureWidth The value of the featureWidth attribute + * @param numScPerChip The value of the numScPerChip attribute + * @param tableName The value of the tableName attribute + * @return a new instance of GetStatsFromListOfSparseCoreCooTensors + */ + @Endpoint( + describeByClass = true + ) + public static GetStatsFromListOfSparseCoreCooTensors create(Scope scope, + Iterable> rowIdsList, Iterable> colIdsList, + Iterable> gainsList, List sampleCountList, List colOffsetList, + Long numReplica, Long tableVocabSize, Long featureWidth, Long numScPerChip, + String tableName) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "GetStatsFromListOfSparseCoreCooTensors"); + opBuilder.addInputList(Operands.asOutputs(rowIdsList)); + opBuilder.addInputList(Operands.asOutputs(colIdsList)); + opBuilder.addInputList(Operands.asOutputs(gainsList)); + long[] sampleCountListArray = new long[sampleCountList.size()]; + for (int i = 0 ; i < sampleCountListArray.length ; i++) { + sampleCountListArray[i] = sampleCountList.get(i); + } + opBuilder.setAttr("sample_count_list", sampleCountListArray); + long[] colOffsetListArray = new long[colOffsetList.size()]; + for (int i = 0 ; i < colOffsetListArray.length ; i++) { + colOffsetListArray[i] = colOffsetList.get(i); + } + opBuilder.setAttr("col_offset_list", colOffsetListArray); + opBuilder.setAttr("num_replica", numReplica); + opBuilder.setAttr("table_vocab_size", tableVocabSize); + opBuilder.setAttr("feature_width", featureWidth); + opBuilder.setAttr("num_sc_per_chip", numScPerChip); + opBuilder.setAttr("table_name", tableName); + return new GetStatsFromListOfSparseCoreCooTensors(opBuilder.build()); + } + + /** + * Gets maxIdsPerSparseCore. + * + * @return maxIdsPerSparseCore. + */ + public Output maxIdsPerSparseCore() { + return maxIdsPerSparseCore; + } + + /** + * Gets maxUniqueIdsPerSparseCore. + * + * @return maxUniqueIdsPerSparseCore. + */ + public Output maxUniqueIdsPerSparseCore() { + return maxUniqueIdsPerSparseCore; + } + + @OpInputsMetadata( + outputsClass = GetStatsFromListOfSparseCoreCooTensors.class + ) + public static class Inputs extends RawOpInputs { + /** + * The rowIdsList input + */ + public final Iterable> rowIdsList; + + /** + * The colIdsList input + */ + public final Iterable> colIdsList; + + /** + * The gainsList input + */ + public final Iterable> gainsList; + + /** + * The sampleCountList attribute + */ + public final long[] sampleCountList; + + /** + * The colOffsetList attribute + */ + public final long[] colOffsetList; + + /** + * The numReplica attribute + */ + public final long numReplica; + + /** + * The tableVocabSize attribute + */ + public final long tableVocabSize; + + /** + * The featureWidth attribute + */ + public final long featureWidth; + + /** + * The numScPerChip attribute + */ + public final long numScPerChip; + + /** + * The tableName attribute + */ + public final String tableName; + + public Inputs(GraphOperation op) { + super(new GetStatsFromListOfSparseCoreCooTensors(op), op, Arrays.asList("sample_count_list", "col_offset_list", "num_replica", "table_vocab_size", "feature_width", "num_sc_per_chip", "table_name")); + int inputIndex = 0; + int rowIdsListLength = op.inputListLength("row_ids_list"); + rowIdsList = Arrays.asList((Operand[]) op.inputList(inputIndex, rowIdsListLength)); + inputIndex += rowIdsListLength; + int colIdsListLength = op.inputListLength("col_ids_list"); + colIdsList = Arrays.asList((Operand[]) op.inputList(inputIndex, colIdsListLength)); + inputIndex += colIdsListLength; + int gainsListLength = op.inputListLength("gains_list"); + gainsList = Arrays.asList((Operand[]) op.inputList(inputIndex, gainsListLength)); + inputIndex += gainsListLength; + sampleCountList = op.attributes().getAttrIntList("sample_count_list"); + colOffsetList = op.attributes().getAttrIntList("col_offset_list"); + numReplica = op.attributes().getAttrInt("num_replica"); + tableVocabSize = op.attributes().getAttrInt("table_vocab_size"); + featureWidth = op.attributes().getAttrInt("feature_width"); + numScPerChip = op.attributes().getAttrInt("num_sc_per_chip"); + tableName = op.attributes().getAttrString("table_name"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SortListOfSparseCoreCooTensors.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SortListOfSparseCoreCooTensors.java new file mode 100644 index 00000000000..fb26033cfd2 --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SortListOfSparseCoreCooTensors.java @@ -0,0 +1,240 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.sparse; + +import java.util.Arrays; +import java.util.List; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.op.Operands; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TInt32; + +/** + * The SortListOfSparseCoreCooTensors operation + */ +@OpMetadata( + opType = SortListOfSparseCoreCooTensors.OP_NAME, + inputsClass = SortListOfSparseCoreCooTensors.Inputs.class +) +public final class SortListOfSparseCoreCooTensors extends RawOp { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "SortListOfSparseCoreCooTensors"; + + private Output sortedRowIds; + + private Output sortedColIds; + + private Output sortedGains; + + private Output idCounts; + + public SortListOfSparseCoreCooTensors(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + sortedRowIds = operation.output(outputIdx++); + sortedColIds = operation.output(outputIdx++); + sortedGains = operation.output(outputIdx++); + idCounts = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new SortListOfSparseCoreCooTensors operation. + * + * @param scope current scope + * @param rowIdsList The rowIdsList value + * @param colIdsList The colIdsList value + * @param gainsList The gainsList value + * @param sampleCountList The value of the sampleCountList attribute + * @param colOffsetList The value of the colOffsetList attribute + * @param numReplica The value of the numReplica attribute + * @param tableVocabSize The value of the tableVocabSize attribute + * @param featureWidth The value of the featureWidth attribute + * @param numScPerChip The value of the numScPerChip attribute + * @param maxIdsPerSparseCore The value of the maxIdsPerSparseCore attribute + * @param maxUniqueIdsPerSparseCore The value of the maxUniqueIdsPerSparseCore attribute + * @param tableName The value of the tableName attribute + * @return a new instance of SortListOfSparseCoreCooTensors + */ + @Endpoint( + describeByClass = true + ) + public static SortListOfSparseCoreCooTensors create(Scope scope, + Iterable> rowIdsList, Iterable> colIdsList, + Iterable> gainsList, List sampleCountList, List colOffsetList, + Long numReplica, Long tableVocabSize, Long featureWidth, Long numScPerChip, + Long maxIdsPerSparseCore, Long maxUniqueIdsPerSparseCore, String tableName) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "SortListOfSparseCoreCooTensors"); + opBuilder.addInputList(Operands.asOutputs(rowIdsList)); + opBuilder.addInputList(Operands.asOutputs(colIdsList)); + opBuilder.addInputList(Operands.asOutputs(gainsList)); + long[] sampleCountListArray = new long[sampleCountList.size()]; + for (int i = 0 ; i < sampleCountListArray.length ; i++) { + sampleCountListArray[i] = sampleCountList.get(i); + } + opBuilder.setAttr("sample_count_list", sampleCountListArray); + long[] colOffsetListArray = new long[colOffsetList.size()]; + for (int i = 0 ; i < colOffsetListArray.length ; i++) { + colOffsetListArray[i] = colOffsetList.get(i); + } + opBuilder.setAttr("col_offset_list", colOffsetListArray); + opBuilder.setAttr("num_replica", numReplica); + opBuilder.setAttr("table_vocab_size", tableVocabSize); + opBuilder.setAttr("feature_width", featureWidth); + opBuilder.setAttr("num_sc_per_chip", numScPerChip); + opBuilder.setAttr("max_ids_per_sparse_core", maxIdsPerSparseCore); + opBuilder.setAttr("max_unique_ids_per_sparse_core", maxUniqueIdsPerSparseCore); + opBuilder.setAttr("table_name", tableName); + return new SortListOfSparseCoreCooTensors(opBuilder.build()); + } + + /** + * Gets sortedRowIds. + * + * @return sortedRowIds. + */ + public Output sortedRowIds() { + return sortedRowIds; + } + + /** + * Gets sortedColIds. + * + * @return sortedColIds. + */ + public Output sortedColIds() { + return sortedColIds; + } + + /** + * Gets sortedGains. + * + * @return sortedGains. + */ + public Output sortedGains() { + return sortedGains; + } + + /** + * Gets idCounts. + * + * @return idCounts. + */ + public Output idCounts() { + return idCounts; + } + + @OpInputsMetadata( + outputsClass = SortListOfSparseCoreCooTensors.class + ) + public static class Inputs extends RawOpInputs { + /** + * The rowIdsList input + */ + public final Iterable> rowIdsList; + + /** + * The colIdsList input + */ + public final Iterable> colIdsList; + + /** + * The gainsList input + */ + public final Iterable> gainsList; + + /** + * The sampleCountList attribute + */ + public final long[] sampleCountList; + + /** + * The colOffsetList attribute + */ + public final long[] colOffsetList; + + /** + * The numReplica attribute + */ + public final long numReplica; + + /** + * The tableVocabSize attribute + */ + public final long tableVocabSize; + + /** + * The featureWidth attribute + */ + public final long featureWidth; + + /** + * The numScPerChip attribute + */ + public final long numScPerChip; + + /** + * The maxIdsPerSparseCore attribute + */ + public final long maxIdsPerSparseCore; + + /** + * The maxUniqueIdsPerSparseCore attribute + */ + public final long maxUniqueIdsPerSparseCore; + + /** + * The tableName attribute + */ + public final String tableName; + + public Inputs(GraphOperation op) { + super(new SortListOfSparseCoreCooTensors(op), op, Arrays.asList("sample_count_list", "col_offset_list", "num_replica", "table_vocab_size", "feature_width", "num_sc_per_chip", "max_ids_per_sparse_core", "max_unique_ids_per_sparse_core", "table_name")); + int inputIndex = 0; + int rowIdsListLength = op.inputListLength("row_ids_list"); + rowIdsList = Arrays.asList((Operand[]) op.inputList(inputIndex, rowIdsListLength)); + inputIndex += rowIdsListLength; + int colIdsListLength = op.inputListLength("col_ids_list"); + colIdsList = Arrays.asList((Operand[]) op.inputList(inputIndex, colIdsListLength)); + inputIndex += colIdsListLength; + int gainsListLength = op.inputListLength("gains_list"); + gainsList = Arrays.asList((Operand[]) op.inputList(inputIndex, gainsListLength)); + inputIndex += gainsListLength; + sampleCountList = op.attributes().getAttrIntList("sample_count_list"); + colOffsetList = op.attributes().getAttrIntList("col_offset_list"); + numReplica = op.attributes().getAttrInt("num_replica"); + tableVocabSize = op.attributes().getAttrInt("table_vocab_size"); + featureWidth = op.attributes().getAttrInt("feature_width"); + numScPerChip = op.attributes().getAttrInt("num_sc_per_chip"); + maxIdsPerSparseCore = op.attributes().getAttrInt("max_ids_per_sparse_core"); + maxUniqueIdsPerSparseCore = op.attributes().getAttrInt("max_unique_ids_per_sparse_core"); + tableName = op.attributes().getAttrString("table_name"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java index aeb639d2d6e..fb8a868349d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java @@ -45,8 +45,6 @@ * average of the accumulated gradients. Also automatically increments * the recorded global_step in the accumulator by 1, and resets the * aggregate to 0. - * - * @param data type for {@code values} output */ @OpMetadata( opType = SparseAccumulatorTakeGradient.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAdd.java index 1591773a20c..88ef61b78a1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAdd.java @@ -48,8 +48,6 @@ * {@code thresh == 0} (default) means everything is kept and actual thresholding happens * only for a positive value. *

    In the following shapes, {@code nnz} is the count after taking {@code thresh} into account. - * - * @param data type for {@code sum_values} output */ @OpMetadata( opType = SparseAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAddGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAddGrad.java index 7d6c0923f4f..8a844c96eff 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAddGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAddGrad.java @@ -40,8 +40,6 @@ * as {@code SparseTensor} objects. This op takes in the upstream gradient w.r.t. * non-empty values of the sum, and outputs the gradients w.r.t. the non-empty * values of A and B. - * - * @param data type for {@code a_val_grad} output */ @OpMetadata( opType = SparseAddGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java index b7414e4ab54..9eca1295d45 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java @@ -42,8 +42,6 @@ * the value in {@code weights} at each index where the corresponding value in {@code arr} is * {@code i}. *

    Values in {@code arr} outside of the range [0, size) are ignored. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseBincount.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConcat.java index 6d53b3a723b..016f010647b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConcat.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConcat.java @@ -74,8 +74,6 @@ * [ a] concat [ d e ] = [ a d e ] * [b c ] [ ] [b c ] * - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseConcat.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java index c3983444bd3..4c59b4e2774 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java @@ -37,8 +37,6 @@ /** * Performs sparse-output bin counting for a sparse tensor input. * Counts the number of times each value occurs in the input. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseCountSparseOutput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseAdd.java index 261d292d3b0..10ac8721d98 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseAdd.java @@ -43,8 +43,6 @@ *

    By these rules, the result is a logical SparseTensor with exactly the same * indices and shape, but possibly with different non-zero values. The output of * this Op is the resultant non-zero values. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseDenseCwiseAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseDiv.java index e0b56d6827c..724997892b1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseDiv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseDiv.java @@ -38,8 +38,6 @@ * Component-wise divides a SparseTensor by a dense Tensor. * Limitation: this Op only broadcasts the dense side to the sparse side, but not * the other direction. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseDenseCwiseDiv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseMul.java index 3fb7a03c683..fe8386f0838 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseMul.java @@ -41,8 +41,6 @@ * contents of the dense tensor (even if it's +/-INF and that INF*0 == NaN). *

    Limitation: this Op only broadcasts the dense side to the sparse side, but not * the other direction. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseDenseCwiseMul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRows.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRows.java index 989fda03492..ef0d2f85afa 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRows.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRows.java @@ -71,8 +71,6 @@ * 

      * reverse_index_map[j] = out_j s.t. indices[j, :] == output_indices[out_j, :]
  *
    - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseFillEmptyRows.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRowsGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRowsGrad.java index 21d4e2f099f..3b1c80bb5b1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRowsGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRowsGrad.java @@ -43,8 +43,6 @@ *

    d_values[j] = grad_values[reverse_index_map[j]] * d_default_value = sum_{k : 0 .. N_full - 1} ( * grad_values[k] * 1{k not in reverse_index_map}) - * - * @param data type for {@code d_values} output */ @OpMetadata( opType = SparseFillEmptyRowsGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java index 1e48a53ea82..256695f0acd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java @@ -47,8 +47,6 @@ *

    If {@code reduction_axes} has no entries, all dimensions are reduced, and a tensor * with a single element is returned. Additionally, the axes can be negative, * which are interpreted according to the indexing rules in Python. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseReduceMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java index 8f337f0c19e..b0a65daea67 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java @@ -47,8 +47,6 @@ *

    If {@code reduction_axes} has no entries, all dimensions are reduced, and a tensor * with a single element is returned. Additionally, the axes can be negative, * which are interpreted according to the indexing rules in Python. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseReduceMaxSparse.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSum.java index 26e0ecbfc45..3589487bece 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSum.java @@ -47,8 +47,6 @@ *

    If {@code reduction_axes} has no entries, all dimensions are reduced, and a tensor * with a single element is returned. Additionally, the axes can be negative, * which are interpreted according to the indexing rules in Python. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseReduceSum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSumSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSumSparse.java index bb434694ccf..ef58eac0af1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSumSparse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSumSparse.java @@ -47,8 +47,6 @@ *

    If {@code reduction_axes} has no entries, all dimensions are reduced, and a tensor * with a single element is returned. Additionally, the axes can be negative, * which are interpreted according to the indexing rules in Python. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseReduceSumSparse.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReorder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReorder.java index 9e963285d77..4e2883435f9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReorder.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReorder.java @@ -42,8 +42,6 @@ *

    Reordering does not affect the shape of the SparseTensor. *

    If the tensor has rank {@code R} and {@code N} non-empty values, {@code input_indices} has * shape {@code [N, R]}, input_values has length {@code N}, and input_shape has length {@code R}. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseReorder.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java index c1899b2fbf6..4703ba10fca 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java @@ -38,8 +38,6 @@ * See {@code tf.sparse.segment_sum} for usage examples. *

    Like {@code SegmentMean}, but {@code segment_ids} can have rank less than {@code data}'s first * dimension, selecting a subset of dimension 0, specified by {@code indices}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseSegmentMean.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java index 50f29512a23..9da8038eee9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java @@ -39,10 +39,6 @@ * Returns tensor "output" with same shape as grad, except for dimension 0 whose * value is the number of unique indexes in "indices". Also returns vector * "sorted_unique_indices" containing the corresponding indexes from "indices". - * - * @param data type for {@code output} output - * - * @param data type for {@code sorted_unique_indices} output */ @OpMetadata( opType = SparseSegmentMeanGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java index d1c0e07c099..99cf33231a5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java @@ -40,8 +40,6 @@ *

    Read * the section on segmentation * for an explanation of segments. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseSegmentMeanWithNumSegments.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java index ee0dc4238fc..5e299d7d124 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java @@ -37,8 +37,6 @@ * Computes the sum along sparse segments of a tensor divided by the sqrt of N. * N is the size of the segment being reduced. *

    See {@code tf.sparse.segment_sum} for usage examples. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseSegmentSqrtN.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java index 075cbacbcfb..b458c7daff9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java @@ -39,10 +39,6 @@ * Returns tensor "output" with same shape as grad, except for dimension 0 whose * value is the number of unique indexes in "indices". Also returns vector * "sorted_unique_indices" containing the corresponding indexes from "indices". - * - * @param data type for {@code output} output - * - * @param data type for {@code sorted_unique_indices} output */ @OpMetadata( opType = SparseSegmentSqrtNGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java index 84ccc501312..146dd696d6e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java @@ -41,8 +41,6 @@ *

    Read * the section on segmentation * for an explanation of segments. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseSegmentSqrtNWithNumSegments.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java index cf2ce2c9851..2f28386d05c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java @@ -61,8 +61,6 @@ * # Which is equivalent to: * tf.segment_sum(c, tf.constant([0, 0, 1])) * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseSegmentSum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumGrad.java index 71b8f92448e..1372d6f7089 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumGrad.java @@ -39,10 +39,6 @@ * Returns tensor "output" with same shape as grad, except for dimension 0 whose * value is the number of unique indexes in "indices". Also returns vector * "sorted_unique_indices" containing the corresponding indexes from "indices". - * - * @param data type for {@code output} output - * - * @param data type for {@code sorted_unique_indices} output */ @OpMetadata( opType = SparseSegmentSumGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java index 4c44377244d..88b577afec1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java @@ -59,8 +59,6 @@ * # [-1 -2 -3 -4] * # [ 0 0 0 0]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseSegmentSumWithNumSegments.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSlice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSlice.java index 58c794dfb2f..a3718f1a7e0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSlice.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSlice.java @@ -52,8 +52,6 @@ * [ d e ] * [ ] * - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseSlice.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSliceGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSliceGrad.java index 4cfa41a7e45..969ef935dc7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSliceGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSliceGrad.java @@ -39,8 +39,6 @@ * This op takes in the upstream gradient w.r.t. non-empty values of * the sliced {@code SparseTensor}, and outputs the gradients w.r.t. * the non-empty values of input {@code SparseTensor}. - * - * @param data type for {@code val_grad} output */ @OpMetadata( opType = SparseSliceGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java index be61533da26..43cd85b5a9f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java @@ -48,8 +48,6 @@ * (3) Renormalizes the remaining elements. *

    Hence, the {@code SparseTensor} result has exactly the same non-zero indices and * shape. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseSoftmax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java index 22a1d407274..80b44623ca8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java @@ -37,8 +37,6 @@ /** * Returns the element-wise max of two SparseTensors. * Assumes the two SparseTensors have the same shape, i.e., no broadcasting. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseSparseMaximum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMinimum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMinimum.java index 8dd8978c627..ecbc022d09d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMinimum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMinimum.java @@ -37,8 +37,6 @@ /** * Returns the element-wise min of two SparseTensors. * Assumes the two SparseTensors have the same shape, i.e., no broadcasting. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseSparseMinimum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSplit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSplit.java index a09e9ff9d38..da66d34d134 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSplit.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSplit.java @@ -55,8 +55,6 @@ * [ d e ] * [ ] * - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseSplit.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseAdd.java index c153cf68776..7f73769030b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseAdd.java @@ -37,8 +37,6 @@ /** * Adds up a {@code SparseTensor} and a dense {@code Tensor}, producing a dense {@code Tensor}. * This Op does not require {@code a_indices} be sorted in standard lexicographic order. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseTensorDenseAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseMatMul.java index 346c9297596..0425354268c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseMatMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseMatMul.java @@ -45,8 +45,6 @@ * if adjoint_a == true: * A should be sorted in order of increasing dimension 1 (i.e., "column major" * order instead of "row major" order). - * - * @param data type for {@code product} output */ @OpMetadata( opType = SparseTensorDenseMatMul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToDense.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToDense.java index 95c8f189d48..448a7c4ec83 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToDense.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToDense.java @@ -52,8 +52,6 @@ *

    Indices should be sorted in lexicographic order, and indices must not * contain any repeats. If {@code validate_indices} is true, these properties * are checked during execution. - * - * @param data type for {@code dense} output */ @OpMetadata( opType = SparseToDense.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToSparseSetOperation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToSparseSetOperation.java index 8a71016a669..e658f88abb7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToSparseSetOperation.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToSparseSetOperation.java @@ -54,8 +54,6 @@ * has rank {@code n} and the same 1st {@code n-1} dimensions as {@code set1} and {@code set2}. The {@code nth} * dimension contains the result of {@code set_operation} applied to the corresponding * {@code [0...n-1]} dimension of {@code set}. - * - * @param data type for {@code result_values} output */ @OpMetadata( opType = SparseToSparseSetOperation.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java index e72ec904466..2c6293f402d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java @@ -77,8 +77,6 @@ * values = [1, 2, 3, 4, 5] * shape = [2 50] * - * - * @param data type for {@code sparse_values} output */ @OpMetadata( opType = TakeManySparseFromTensorsMap.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java index 6f5739989d0..c04fa6cd987 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java @@ -40,8 +40,6 @@ * This op accepts a ragged tensor with 1 ragged dimension containing only * strings and outputs a ragged tensor with 1 ragged dimension containing ngrams * of that string, joined along the innermost axis. - * - * @param data type for {@code ngrams_splits} output */ @OpMetadata( opType = StringNGrams.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java index e4564334bf1..74e4816ed43 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java @@ -50,8 +50,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = ToNumber.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java index bffb35e17e0..40624c66adf 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java @@ -52,8 +52,6 @@ *

  • {@code row_splits[i+1] - row_splits[i]} is the number of characters in the {@code i}th * string (in row-major order).
    • * - * - * @param data type for {@code row_splits} output */ @OpMetadata( opType = UnicodeDecode.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java index 690789b6843..5989e8e7106 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java @@ -56,8 +56,6 @@ *
  • {@code row_splits[i+1] - row_splits[i]} is the number of characters in the {@code i}th * string (in row-major order).
    • * - * - * @param data type for {@code row_splits} output */ @OpMetadata( opType = UnicodeDecodeWithOffsets.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/AllToAll.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/AllToAll.java index dfe6664886c..3bd1592cbc7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/AllToAll.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/AllToAll.java @@ -49,8 +49,6 @@ * split_count=2 *

    replica 0's output: {@code [[A], [C]]} * replica 1's output: {@code [[B], [D]]} - * - * @param data type for {@code output} output */ @OpMetadata( opType = AllToAll.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ComputeDedupDataSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ComputeDedupDataSize.java index 4305affd43e..6ff27567e92 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ComputeDedupDataSize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ComputeDedupDataSize.java @@ -29,7 +29,6 @@ import org.tensorflow.op.annotation.Endpoint; import org.tensorflow.op.annotation.OpInputsMetadata; import org.tensorflow.op.annotation.OpMetadata; -import org.tensorflow.op.annotation.Operator; import org.tensorflow.types.TInt32; /** @@ -42,14 +41,11 @@ opType = ComputeDedupDataSize.OP_NAME, inputsClass = ComputeDedupDataSize.Inputs.class ) -@Operator( - group = "tpu" -) public final class ComputeDedupDataSize extends RawOp implements Operand { /** * The name of this op, as known by TensorFlow core engine */ - public static final String OP_NAME = "ComputeDedupDataSize"; + public static final String OP_NAME = "ComputeDedupDataSizeV2"; private Output numElements; @@ -60,18 +56,25 @@ public ComputeDedupDataSize(Operation operation) { } /** - * Factory method to create a class wrapping a new ComputeDedupDataSize operation. + * Factory method to create a class wrapping a new ComputeDedupDataSizeV2 operation. * * @param scope current scope * @param config Serialized TPUEmbeddingConfiguration proto. + * @param embeddingPartitions Serialized EmbeddingPartitionsProto proto. + * @param hbmBuffersConfig Serialized HbmBuffersConfig proto. + * @param tpuTopology Serialized TpuTopologyArgsProto proto. * @return a new instance of ComputeDedupDataSize */ @Endpoint( describeByClass = true ) - public static ComputeDedupDataSize create(Scope scope, String config) { + public static ComputeDedupDataSize create(Scope scope, String config, String embeddingPartitions, + String hbmBuffersConfig, String tpuTopology) { OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "ComputeDedupDataSize"); opBuilder.setAttr("config", config); + opBuilder.setAttr("embedding_partitions", embeddingPartitions); + opBuilder.setAttr("hbm_buffers_config", hbmBuffersConfig); + opBuilder.setAttr("tpu_topology", tpuTopology); return new ComputeDedupDataSize(opBuilder.build()); } @@ -98,10 +101,28 @@ public static class Inputs extends RawOpInputs { */ public final String config; + /** + * Serialized EmbeddingPartitionsProto proto. + */ + public final String embeddingPartitions; + + /** + * Serialized HbmBuffersConfig proto. + */ + public final String hbmBuffersConfig; + + /** + * Serialized TpuTopologyArgsProto proto. + */ + public final String tpuTopology; + public Inputs(GraphOperation op) { - super(new ComputeDedupDataSize(op), op, Arrays.asList("config")); + super(new ComputeDedupDataSize(op), op, Arrays.asList("config", "embedding_partitions", "hbm_buffers_config", "tpu_topology")); int inputIndex = 0; config = op.attributes().getAttrString("config"); + embeddingPartitions = op.attributes().getAttrString("embedding_partitions"); + hbmBuffersConfig = op.attributes().getAttrString("hbm_buffers_config"); + tpuTopology = op.attributes().getAttrString("tpu_topology"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ComputeDedupDataTupleMask.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ComputeDedupDataTupleMask.java index 95078aebabc..1160a8536a2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ComputeDedupDataTupleMask.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ComputeDedupDataTupleMask.java @@ -29,7 +29,6 @@ import org.tensorflow.op.annotation.Endpoint; import org.tensorflow.op.annotation.OpInputsMetadata; import org.tensorflow.op.annotation.OpMetadata; -import org.tensorflow.op.annotation.Operator; import org.tensorflow.types.TInt32; /** @@ -42,14 +41,11 @@ opType = ComputeDedupDataTupleMask.OP_NAME, inputsClass = ComputeDedupDataTupleMask.Inputs.class ) -@Operator( - group = "tpu" -) public final class ComputeDedupDataTupleMask extends RawOp implements Operand { /** * The name of this op, as known by TensorFlow core engine */ - public static final String OP_NAME = "ComputeDedupDataTupleMask"; + public static final String OP_NAME = "ComputeDedupDataTupleMaskV2"; private Output outputShape; @@ -60,18 +56,25 @@ public ComputeDedupDataTupleMask(Operation operation) { } /** - * Factory method to create a class wrapping a new ComputeDedupDataTupleMask operation. + * Factory method to create a class wrapping a new ComputeDedupDataTupleMaskV2 operation. * * @param scope current scope * @param config Serialized TPUEmbeddingConfiguration proto. + * @param embeddingPartitions Serialized EmbeddingPartitionsProto proto. + * @param hbmBuffersConfig Serialized HbmBuffersConfig proto. + * @param tpuTopology Serialized TpuTopologyArgsProto proto. * @return a new instance of ComputeDedupDataTupleMask */ @Endpoint( describeByClass = true ) - public static ComputeDedupDataTupleMask create(Scope scope, String config) { + public static ComputeDedupDataTupleMask create(Scope scope, String config, + String embeddingPartitions, String hbmBuffersConfig, String tpuTopology) { OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "ComputeDedupDataTupleMask"); opBuilder.setAttr("config", config); + opBuilder.setAttr("embedding_partitions", embeddingPartitions); + opBuilder.setAttr("hbm_buffers_config", hbmBuffersConfig); + opBuilder.setAttr("tpu_topology", tpuTopology); return new ComputeDedupDataTupleMask(opBuilder.build()); } @@ -103,10 +106,28 @@ public static class Inputs extends RawOpInputs { */ public final String config; + /** + * Serialized EmbeddingPartitionsProto proto. + */ + public final String embeddingPartitions; + + /** + * Serialized HbmBuffersConfig proto. + */ + public final String hbmBuffersConfig; + + /** + * Serialized TpuTopologyArgsProto proto. + */ + public final String tpuTopology; + public Inputs(GraphOperation op) { - super(new ComputeDedupDataTupleMask(op), op, Arrays.asList("config")); + super(new ComputeDedupDataTupleMask(op), op, Arrays.asList("config", "embedding_partitions", "hbm_buffers_config", "tpu_topology")); int inputIndex = 0; config = op.attributes().getAttrString("config"); + embeddingPartitions = op.attributes().getAttrString("embedding_partitions"); + hbmBuffersConfig = op.attributes().getAttrString("hbm_buffers_config"); + tpuTopology = op.attributes().getAttrString("tpu_topology"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java index c56e985eafb..15e942cac31 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java @@ -41,8 +41,6 @@ * Passing group_assignment={@code [[0,2,4,6],[1,3,5,7]]} sets {@code A, C, E, G} as group 0, * and {@code B, D, F, H} as group 1. Thus we get the outputs: * {@code [A+C+E+G, B+D+F+H, A+C+E+G, B+D+F+H, A+C+E+G, B+D+F+H, A+C+E+G, B+D+F+H]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CrossReplicaSum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/FinalizeTPUEmbedding.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/FinalizeTPUEmbedding.java index 6ce405ea522..db44a52d05b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/FinalizeTPUEmbedding.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/FinalizeTPUEmbedding.java @@ -22,6 +22,7 @@ import org.tensorflow.Operand; import org.tensorflow.Operation; import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; import org.tensorflow.op.RawOp; import org.tensorflow.op.RawOpInputs; import org.tensorflow.op.Scope; @@ -45,14 +46,21 @@ public final class FinalizeTPUEmbedding extends RawOp { /** * The name of this op, as known by TensorFlow core engine */ - public static final String OP_NAME = "FinalizeTPUEmbedding"; + public static final String OP_NAME = "FinalizeTPUEmbeddingV2"; + + private Output embeddingPartitions; + + private Output hbmBuffersConfig; public FinalizeTPUEmbedding(Operation operation) { super(operation, OP_NAME); + int outputIdx = 0; + embeddingPartitions = operation.output(outputIdx++); + hbmBuffersConfig = operation.output(outputIdx++); } /** - * Factory method to create a class wrapping a new FinalizeTPUEmbedding operation. + * Factory method to create a class wrapping a new FinalizeTPUEmbeddingV2 operation. * * @param scope current scope * @param commonConfig A string-encoded common configuration proto containing metadata @@ -73,6 +81,26 @@ public static FinalizeTPUEmbedding create(Scope scope, Operand commonCo return new FinalizeTPUEmbedding(opBuilder.build()); } + /** + * Gets embeddingPartitions. + * A string-encoded embedding partitions proto describing how embedding tables are + * partitioned along their feature and ID. + * @return embeddingPartitions. + */ + public Output embeddingPartitions() { + return embeddingPartitions; + } + + /** + * Gets hbmBuffersConfig. + * A string-encoded HBM buffers config proto specifies where HBM buffers are + * located. + * @return hbmBuffersConfig. + */ + public Output hbmBuffersConfig() { + return hbmBuffersConfig; + } + @OpInputsMetadata( outputsClass = FinalizeTPUEmbedding.class ) diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/GetTpuTaskId.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/GetTpuTaskId.java new file mode 100644 index 00000000000..c4eb00be8dd --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/GetTpuTaskId.java @@ -0,0 +1,97 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.tpu; + +import java.util.Arrays; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.op.annotation.Operator; +import org.tensorflow.types.TInt32; + +/** + * An op returns the TPU task ID from TPU topology. + * This op is to return the TPU task ID from TPU topology. + */ +@OpMetadata( + opType = GetTpuTaskId.OP_NAME, + inputsClass = GetTpuTaskId.Inputs.class +) +@Operator( + group = "tpu" +) +public final class GetTpuTaskId extends RawOp implements Operand { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "GetTpuTaskId"; + + private Output tpuTaskId; + + public GetTpuTaskId(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + tpuTaskId = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new GetTpuTaskId operation. + * + * @param scope current scope + * @return a new instance of GetTpuTaskId + */ + @Endpoint( + describeByClass = true + ) + public static GetTpuTaskId create(Scope scope) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "GetTpuTaskId"); + return new GetTpuTaskId(opBuilder.build()); + } + + /** + * Gets tpuTaskId. + * The TPU task ID from TPU topology. + * @return tpuTaskId. + */ + public Output tpuTaskId() { + return tpuTaskId; + } + + @Override + public Output asOutput() { + return tpuTaskId; + } + + @OpInputsMetadata( + outputsClass = GetTpuTaskId.class + ) + public static class Inputs extends RawOpInputs { + public Inputs(GraphOperation op) { + super(new GetTpuTaskId(op), op, Arrays.asList()); + int inputIndex = 0; + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java index 20e200e26af..2f2d689a23a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java @@ -37,8 +37,6 @@ /** * A placeholder op for a value that will be fed into the computation. - * - * @param data type for {@code output} output */ @OpMetadata( opType = InfeedDequeue.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java index 27a9edc8214..f2043c5047c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java @@ -38,8 +38,6 @@ /** * Retrieves a single tensor from the computation outfeed. * This operation will block indefinitely until data is available. - * - * @param data type for {@code output} output */ @OpMetadata( opType = OutfeedDequeue.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueV2.java index 481f916e86a..dc0d6a3649a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueV2.java @@ -40,8 +40,6 @@ * Retrieves a single tensor from the computation outfeed. Device ordinal is a * tensor allowing dynamic outfeed. * This operation will block indefinitely until data is available. - * - * @param data type for {@code output} output */ @OpMetadata( opType = OutfeedDequeueV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedInput.java index be69029e573..89d11541c1b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedInput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedInput.java @@ -37,8 +37,6 @@ /** * An op that groups a list of partitioned inputs together. Supports ND sharding. - * - * @param data type for {@code output} output */ @OpMetadata( opType = PartitionedInput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedOutput.java index a49b96f066d..b69bdea9a7b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedOutput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedOutput.java @@ -38,8 +38,6 @@ /** * An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned * outputs outside the XLA computation. Supports ND sharding. - * - * @param data type for {@code output} output */ @OpMetadata( opType = PartitionedOutput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedInput.java index 37c057fc375..5f5ae14be0e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedInput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedInput.java @@ -46,8 +46,6 @@ * %computation = "tf.Computation"(%replicated_input) * *

    The above computation has a replicated input of two replicas. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ReplicatedInput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedOutput.java index fcc447fb932..6daab9ae1a2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedOutput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedOutput.java @@ -45,8 +45,6 @@ * %replicated_output:2 = "tf.TPUReplicatedOutput"(%computation) * *

    The above computation has a replicated output of two replicas. - * - * @param data type for {@code outputs} output */ @OpMetadata( opType = ReplicatedOutput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/SplitDedupData.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/SplitDedupData.java index ad72b480077..8e8d4537dff 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/SplitDedupData.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/SplitDedupData.java @@ -41,10 +41,6 @@ * Deduplication data is an XLA tuple, which consists of integer and floating point * values. This op is to split these values into two groups for two types, and * construct each group as one tensor to return. - * - * @param data type for {@code integer_tensor} output - * - * @param data type for {@code float_tensor} output */ @OpMetadata( opType = SplitDedupData.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedInput.java index 1816bb842df..80ac7e3ea03 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedInput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedInput.java @@ -47,8 +47,6 @@ * *

    The above computation has a replicated input of two replicas. * - * @param data type for {@code output} output - * * @deprecated use {@link org.tensorflow.op.tpu.ReplicatedInput} instead */ @OpMetadata( diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedOutput.java index ea53c36f109..dcc1b12b2b8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedOutput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedOutput.java @@ -46,8 +46,6 @@ * *

    The above computation has a replicated output of two replicas. * - * @param data type for {@code outputs} output - * * @deprecated use {@link org.tensorflow.op.tpu.ReplicatedOutput} instead */ @OpMetadata( diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/UpdateTaskIdAndGlobalCoreArray.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/UpdateTaskIdAndGlobalCoreArray.java new file mode 100644 index 00000000000..1a0fb866178 --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/UpdateTaskIdAndGlobalCoreArray.java @@ -0,0 +1,86 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.tpu; + +import java.util.Arrays; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.op.Operands; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.types.TInt32; + +/** + * An op to update the task ID and global core array. + * This op is to update the task ID and global core array. + */ +@OpMetadata( + opType = UpdateTaskIdAndGlobalCoreArray.OP_NAME, + inputsClass = UpdateTaskIdAndGlobalCoreArray.Inputs.class +) +public final class UpdateTaskIdAndGlobalCoreArray extends RawOp { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "UpdateTaskIdAndGlobalCoreArray"; + + public UpdateTaskIdAndGlobalCoreArray(Operation operation) { + super(operation, OP_NAME); + } + + /** + * Factory method to create a class wrapping a new UpdateTaskIdAndGlobalCoreArray operation. + * + * @param scope current scope + * @param tpuTaskIdToShardId An array of int32 that maps TPU task ID to shard ID. + * @return a new instance of UpdateTaskIdAndGlobalCoreArray + */ + @Endpoint( + describeByClass = true + ) + public static UpdateTaskIdAndGlobalCoreArray create(Scope scope, + Iterable> tpuTaskIdToShardId) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "UpdateTaskIdAndGlobalCoreArray"); + opBuilder.addInputList(Operands.asOutputs(tpuTaskIdToShardId)); + return new UpdateTaskIdAndGlobalCoreArray(opBuilder.build()); + } + + @OpInputsMetadata( + outputsClass = UpdateTaskIdAndGlobalCoreArray.class + ) + public static class Inputs extends RawOpInputs { + /** + * An array of int32 that maps TPU task ID to shard ID. + */ + public final Iterable> tpuTaskIdToShardId; + + public Inputs(GraphOperation op) { + super(new UpdateTaskIdAndGlobalCoreArray(op), op, Arrays.asList()); + int inputIndex = 0; + int tpuTaskIdToShardIdLength = op.inputListLength("tpu_task_id_to_shard_id"); + tpuTaskIdToShardId = Arrays.asList((Operand[]) op.inputList(inputIndex, tpuTaskIdToShardIdLength)); + inputIndex += tpuTaskIdToShardIdLength; + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java index a2d152ab93e..e7c94866732 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java @@ -43,8 +43,6 @@ * aggregated more than num_required gradients, it returns the average of * the accumulated gradients. Also automatically increments the recorded * global_step in the accumulator by 1, and resets the aggregate to 0. - * - * @param data type for {@code average} output */ @OpMetadata( opType = AccumulatorTakeGradient.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdaMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdaMax.java index 5a6b4fa2871..0bdb47444ad 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdaMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdaMax.java @@ -38,8 +38,6 @@ * m_t <- beta1 * m_{t-1} + (1 - beta1) * g * v_t <- max(beta2 * v_{t-1}, abs(g)) * variable <- variable - learning_rate / (1 - beta1^t) * m_t / (v_t + epsilon) - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyAdaMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdadelta.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdadelta.java index be5bdc297ea..7d53245fe2a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdadelta.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdadelta.java @@ -39,8 +39,6 @@ * update = (update_accum + epsilon).sqrt() * (accum + epsilon()).rsqrt() * grad; * update_accum = rho() * update_accum + (1 - rho()) * update.square(); * var -= update; - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyAdadelta.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagrad.java index 9a717cb0daf..0d243bfce4b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagrad.java @@ -37,8 +37,6 @@ * Update '*var' according to the adagrad scheme. * accum += grad * grad * var -= lr * grad * (1 / sqrt(accum)) - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyAdagrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradDa.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradDa.java index b1577260bf8..a2769eae2e7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradDa.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradDa.java @@ -36,8 +36,6 @@ /** * Update '*var' according to the proximal adagrad scheme. - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyAdagradDa.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradV2.java index 6766d80538e..22d0edd340e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradV2.java @@ -37,8 +37,6 @@ * Update '*var' according to the adagrad scheme. * accum += grad * grad * var -= lr * grad * (1 / sqrt(accum)) - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyAdagradV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdam.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdam.java index 91dbb1d72f6..8dbd525dc98 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdam.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdam.java @@ -39,8 +39,6 @@ * $$m_t := \beta_1 \cdot m{t-1} + (1 - \beta_1) \cdot g$$ * $$v_t := \beta_2 \cdot v_{t-1} + (1 - \beta_2) \cdot g^2$$ * $$\text{var} := \begin{cases} \text{var} - (m_t \beta_1 + g \cdot (1 - \beta_1))\cdot\text{lr}_t/(\sqrt{v_t} + \epsilon), &\text{if use_nesterov}\\ \text{var} - m_t \cdot \text{lr}_t /(\sqrt{v_t} + \epsilon), &\text{otherwise} \end{cases}$$ - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyAdam.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAddSign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAddSign.java index 434802b1590..69127231eb1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAddSign.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAddSign.java @@ -38,8 +38,6 @@ * m_t <- beta1 * m_{t-1} + (1 - beta1) * g * update <- (alpha + sign_decay * sign(g) *sign(m)) * g * variable <- variable - lr_t * update - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyAddSign.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyCenteredRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyCenteredRmsProp.java index 46f9975e74a..f7801bf277e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyCenteredRmsProp.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyCenteredRmsProp.java @@ -49,8 +49,6 @@ * ms <- rho * ms_{t-1} + (1-rho) * grad * grad * mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms - mg * mg + epsilon) * var <- var - mom - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyCenteredRmsProp.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyFtrl.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyFtrl.java index c14505600ef..cd010677d47 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyFtrl.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyFtrl.java @@ -42,8 +42,6 @@ * quadratic = 1.0 / (accum_new^(lr_power) * lr) + 2 * l2 * var = (sign(linear) * l1 - linear) / quadratic if |linear| > l1 else 0.0 * accum = accum_new - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyFtrl.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyGradientDescent.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyGradientDescent.java index f7c93955d6b..5ebb7b31330 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyGradientDescent.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyGradientDescent.java @@ -35,8 +35,6 @@ /** * Update '*var' by subtracting 'alpha' * 'delta' from it. - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyGradientDescent.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyMomentum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyMomentum.java index fc82fa94853..1aa402b6783 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyMomentum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyMomentum.java @@ -38,8 +38,6 @@ * Set use_nesterov = True if you want to use Nesterov momentum. *

    accum = accum * momentum + grad * var -= lr * accum - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyMomentum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyPowerSign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyPowerSign.java index dad41ae5e50..f298f853be2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyPowerSign.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyPowerSign.java @@ -38,8 +38,6 @@ * m_t <- beta1 * m_{t-1} + (1 - beta1) * g * update <- exp(logbase * sign_decay * sign(g) * sign(m_t)) * g * variable <- variable - lr_t * update - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyPowerSign.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalAdagrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalAdagrad.java index 8f2c0b1d0b2..a095146963b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalAdagrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalAdagrad.java @@ -38,8 +38,6 @@ * accum += grad * grad * prox_v = var - lr * grad * (1 / sqrt(accum)) * var = sign(prox_v)/(1+lrl2) * max{|prox_v|-lrl1,0} - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyProximalAdagrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalGradientDescent.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalGradientDescent.java index 488faf4d559..ffd6ee70e68 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalGradientDescent.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalGradientDescent.java @@ -37,8 +37,6 @@ * Update '*var' as FOBOS algorithm with fixed learning rate. * prox_v = var - alpha * delta * var = sign(prox_v)/(1+alphal2) * max{|prox_v|-alphal1,0} - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyProximalGradientDescent.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyRmsProp.java index 539fa33e176..fcfeb5b895a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyRmsProp.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyRmsProp.java @@ -43,8 +43,6 @@ *

    ms <- rho * ms_{t-1} + (1-rho) * grad * grad * mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon) * var <- var - mom - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyRmsProp.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/BatchMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/BatchMatMul.java index 14fdcd8d781..17560573705 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/BatchMatMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/BatchMatMul.java @@ -56,8 +56,6 @@ *

    NOTE: {@code train.BatchMatMul} supports broadcasting in the batch dimensions. More * about broadcasting * here . - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatMul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/PreventGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/PreventGradient.java index a7181e6cb0b..c98b11d0050 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/PreventGradient.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/PreventGradient.java @@ -41,8 +41,6 @@ * because no gradient must ever be registered for this function. This * op exists to prevent subtle bugs from silently returning unimplemented * gradients in some corner cases. - * - * @param data type for {@code output} output */ @OpMetadata( opType = PreventGradient.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java index 4b7a918f597..843ecae89f1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java @@ -42,8 +42,6 @@ * aggregated more than num_required gradients, it returns the average of * the accumulated gradients. Also automatically increments the recorded * global_step in the accumulator by 1, and resets the aggregate to 0. - * - * @param data type for {@code average} output */ @OpMetadata( opType = ResourceAccumulatorTakeGradient.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/RestoreSlice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/RestoreSlice.java index b0faba2454c..a33a34b3179 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/RestoreSlice.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/RestoreSlice.java @@ -42,8 +42,6 @@ * larger tensor and the slice that the restored tensor covers. *

    The {@code shape_and_slice} input has the same format as the * elements of the {@code shapes_and_slices} input of the {@code SaveSlices} op. - * - * @param data type for {@code tensor} output */ @OpMetadata( opType = RestoreSlice.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdadelta.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdadelta.java index c68618fecc1..8b12e83f51f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdadelta.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdadelta.java @@ -36,8 +36,6 @@ /** * var: Should be from a Variable(). - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyAdadelta.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagrad.java index a75507dde54..fbda4c582a0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagrad.java @@ -39,8 +39,6 @@ * That is for rows we have grad for, we update var and accum as follows: * $$accum += grad * grad$$ * $$var -= lr * grad * (1 / sqrt(accum))$$ - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyAdagrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagradDa.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagradDa.java index cdd24328bb6..33cdae176f0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagradDa.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagradDa.java @@ -37,8 +37,6 @@ /** * Update entries in '*var' and '*accum' according to the proximal adagrad scheme. - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyAdagradDa.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyCenteredRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyCenteredRmsProp.java index 731ecdd88a7..cfbf01b8044 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyCenteredRmsProp.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyCenteredRmsProp.java @@ -49,8 +49,6 @@ *

    $$ms <- rho * ms_{t-1} + (1-rho) * grad * grad$$ * $$mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)$$ * $$var <- var - mom$$ - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyCenteredRmsProp.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyFtrl.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyFtrl.java index 8c609b198bd..72cce364480 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyFtrl.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyFtrl.java @@ -44,8 +44,6 @@ * quadratic = 1.0 / (accum_new^(lr_power) * lr) + 2 * l2 * var = (sign(linear) * l1 - linear) / quadratic if |linear| > l1 else 0.0 * accum = accum_new - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyFtrl.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyMomentum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyMomentum.java index 2e22789fd23..d2ae83d8c17 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyMomentum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyMomentum.java @@ -40,8 +40,6 @@ *

    That is for rows we have grad for, we update var and accum as follows: *

    $$accum = accum * momentum + grad$$ * $$var -= lr * accum$$ - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyMomentum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalAdagrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalAdagrad.java index 68ca59089e1..70b28897f24 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalAdagrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalAdagrad.java @@ -41,8 +41,6 @@ * $$prox_v = var$$ * $$prox_v -= lr * grad * (1 / sqrt(accum))$$ * $$var = sign(prox_v)/(1+lrl2) * max{|prox_v|-lrl1,0}$$ - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyProximalAdagrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalGradientDescent.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalGradientDescent.java index 08b098f80ca..3da972089e7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalGradientDescent.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalGradientDescent.java @@ -39,8 +39,6 @@ * That is for rows we have grad for, we update var as follows: * $$prox_v = var - alpha * grad$$ * $$var = sign(prox_v)/(1+alphal2) * max{|prox_v|-alphal1,0}$$ - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyProximalGradientDescent.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyRmsProp.java index a648dc04b08..3c642ebcf81 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyRmsProp.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyRmsProp.java @@ -44,8 +44,6 @@ *

    $$ms <- rho * ms_{t-1} + (1-rho) * grad * grad$$ * $$mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)$$ * $$var <- var - mom$$ - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyRmsProp.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/TileGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/TileGrad.java index bdc5c23fc46..9e1b7e0fbb4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/TileGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/TileGrad.java @@ -39,8 +39,6 @@ * Since {@code Tile} takes an input and repeats the input {@code multiples} times * along each dimension, {@code train.TileGrad} takes in {@code multiples} and aggregates * each repeated tile of {@code input} into {@code output}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = TileGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/AssignVariableConcatND.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/AssignVariableConcatND.java index 51f000b2687..c58943ff50d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/AssignVariableConcatND.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/AssignVariableConcatND.java @@ -88,18 +88,8 @@ public AssignVariableConcatND(Operation operation) { * * @param scope current scope * @param resource Resource variable for concatenated input tensors across all dimensions. - * } - * in_arg { - * name: "inputs" - * description: <<END - * Input tensor slices in row-major order to merge across all dimensions. All + * @param inputs Input tensor slices in row-major order to merge across all dimensions. All * inputs must have the same shape. - * } - * out_arg { - * name: "output" - * description: <<END - * Output tensor formed from merging input slices based on num_concats defined. - * @param inputs The inputs value * @param numConcats Number of ways to merge per dimension. * @param options carries optional attribute values * @return a new instance of AssignVariableConcatND @@ -197,22 +187,12 @@ public Options paddings(Long... paddings) { public static class Inputs extends RawOpInputs { /** * Resource variable for concatenated input tensors across all dimensions. - * } - * in_arg { - * name: "inputs" - * description: <<END - * Input tensor slices in row-major order to merge across all dimensions. All - * inputs must have the same shape. - * } - * out_arg { - * name: "output" - * description: <<END - * Output tensor formed from merging input slices based on num_concats defined. */ public final Operand resource; /** - * The inputs input + * Input tensor slices in row-major order to merge across all dimensions. All + * inputs must have the same shape. */ public final Iterable> inputs; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ConcatND.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ConcatND.java index 7e55c95e679..5749305af89 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ConcatND.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ConcatND.java @@ -66,8 +66,6 @@ * [4, 5, 6], * [8, 9, 10]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = ConcatND.OP_NAME, @@ -96,11 +94,6 @@ public ConcatND(Operation operation) { * @param scope current scope * @param inputs Input tensor slices in row-major order to merge across all dimensions. All * inputs must have the same shape. - * } - * out_arg { - * name: "output" - * description: <<END - * Output tensor formed from merging input slices based on num_concats defined. * @param numConcats Number of ways to merge per dimension. * @param options carries optional attribute values * @param data type for {@code XlaConcatND} output and operands @@ -158,7 +151,7 @@ public static Options paddings(Long... paddings) { /** * Gets output. - * + * Output tensor formed from merging input slices based on num_concats defined. * @return output. */ public Output output() { @@ -213,11 +206,6 @@ public static class Inputs extends RawOpInputs> { /** * Input tensor slices in row-major order to merge across all dimensions. All * inputs must have the same shape. - * } - * out_arg { - * name: "output" - * description: <<END - * Output tensor formed from merging input slices based on num_concats defined. */ public final Iterable> inputs; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReadVariableSplitND.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReadVariableSplitND.java index 666103dd273..9788f2927f0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReadVariableSplitND.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReadVariableSplitND.java @@ -67,8 +67,6 @@ * [[8, 0], * [0, 0]] * - * - * @param data type for {@code outputs} output */ @OpMetadata( opType = ReadVariableSplitND.OP_NAME, @@ -99,11 +97,6 @@ public ReadVariableSplitND(Operation operation) { * * @param scope current scope * @param resource Resource variable of input tensor to split across all dimensions. - * } - * out_arg { - * name: "outputs" - * description: <<END - * Output slices based on input and num_splits defined, in row-major order. * @param T The value of the T attribute * @param N The value of the N attribute * @param numSplits Number of ways to split per dimension. Shape dimensions must be evenly @@ -165,7 +158,7 @@ public static Options paddings(Long... paddings) { /** * Gets outputs. - * + * Output slices based on input and num_splits defined, in row-major order. * @return outputs. */ public List> outputs() { @@ -218,11 +211,6 @@ public Options paddings(Long... paddings) { public static class Inputs extends RawOpInputs> { /** * Resource variable of input tensor to split across all dimensions. - * } - * out_arg { - * name: "outputs" - * description: <<END - * Output slices based on input and num_splits defined, in row-major order. */ public final Operand resource; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SplitND.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SplitND.java index 6bf5656f68c..299b2f95437 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SplitND.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SplitND.java @@ -66,8 +66,6 @@ * [[8, 0], * [0, 0]] * - * - * @param data type for {@code outputs} output */ @OpMetadata( opType = SplitND.OP_NAME, @@ -98,11 +96,6 @@ public SplitND(Operation operation) { * * @param scope current scope * @param input Input tensor to split across all dimensions. - * } - * out_arg { - * name: "outputs" - * description: <<END - * Output slices based on input and num_splits defined, in row-major order. * @param N The value of the N attribute * @param numSplits Number of ways to split per dimension. Shape dimensions must be evenly * divisible. @@ -161,7 +154,7 @@ public static Options paddings(Long... paddings) { /** * Gets outputs. - * + * Output slices based on input and num_splits defined, in row-major order. * @return outputs. */ public List> outputs() { @@ -214,11 +207,6 @@ public Options paddings(Long... paddings) { public static class Inputs extends RawOpInputs> { /** * Input tensor to split across all dimensions. - * } - * out_arg { - * name: "outputs" - * description: <<END - * Output slices based on input and num_splits defined, in row-major order. */ public final Operand input; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvFromHost.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvFromHost.java index c8d5507a673..b05f7199f7a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvFromHost.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvFromHost.java @@ -41,8 +41,6 @@ * Toutput: element type for output. * shape: shape for output. * key: A unique identifier for this region used to match up host transfers. - * - * @param data type for {@code output} output */ @OpMetadata( opType = XlaRecvFromHost.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvTPUEmbeddingActivations.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvTPUEmbeddingActivations.java index 1af06a9de56..b3499a237f0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvTPUEmbeddingActivations.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvTPUEmbeddingActivations.java @@ -31,7 +31,6 @@ import org.tensorflow.op.annotation.Endpoint; import org.tensorflow.op.annotation.OpInputsMetadata; import org.tensorflow.op.annotation.OpMetadata; -import org.tensorflow.op.annotation.Operator; import org.tensorflow.types.TFloat32; import org.tensorflow.types.family.TType; @@ -46,14 +45,11 @@ opType = XlaRecvTPUEmbeddingActivations.OP_NAME, inputsClass = XlaRecvTPUEmbeddingActivations.Inputs.class ) -@Operator( - group = "xla" -) public final class XlaRecvTPUEmbeddingActivations extends RawOp implements Iterable> { /** * The name of this op, as known by TensorFlow core engine */ - public static final String OP_NAME = "XlaRecvTPUEmbeddingActivations"; + public static final String OP_NAME = "XlaRecvTPUEmbeddingActivationsV2"; private List> outputs; @@ -67,7 +63,7 @@ public XlaRecvTPUEmbeddingActivations(Operation operation) { } /** - * Factory method to create a class wrapping a new XlaRecvTPUEmbeddingActivations operation. + * Factory method to create a class wrapping a new XlaRecvTPUEmbeddingActivationsV2 operation. * * @param scope current scope * @param deduplicationData A Tensor with type=DT_VARIANT containing the deduplication @@ -80,17 +76,24 @@ public XlaRecvTPUEmbeddingActivations(Operation operation) { * present in the tpu embedding config, it is equal to the number of features * otherwise equal to number of embedding tables in the model. * @param config Serialized TPUEmbeddingConfiguration proto. + * @param embeddingPartitions Serialized EmbeddingPartitionsProto proto. + * @param hbmBuffersConfig Serialized HbmBuffersConfig proto. + * @param tpuTopology Serialized TpuTopologyArgsProto proto. * @return a new instance of XlaRecvTPUEmbeddingActivations */ @Endpoint( describeByClass = true ) public static XlaRecvTPUEmbeddingActivations create(Scope scope, - Operand deduplicationData, Long numTables, String config) { + Operand deduplicationData, Long numTables, String config, + String embeddingPartitions, String hbmBuffersConfig, String tpuTopology) { OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "XlaRecvTPUEmbeddingActivations"); opBuilder.addInput(deduplicationData.asOutput()); opBuilder.setAttr("num_tables", numTables); opBuilder.setAttr("config", config); + opBuilder.setAttr("embedding_partitions", embeddingPartitions); + opBuilder.setAttr("hbm_buffers_config", hbmBuffersConfig); + opBuilder.setAttr("tpu_topology", tpuTopology); return new XlaRecvTPUEmbeddingActivations(opBuilder.build()); } @@ -129,11 +132,29 @@ public static class Inputs extends RawOpInputs { */ public final String config; + /** + * Serialized EmbeddingPartitionsProto proto. + */ + public final String embeddingPartitions; + + /** + * Serialized HbmBuffersConfig proto. + */ + public final String hbmBuffersConfig; + + /** + * Serialized TpuTopologyArgsProto proto. + */ + public final String tpuTopology; + public Inputs(GraphOperation op) { - super(new XlaRecvTPUEmbeddingActivations(op), op, Arrays.asList("config")); + super(new XlaRecvTPUEmbeddingActivations(op), op, Arrays.asList("config", "embedding_partitions", "hbm_buffers_config", "tpu_topology")); int inputIndex = 0; deduplicationData = (Operand) op.input(inputIndex++); config = op.attributes().getAttrString("config"); + embeddingPartitions = op.attributes().getAttrString("embedding_partitions"); + hbmBuffersConfig = op.attributes().getAttrString("hbm_buffers_config"); + tpuTopology = op.attributes().getAttrString("tpu_topology"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvTPUEmbeddingDeduplicationData.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvTPUEmbeddingDeduplicationData.java index abf76b9a0ad..a0c18fb338c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvTPUEmbeddingDeduplicationData.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvTPUEmbeddingDeduplicationData.java @@ -29,7 +29,6 @@ import org.tensorflow.op.annotation.Endpoint; import org.tensorflow.op.annotation.OpInputsMetadata; import org.tensorflow.op.annotation.OpMetadata; -import org.tensorflow.op.annotation.Operator; import org.tensorflow.types.family.TType; /** @@ -45,14 +44,11 @@ opType = XlaRecvTPUEmbeddingDeduplicationData.OP_NAME, inputsClass = XlaRecvTPUEmbeddingDeduplicationData.Inputs.class ) -@Operator( - group = "xla" -) public final class XlaRecvTPUEmbeddingDeduplicationData extends RawOp implements Operand { /** * The name of this op, as known by TensorFlow core engine */ - public static final String OP_NAME = "XlaRecvTPUEmbeddingDeduplicationData"; + public static final String OP_NAME = "XlaRecvTPUEmbeddingDeduplicationDataV2"; private Output output; @@ -64,18 +60,25 @@ public XlaRecvTPUEmbeddingDeduplicationData(Operation operation) { } /** - * Factory method to create a class wrapping a new XlaRecvTPUEmbeddingDeduplicationData operation. + * Factory method to create a class wrapping a new XlaRecvTPUEmbeddingDeduplicationDataV2 operation. * * @param scope current scope * @param config Serialized TPUEmbeddingConfiguration proto. + * @param embeddingPartitions Serialized EmbeddingPartitionsProto proto. + * @param hbmBuffersConfig Serialized HbmBuffersConfig proto. + * @param tpuTopology Serialized TpuTopologyArgsProto proto. * @return a new instance of XlaRecvTPUEmbeddingDeduplicationData */ @Endpoint( describeByClass = true ) - public static XlaRecvTPUEmbeddingDeduplicationData create(Scope scope, String config) { + public static XlaRecvTPUEmbeddingDeduplicationData create(Scope scope, String config, + String embeddingPartitions, String hbmBuffersConfig, String tpuTopology) { OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "XlaRecvTPUEmbeddingDeduplicationData"); opBuilder.setAttr("config", config); + opBuilder.setAttr("embedding_partitions", embeddingPartitions); + opBuilder.setAttr("hbm_buffers_config", hbmBuffersConfig); + opBuilder.setAttr("tpu_topology", tpuTopology); return new XlaRecvTPUEmbeddingDeduplicationData(opBuilder.build()); } @@ -103,10 +106,28 @@ public static class Inputs extends RawOpInputs> gradients, Iterable> learningRates, - Operand deduplicationData, String config, Options... options) { + Operand deduplicationData, String config, String embeddingPartitions, + String hbmBuffersConfig, String tpuTopology, Options... options) { OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "XlaSendTPUEmbeddingGradients"); opBuilder.addInputList(Operands.asOutputs(gradients)); opBuilder.addInputList(Operands.asOutputs(learningRates)); opBuilder.addInput(deduplicationData.asOutput()); opBuilder.setAttr("config", config); + opBuilder.setAttr("embedding_partitions", embeddingPartitions); + opBuilder.setAttr("hbm_buffers_config", hbmBuffersConfig); + opBuilder.setAttr("tpu_topology", tpuTopology); if (options != null) { for (Options opts : options) { if (opts.NumLearningRateTags != null) { @@ -161,8 +164,23 @@ public static class Inputs extends RawOpInputs { */ public final String config; + /** + * Serialized EmbeddingPartitionsProto proto. + */ + public final String embeddingPartitions; + + /** + * Serialized HbmBuffersConfig proto. + */ + public final String hbmBuffersConfig; + + /** + * Serialized TpuTopologyArgsProto proto. + */ + public final String tpuTopology; + public Inputs(GraphOperation op) { - super(new XlaSendTPUEmbeddingGradients(op), op, Arrays.asList("config")); + super(new XlaSendTPUEmbeddingGradients(op), op, Arrays.asList("config", "embedding_partitions", "hbm_buffers_config", "tpu_topology")); int inputIndex = 0; int gradientsLength = op.inputListLength("gradients"); gradients = Arrays.asList((Operand[]) op.inputList(inputIndex, gradientsLength)); @@ -172,6 +190,9 @@ public Inputs(GraphOperation op) { inputIndex += learningRatesLength; deduplicationData = (Operand) op.input(inputIndex++); config = op.attributes().getAttrString("config"); + embeddingPartitions = op.attributes().getAttrString("embedding_partitions"); + hbmBuffersConfig = op.attributes().getAttrString("hbm_buffers_config"); + tpuTopology = op.attributes().getAttrString("tpu_topology"); } } } diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize.java new file mode 100644 index 00000000000..f8ab65a6ee1 --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize.java @@ -0,0 +1,279 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.xla; + +import java.util.Arrays; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TInt32; + +/** + * The XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize operation + */ +@OpMetadata( + opType = XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize.OP_NAME, + inputsClass = XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize.Inputs.class +) +public final class XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize extends RawOp { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize"; + + private Output updatedEmbeddingTable; + + private Output updatedAccumulator; + + public XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + updatedEmbeddingTable = operation.output(outputIdx++); + updatedAccumulator = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize operation. + * + * @param scope current scope + * @param rowPointers The rowPointers value + * @param sortedSampleIds The sortedSampleIds value + * @param sortedTokenIds The sortedTokenIds value + * @param sortedGains The sortedGains value + * @param activationGradients The activationGradients value + * @param learningRate The learningRate value + * @param embeddingTable The embeddingTable value + * @param accumulator The accumulator value + * @param numMinibatchesPerPhysicalSparseCore The numMinibatchesPerPhysicalSparseCore value + * @param maxIdsPerSparseCore The value of the maxIdsPerSparseCore attribute + * @param maxUniqueIdsPerSparseCore The value of the maxUniqueIdsPerSparseCore attribute + * @param tableName The value of the tableName attribute + * @param options carries optional attribute values + * @return a new instance of XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize + */ + @Endpoint( + describeByClass = true + ) + public static XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize create(Scope scope, + Operand rowPointers, Operand sortedSampleIds, Operand sortedTokenIds, + Operand sortedGains, Operand activationGradients, + Operand learningRate, Operand embeddingTable, + Operand accumulator, Operand numMinibatchesPerPhysicalSparseCore, + Long maxIdsPerSparseCore, Long maxUniqueIdsPerSparseCore, String tableName, + Options... options) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize"); + opBuilder.addInput(rowPointers.asOutput()); + opBuilder.addInput(sortedSampleIds.asOutput()); + opBuilder.addInput(sortedTokenIds.asOutput()); + opBuilder.addInput(sortedGains.asOutput()); + opBuilder.addInput(activationGradients.asOutput()); + opBuilder.addInput(learningRate.asOutput()); + opBuilder.addInput(embeddingTable.asOutput()); + opBuilder.addInput(accumulator.asOutput()); + opBuilder.addInput(numMinibatchesPerPhysicalSparseCore.asOutput()); + opBuilder.setAttr("max_ids_per_sparse_core", maxIdsPerSparseCore); + opBuilder.setAttr("max_unique_ids_per_sparse_core", maxUniqueIdsPerSparseCore); + opBuilder.setAttr("table_name", tableName); + if (options != null) { + for (Options opts : options) { + if (opts.clipWeightMin != null) { + opBuilder.setAttr("clip_weight_min", opts.clipWeightMin); + } + if (opts.clipWeightMax != null) { + opBuilder.setAttr("clip_weight_max", opts.clipWeightMax); + } + } + } + return new XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize(opBuilder.build()); + } + + /** + * Sets the clipWeightMin option. + * + * @param clipWeightMin the clipWeightMin option + * @return this Options instance. + */ + public static Options clipWeightMin(Float clipWeightMin) { + return new Options().clipWeightMin(clipWeightMin); + } + + /** + * Sets the clipWeightMax option. + * + * @param clipWeightMax the clipWeightMax option + * @return this Options instance. + */ + public static Options clipWeightMax(Float clipWeightMax) { + return new Options().clipWeightMax(clipWeightMax); + } + + /** + * Gets updatedEmbeddingTable. + * + * @return updatedEmbeddingTable. + */ + public Output updatedEmbeddingTable() { + return updatedEmbeddingTable; + } + + /** + * Gets updatedAccumulator. + * + * @return updatedAccumulator. + */ + public Output updatedAccumulator() { + return updatedAccumulator; + } + + /** + * Optional attributes for {@link org.tensorflow.op.xla.XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize} + */ + public static class Options { + private Float clipWeightMin; + + private Float clipWeightMax; + + private Options() { + } + + /** + * Sets the clipWeightMin option. + * + * @param clipWeightMin the clipWeightMin option + * @return this Options instance. + */ + public Options clipWeightMin(Float clipWeightMin) { + this.clipWeightMin = clipWeightMin; + return this; + } + + /** + * Sets the clipWeightMax option. + * + * @param clipWeightMax the clipWeightMax option + * @return this Options instance. + */ + public Options clipWeightMax(Float clipWeightMax) { + this.clipWeightMax = clipWeightMax; + return this; + } + } + + @OpInputsMetadata( + outputsClass = XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize.class + ) + public static class Inputs extends RawOpInputs { + /** + * The rowPointers input + */ + public final Operand rowPointers; + + /** + * The sortedSampleIds input + */ + public final Operand sortedSampleIds; + + /** + * The sortedTokenIds input + */ + public final Operand sortedTokenIds; + + /** + * The sortedGains input + */ + public final Operand sortedGains; + + /** + * The activationGradients input + */ + public final Operand activationGradients; + + /** + * The learningRate input + */ + public final Operand learningRate; + + /** + * The embeddingTable input + */ + public final Operand embeddingTable; + + /** + * The accumulator input + */ + public final Operand accumulator; + + /** + * The numMinibatchesPerPhysicalSparseCore input + */ + public final Operand numMinibatchesPerPhysicalSparseCore; + + /** + * The clipWeightMin attribute + */ + public final float clipWeightMin; + + /** + * The clipWeightMax attribute + */ + public final float clipWeightMax; + + /** + * The maxIdsPerSparseCore attribute + */ + public final long maxIdsPerSparseCore; + + /** + * The maxUniqueIdsPerSparseCore attribute + */ + public final long maxUniqueIdsPerSparseCore; + + /** + * The tableName attribute + */ + public final String tableName; + + public Inputs(GraphOperation op) { + super(new XlaSparseDenseMatmulGradWithAdagradAndStaticBufferSize(op), op, Arrays.asList("clip_weight_min", "clip_weight_max", "max_ids_per_sparse_core", "max_unique_ids_per_sparse_core", "table_name")); + int inputIndex = 0; + rowPointers = (Operand) op.input(inputIndex++); + sortedSampleIds = (Operand) op.input(inputIndex++); + sortedTokenIds = (Operand) op.input(inputIndex++); + sortedGains = (Operand) op.input(inputIndex++); + activationGradients = (Operand) op.input(inputIndex++); + learningRate = (Operand) op.input(inputIndex++); + embeddingTable = (Operand) op.input(inputIndex++); + accumulator = (Operand) op.input(inputIndex++); + numMinibatchesPerPhysicalSparseCore = (Operand) op.input(inputIndex++); + clipWeightMin = op.attributes().getAttrFloat("clip_weight_min"); + clipWeightMax = op.attributes().getAttrFloat("clip_weight_max"); + maxIdsPerSparseCore = op.attributes().getAttrInt("max_ids_per_sparse_core"); + maxUniqueIdsPerSparseCore = op.attributes().getAttrInt("max_unique_ids_per_sparse_core"); + tableName = op.attributes().getAttrString("table_name"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize.java new file mode 100644 index 00000000000..e007641d72a --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize.java @@ -0,0 +1,340 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.xla; + +import java.util.Arrays; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TInt32; + +/** + * The XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize operation + */ +@OpMetadata( + opType = XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize.OP_NAME, + inputsClass = XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize.Inputs.class +) +public final class XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize extends RawOp { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize"; + + private Output updatedEmbeddingTable; + + private Output updatedAccumulator; + + private Output updatedMomenta; + + public XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + updatedEmbeddingTable = operation.output(outputIdx++); + updatedAccumulator = operation.output(outputIdx++); + updatedMomenta = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize operation. + * + * @param scope current scope + * @param rowPointers The rowPointers value + * @param sortedSampleIds The sortedSampleIds value + * @param sortedTokenIds The sortedTokenIds value + * @param sortedGains The sortedGains value + * @param activationGradients The activationGradients value + * @param learningRate The learningRate value + * @param embeddingTable The embeddingTable value + * @param accumulator The accumulator value + * @param momenta The momenta value + * @param numMinibatchesPerPhysicalSparseCore The numMinibatchesPerPhysicalSparseCore value + * @param useNesterov The value of the useNesterov attribute + * @param exponent The value of the exponent attribute + * @param beta1 The value of the beta1 attribute + * @param beta2 The value of the beta2 attribute + * @param epsilon The value of the epsilon attribute + * @param maxIdsPerSparseCore The value of the maxIdsPerSparseCore attribute + * @param maxUniqueIdsPerSparseCore The value of the maxUniqueIdsPerSparseCore attribute + * @param tableName The value of the tableName attribute + * @param options carries optional attribute values + * @return a new instance of XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize + */ + @Endpoint( + describeByClass = true + ) + public static XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize create(Scope scope, + Operand rowPointers, Operand sortedSampleIds, Operand sortedTokenIds, + Operand sortedGains, Operand activationGradients, + Operand learningRate, Operand embeddingTable, + Operand accumulator, Operand momenta, + Operand numMinibatchesPerPhysicalSparseCore, Boolean useNesterov, Float exponent, + Float beta1, Float beta2, Float epsilon, Long maxIdsPerSparseCore, + Long maxUniqueIdsPerSparseCore, String tableName, Options... options) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize"); + opBuilder.addInput(rowPointers.asOutput()); + opBuilder.addInput(sortedSampleIds.asOutput()); + opBuilder.addInput(sortedTokenIds.asOutput()); + opBuilder.addInput(sortedGains.asOutput()); + opBuilder.addInput(activationGradients.asOutput()); + opBuilder.addInput(learningRate.asOutput()); + opBuilder.addInput(embeddingTable.asOutput()); + opBuilder.addInput(accumulator.asOutput()); + opBuilder.addInput(momenta.asOutput()); + opBuilder.addInput(numMinibatchesPerPhysicalSparseCore.asOutput()); + opBuilder.setAttr("use_nesterov", useNesterov); + opBuilder.setAttr("exponent", exponent); + opBuilder.setAttr("beta1", beta1); + opBuilder.setAttr("beta2", beta2); + opBuilder.setAttr("epsilon", epsilon); + opBuilder.setAttr("max_ids_per_sparse_core", maxIdsPerSparseCore); + opBuilder.setAttr("max_unique_ids_per_sparse_core", maxUniqueIdsPerSparseCore); + opBuilder.setAttr("table_name", tableName); + if (options != null) { + for (Options opts : options) { + if (opts.clipWeightMin != null) { + opBuilder.setAttr("clip_weight_min", opts.clipWeightMin); + } + if (opts.clipWeightMax != null) { + opBuilder.setAttr("clip_weight_max", opts.clipWeightMax); + } + } + } + return new XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize(opBuilder.build()); + } + + /** + * Sets the clipWeightMin option. + * + * @param clipWeightMin the clipWeightMin option + * @return this Options instance. + */ + public static Options clipWeightMin(Float clipWeightMin) { + return new Options().clipWeightMin(clipWeightMin); + } + + /** + * Sets the clipWeightMax option. + * + * @param clipWeightMax the clipWeightMax option + * @return this Options instance. + */ + public static Options clipWeightMax(Float clipWeightMax) { + return new Options().clipWeightMax(clipWeightMax); + } + + /** + * Gets updatedEmbeddingTable. + * + * @return updatedEmbeddingTable. + */ + public Output updatedEmbeddingTable() { + return updatedEmbeddingTable; + } + + /** + * Gets updatedAccumulator. + * + * @return updatedAccumulator. + */ + public Output updatedAccumulator() { + return updatedAccumulator; + } + + /** + * Gets updatedMomenta. + * + * @return updatedMomenta. + */ + public Output updatedMomenta() { + return updatedMomenta; + } + + /** + * Optional attributes for {@link org.tensorflow.op.xla.XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize} + */ + public static class Options { + private Float clipWeightMin; + + private Float clipWeightMax; + + private Options() { + } + + /** + * Sets the clipWeightMin option. + * + * @param clipWeightMin the clipWeightMin option + * @return this Options instance. + */ + public Options clipWeightMin(Float clipWeightMin) { + this.clipWeightMin = clipWeightMin; + return this; + } + + /** + * Sets the clipWeightMax option. + * + * @param clipWeightMax the clipWeightMax option + * @return this Options instance. + */ + public Options clipWeightMax(Float clipWeightMax) { + this.clipWeightMax = clipWeightMax; + return this; + } + } + + @OpInputsMetadata( + outputsClass = XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize.class + ) + public static class Inputs extends RawOpInputs { + /** + * The rowPointers input + */ + public final Operand rowPointers; + + /** + * The sortedSampleIds input + */ + public final Operand sortedSampleIds; + + /** + * The sortedTokenIds input + */ + public final Operand sortedTokenIds; + + /** + * The sortedGains input + */ + public final Operand sortedGains; + + /** + * The activationGradients input + */ + public final Operand activationGradients; + + /** + * The learningRate input + */ + public final Operand learningRate; + + /** + * The embeddingTable input + */ + public final Operand embeddingTable; + + /** + * The accumulator input + */ + public final Operand accumulator; + + /** + * The momenta input + */ + public final Operand momenta; + + /** + * The numMinibatchesPerPhysicalSparseCore input + */ + public final Operand numMinibatchesPerPhysicalSparseCore; + + /** + * The useNesterov attribute + */ + public final boolean useNesterov; + + /** + * The exponent attribute + */ + public final float exponent; + + /** + * The beta1 attribute + */ + public final float beta1; + + /** + * The beta2 attribute + */ + public final float beta2; + + /** + * The epsilon attribute + */ + public final float epsilon; + + /** + * The clipWeightMin attribute + */ + public final float clipWeightMin; + + /** + * The clipWeightMax attribute + */ + public final float clipWeightMax; + + /** + * The maxIdsPerSparseCore attribute + */ + public final long maxIdsPerSparseCore; + + /** + * The maxUniqueIdsPerSparseCore attribute + */ + public final long maxUniqueIdsPerSparseCore; + + /** + * The tableName attribute + */ + public final String tableName; + + public Inputs(GraphOperation op) { + super(new XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize(op), op, Arrays.asList("use_nesterov", "exponent", "beta1", "beta2", "epsilon", "clip_weight_min", "clip_weight_max", "max_ids_per_sparse_core", "max_unique_ids_per_sparse_core", "table_name")); + int inputIndex = 0; + rowPointers = (Operand) op.input(inputIndex++); + sortedSampleIds = (Operand) op.input(inputIndex++); + sortedTokenIds = (Operand) op.input(inputIndex++); + sortedGains = (Operand) op.input(inputIndex++); + activationGradients = (Operand) op.input(inputIndex++); + learningRate = (Operand) op.input(inputIndex++); + embeddingTable = (Operand) op.input(inputIndex++); + accumulator = (Operand) op.input(inputIndex++); + momenta = (Operand) op.input(inputIndex++); + numMinibatchesPerPhysicalSparseCore = (Operand) op.input(inputIndex++); + useNesterov = op.attributes().getAttrBool("use_nesterov"); + exponent = op.attributes().getAttrFloat("exponent"); + beta1 = op.attributes().getAttrFloat("beta1"); + beta2 = op.attributes().getAttrFloat("beta2"); + epsilon = op.attributes().getAttrFloat("epsilon"); + clipWeightMin = op.attributes().getAttrFloat("clip_weight_min"); + clipWeightMax = op.attributes().getAttrFloat("clip_weight_max"); + maxIdsPerSparseCore = op.attributes().getAttrInt("max_ids_per_sparse_core"); + maxUniqueIdsPerSparseCore = op.attributes().getAttrInt("max_unique_ids_per_sparse_core"); + tableName = op.attributes().getAttrString("table_name"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize.java new file mode 100644 index 00000000000..fe875c67f69 --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize.java @@ -0,0 +1,331 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.xla; + +import java.util.Arrays; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TInt32; + +/** + * The XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize operation + */ +@OpMetadata( + opType = XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize.OP_NAME, + inputsClass = XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize.Inputs.class +) +public final class XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize extends RawOp { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize"; + + private Output updatedEmbeddingTable; + + private Output updatedMomenta; + + private Output updatedVelocity; + + public XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + updatedEmbeddingTable = operation.output(outputIdx++); + updatedMomenta = operation.output(outputIdx++); + updatedVelocity = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize operation. + * + * @param scope current scope + * @param rowPointers The rowPointers value + * @param sortedSampleIds The sortedSampleIds value + * @param sortedTokenIds The sortedTokenIds value + * @param sortedGains The sortedGains value + * @param activationGradients The activationGradients value + * @param learningRate The learningRate value + * @param embeddingTable The embeddingTable value + * @param momenta The momenta value + * @param velocity The velocity value + * @param numMinibatchesPerPhysicalSparseCore The numMinibatchesPerPhysicalSparseCore value + * @param useSumInsideSqrt The value of the useSumInsideSqrt attribute + * @param beta1 The value of the beta1 attribute + * @param beta2 The value of the beta2 attribute + * @param epsilon The value of the epsilon attribute + * @param maxIdsPerSparseCore The value of the maxIdsPerSparseCore attribute + * @param maxUniqueIdsPerSparseCore The value of the maxUniqueIdsPerSparseCore attribute + * @param tableName The value of the tableName attribute + * @param options carries optional attribute values + * @return a new instance of XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize + */ + @Endpoint( + describeByClass = true + ) + public static XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize create(Scope scope, + Operand rowPointers, Operand sortedSampleIds, Operand sortedTokenIds, + Operand sortedGains, Operand activationGradients, + Operand learningRate, Operand embeddingTable, Operand momenta, + Operand velocity, Operand numMinibatchesPerPhysicalSparseCore, + Boolean useSumInsideSqrt, Float beta1, Float beta2, Float epsilon, Long maxIdsPerSparseCore, + Long maxUniqueIdsPerSparseCore, String tableName, Options... options) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize"); + opBuilder.addInput(rowPointers.asOutput()); + opBuilder.addInput(sortedSampleIds.asOutput()); + opBuilder.addInput(sortedTokenIds.asOutput()); + opBuilder.addInput(sortedGains.asOutput()); + opBuilder.addInput(activationGradients.asOutput()); + opBuilder.addInput(learningRate.asOutput()); + opBuilder.addInput(embeddingTable.asOutput()); + opBuilder.addInput(momenta.asOutput()); + opBuilder.addInput(velocity.asOutput()); + opBuilder.addInput(numMinibatchesPerPhysicalSparseCore.asOutput()); + opBuilder.setAttr("use_sum_inside_sqrt", useSumInsideSqrt); + opBuilder.setAttr("beta1", beta1); + opBuilder.setAttr("beta2", beta2); + opBuilder.setAttr("epsilon", epsilon); + opBuilder.setAttr("max_ids_per_sparse_core", maxIdsPerSparseCore); + opBuilder.setAttr("max_unique_ids_per_sparse_core", maxUniqueIdsPerSparseCore); + opBuilder.setAttr("table_name", tableName); + if (options != null) { + for (Options opts : options) { + if (opts.clipWeightMin != null) { + opBuilder.setAttr("clip_weight_min", opts.clipWeightMin); + } + if (opts.clipWeightMax != null) { + opBuilder.setAttr("clip_weight_max", opts.clipWeightMax); + } + } + } + return new XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize(opBuilder.build()); + } + + /** + * Sets the clipWeightMin option. + * + * @param clipWeightMin the clipWeightMin option + * @return this Options instance. + */ + public static Options clipWeightMin(Float clipWeightMin) { + return new Options().clipWeightMin(clipWeightMin); + } + + /** + * Sets the clipWeightMax option. + * + * @param clipWeightMax the clipWeightMax option + * @return this Options instance. + */ + public static Options clipWeightMax(Float clipWeightMax) { + return new Options().clipWeightMax(clipWeightMax); + } + + /** + * Gets updatedEmbeddingTable. + * + * @return updatedEmbeddingTable. + */ + public Output updatedEmbeddingTable() { + return updatedEmbeddingTable; + } + + /** + * Gets updatedMomenta. + * + * @return updatedMomenta. + */ + public Output updatedMomenta() { + return updatedMomenta; + } + + /** + * Gets updatedVelocity. + * + * @return updatedVelocity. + */ + public Output updatedVelocity() { + return updatedVelocity; + } + + /** + * Optional attributes for {@link org.tensorflow.op.xla.XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize} + */ + public static class Options { + private Float clipWeightMin; + + private Float clipWeightMax; + + private Options() { + } + + /** + * Sets the clipWeightMin option. + * + * @param clipWeightMin the clipWeightMin option + * @return this Options instance. + */ + public Options clipWeightMin(Float clipWeightMin) { + this.clipWeightMin = clipWeightMin; + return this; + } + + /** + * Sets the clipWeightMax option. + * + * @param clipWeightMax the clipWeightMax option + * @return this Options instance. + */ + public Options clipWeightMax(Float clipWeightMax) { + this.clipWeightMax = clipWeightMax; + return this; + } + } + + @OpInputsMetadata( + outputsClass = XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize.class + ) + public static class Inputs extends RawOpInputs { + /** + * The rowPointers input + */ + public final Operand rowPointers; + + /** + * The sortedSampleIds input + */ + public final Operand sortedSampleIds; + + /** + * The sortedTokenIds input + */ + public final Operand sortedTokenIds; + + /** + * The sortedGains input + */ + public final Operand sortedGains; + + /** + * The activationGradients input + */ + public final Operand activationGradients; + + /** + * The learningRate input + */ + public final Operand learningRate; + + /** + * The embeddingTable input + */ + public final Operand embeddingTable; + + /** + * The momenta input + */ + public final Operand momenta; + + /** + * The velocity input + */ + public final Operand velocity; + + /** + * The numMinibatchesPerPhysicalSparseCore input + */ + public final Operand numMinibatchesPerPhysicalSparseCore; + + /** + * The useSumInsideSqrt attribute + */ + public final boolean useSumInsideSqrt; + + /** + * The beta1 attribute + */ + public final float beta1; + + /** + * The beta2 attribute + */ + public final float beta2; + + /** + * The epsilon attribute + */ + public final float epsilon; + + /** + * The clipWeightMin attribute + */ + public final float clipWeightMin; + + /** + * The clipWeightMax attribute + */ + public final float clipWeightMax; + + /** + * The maxIdsPerSparseCore attribute + */ + public final long maxIdsPerSparseCore; + + /** + * The maxUniqueIdsPerSparseCore attribute + */ + public final long maxUniqueIdsPerSparseCore; + + /** + * The tableName attribute + */ + public final String tableName; + + public Inputs(GraphOperation op) { + super(new XlaSparseDenseMatmulGradWithAdamAndStaticBufferSize(op), op, Arrays.asList("use_sum_inside_sqrt", "beta1", "beta2", "epsilon", "clip_weight_min", "clip_weight_max", "max_ids_per_sparse_core", "max_unique_ids_per_sparse_core", "table_name")); + int inputIndex = 0; + rowPointers = (Operand) op.input(inputIndex++); + sortedSampleIds = (Operand) op.input(inputIndex++); + sortedTokenIds = (Operand) op.input(inputIndex++); + sortedGains = (Operand) op.input(inputIndex++); + activationGradients = (Operand) op.input(inputIndex++); + learningRate = (Operand) op.input(inputIndex++); + embeddingTable = (Operand) op.input(inputIndex++); + momenta = (Operand) op.input(inputIndex++); + velocity = (Operand) op.input(inputIndex++); + numMinibatchesPerPhysicalSparseCore = (Operand) op.input(inputIndex++); + useSumInsideSqrt = op.attributes().getAttrBool("use_sum_inside_sqrt"); + beta1 = op.attributes().getAttrFloat("beta1"); + beta2 = op.attributes().getAttrFloat("beta2"); + epsilon = op.attributes().getAttrFloat("epsilon"); + clipWeightMin = op.attributes().getAttrFloat("clip_weight_min"); + clipWeightMax = op.attributes().getAttrFloat("clip_weight_max"); + maxIdsPerSparseCore = op.attributes().getAttrInt("max_ids_per_sparse_core"); + maxUniqueIdsPerSparseCore = op.attributes().getAttrInt("max_unique_ids_per_sparse_core"); + tableName = op.attributes().getAttrString("table_name"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithCsrInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithCsrInput.java new file mode 100644 index 00000000000..7ac92263e93 --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithCsrInput.java @@ -0,0 +1,184 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.xla; + +import java.util.Arrays; +import java.util.Iterator; +import java.util.List; +import org.tensorflow.ConcreteFunction; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.op.Operands; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TInt32; + +/** + * The XlaSparseDenseMatmulGradWithCsrInput operation + */ +@OpMetadata( + opType = XlaSparseDenseMatmulGradWithCsrInput.OP_NAME, + inputsClass = XlaSparseDenseMatmulGradWithCsrInput.Inputs.class +) +public final class XlaSparseDenseMatmulGradWithCsrInput extends RawOp implements Iterable> { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "XlaSparseDenseMatmulGradWithCsrInput"; + + private List> updatedTables; + + @SuppressWarnings("unchecked") + public XlaSparseDenseMatmulGradWithCsrInput(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + int updatedTablesLength = operation.outputListLength("updated_tables"); + updatedTables = Arrays.asList((Output[]) operation.outputList(outputIdx, updatedTablesLength)); + outputIdx += updatedTablesLength; + } + + /** + * Factory method to create a class wrapping a new XlaSparseDenseMatmulGradWithCsrInput operation. + * + * @param scope current scope + * @param rowPointers The rowPointers value + * @param sortedSampleIds The sortedSampleIds value + * @param sortedTokenIds The sortedTokenIds value + * @param sortedGains The sortedGains value + * @param activationGradients The activationGradients value + * @param tables The tables value + * @param hyperparameters The hyperparameters value + * @param numMinibatchesPerPhysicalSparseCore The numMinibatchesPerPhysicalSparseCore value + * @param customComputation The value of the customComputation attribute + * @param tableName The value of the tableName attribute + * @return a new instance of XlaSparseDenseMatmulGradWithCsrInput + */ + @Endpoint( + describeByClass = true + ) + public static XlaSparseDenseMatmulGradWithCsrInput create(Scope scope, + Operand rowPointers, Operand sortedSampleIds, Operand sortedTokenIds, + Operand sortedGains, Operand activationGradients, + Iterable> tables, Iterable> hyperparameters, + Operand numMinibatchesPerPhysicalSparseCore, ConcreteFunction customComputation, + String tableName) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "XlaSparseDenseMatmulGradWithCsrInput"); + opBuilder.addInput(rowPointers.asOutput()); + opBuilder.addInput(sortedSampleIds.asOutput()); + opBuilder.addInput(sortedTokenIds.asOutput()); + opBuilder.addInput(sortedGains.asOutput()); + opBuilder.addInput(activationGradients.asOutput()); + opBuilder.addInputList(Operands.asOutputs(tables)); + opBuilder.addInputList(Operands.asOutputs(hyperparameters)); + opBuilder.addInput(numMinibatchesPerPhysicalSparseCore.asOutput()); + opBuilder.setAttr("custom_computation", customComputation); + opBuilder.setAttr("table_name", tableName); + return new XlaSparseDenseMatmulGradWithCsrInput(opBuilder.build()); + } + + /** + * Gets updatedTables. + * + * @return updatedTables. + */ + public List> updatedTables() { + return updatedTables; + } + + @Override + @SuppressWarnings({"rawtypes", "unchecked"}) + public Iterator> iterator() { + return (Iterator) updatedTables.iterator(); + } + + @OpInputsMetadata( + outputsClass = XlaSparseDenseMatmulGradWithCsrInput.class + ) + public static class Inputs extends RawOpInputs { + /** + * The rowPointers input + */ + public final Operand rowPointers; + + /** + * The sortedSampleIds input + */ + public final Operand sortedSampleIds; + + /** + * The sortedTokenIds input + */ + public final Operand sortedTokenIds; + + /** + * The sortedGains input + */ + public final Operand sortedGains; + + /** + * The activationGradients input + */ + public final Operand activationGradients; + + /** + * The tables input + */ + public final Iterable> tables; + + /** + * The hyperparameters input + */ + public final Iterable> hyperparameters; + + /** + * The numMinibatchesPerPhysicalSparseCore input + */ + public final Operand numMinibatchesPerPhysicalSparseCore; + + /** + * The tableName attribute + */ + public final String tableName; + + public Inputs(GraphOperation op) { + super(new XlaSparseDenseMatmulGradWithCsrInput(op), op, Arrays.asList("table_name")); + int inputIndex = 0; + rowPointers = (Operand) op.input(inputIndex++); + sortedSampleIds = (Operand) op.input(inputIndex++); + sortedTokenIds = (Operand) op.input(inputIndex++); + sortedGains = (Operand) op.input(inputIndex++); + activationGradients = (Operand) op.input(inputIndex++); + int tablesLength = op.inputListLength("tables"); + tables = Arrays.asList((Operand[]) op.inputList(inputIndex, tablesLength)); + inputIndex += tablesLength; + int hyperparametersLength = op.inputListLength("hyperparameters"); + hyperparameters = Arrays.asList((Operand[]) op.inputList(inputIndex, hyperparametersLength)); + inputIndex += hyperparametersLength; + numMinibatchesPerPhysicalSparseCore = (Operand) op.input(inputIndex++); + tableName = op.attributes().getAttrString("table_name"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize.java new file mode 100644 index 00000000000..7bfa0c2cc45 --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize.java @@ -0,0 +1,341 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.xla; + +import java.util.Arrays; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TInt32; + +/** + * The XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize operation + */ +@OpMetadata( + opType = XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize.OP_NAME, + inputsClass = XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize.Inputs.class +) +public final class XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize extends RawOp { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize"; + + private Output updatedEmbeddingTable; + + private Output updatedAccumulator; + + private Output updatedLinear; + + public XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + updatedEmbeddingTable = operation.output(outputIdx++); + updatedAccumulator = operation.output(outputIdx++); + updatedLinear = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize operation. + * + * @param scope current scope + * @param rowPointers The rowPointers value + * @param sortedSampleIds The sortedSampleIds value + * @param sortedTokenIds The sortedTokenIds value + * @param sortedGains The sortedGains value + * @param activationGradients The activationGradients value + * @param learningRate The learningRate value + * @param embeddingTable The embeddingTable value + * @param accumulator The accumulator value + * @param linear The linear value + * @param numMinibatchesPerPhysicalSparseCore The numMinibatchesPerPhysicalSparseCore value + * @param multiplyLinearByLearningRate The value of the multiplyLinearByLearningRate attribute + * @param beta The value of the beta attribute + * @param learningRatePower The value of the learningRatePower attribute + * @param l1RegularizationStrength The value of the l1RegularizationStrength attribute + * @param l2RegularizationStrength The value of the l2RegularizationStrength attribute + * @param maxIdsPerSparseCore The value of the maxIdsPerSparseCore attribute + * @param maxUniqueIdsPerSparseCore The value of the maxUniqueIdsPerSparseCore attribute + * @param tableName The value of the tableName attribute + * @param options carries optional attribute values + * @return a new instance of XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize + */ + @Endpoint( + describeByClass = true + ) + public static XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize create(Scope scope, + Operand rowPointers, Operand sortedSampleIds, Operand sortedTokenIds, + Operand sortedGains, Operand activationGradients, + Operand learningRate, Operand embeddingTable, + Operand accumulator, Operand linear, + Operand numMinibatchesPerPhysicalSparseCore, Boolean multiplyLinearByLearningRate, + Float beta, Float learningRatePower, Float l1RegularizationStrength, + Float l2RegularizationStrength, Long maxIdsPerSparseCore, Long maxUniqueIdsPerSparseCore, + String tableName, Options... options) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize"); + opBuilder.addInput(rowPointers.asOutput()); + opBuilder.addInput(sortedSampleIds.asOutput()); + opBuilder.addInput(sortedTokenIds.asOutput()); + opBuilder.addInput(sortedGains.asOutput()); + opBuilder.addInput(activationGradients.asOutput()); + opBuilder.addInput(learningRate.asOutput()); + opBuilder.addInput(embeddingTable.asOutput()); + opBuilder.addInput(accumulator.asOutput()); + opBuilder.addInput(linear.asOutput()); + opBuilder.addInput(numMinibatchesPerPhysicalSparseCore.asOutput()); + opBuilder.setAttr("multiply_linear_by_learning_rate", multiplyLinearByLearningRate); + opBuilder.setAttr("beta", beta); + opBuilder.setAttr("learning_rate_power", learningRatePower); + opBuilder.setAttr("l1_regularization_strength", l1RegularizationStrength); + opBuilder.setAttr("l2_regularization_strength", l2RegularizationStrength); + opBuilder.setAttr("max_ids_per_sparse_core", maxIdsPerSparseCore); + opBuilder.setAttr("max_unique_ids_per_sparse_core", maxUniqueIdsPerSparseCore); + opBuilder.setAttr("table_name", tableName); + if (options != null) { + for (Options opts : options) { + if (opts.clipWeightMin != null) { + opBuilder.setAttr("clip_weight_min", opts.clipWeightMin); + } + if (opts.clipWeightMax != null) { + opBuilder.setAttr("clip_weight_max", opts.clipWeightMax); + } + } + } + return new XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize(opBuilder.build()); + } + + /** + * Sets the clipWeightMin option. + * + * @param clipWeightMin the clipWeightMin option + * @return this Options instance. + */ + public static Options clipWeightMin(Float clipWeightMin) { + return new Options().clipWeightMin(clipWeightMin); + } + + /** + * Sets the clipWeightMax option. + * + * @param clipWeightMax the clipWeightMax option + * @return this Options instance. + */ + public static Options clipWeightMax(Float clipWeightMax) { + return new Options().clipWeightMax(clipWeightMax); + } + + /** + * Gets updatedEmbeddingTable. + * + * @return updatedEmbeddingTable. + */ + public Output updatedEmbeddingTable() { + return updatedEmbeddingTable; + } + + /** + * Gets updatedAccumulator. + * + * @return updatedAccumulator. + */ + public Output updatedAccumulator() { + return updatedAccumulator; + } + + /** + * Gets updatedLinear. + * + * @return updatedLinear. + */ + public Output updatedLinear() { + return updatedLinear; + } + + /** + * Optional attributes for {@link org.tensorflow.op.xla.XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize} + */ + public static class Options { + private Float clipWeightMin; + + private Float clipWeightMax; + + private Options() { + } + + /** + * Sets the clipWeightMin option. + * + * @param clipWeightMin the clipWeightMin option + * @return this Options instance. + */ + public Options clipWeightMin(Float clipWeightMin) { + this.clipWeightMin = clipWeightMin; + return this; + } + + /** + * Sets the clipWeightMax option. + * + * @param clipWeightMax the clipWeightMax option + * @return this Options instance. + */ + public Options clipWeightMax(Float clipWeightMax) { + this.clipWeightMax = clipWeightMax; + return this; + } + } + + @OpInputsMetadata( + outputsClass = XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize.class + ) + public static class Inputs extends RawOpInputs { + /** + * The rowPointers input + */ + public final Operand rowPointers; + + /** + * The sortedSampleIds input + */ + public final Operand sortedSampleIds; + + /** + * The sortedTokenIds input + */ + public final Operand sortedTokenIds; + + /** + * The sortedGains input + */ + public final Operand sortedGains; + + /** + * The activationGradients input + */ + public final Operand activationGradients; + + /** + * The learningRate input + */ + public final Operand learningRate; + + /** + * The embeddingTable input + */ + public final Operand embeddingTable; + + /** + * The accumulator input + */ + public final Operand accumulator; + + /** + * The linear input + */ + public final Operand linear; + + /** + * The numMinibatchesPerPhysicalSparseCore input + */ + public final Operand numMinibatchesPerPhysicalSparseCore; + + /** + * The multiplyLinearByLearningRate attribute + */ + public final boolean multiplyLinearByLearningRate; + + /** + * The beta attribute + */ + public final float beta; + + /** + * The learningRatePower attribute + */ + public final float learningRatePower; + + /** + * The l1RegularizationStrength attribute + */ + public final float l1RegularizationStrength; + + /** + * The l2RegularizationStrength attribute + */ + public final float l2RegularizationStrength; + + /** + * The clipWeightMin attribute + */ + public final float clipWeightMin; + + /** + * The clipWeightMax attribute + */ + public final float clipWeightMax; + + /** + * The maxIdsPerSparseCore attribute + */ + public final long maxIdsPerSparseCore; + + /** + * The maxUniqueIdsPerSparseCore attribute + */ + public final long maxUniqueIdsPerSparseCore; + + /** + * The tableName attribute + */ + public final String tableName; + + public Inputs(GraphOperation op) { + super(new XlaSparseDenseMatmulGradWithFtrlAndStaticBufferSize(op), op, Arrays.asList("multiply_linear_by_learning_rate", "beta", "learning_rate_power", "l1_regularization_strength", "l2_regularization_strength", "clip_weight_min", "clip_weight_max", "max_ids_per_sparse_core", "max_unique_ids_per_sparse_core", "table_name")); + int inputIndex = 0; + rowPointers = (Operand) op.input(inputIndex++); + sortedSampleIds = (Operand) op.input(inputIndex++); + sortedTokenIds = (Operand) op.input(inputIndex++); + sortedGains = (Operand) op.input(inputIndex++); + activationGradients = (Operand) op.input(inputIndex++); + learningRate = (Operand) op.input(inputIndex++); + embeddingTable = (Operand) op.input(inputIndex++); + accumulator = (Operand) op.input(inputIndex++); + linear = (Operand) op.input(inputIndex++); + numMinibatchesPerPhysicalSparseCore = (Operand) op.input(inputIndex++); + multiplyLinearByLearningRate = op.attributes().getAttrBool("multiply_linear_by_learning_rate"); + beta = op.attributes().getAttrFloat("beta"); + learningRatePower = op.attributes().getAttrFloat("learning_rate_power"); + l1RegularizationStrength = op.attributes().getAttrFloat("l1_regularization_strength"); + l2RegularizationStrength = op.attributes().getAttrFloat("l2_regularization_strength"); + clipWeightMin = op.attributes().getAttrFloat("clip_weight_min"); + clipWeightMax = op.attributes().getAttrFloat("clip_weight_max"); + maxIdsPerSparseCore = op.attributes().getAttrInt("max_ids_per_sparse_core"); + maxUniqueIdsPerSparseCore = op.attributes().getAttrInt("max_unique_ids_per_sparse_core"); + tableName = op.attributes().getAttrString("table_name"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize.java new file mode 100644 index 00000000000..65c059d2821 --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize.java @@ -0,0 +1,263 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.xla; + +import java.util.Arrays; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TInt32; + +/** + * The XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize operation + */ +@OpMetadata( + opType = XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize.OP_NAME, + inputsClass = XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize.Inputs.class +) +public final class XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize extends RawOp implements Operand { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize"; + + private Output updatedEmbeddingTable; + + public XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + updatedEmbeddingTable = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize operation. + * + * @param scope current scope + * @param rowPointers The rowPointers value + * @param sortedSampleIds The sortedSampleIds value + * @param sortedTokenIds The sortedTokenIds value + * @param sortedGains The sortedGains value + * @param activationGradients The activationGradients value + * @param learningRate The learningRate value + * @param embeddingTable The embeddingTable value + * @param numMinibatchesPerPhysicalSparseCore The numMinibatchesPerPhysicalSparseCore value + * @param maxIdsPerSparseCore The value of the maxIdsPerSparseCore attribute + * @param maxUniqueIdsPerSparseCore The value of the maxUniqueIdsPerSparseCore attribute + * @param tableName The value of the tableName attribute + * @param options carries optional attribute values + * @return a new instance of XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize + */ + @Endpoint( + describeByClass = true + ) + public static XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize create(Scope scope, + Operand rowPointers, Operand sortedSampleIds, Operand sortedTokenIds, + Operand sortedGains, Operand activationGradients, + Operand learningRate, Operand embeddingTable, + Operand numMinibatchesPerPhysicalSparseCore, Long maxIdsPerSparseCore, + Long maxUniqueIdsPerSparseCore, String tableName, Options... options) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize"); + opBuilder.addInput(rowPointers.asOutput()); + opBuilder.addInput(sortedSampleIds.asOutput()); + opBuilder.addInput(sortedTokenIds.asOutput()); + opBuilder.addInput(sortedGains.asOutput()); + opBuilder.addInput(activationGradients.asOutput()); + opBuilder.addInput(learningRate.asOutput()); + opBuilder.addInput(embeddingTable.asOutput()); + opBuilder.addInput(numMinibatchesPerPhysicalSparseCore.asOutput()); + opBuilder.setAttr("max_ids_per_sparse_core", maxIdsPerSparseCore); + opBuilder.setAttr("max_unique_ids_per_sparse_core", maxUniqueIdsPerSparseCore); + opBuilder.setAttr("table_name", tableName); + if (options != null) { + for (Options opts : options) { + if (opts.clipWeightMin != null) { + opBuilder.setAttr("clip_weight_min", opts.clipWeightMin); + } + if (opts.clipWeightMax != null) { + opBuilder.setAttr("clip_weight_max", opts.clipWeightMax); + } + } + } + return new XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize(opBuilder.build()); + } + + /** + * Sets the clipWeightMin option. + * + * @param clipWeightMin the clipWeightMin option + * @return this Options instance. + */ + public static Options clipWeightMin(Float clipWeightMin) { + return new Options().clipWeightMin(clipWeightMin); + } + + /** + * Sets the clipWeightMax option. + * + * @param clipWeightMax the clipWeightMax option + * @return this Options instance. + */ + public static Options clipWeightMax(Float clipWeightMax) { + return new Options().clipWeightMax(clipWeightMax); + } + + /** + * Gets updatedEmbeddingTable. + * + * @return updatedEmbeddingTable. + */ + public Output updatedEmbeddingTable() { + return updatedEmbeddingTable; + } + + @Override + public Output asOutput() { + return updatedEmbeddingTable; + } + + /** + * Optional attributes for {@link org.tensorflow.op.xla.XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize} + */ + public static class Options { + private Float clipWeightMin; + + private Float clipWeightMax; + + private Options() { + } + + /** + * Sets the clipWeightMin option. + * + * @param clipWeightMin the clipWeightMin option + * @return this Options instance. + */ + public Options clipWeightMin(Float clipWeightMin) { + this.clipWeightMin = clipWeightMin; + return this; + } + + /** + * Sets the clipWeightMax option. + * + * @param clipWeightMax the clipWeightMax option + * @return this Options instance. + */ + public Options clipWeightMax(Float clipWeightMax) { + this.clipWeightMax = clipWeightMax; + return this; + } + } + + @OpInputsMetadata( + outputsClass = XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize.class + ) + public static class Inputs extends RawOpInputs { + /** + * The rowPointers input + */ + public final Operand rowPointers; + + /** + * The sortedSampleIds input + */ + public final Operand sortedSampleIds; + + /** + * The sortedTokenIds input + */ + public final Operand sortedTokenIds; + + /** + * The sortedGains input + */ + public final Operand sortedGains; + + /** + * The activationGradients input + */ + public final Operand activationGradients; + + /** + * The learningRate input + */ + public final Operand learningRate; + + /** + * The embeddingTable input + */ + public final Operand embeddingTable; + + /** + * The numMinibatchesPerPhysicalSparseCore input + */ + public final Operand numMinibatchesPerPhysicalSparseCore; + + /** + * The clipWeightMin attribute + */ + public final float clipWeightMin; + + /** + * The clipWeightMax attribute + */ + public final float clipWeightMax; + + /** + * The maxIdsPerSparseCore attribute + */ + public final long maxIdsPerSparseCore; + + /** + * The maxUniqueIdsPerSparseCore attribute + */ + public final long maxUniqueIdsPerSparseCore; + + /** + * The tableName attribute + */ + public final String tableName; + + public Inputs(GraphOperation op) { + super(new XlaSparseDenseMatmulGradWithSgdAndStaticBufferSize(op), op, Arrays.asList("clip_weight_min", "clip_weight_max", "max_ids_per_sparse_core", "max_unique_ids_per_sparse_core", "table_name")); + int inputIndex = 0; + rowPointers = (Operand) op.input(inputIndex++); + sortedSampleIds = (Operand) op.input(inputIndex++); + sortedTokenIds = (Operand) op.input(inputIndex++); + sortedGains = (Operand) op.input(inputIndex++); + activationGradients = (Operand) op.input(inputIndex++); + learningRate = (Operand) op.input(inputIndex++); + embeddingTable = (Operand) op.input(inputIndex++); + numMinibatchesPerPhysicalSparseCore = (Operand) op.input(inputIndex++); + clipWeightMin = op.attributes().getAttrFloat("clip_weight_min"); + clipWeightMax = op.attributes().getAttrFloat("clip_weight_max"); + maxIdsPerSparseCore = op.attributes().getAttrInt("max_ids_per_sparse_core"); + maxUniqueIdsPerSparseCore = op.attributes().getAttrInt("max_unique_ids_per_sparse_core"); + tableName = op.attributes().getAttrString("table_name"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulWithStaticBufferSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulWithStaticBufferSize.java new file mode 100644 index 00000000000..268a9b0fc4b --- /dev/null +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulWithStaticBufferSize.java @@ -0,0 +1,202 @@ +/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +=======================================================================*/ + +// This class has been generated, DO NOT EDIT! + +package org.tensorflow.op.xla; + +import java.util.Arrays; +import org.tensorflow.GraphOperation; +import org.tensorflow.Operand; +import org.tensorflow.Operation; +import org.tensorflow.OperationBuilder; +import org.tensorflow.Output; +import org.tensorflow.op.RawOp; +import org.tensorflow.op.RawOpInputs; +import org.tensorflow.op.Scope; +import org.tensorflow.op.annotation.Endpoint; +import org.tensorflow.op.annotation.OpInputsMetadata; +import org.tensorflow.op.annotation.OpMetadata; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TInt32; + +/** + * The XlaSparseDenseMatmulWithStaticBufferSize operation + */ +@OpMetadata( + opType = XlaSparseDenseMatmulWithStaticBufferSize.OP_NAME, + inputsClass = XlaSparseDenseMatmulWithStaticBufferSize.Inputs.class +) +public final class XlaSparseDenseMatmulWithStaticBufferSize extends RawOp implements Operand { + /** + * The name of this op, as known by TensorFlow core engine + */ + public static final String OP_NAME = "XlaSparseDenseMatmulWithStaticBufferSize"; + + private Output activations; + + public XlaSparseDenseMatmulWithStaticBufferSize(Operation operation) { + super(operation, OP_NAME); + int outputIdx = 0; + activations = operation.output(outputIdx++); + } + + /** + * Factory method to create a class wrapping a new XlaSparseDenseMatmulWithStaticBufferSize operation. + * + * @param scope current scope + * @param rowPointers The rowPointers value + * @param sortedSampleIds The sortedSampleIds value + * @param sortedTokenIds The sortedTokenIds value + * @param sortedGains The sortedGains value + * @param embeddingTable The embeddingTable value + * @param numMinibatchesPerPhysicalSparseCore The numMinibatchesPerPhysicalSparseCore value + * @param inputSize The value of the inputSize attribute + * @param quantizationConfigLow The value of the quantizationConfigLow attribute + * @param quantizationConfigHigh The value of the quantizationConfigHigh attribute + * @param quantizationConfigNumBuckets The value of the quantizationConfigNumBuckets attribute + * @param maxIdsPerSparseCore The value of the maxIdsPerSparseCore attribute + * @param maxUniqueIdsPerSparseCore The value of the maxUniqueIdsPerSparseCore attribute + * @param tableName The value of the tableName attribute + * @return a new instance of XlaSparseDenseMatmulWithStaticBufferSize + */ + @Endpoint( + describeByClass = true + ) + public static XlaSparseDenseMatmulWithStaticBufferSize create(Scope scope, + Operand rowPointers, Operand sortedSampleIds, Operand sortedTokenIds, + Operand sortedGains, Operand embeddingTable, + Operand numMinibatchesPerPhysicalSparseCore, Long inputSize, + Float quantizationConfigLow, Float quantizationConfigHigh, Long quantizationConfigNumBuckets, + Long maxIdsPerSparseCore, Long maxUniqueIdsPerSparseCore, String tableName) { + OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "XlaSparseDenseMatmulWithStaticBufferSize"); + opBuilder.addInput(rowPointers.asOutput()); + opBuilder.addInput(sortedSampleIds.asOutput()); + opBuilder.addInput(sortedTokenIds.asOutput()); + opBuilder.addInput(sortedGains.asOutput()); + opBuilder.addInput(embeddingTable.asOutput()); + opBuilder.addInput(numMinibatchesPerPhysicalSparseCore.asOutput()); + opBuilder.setAttr("input_size", inputSize); + opBuilder.setAttr("quantization_config_low", quantizationConfigLow); + opBuilder.setAttr("quantization_config_high", quantizationConfigHigh); + opBuilder.setAttr("quantization_config_num_buckets", quantizationConfigNumBuckets); + opBuilder.setAttr("max_ids_per_sparse_core", maxIdsPerSparseCore); + opBuilder.setAttr("max_unique_ids_per_sparse_core", maxUniqueIdsPerSparseCore); + opBuilder.setAttr("table_name", tableName); + return new XlaSparseDenseMatmulWithStaticBufferSize(opBuilder.build()); + } + + /** + * Gets activations. + * + * @return activations. + */ + public Output activations() { + return activations; + } + + @Override + public Output asOutput() { + return activations; + } + + @OpInputsMetadata( + outputsClass = XlaSparseDenseMatmulWithStaticBufferSize.class + ) + public static class Inputs extends RawOpInputs { + /** + * The rowPointers input + */ + public final Operand rowPointers; + + /** + * The sortedSampleIds input + */ + public final Operand sortedSampleIds; + + /** + * The sortedTokenIds input + */ + public final Operand sortedTokenIds; + + /** + * The sortedGains input + */ + public final Operand sortedGains; + + /** + * The embeddingTable input + */ + public final Operand embeddingTable; + + /** + * The numMinibatchesPerPhysicalSparseCore input + */ + public final Operand numMinibatchesPerPhysicalSparseCore; + + /** + * The inputSize attribute + */ + public final long inputSize; + + /** + * The quantizationConfigLow attribute + */ + public final float quantizationConfigLow; + + /** + * The quantizationConfigHigh attribute + */ + public final float quantizationConfigHigh; + + /** + * The quantizationConfigNumBuckets attribute + */ + public final long quantizationConfigNumBuckets; + + /** + * The maxIdsPerSparseCore attribute + */ + public final long maxIdsPerSparseCore; + + /** + * The maxUniqueIdsPerSparseCore attribute + */ + public final long maxUniqueIdsPerSparseCore; + + /** + * The tableName attribute + */ + public final String tableName; + + public Inputs(GraphOperation op) { + super(new XlaSparseDenseMatmulWithStaticBufferSize(op), op, Arrays.asList("input_size", "quantization_config_low", "quantization_config_high", "quantization_config_num_buckets", "max_ids_per_sparse_core", "max_unique_ids_per_sparse_core", "table_name")); + int inputIndex = 0; + rowPointers = (Operand) op.input(inputIndex++); + sortedSampleIds = (Operand) op.input(inputIndex++); + sortedTokenIds = (Operand) op.input(inputIndex++); + sortedGains = (Operand) op.input(inputIndex++); + embeddingTable = (Operand) op.input(inputIndex++); + numMinibatchesPerPhysicalSparseCore = (Operand) op.input(inputIndex++); + inputSize = op.attributes().getAttrInt("input_size"); + quantizationConfigLow = op.attributes().getAttrFloat("quantization_config_low"); + quantizationConfigHigh = op.attributes().getAttrFloat("quantization_config_high"); + quantizationConfigNumBuckets = op.attributes().getAttrInt("quantization_config_num_buckets"); + maxIdsPerSparseCore = op.attributes().getAttrInt("max_ids_per_sparse_core"); + maxUniqueIdsPerSparseCore = op.attributes().getAttrInt("max_unique_ids_per_sparse_core"); + tableName = op.attributes().getAttrString("table_name"); + } + } +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/internal/c_api/global/tensorflow.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/internal/c_api/global/tensorflow.java index 8461874c1bc..8a6ef604683 100644 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/internal/c_api/global/tensorflow.java +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/internal/c_api/global/tensorflow.java @@ -1,4 +1,4 @@ -// Targeted by JavaCPP version 1.5.10: DO NOT EDIT THIS FILE +// Targeted by JavaCPP version 1.5.12-SNAPSHOT: DO NOT EDIT THIS FILE package org.tensorflow.internal.c_api.global; @@ -274,9 +274,9 @@ public static native void TF_TString_Copy(TF_TString dst, String src, // #endif // TENSORFLOW_TSL_PLATFORM_CTSTRING_H_ -// Parsed from tsl/platform/status.h +// Parsed from xla/tsl/c/tsl_status.h -/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. +/* Copyright 2019 The TensorFlow Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. @@ -291,130 +291,67 @@ public static native void TF_TString_Copy(TF_TString dst, String src, limitations under the License. ==============================================================================*/ -// #ifndef TENSORFLOW_TSL_PLATFORM_STATUS_H_ -// #define TENSORFLOW_TSL_PLATFORM_STATUS_H_ +// #ifndef XLA_TSL_C_TSL_STATUS_H_ +// #define XLA_TSL_C_TSL_STATUS_H_ -// #include -// #include -// #include -// #include -// #include -// #include -// #include -// #include - -// #include "absl/base/attributes.h" -// #include "absl/base/macros.h" -// #include "absl/functional/function_ref.h" -// #include "absl/status/status.h" -// #include "absl/strings/cord.h" -// #include "absl/strings/string_view.h" -// #include "absl/types/optional.h" -// #include "tsl/platform/logging.h" -// #include "tsl/platform/macros.h" -// #include "tsl/platform/platform.h" -// #include "tsl/platform/stack_frame.h" -// #include "tsl/platform/types.h" -// #include "tsl/protobuf/error_codes.pb.h" - -// Include appropriate platform-dependent parts of status. -// #if defined(PLATFORM_GOOGLE) -// #include "tsl/platform/google/status.h" // IWYU pragma: export -// #else -// #include "tsl/platform/default/status.h" // IWYU pragma: export +// #ifdef __cplusplus // #endif -// TODO: b/323943471 - This macro should eventually be provided by Abseil. -// #ifndef ABSL_DEPRECATE_AND_INLINE -// #define ABSL_DEPRECATE_AND_INLINE() -// #endif +// -------------------------------------------------------------------------- +// TSL_Code holds an error code. The enum values here are identical to +// corresponding values in error_codes.proto. +/** enum TSL_Code */ +public static final int + TSL_OK = 0, + TSL_CANCELLED = 1, + TSL_UNKNOWN = 2, + TSL_INVALID_ARGUMENT = 3, + TSL_DEADLINE_EXCEEDED = 4, + TSL_NOT_FOUND = 5, + TSL_ALREADY_EXISTS = 6, + TSL_PERMISSION_DENIED = 7, + TSL_UNAUTHENTICATED = 16, + TSL_RESOURCE_EXHAUSTED = 8, + TSL_FAILED_PRECONDITION = 9, + TSL_ABORTED = 10, + TSL_OUT_OF_RANGE = 11, + TSL_UNIMPLEMENTED = 12, + TSL_INTERNAL = 13, + TSL_UNAVAILABLE = 14, + TSL_DATA_LOSS = 15; -// Since April 2023, tensorflow::Status is an alias to absl::Status. The first -// TF release including this change will be TF 2.14 (the latest release in -// April 2023 is 2.13). -// At the same time `tsl::errors::Code` aliases `absl::StatusCode`. -// -// Here is a set of correspondences: -// - Use `absl::OkStatus()` instead of `tsl::OkStatus()`. - // namespace errors - // namespace error - // namespace tsl - -// Transparent comparison between tensorflow::error::Code protobuf enum and -// absl::Status. -// -// The longer term objective is to delete these when we have done the transition -// to absl::Status. -@Namespace("tensorflow::error") public static native @Cast("bool") @Name("operator ==") boolean equals(@Const @ByRef Code c1, - @Const @ByRef StatusCode c2); - -@Namespace("tensorflow::error") public static native @Cast("bool") @Name("operator !=") boolean notEquals(@Const @ByRef Code c1, - @Const @ByRef StatusCode c2); - // namespace tensorflow::error -@Namespace("absl") public static native @Cast("bool") @Name("operator ==") boolean equals(@Const @ByRef StatusCode c1, - @Const @ByRef Code c2); - -@Namespace("absl") public static native @Cast("bool") @Name("operator !=") boolean notEquals(@Const @ByRef StatusCode c1, - @Const @ByRef Code c2); - // namespace absl - -// OkStatus() -// -// Returns an OK status, equivalent to a default constructed instance. Prefer -// usage of `OkStatus()` when constructing such an OK status. -@Namespace("tsl") public static native @ByVal Status OkStatus(); - -@Namespace("tsl") public static native @ByVal Status FromAbslStatus(@Const @ByRef Status s); -@Namespace("tsl") public static native @ByVal Status ToAbslStatus(@Const @ByRef Status s); - -// Given `Status.message()` does not guarantee to be always backed by a -// null-terminated string, we have this utility function when it's needed for -// the Tensorflow C-API. -// A more robust API would be to get both a `char*` of the beginning of the -// string, plus the size (see e.g. `XlaCustomCallStatusSetFailure`). -// NB: This Windows-only implementation is exists only to avoid a linker error. -// Remove if this is resolved. -// #ifdef _WIN32 -@Namespace("tsl") public static native @Cast("const char*") BytePointer NullTerminatedMessage(@Const @ByRef Status status); -// #else -// #endif +// -------------------------------------------------------------------------- -// TODO(b/197552541) Move this namespace to errors.h. +// Return a new status object. -@Namespace("tsl::errors") public static native void SetStackTrace(@ByRef Status status, @StdVector StackFrame stack_trace); +// Delete a previously created status object. -@Namespace("tsl::errors") public static native @StdVector StackFrame GetStackTrace(@Const @ByRef Status status); - // namespace errors +// Record in *s. Any previous information is lost. +// A common use is to clear a status: TSL_SetStatus(s, TSL_OK, ""); -// Helper class to manage multiple child status values. +// Record as a payload in *s. The previous payload having the +// same key (if any) is overwritten. Payload will not be added if the Status +// is OK. -@Namespace("tsl") public static native string TfCheckOpHelperOutOfLine(@Const @ByRef Status v, - @Cast("const char*") BytePointer msg); -@Namespace("tsl") public static native string TfCheckOpHelperOutOfLine(@Const @ByRef Status v, - String msg); +// Iterates over the stored payloads and calls the `visitor(key, value)` +// callable for each one. `key` and `value` is only usable during the callback. +// `capture` will be passed to the callback without modification. -@Namespace("tsl") public static native string TfCheckOpHelper(@ByVal Status v, @Cast("const char*") BytePointer msg); -@Namespace("tsl") public static native string TfCheckOpHelper(@ByVal Status v, String msg); +// Convert from an I/O error code (e.g., errno) to a TSL_Status value. +// Any previous information is lost. Prefer to use this instead of TSL_SetStatus +// when the error comes from I/O operations. -// #define TF_DO_CHECK_OK(val, level) -// while (auto* _result = ::tsl::TfCheckOpHelper(val, #val)) -// LOG(level) << *(_result) +// Return the code record in *s. -// #define TF_CHECK_OK(val) TF_DO_CHECK_OK(val, FATAL) -// #define TF_QCHECK_OK(val) TF_DO_CHECK_OK(val, QFATAL) +// Return a pointer to the (null-terminated) error message in *s. The +// return value points to memory that is only usable until the next +// mutation to *s. Always returns an empty string if TSL_GetCode(s) is +// TSL_OK. -// DEBUG only version of TF_CHECK_OK. Compiler still parses 'val' even in opt -// mode. -// #ifndef NDEBUG -// #define TF_DCHECK_OK(val) TF_CHECK_OK(val) -// #else -// #define TF_DCHECK_OK(val) -// while (false && (::tsl::OkStatus() == (val))) LOG(FATAL) +// #ifdef __cplusplus /* end extern "C" */ // #endif - // namespace tsl - -// #endif // TENSORFLOW_TSL_PLATFORM_STATUS_H_ +// #endif // XLA_TSL_C_TSL_STATUS_H_ // Parsed from tensorflow/c/c_api_macros.h @@ -610,9 +547,9 @@ public static native void TF_TString_Copy(TF_TString dst, String src, // Record in *s. Any previous information is lost. // A common use is to clear a status: TF_SetStatus(s, TF_OK, ""); -public static native void TF_SetStatus(TF_Status s, @ByVal @Cast("TF_Code*") TSL_Code code, +public static native void TF_SetStatus(TF_Status s, @Cast("TF_Code") int code, @Cast("const char*") BytePointer msg); -public static native void TF_SetStatus(TF_Status s, @ByVal @Cast("TF_Code*") TSL_Code code, +public static native void TF_SetStatus(TF_Status s, @Cast("TF_Code") int code, String msg); // Record as a payload in *s. The previous payload having the @@ -638,7 +575,7 @@ public static native void TF_SetStatusFromIOError(TF_Status s, int error_code, String context); // Return the code record in *s. -public static native @ByVal @Cast("TF_Code*") TSL_Code TF_GetCode(@Const TF_Status s); +public static native @Cast("TF_Code") int TF_GetCode(@Const TF_Status s); // Return a pointer to the (null-terminated) error message in *s. The // return value points to memory that is only usable until the next diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/AvailableDeviceInfo.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/AvailableDeviceInfo.java new file mode 100644 index 00000000000..50aa7d93009 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/AvailableDeviceInfo.java @@ -0,0 +1,985 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +/** + * 

    + * Matches DeviceAttributes
+ *
    + * + * Protobuf type {@code tensorflow.AvailableDeviceInfo} + */ +public final class AvailableDeviceInfo extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.AvailableDeviceInfo) + AvailableDeviceInfoOrBuilder { +private static final long serialVersionUID = 0L; + // Use AvailableDeviceInfo.newBuilder() to construct. + private AvailableDeviceInfo(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private AvailableDeviceInfo() { + name_ = ""; + type_ = ""; + physicalDescription_ = ""; + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new AvailableDeviceInfo(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_AvailableDeviceInfo_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_AvailableDeviceInfo_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.AvailableDeviceInfo.class, org.tensorflow.proto.AvailableDeviceInfo.Builder.class); + } + + public static final int NAME_FIELD_NUMBER = 1; + private volatile java.lang.Object name_; + /** + * 
    +   * Device name.
+   *
    + * + * string name = 1; + * @return The name. + */ + @java.lang.Override + public java.lang.String getName() { + java.lang.Object ref = name_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + name_ = s; + return s; + } + } + /** + * 
    +   * Device name.
+   *
    + * + * string name = 1; + * @return The bytes for name. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getNameBytes() { + java.lang.Object ref = name_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + name_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int TYPE_FIELD_NUMBER = 2; + private volatile java.lang.Object type_; + /** + * 
    +   * Device type, e.g. 'CPU' or 'GPU'.
+   *
    + * + * string type = 2; + * @return The type. + */ + @java.lang.Override + public java.lang.String getType() { + java.lang.Object ref = type_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + type_ = s; + return s; + } + } + /** + * 
    +   * Device type, e.g. 'CPU' or 'GPU'.
+   *
    + * + * string type = 2; + * @return The bytes for type. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getTypeBytes() { + java.lang.Object ref = type_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + type_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int MEMORY_LIMIT_FIELD_NUMBER = 3; + private long memoryLimit_; + /** + * 
    +   * Memory capacity in bytes.
+   *
    + * + * int64 memory_limit = 3; + * @return The memoryLimit. + */ + @java.lang.Override + public long getMemoryLimit() { + return memoryLimit_; + } + + public static final int PHYSICAL_DESCRIPTION_FIELD_NUMBER = 4; + private volatile java.lang.Object physicalDescription_; + /** + * 
    +   * The physical description of this device.
+   *
    + * + * string physical_description = 4; + * @return The physicalDescription. + */ + @java.lang.Override + public java.lang.String getPhysicalDescription() { + java.lang.Object ref = physicalDescription_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + physicalDescription_ = s; + return s; + } + } + /** + * 
    +   * The physical description of this device.
+   *
    + * + * string physical_description = 4; + * @return The bytes for physicalDescription. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getPhysicalDescriptionBytes() { + java.lang.Object ref = physicalDescription_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + physicalDescription_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 1, name_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(type_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 2, type_); + } + if (memoryLimit_ != 0L) { + output.writeInt64(3, memoryLimit_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(physicalDescription_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 4, physicalDescription_); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, name_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(type_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(2, type_); + } + if (memoryLimit_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(3, memoryLimit_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(physicalDescription_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(4, physicalDescription_); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.AvailableDeviceInfo)) { + return super.equals(obj); + } + org.tensorflow.proto.AvailableDeviceInfo other = (org.tensorflow.proto.AvailableDeviceInfo) obj; + + if (!getName() + .equals(other.getName())) return false; + if (!getType() + .equals(other.getType())) return false; + if (getMemoryLimit() + != other.getMemoryLimit()) return false; + if (!getPhysicalDescription() + .equals(other.getPhysicalDescription())) return false; + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + NAME_FIELD_NUMBER; + hash = (53 * hash) + getName().hashCode(); + hash = (37 * hash) + TYPE_FIELD_NUMBER; + hash = (53 * hash) + getType().hashCode(); + hash = (37 * hash) + MEMORY_LIMIT_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getMemoryLimit()); + hash = (37 * hash) + PHYSICAL_DESCRIPTION_FIELD_NUMBER; + hash = (53 * hash) + getPhysicalDescription().hashCode(); + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.AvailableDeviceInfo parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.AvailableDeviceInfo parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.AvailableDeviceInfo parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.AvailableDeviceInfo parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.AvailableDeviceInfo parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.AvailableDeviceInfo prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * 
    +   * Matches DeviceAttributes
+   *
    + * + * Protobuf type {@code tensorflow.AvailableDeviceInfo} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.AvailableDeviceInfo) + org.tensorflow.proto.AvailableDeviceInfoOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_AvailableDeviceInfo_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_AvailableDeviceInfo_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.AvailableDeviceInfo.class, org.tensorflow.proto.AvailableDeviceInfo.Builder.class); + } + + // Construct using org.tensorflow.proto.AvailableDeviceInfo.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + name_ = ""; + + type_ = ""; + + memoryLimit_ = 0L; + + physicalDescription_ = ""; + + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_AvailableDeviceInfo_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.AvailableDeviceInfo getDefaultInstanceForType() { + return org.tensorflow.proto.AvailableDeviceInfo.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.AvailableDeviceInfo build() { + org.tensorflow.proto.AvailableDeviceInfo result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.AvailableDeviceInfo buildPartial() { + org.tensorflow.proto.AvailableDeviceInfo result = new org.tensorflow.proto.AvailableDeviceInfo(this); + result.name_ = name_; + result.type_ = type_; + result.memoryLimit_ = memoryLimit_; + result.physicalDescription_ = physicalDescription_; + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.AvailableDeviceInfo) { + return mergeFrom((org.tensorflow.proto.AvailableDeviceInfo)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.AvailableDeviceInfo other) { + if (other == org.tensorflow.proto.AvailableDeviceInfo.getDefaultInstance()) return this; + if (!other.getName().isEmpty()) { + name_ = other.name_; + onChanged(); + } + if (!other.getType().isEmpty()) { + type_ = other.type_; + onChanged(); + } + if (other.getMemoryLimit() != 0L) { + setMemoryLimit(other.getMemoryLimit()); + } + if (!other.getPhysicalDescription().isEmpty()) { + physicalDescription_ = other.physicalDescription_; + onChanged(); + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 10: { + name_ = input.readStringRequireUtf8(); + + break; + } // case 10 + case 18: { + type_ = input.readStringRequireUtf8(); + + break; + } // case 18 + case 24: { + memoryLimit_ = input.readInt64(); + + break; + } // case 24 + case 34: { + physicalDescription_ = input.readStringRequireUtf8(); + + break; + } // case 34 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + + private java.lang.Object name_ = ""; + /** + * 
    +     * Device name.
+     *
    + * + * string name = 1; + * @return The name. + */ + public java.lang.String getName() { + java.lang.Object ref = name_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + name_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * Device name.
+     *
    + * + * string name = 1; + * @return The bytes for name. + */ + public com.google.protobuf.ByteString + getNameBytes() { + java.lang.Object ref = name_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + name_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * Device name.
+     *
    + * + * string name = 1; + * @param value The name to set. + * @return This builder for chaining. + */ + public Builder setName( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + name_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Device name.
+     *
    + * + * string name = 1; + * @return This builder for chaining. + */ + public Builder clearName() { + + name_ = getDefaultInstance().getName(); + onChanged(); + return this; + } + /** + * 
    +     * Device name.
+     *
    + * + * string name = 1; + * @param value The bytes for name to set. + * @return This builder for chaining. + */ + public Builder setNameBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + name_ = value; + onChanged(); + return this; + } + + private java.lang.Object type_ = ""; + /** + * 
    +     * Device type, e.g. 'CPU' or 'GPU'.
+     *
    + * + * string type = 2; + * @return The type. + */ + public java.lang.String getType() { + java.lang.Object ref = type_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + type_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * Device type, e.g. 'CPU' or 'GPU'.
+     *
    + * + * string type = 2; + * @return The bytes for type. + */ + public com.google.protobuf.ByteString + getTypeBytes() { + java.lang.Object ref = type_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + type_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * Device type, e.g. 'CPU' or 'GPU'.
+     *
    + * + * string type = 2; + * @param value The type to set. + * @return This builder for chaining. + */ + public Builder setType( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + type_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Device type, e.g. 'CPU' or 'GPU'.
+     *
    + * + * string type = 2; + * @return This builder for chaining. + */ + public Builder clearType() { + + type_ = getDefaultInstance().getType(); + onChanged(); + return this; + } + /** + * 
    +     * Device type, e.g. 'CPU' or 'GPU'.
+     *
    + * + * string type = 2; + * @param value The bytes for type to set. + * @return This builder for chaining. + */ + public Builder setTypeBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + type_ = value; + onChanged(); + return this; + } + + private long memoryLimit_ ; + /** + * 
    +     * Memory capacity in bytes.
+     *
    + * + * int64 memory_limit = 3; + * @return The memoryLimit. + */ + @java.lang.Override + public long getMemoryLimit() { + return memoryLimit_; + } + /** + * 
    +     * Memory capacity in bytes.
+     *
    + * + * int64 memory_limit = 3; + * @param value The memoryLimit to set. + * @return This builder for chaining. + */ + public Builder setMemoryLimit(long value) { + + memoryLimit_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Memory capacity in bytes.
+     *
    + * + * int64 memory_limit = 3; + * @return This builder for chaining. + */ + public Builder clearMemoryLimit() { + + memoryLimit_ = 0L; + onChanged(); + return this; + } + + private java.lang.Object physicalDescription_ = ""; + /** + * 
    +     * The physical description of this device.
+     *
    + * + * string physical_description = 4; + * @return The physicalDescription. + */ + public java.lang.String getPhysicalDescription() { + java.lang.Object ref = physicalDescription_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + physicalDescription_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * The physical description of this device.
+     *
    + * + * string physical_description = 4; + * @return The bytes for physicalDescription. + */ + public com.google.protobuf.ByteString + getPhysicalDescriptionBytes() { + java.lang.Object ref = physicalDescription_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + physicalDescription_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * The physical description of this device.
+     *
    + * + * string physical_description = 4; + * @param value The physicalDescription to set. + * @return This builder for chaining. + */ + public Builder setPhysicalDescription( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + physicalDescription_ = value; + onChanged(); + return this; + } + /** + * 
    +     * The physical description of this device.
+     *
    + * + * string physical_description = 4; + * @return This builder for chaining. + */ + public Builder clearPhysicalDescription() { + + physicalDescription_ = getDefaultInstance().getPhysicalDescription(); + onChanged(); + return this; + } + /** + * 
    +     * The physical description of this device.
+     *
    + * + * string physical_description = 4; + * @param value The bytes for physicalDescription to set. + * @return This builder for chaining. + */ + public Builder setPhysicalDescriptionBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + physicalDescription_ = value; + onChanged(); + return this; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.AvailableDeviceInfo) + } + + // @@protoc_insertion_point(class_scope:tensorflow.AvailableDeviceInfo) + private static final org.tensorflow.proto.AvailableDeviceInfo DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.AvailableDeviceInfo(); + } + + public static org.tensorflow.proto.AvailableDeviceInfo getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public AvailableDeviceInfo parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.AvailableDeviceInfo getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + +} + diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/AvailableDeviceInfoOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/AvailableDeviceInfoOrBuilder.java new file mode 100644 index 00000000000..c35a7c6a745 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/AvailableDeviceInfoOrBuilder.java @@ -0,0 +1,79 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public interface AvailableDeviceInfoOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.AvailableDeviceInfo) + com.google.protobuf.MessageOrBuilder { + + /** + * 
    +   * Device name.
+   *
    + * + * string name = 1; + * @return The name. + */ + java.lang.String getName(); + /** + * 
    +   * Device name.
+   *
    + * + * string name = 1; + * @return The bytes for name. + */ + com.google.protobuf.ByteString + getNameBytes(); + + /** + * 
    +   * Device type, e.g. 'CPU' or 'GPU'.
+   *
    + * + * string type = 2; + * @return The type. + */ + java.lang.String getType(); + /** + * 
    +   * Device type, e.g. 'CPU' or 'GPU'.
+   *
    + * + * string type = 2; + * @return The bytes for type. + */ + com.google.protobuf.ByteString + getTypeBytes(); + + /** + * 
    +   * Memory capacity in bytes.
+   *
    + * + * int64 memory_limit = 3; + * @return The memoryLimit. + */ + long getMemoryLimit(); + + /** + * 
    +   * The physical description of this device.
+   *
    + * + * string physical_description = 4; + * @return The physicalDescription. + */ + java.lang.String getPhysicalDescription(); + /** + * 
    +   * The physical description of this device.
+   *
    + * + * string physical_description = 4; + * @return The bytes for physicalDescription. + */ + com.google.protobuf.ByteString + getPhysicalDescriptionBytes(); +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntries.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntries.java new file mode 100644 index 00000000000..73be037bfe8 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntries.java @@ -0,0 +1,752 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +/** + * Protobuf type {@code tensorflow.BenchmarkEntries} + */ +public final class BenchmarkEntries extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.BenchmarkEntries) + BenchmarkEntriesOrBuilder { +private static final long serialVersionUID = 0L; + // Use BenchmarkEntries.newBuilder() to construct. + private BenchmarkEntries(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private BenchmarkEntries() { + entry_ = java.util.Collections.emptyList(); + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new BenchmarkEntries(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntries_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntries_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BenchmarkEntries.class, org.tensorflow.proto.BenchmarkEntries.Builder.class); + } + + public static final int ENTRY_FIELD_NUMBER = 1; + private java.util.List entry_; + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + @java.lang.Override + public java.util.List getEntryList() { + return entry_; + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + @java.lang.Override + public java.util.List + getEntryOrBuilderList() { + return entry_; + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + @java.lang.Override + public int getEntryCount() { + return entry_.size(); + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + @java.lang.Override + public org.tensorflow.proto.BenchmarkEntry getEntry(int index) { + return entry_.get(index); + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + @java.lang.Override + public org.tensorflow.proto.BenchmarkEntryOrBuilder getEntryOrBuilder( + int index) { + return entry_.get(index); + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + for (int i = 0; i < entry_.size(); i++) { + output.writeMessage(1, entry_.get(i)); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + for (int i = 0; i < entry_.size(); i++) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(1, entry_.get(i)); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.BenchmarkEntries)) { + return super.equals(obj); + } + org.tensorflow.proto.BenchmarkEntries other = (org.tensorflow.proto.BenchmarkEntries) obj; + + if (!getEntryList() + .equals(other.getEntryList())) return false; + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + if (getEntryCount() > 0) { + hash = (37 * hash) + ENTRY_FIELD_NUMBER; + hash = (53 * hash) + getEntryList().hashCode(); + } + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.BenchmarkEntries parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BenchmarkEntries parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BenchmarkEntries parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BenchmarkEntries parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BenchmarkEntries parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BenchmarkEntries parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BenchmarkEntries parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BenchmarkEntries parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BenchmarkEntries parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BenchmarkEntries parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BenchmarkEntries parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BenchmarkEntries parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.BenchmarkEntries prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * Protobuf type {@code tensorflow.BenchmarkEntries} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.BenchmarkEntries) + org.tensorflow.proto.BenchmarkEntriesOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntries_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntries_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BenchmarkEntries.class, org.tensorflow.proto.BenchmarkEntries.Builder.class); + } + + // Construct using org.tensorflow.proto.BenchmarkEntries.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + if (entryBuilder_ == null) { + entry_ = java.util.Collections.emptyList(); + } else { + entry_ = null; + entryBuilder_.clear(); + } + bitField0_ = (bitField0_ & ~0x00000001); + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntries_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.BenchmarkEntries getDefaultInstanceForType() { + return org.tensorflow.proto.BenchmarkEntries.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.BenchmarkEntries build() { + org.tensorflow.proto.BenchmarkEntries result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.BenchmarkEntries buildPartial() { + org.tensorflow.proto.BenchmarkEntries result = new org.tensorflow.proto.BenchmarkEntries(this); + int from_bitField0_ = bitField0_; + if (entryBuilder_ == null) { + if (((bitField0_ & 0x00000001) != 0)) { + entry_ = java.util.Collections.unmodifiableList(entry_); + bitField0_ = (bitField0_ & ~0x00000001); + } + result.entry_ = entry_; + } else { + result.entry_ = entryBuilder_.build(); + } + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.BenchmarkEntries) { + return mergeFrom((org.tensorflow.proto.BenchmarkEntries)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.BenchmarkEntries other) { + if (other == org.tensorflow.proto.BenchmarkEntries.getDefaultInstance()) return this; + if (entryBuilder_ == null) { + if (!other.entry_.isEmpty()) { + if (entry_.isEmpty()) { + entry_ = other.entry_; + bitField0_ = (bitField0_ & ~0x00000001); + } else { + ensureEntryIsMutable(); + entry_.addAll(other.entry_); + } + onChanged(); + } + } else { + if (!other.entry_.isEmpty()) { + if (entryBuilder_.isEmpty()) { + entryBuilder_.dispose(); + entryBuilder_ = null; + entry_ = other.entry_; + bitField0_ = (bitField0_ & ~0x00000001); + entryBuilder_ = + com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ? + getEntryFieldBuilder() : null; + } else { + entryBuilder_.addAllMessages(other.entry_); + } + } + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 10: { + org.tensorflow.proto.BenchmarkEntry m = + input.readMessage( + org.tensorflow.proto.BenchmarkEntry.parser(), + extensionRegistry); + if (entryBuilder_ == null) { + ensureEntryIsMutable(); + entry_.add(m); + } else { + entryBuilder_.addMessage(m); + } + break; + } // case 10 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + private int bitField0_; + + private java.util.List entry_ = + java.util.Collections.emptyList(); + private void ensureEntryIsMutable() { + if (!((bitField0_ & 0x00000001) != 0)) { + entry_ = new java.util.ArrayList(entry_); + bitField0_ |= 0x00000001; + } + } + + private com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.BenchmarkEntry, org.tensorflow.proto.BenchmarkEntry.Builder, org.tensorflow.proto.BenchmarkEntryOrBuilder> entryBuilder_; + + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public java.util.List getEntryList() { + if (entryBuilder_ == null) { + return java.util.Collections.unmodifiableList(entry_); + } else { + return entryBuilder_.getMessageList(); + } + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public int getEntryCount() { + if (entryBuilder_ == null) { + return entry_.size(); + } else { + return entryBuilder_.getCount(); + } + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public org.tensorflow.proto.BenchmarkEntry getEntry(int index) { + if (entryBuilder_ == null) { + return entry_.get(index); + } else { + return entryBuilder_.getMessage(index); + } + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public Builder setEntry( + int index, org.tensorflow.proto.BenchmarkEntry value) { + if (entryBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureEntryIsMutable(); + entry_.set(index, value); + onChanged(); + } else { + entryBuilder_.setMessage(index, value); + } + return this; + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public Builder setEntry( + int index, org.tensorflow.proto.BenchmarkEntry.Builder builderForValue) { + if (entryBuilder_ == null) { + ensureEntryIsMutable(); + entry_.set(index, builderForValue.build()); + onChanged(); + } else { + entryBuilder_.setMessage(index, builderForValue.build()); + } + return this; + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public Builder addEntry(org.tensorflow.proto.BenchmarkEntry value) { + if (entryBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureEntryIsMutable(); + entry_.add(value); + onChanged(); + } else { + entryBuilder_.addMessage(value); + } + return this; + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public Builder addEntry( + int index, org.tensorflow.proto.BenchmarkEntry value) { + if (entryBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureEntryIsMutable(); + entry_.add(index, value); + onChanged(); + } else { + entryBuilder_.addMessage(index, value); + } + return this; + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public Builder addEntry( + org.tensorflow.proto.BenchmarkEntry.Builder builderForValue) { + if (entryBuilder_ == null) { + ensureEntryIsMutable(); + entry_.add(builderForValue.build()); + onChanged(); + } else { + entryBuilder_.addMessage(builderForValue.build()); + } + return this; + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public Builder addEntry( + int index, org.tensorflow.proto.BenchmarkEntry.Builder builderForValue) { + if (entryBuilder_ == null) { + ensureEntryIsMutable(); + entry_.add(index, builderForValue.build()); + onChanged(); + } else { + entryBuilder_.addMessage(index, builderForValue.build()); + } + return this; + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public Builder addAllEntry( + java.lang.Iterable values) { + if (entryBuilder_ == null) { + ensureEntryIsMutable(); + com.google.protobuf.AbstractMessageLite.Builder.addAll( + values, entry_); + onChanged(); + } else { + entryBuilder_.addAllMessages(values); + } + return this; + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public Builder clearEntry() { + if (entryBuilder_ == null) { + entry_ = java.util.Collections.emptyList(); + bitField0_ = (bitField0_ & ~0x00000001); + onChanged(); + } else { + entryBuilder_.clear(); + } + return this; + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public Builder removeEntry(int index) { + if (entryBuilder_ == null) { + ensureEntryIsMutable(); + entry_.remove(index); + onChanged(); + } else { + entryBuilder_.remove(index); + } + return this; + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public org.tensorflow.proto.BenchmarkEntry.Builder getEntryBuilder( + int index) { + return getEntryFieldBuilder().getBuilder(index); + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public org.tensorflow.proto.BenchmarkEntryOrBuilder getEntryOrBuilder( + int index) { + if (entryBuilder_ == null) { + return entry_.get(index); } else { + return entryBuilder_.getMessageOrBuilder(index); + } + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public java.util.List + getEntryOrBuilderList() { + if (entryBuilder_ != null) { + return entryBuilder_.getMessageOrBuilderList(); + } else { + return java.util.Collections.unmodifiableList(entry_); + } + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public org.tensorflow.proto.BenchmarkEntry.Builder addEntryBuilder() { + return getEntryFieldBuilder().addBuilder( + org.tensorflow.proto.BenchmarkEntry.getDefaultInstance()); + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public org.tensorflow.proto.BenchmarkEntry.Builder addEntryBuilder( + int index) { + return getEntryFieldBuilder().addBuilder( + index, org.tensorflow.proto.BenchmarkEntry.getDefaultInstance()); + } + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + public java.util.List + getEntryBuilderList() { + return getEntryFieldBuilder().getBuilderList(); + } + private com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.BenchmarkEntry, org.tensorflow.proto.BenchmarkEntry.Builder, org.tensorflow.proto.BenchmarkEntryOrBuilder> + getEntryFieldBuilder() { + if (entryBuilder_ == null) { + entryBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.BenchmarkEntry, org.tensorflow.proto.BenchmarkEntry.Builder, org.tensorflow.proto.BenchmarkEntryOrBuilder>( + entry_, + ((bitField0_ & 0x00000001) != 0), + getParentForChildren(), + isClean()); + entry_ = null; + } + return entryBuilder_; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.BenchmarkEntries) + } + + // @@protoc_insertion_point(class_scope:tensorflow.BenchmarkEntries) + private static final org.tensorflow.proto.BenchmarkEntries DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.BenchmarkEntries(); + } + + public static org.tensorflow.proto.BenchmarkEntries getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public BenchmarkEntries parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.BenchmarkEntries getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + +} + diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntriesOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntriesOrBuilder.java new file mode 100644 index 00000000000..de029d1d399 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntriesOrBuilder.java @@ -0,0 +1,33 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public interface BenchmarkEntriesOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.BenchmarkEntries) + com.google.protobuf.MessageOrBuilder { + + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + java.util.List + getEntryList(); + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + org.tensorflow.proto.BenchmarkEntry getEntry(int index); + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + int getEntryCount(); + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + java.util.List + getEntryOrBuilderList(); + /** + * repeated .tensorflow.BenchmarkEntry entry = 1; + */ + org.tensorflow.proto.BenchmarkEntryOrBuilder getEntryOrBuilder( + int index); +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntry.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntry.java new file mode 100644 index 00000000000..efe111640d5 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntry.java @@ -0,0 +1,1709 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +/** + * 
    + * Each unit test or benchmark in a test or benchmark run provides
+ * some set of information.  Here we provide some reasonable keys
+ * one would expect to see, with optional key/value pairs for things
+ * we haven't considered.
+ * This BenchmarkEntry should be emitted by each unit test or benchmark
+ * reporter.
+ *
    + * + * Protobuf type {@code tensorflow.BenchmarkEntry} + */ +public final class BenchmarkEntry extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.BenchmarkEntry) + BenchmarkEntryOrBuilder { +private static final long serialVersionUID = 0L; + // Use BenchmarkEntry.newBuilder() to construct. + private BenchmarkEntry(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private BenchmarkEntry() { + name_ = ""; + metrics_ = java.util.Collections.emptyList(); + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new BenchmarkEntry(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntry_descriptor; + } + + @SuppressWarnings({"rawtypes"}) + @java.lang.Override + protected com.google.protobuf.MapField internalGetMapField( + int number) { + switch (number) { + case 6: + return internalGetExtras(); + default: + throw new RuntimeException( + "Invalid map field number: " + number); + } + } + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntry_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BenchmarkEntry.class, org.tensorflow.proto.BenchmarkEntry.Builder.class); + } + + public static final int NAME_FIELD_NUMBER = 1; + private volatile java.lang.Object name_; + /** + * 
    +   * The name of the specific benchmark or test
+   * (e.g. BM_AdjustContrast_gpu_B_W_H)
+   *
    + * + * string name = 1; + * @return The name. + */ + @java.lang.Override + public java.lang.String getName() { + java.lang.Object ref = name_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + name_ = s; + return s; + } + } + /** + * 
    +   * The name of the specific benchmark or test
+   * (e.g. BM_AdjustContrast_gpu_B_W_H)
+   *
    + * + * string name = 1; + * @return The bytes for name. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getNameBytes() { + java.lang.Object ref = name_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + name_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int ITERS_FIELD_NUMBER = 2; + private long iters_; + /** + * 
    +   * If a benchmark, how many iterations it was run for
+   *
    + * + * int64 iters = 2; + * @return The iters. + */ + @java.lang.Override + public long getIters() { + return iters_; + } + + public static final int CPU_TIME_FIELD_NUMBER = 3; + private double cpuTime_; + /** + * 
    +   * Total cpu time used for all iterations (in seconds)
+   *
    + * + * double cpu_time = 3; + * @return The cpuTime. + */ + @java.lang.Override + public double getCpuTime() { + return cpuTime_; + } + + public static final int WALL_TIME_FIELD_NUMBER = 4; + private double wallTime_; + /** + * 
    +   * Total wall time used for all iterations (in seconds)
+   *
    + * + * double wall_time = 4; + * @return The wallTime. + */ + @java.lang.Override + public double getWallTime() { + return wallTime_; + } + + public static final int THROUGHPUT_FIELD_NUMBER = 5; + private double throughput_; + /** + * 
    +   * Throughput (in MB/s)
+   *
    + * + * double throughput = 5; + * @return The throughput. + */ + @java.lang.Override + public double getThroughput() { + return throughput_; + } + + public static final int EXTRAS_FIELD_NUMBER = 6; + private static final class ExtrasDefaultEntryHolder { + static final com.google.protobuf.MapEntry< + java.lang.String, org.tensorflow.proto.EntryValue> defaultEntry = + com.google.protobuf.MapEntry + .newDefaultInstance( + org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntry_ExtrasEntry_descriptor, + com.google.protobuf.WireFormat.FieldType.STRING, + "", + com.google.protobuf.WireFormat.FieldType.MESSAGE, + org.tensorflow.proto.EntryValue.getDefaultInstance()); + } + private com.google.protobuf.MapField< + java.lang.String, org.tensorflow.proto.EntryValue> extras_; + private com.google.protobuf.MapField + internalGetExtras() { + if (extras_ == null) { + return com.google.protobuf.MapField.emptyMapField( + ExtrasDefaultEntryHolder.defaultEntry); + } + return extras_; + } + + public int getExtrasCount() { + return internalGetExtras().getMap().size(); + } + /** + * 
    +   * Generic map from result key to value.
+   *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + + @java.lang.Override + public boolean containsExtras( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + return internalGetExtras().getMap().containsKey(key); + } + /** + * Use {@link #getExtrasMap()} instead. + */ + @java.lang.Override + @java.lang.Deprecated + public java.util.Map getExtras() { + return getExtrasMap(); + } + /** + * 
    +   * Generic map from result key to value.
+   *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + @java.lang.Override + + public java.util.Map getExtrasMap() { + return internalGetExtras().getMap(); + } + /** + * 
    +   * Generic map from result key to value.
+   *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + @java.lang.Override + + public org.tensorflow.proto.EntryValue getExtrasOrDefault( + java.lang.String key, + org.tensorflow.proto.EntryValue defaultValue) { + if (key == null) { throw new NullPointerException("map key"); } + java.util.Map map = + internalGetExtras().getMap(); + return map.containsKey(key) ? map.get(key) : defaultValue; + } + /** + * 
    +   * Generic map from result key to value.
+   *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + @java.lang.Override + + public org.tensorflow.proto.EntryValue getExtrasOrThrow( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + java.util.Map map = + internalGetExtras().getMap(); + if (!map.containsKey(key)) { + throw new java.lang.IllegalArgumentException(); + } + return map.get(key); + } + + public static final int METRICS_FIELD_NUMBER = 7; + private java.util.List metrics_; + /** + * 
    +   * Metric name, value and expected range. This can include accuracy metrics
+   * typically used to determine whether the accuracy test has passed
+   *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + @java.lang.Override + public java.util.List getMetricsList() { + return metrics_; + } + /** + * 
    +   * Metric name, value and expected range. This can include accuracy metrics
+   * typically used to determine whether the accuracy test has passed
+   *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + @java.lang.Override + public java.util.List + getMetricsOrBuilderList() { + return metrics_; + } + /** + * 
    +   * Metric name, value and expected range. This can include accuracy metrics
+   * typically used to determine whether the accuracy test has passed
+   *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + @java.lang.Override + public int getMetricsCount() { + return metrics_.size(); + } + /** + * 
    +   * Metric name, value and expected range. This can include accuracy metrics
+   * typically used to determine whether the accuracy test has passed
+   *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + @java.lang.Override + public org.tensorflow.proto.MetricEntry getMetrics(int index) { + return metrics_.get(index); + } + /** + * 
    +   * Metric name, value and expected range. This can include accuracy metrics
+   * typically used to determine whether the accuracy test has passed
+   *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + @java.lang.Override + public org.tensorflow.proto.MetricEntryOrBuilder getMetricsOrBuilder( + int index) { + return metrics_.get(index); + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 1, name_); + } + if (iters_ != 0L) { + output.writeInt64(2, iters_); + } + if (java.lang.Double.doubleToRawLongBits(cpuTime_) != 0) { + output.writeDouble(3, cpuTime_); + } + if (java.lang.Double.doubleToRawLongBits(wallTime_) != 0) { + output.writeDouble(4, wallTime_); + } + if (java.lang.Double.doubleToRawLongBits(throughput_) != 0) { + output.writeDouble(5, throughput_); + } + com.google.protobuf.GeneratedMessageV3 + .serializeStringMapTo( + output, + internalGetExtras(), + ExtrasDefaultEntryHolder.defaultEntry, + 6); + for (int i = 0; i < metrics_.size(); i++) { + output.writeMessage(7, metrics_.get(i)); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, name_); + } + if (iters_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(2, iters_); + } + if (java.lang.Double.doubleToRawLongBits(cpuTime_) != 0) { + size += com.google.protobuf.CodedOutputStream + .computeDoubleSize(3, cpuTime_); + } + if (java.lang.Double.doubleToRawLongBits(wallTime_) != 0) { + size += com.google.protobuf.CodedOutputStream + .computeDoubleSize(4, wallTime_); + } + if (java.lang.Double.doubleToRawLongBits(throughput_) != 0) { + size += com.google.protobuf.CodedOutputStream + .computeDoubleSize(5, throughput_); + } + for (java.util.Map.Entry entry + : internalGetExtras().getMap().entrySet()) { + com.google.protobuf.MapEntry + extras__ = ExtrasDefaultEntryHolder.defaultEntry.newBuilderForType() + .setKey(entry.getKey()) + .setValue(entry.getValue()) + .build(); + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(6, extras__); + } + for (int i = 0; i < metrics_.size(); i++) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(7, metrics_.get(i)); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.BenchmarkEntry)) { + return super.equals(obj); + } + org.tensorflow.proto.BenchmarkEntry other = (org.tensorflow.proto.BenchmarkEntry) obj; + + if (!getName() + .equals(other.getName())) return false; + if (getIters() + != other.getIters()) return false; + if (java.lang.Double.doubleToLongBits(getCpuTime()) + != java.lang.Double.doubleToLongBits( + other.getCpuTime())) return false; + if (java.lang.Double.doubleToLongBits(getWallTime()) + != java.lang.Double.doubleToLongBits( + other.getWallTime())) return false; + if (java.lang.Double.doubleToLongBits(getThroughput()) + != java.lang.Double.doubleToLongBits( + other.getThroughput())) return false; + if (!internalGetExtras().equals( + other.internalGetExtras())) return false; + if (!getMetricsList() + .equals(other.getMetricsList())) return false; + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + NAME_FIELD_NUMBER; + hash = (53 * hash) + getName().hashCode(); + hash = (37 * hash) + ITERS_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getIters()); + hash = (37 * hash) + CPU_TIME_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + java.lang.Double.doubleToLongBits(getCpuTime())); + hash = (37 * hash) + WALL_TIME_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + java.lang.Double.doubleToLongBits(getWallTime())); + hash = (37 * hash) + THROUGHPUT_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + java.lang.Double.doubleToLongBits(getThroughput())); + if (!internalGetExtras().getMap().isEmpty()) { + hash = (37 * hash) + EXTRAS_FIELD_NUMBER; + hash = (53 * hash) + internalGetExtras().hashCode(); + } + if (getMetricsCount() > 0) { + hash = (37 * hash) + METRICS_FIELD_NUMBER; + hash = (53 * hash) + getMetricsList().hashCode(); + } + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.BenchmarkEntry parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BenchmarkEntry parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BenchmarkEntry parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BenchmarkEntry parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BenchmarkEntry parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BenchmarkEntry parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BenchmarkEntry parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BenchmarkEntry parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BenchmarkEntry parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BenchmarkEntry parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BenchmarkEntry parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BenchmarkEntry parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.BenchmarkEntry prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * 
    +   * Each unit test or benchmark in a test or benchmark run provides
+   * some set of information.  Here we provide some reasonable keys
+   * one would expect to see, with optional key/value pairs for things
+   * we haven't considered.
+   * This BenchmarkEntry should be emitted by each unit test or benchmark
+   * reporter.
+   *
    + * + * Protobuf type {@code tensorflow.BenchmarkEntry} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.BenchmarkEntry) + org.tensorflow.proto.BenchmarkEntryOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntry_descriptor; + } + + @SuppressWarnings({"rawtypes"}) + protected com.google.protobuf.MapField internalGetMapField( + int number) { + switch (number) { + case 6: + return internalGetExtras(); + default: + throw new RuntimeException( + "Invalid map field number: " + number); + } + } + @SuppressWarnings({"rawtypes"}) + protected com.google.protobuf.MapField internalGetMutableMapField( + int number) { + switch (number) { + case 6: + return internalGetMutableExtras(); + default: + throw new RuntimeException( + "Invalid map field number: " + number); + } + } + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntry_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BenchmarkEntry.class, org.tensorflow.proto.BenchmarkEntry.Builder.class); + } + + // Construct using org.tensorflow.proto.BenchmarkEntry.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + name_ = ""; + + iters_ = 0L; + + cpuTime_ = 0D; + + wallTime_ = 0D; + + throughput_ = 0D; + + internalGetMutableExtras().clear(); + if (metricsBuilder_ == null) { + metrics_ = java.util.Collections.emptyList(); + } else { + metrics_ = null; + metricsBuilder_.clear(); + } + bitField0_ = (bitField0_ & ~0x00000002); + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BenchmarkEntry_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.BenchmarkEntry getDefaultInstanceForType() { + return org.tensorflow.proto.BenchmarkEntry.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.BenchmarkEntry build() { + org.tensorflow.proto.BenchmarkEntry result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.BenchmarkEntry buildPartial() { + org.tensorflow.proto.BenchmarkEntry result = new org.tensorflow.proto.BenchmarkEntry(this); + int from_bitField0_ = bitField0_; + result.name_ = name_; + result.iters_ = iters_; + result.cpuTime_ = cpuTime_; + result.wallTime_ = wallTime_; + result.throughput_ = throughput_; + result.extras_ = internalGetExtras(); + result.extras_.makeImmutable(); + if (metricsBuilder_ == null) { + if (((bitField0_ & 0x00000002) != 0)) { + metrics_ = java.util.Collections.unmodifiableList(metrics_); + bitField0_ = (bitField0_ & ~0x00000002); + } + result.metrics_ = metrics_; + } else { + result.metrics_ = metricsBuilder_.build(); + } + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.BenchmarkEntry) { + return mergeFrom((org.tensorflow.proto.BenchmarkEntry)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.BenchmarkEntry other) { + if (other == org.tensorflow.proto.BenchmarkEntry.getDefaultInstance()) return this; + if (!other.getName().isEmpty()) { + name_ = other.name_; + onChanged(); + } + if (other.getIters() != 0L) { + setIters(other.getIters()); + } + if (other.getCpuTime() != 0D) { + setCpuTime(other.getCpuTime()); + } + if (other.getWallTime() != 0D) { + setWallTime(other.getWallTime()); + } + if (other.getThroughput() != 0D) { + setThroughput(other.getThroughput()); + } + internalGetMutableExtras().mergeFrom( + other.internalGetExtras()); + if (metricsBuilder_ == null) { + if (!other.metrics_.isEmpty()) { + if (metrics_.isEmpty()) { + metrics_ = other.metrics_; + bitField0_ = (bitField0_ & ~0x00000002); + } else { + ensureMetricsIsMutable(); + metrics_.addAll(other.metrics_); + } + onChanged(); + } + } else { + if (!other.metrics_.isEmpty()) { + if (metricsBuilder_.isEmpty()) { + metricsBuilder_.dispose(); + metricsBuilder_ = null; + metrics_ = other.metrics_; + bitField0_ = (bitField0_ & ~0x00000002); + metricsBuilder_ = + com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ? + getMetricsFieldBuilder() : null; + } else { + metricsBuilder_.addAllMessages(other.metrics_); + } + } + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 10: { + name_ = input.readStringRequireUtf8(); + + break; + } // case 10 + case 16: { + iters_ = input.readInt64(); + + break; + } // case 16 + case 25: { + cpuTime_ = input.readDouble(); + + break; + } // case 25 + case 33: { + wallTime_ = input.readDouble(); + + break; + } // case 33 + case 41: { + throughput_ = input.readDouble(); + + break; + } // case 41 + case 50: { + com.google.protobuf.MapEntry + extras__ = input.readMessage( + ExtrasDefaultEntryHolder.defaultEntry.getParserForType(), extensionRegistry); + internalGetMutableExtras().getMutableMap().put( + extras__.getKey(), extras__.getValue()); + break; + } // case 50 + case 58: { + org.tensorflow.proto.MetricEntry m = + input.readMessage( + org.tensorflow.proto.MetricEntry.parser(), + extensionRegistry); + if (metricsBuilder_ == null) { + ensureMetricsIsMutable(); + metrics_.add(m); + } else { + metricsBuilder_.addMessage(m); + } + break; + } // case 58 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + private int bitField0_; + + private java.lang.Object name_ = ""; + /** + * 
    +     * The name of the specific benchmark or test
+     * (e.g. BM_AdjustContrast_gpu_B_W_H)
+     *
    + * + * string name = 1; + * @return The name. + */ + public java.lang.String getName() { + java.lang.Object ref = name_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + name_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * The name of the specific benchmark or test
+     * (e.g. BM_AdjustContrast_gpu_B_W_H)
+     *
    + * + * string name = 1; + * @return The bytes for name. + */ + public com.google.protobuf.ByteString + getNameBytes() { + java.lang.Object ref = name_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + name_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * The name of the specific benchmark or test
+     * (e.g. BM_AdjustContrast_gpu_B_W_H)
+     *
    + * + * string name = 1; + * @param value The name to set. + * @return This builder for chaining. + */ + public Builder setName( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + name_ = value; + onChanged(); + return this; + } + /** + * 
    +     * The name of the specific benchmark or test
+     * (e.g. BM_AdjustContrast_gpu_B_W_H)
+     *
    + * + * string name = 1; + * @return This builder for chaining. + */ + public Builder clearName() { + + name_ = getDefaultInstance().getName(); + onChanged(); + return this; + } + /** + * 
    +     * The name of the specific benchmark or test
+     * (e.g. BM_AdjustContrast_gpu_B_W_H)
+     *
    + * + * string name = 1; + * @param value The bytes for name to set. + * @return This builder for chaining. + */ + public Builder setNameBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + name_ = value; + onChanged(); + return this; + } + + private long iters_ ; + /** + * 
    +     * If a benchmark, how many iterations it was run for
+     *
    + * + * int64 iters = 2; + * @return The iters. + */ + @java.lang.Override + public long getIters() { + return iters_; + } + /** + * 
    +     * If a benchmark, how many iterations it was run for
+     *
    + * + * int64 iters = 2; + * @param value The iters to set. + * @return This builder for chaining. + */ + public Builder setIters(long value) { + + iters_ = value; + onChanged(); + return this; + } + /** + * 
    +     * If a benchmark, how many iterations it was run for
+     *
    + * + * int64 iters = 2; + * @return This builder for chaining. + */ + public Builder clearIters() { + + iters_ = 0L; + onChanged(); + return this; + } + + private double cpuTime_ ; + /** + * 
    +     * Total cpu time used for all iterations (in seconds)
+     *
    + * + * double cpu_time = 3; + * @return The cpuTime. + */ + @java.lang.Override + public double getCpuTime() { + return cpuTime_; + } + /** + * 
    +     * Total cpu time used for all iterations (in seconds)
+     *
    + * + * double cpu_time = 3; + * @param value The cpuTime to set. + * @return This builder for chaining. + */ + public Builder setCpuTime(double value) { + + cpuTime_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Total cpu time used for all iterations (in seconds)
+     *
    + * + * double cpu_time = 3; + * @return This builder for chaining. + */ + public Builder clearCpuTime() { + + cpuTime_ = 0D; + onChanged(); + return this; + } + + private double wallTime_ ; + /** + * 
    +     * Total wall time used for all iterations (in seconds)
+     *
    + * + * double wall_time = 4; + * @return The wallTime. + */ + @java.lang.Override + public double getWallTime() { + return wallTime_; + } + /** + * 
    +     * Total wall time used for all iterations (in seconds)
+     *
    + * + * double wall_time = 4; + * @param value The wallTime to set. + * @return This builder for chaining. + */ + public Builder setWallTime(double value) { + + wallTime_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Total wall time used for all iterations (in seconds)
+     *
    + * + * double wall_time = 4; + * @return This builder for chaining. + */ + public Builder clearWallTime() { + + wallTime_ = 0D; + onChanged(); + return this; + } + + private double throughput_ ; + /** + * 
    +     * Throughput (in MB/s)
+     *
    + * + * double throughput = 5; + * @return The throughput. + */ + @java.lang.Override + public double getThroughput() { + return throughput_; + } + /** + * 
    +     * Throughput (in MB/s)
+     *
    + * + * double throughput = 5; + * @param value The throughput to set. + * @return This builder for chaining. + */ + public Builder setThroughput(double value) { + + throughput_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Throughput (in MB/s)
+     *
    + * + * double throughput = 5; + * @return This builder for chaining. + */ + public Builder clearThroughput() { + + throughput_ = 0D; + onChanged(); + return this; + } + + private com.google.protobuf.MapField< + java.lang.String, org.tensorflow.proto.EntryValue> extras_; + private com.google.protobuf.MapField + internalGetExtras() { + if (extras_ == null) { + return com.google.protobuf.MapField.emptyMapField( + ExtrasDefaultEntryHolder.defaultEntry); + } + return extras_; + } + private com.google.protobuf.MapField + internalGetMutableExtras() { + onChanged();; + if (extras_ == null) { + extras_ = com.google.protobuf.MapField.newMapField( + ExtrasDefaultEntryHolder.defaultEntry); + } + if (!extras_.isMutable()) { + extras_ = extras_.copy(); + } + return extras_; + } + + public int getExtrasCount() { + return internalGetExtras().getMap().size(); + } + /** + * 
    +     * Generic map from result key to value.
+     *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + + @java.lang.Override + public boolean containsExtras( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + return internalGetExtras().getMap().containsKey(key); + } + /** + * Use {@link #getExtrasMap()} instead. + */ + @java.lang.Override + @java.lang.Deprecated + public java.util.Map getExtras() { + return getExtrasMap(); + } + /** + * 
    +     * Generic map from result key to value.
+     *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + @java.lang.Override + + public java.util.Map getExtrasMap() { + return internalGetExtras().getMap(); + } + /** + * 
    +     * Generic map from result key to value.
+     *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + @java.lang.Override + + public org.tensorflow.proto.EntryValue getExtrasOrDefault( + java.lang.String key, + org.tensorflow.proto.EntryValue defaultValue) { + if (key == null) { throw new NullPointerException("map key"); } + java.util.Map map = + internalGetExtras().getMap(); + return map.containsKey(key) ? map.get(key) : defaultValue; + } + /** + * 
    +     * Generic map from result key to value.
+     *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + @java.lang.Override + + public org.tensorflow.proto.EntryValue getExtrasOrThrow( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + java.util.Map map = + internalGetExtras().getMap(); + if (!map.containsKey(key)) { + throw new java.lang.IllegalArgumentException(); + } + return map.get(key); + } + + public Builder clearExtras() { + internalGetMutableExtras().getMutableMap() + .clear(); + return this; + } + /** + * 
    +     * Generic map from result key to value.
+     *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + + public Builder removeExtras( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + internalGetMutableExtras().getMutableMap() + .remove(key); + return this; + } + /** + * Use alternate mutation accessors instead. + */ + @java.lang.Deprecated + public java.util.Map + getMutableExtras() { + return internalGetMutableExtras().getMutableMap(); + } + /** + * 
    +     * Generic map from result key to value.
+     *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + public Builder putExtras( + java.lang.String key, + org.tensorflow.proto.EntryValue value) { + if (key == null) { throw new NullPointerException("map key"); } + if (value == null) { + throw new NullPointerException("map value"); +} + + internalGetMutableExtras().getMutableMap() + .put(key, value); + return this; + } + /** + * 
    +     * Generic map from result key to value.
+     *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + + public Builder putAllExtras( + java.util.Map values) { + internalGetMutableExtras().getMutableMap() + .putAll(values); + return this; + } + + private java.util.List metrics_ = + java.util.Collections.emptyList(); + private void ensureMetricsIsMutable() { + if (!((bitField0_ & 0x00000002) != 0)) { + metrics_ = new java.util.ArrayList(metrics_); + bitField0_ |= 0x00000002; + } + } + + private com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.MetricEntry, org.tensorflow.proto.MetricEntry.Builder, org.tensorflow.proto.MetricEntryOrBuilder> metricsBuilder_; + + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public java.util.List getMetricsList() { + if (metricsBuilder_ == null) { + return java.util.Collections.unmodifiableList(metrics_); + } else { + return metricsBuilder_.getMessageList(); + } + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public int getMetricsCount() { + if (metricsBuilder_ == null) { + return metrics_.size(); + } else { + return metricsBuilder_.getCount(); + } + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public org.tensorflow.proto.MetricEntry getMetrics(int index) { + if (metricsBuilder_ == null) { + return metrics_.get(index); + } else { + return metricsBuilder_.getMessage(index); + } + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public Builder setMetrics( + int index, org.tensorflow.proto.MetricEntry value) { + if (metricsBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureMetricsIsMutable(); + metrics_.set(index, value); + onChanged(); + } else { + metricsBuilder_.setMessage(index, value); + } + return this; + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public Builder setMetrics( + int index, org.tensorflow.proto.MetricEntry.Builder builderForValue) { + if (metricsBuilder_ == null) { + ensureMetricsIsMutable(); + metrics_.set(index, builderForValue.build()); + onChanged(); + } else { + metricsBuilder_.setMessage(index, builderForValue.build()); + } + return this; + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public Builder addMetrics(org.tensorflow.proto.MetricEntry value) { + if (metricsBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureMetricsIsMutable(); + metrics_.add(value); + onChanged(); + } else { + metricsBuilder_.addMessage(value); + } + return this; + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public Builder addMetrics( + int index, org.tensorflow.proto.MetricEntry value) { + if (metricsBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureMetricsIsMutable(); + metrics_.add(index, value); + onChanged(); + } else { + metricsBuilder_.addMessage(index, value); + } + return this; + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public Builder addMetrics( + org.tensorflow.proto.MetricEntry.Builder builderForValue) { + if (metricsBuilder_ == null) { + ensureMetricsIsMutable(); + metrics_.add(builderForValue.build()); + onChanged(); + } else { + metricsBuilder_.addMessage(builderForValue.build()); + } + return this; + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public Builder addMetrics( + int index, org.tensorflow.proto.MetricEntry.Builder builderForValue) { + if (metricsBuilder_ == null) { + ensureMetricsIsMutable(); + metrics_.add(index, builderForValue.build()); + onChanged(); + } else { + metricsBuilder_.addMessage(index, builderForValue.build()); + } + return this; + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public Builder addAllMetrics( + java.lang.Iterable values) { + if (metricsBuilder_ == null) { + ensureMetricsIsMutable(); + com.google.protobuf.AbstractMessageLite.Builder.addAll( + values, metrics_); + onChanged(); + } else { + metricsBuilder_.addAllMessages(values); + } + return this; + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public Builder clearMetrics() { + if (metricsBuilder_ == null) { + metrics_ = java.util.Collections.emptyList(); + bitField0_ = (bitField0_ & ~0x00000002); + onChanged(); + } else { + metricsBuilder_.clear(); + } + return this; + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public Builder removeMetrics(int index) { + if (metricsBuilder_ == null) { + ensureMetricsIsMutable(); + metrics_.remove(index); + onChanged(); + } else { + metricsBuilder_.remove(index); + } + return this; + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public org.tensorflow.proto.MetricEntry.Builder getMetricsBuilder( + int index) { + return getMetricsFieldBuilder().getBuilder(index); + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public org.tensorflow.proto.MetricEntryOrBuilder getMetricsOrBuilder( + int index) { + if (metricsBuilder_ == null) { + return metrics_.get(index); } else { + return metricsBuilder_.getMessageOrBuilder(index); + } + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public java.util.List + getMetricsOrBuilderList() { + if (metricsBuilder_ != null) { + return metricsBuilder_.getMessageOrBuilderList(); + } else { + return java.util.Collections.unmodifiableList(metrics_); + } + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public org.tensorflow.proto.MetricEntry.Builder addMetricsBuilder() { + return getMetricsFieldBuilder().addBuilder( + org.tensorflow.proto.MetricEntry.getDefaultInstance()); + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public org.tensorflow.proto.MetricEntry.Builder addMetricsBuilder( + int index) { + return getMetricsFieldBuilder().addBuilder( + index, org.tensorflow.proto.MetricEntry.getDefaultInstance()); + } + /** + * 
    +     * Metric name, value and expected range. This can include accuracy metrics
+     * typically used to determine whether the accuracy test has passed
+     *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + public java.util.List + getMetricsBuilderList() { + return getMetricsFieldBuilder().getBuilderList(); + } + private com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.MetricEntry, org.tensorflow.proto.MetricEntry.Builder, org.tensorflow.proto.MetricEntryOrBuilder> + getMetricsFieldBuilder() { + if (metricsBuilder_ == null) { + metricsBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.MetricEntry, org.tensorflow.proto.MetricEntry.Builder, org.tensorflow.proto.MetricEntryOrBuilder>( + metrics_, + ((bitField0_ & 0x00000002) != 0), + getParentForChildren(), + isClean()); + metrics_ = null; + } + return metricsBuilder_; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.BenchmarkEntry) + } + + // @@protoc_insertion_point(class_scope:tensorflow.BenchmarkEntry) + private static final org.tensorflow.proto.BenchmarkEntry DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.BenchmarkEntry(); + } + + public static org.tensorflow.proto.BenchmarkEntry getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public BenchmarkEntry parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.BenchmarkEntry getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + +} + diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntryOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntryOrBuilder.java new file mode 100644 index 00000000000..fba00ccb7f1 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BenchmarkEntryOrBuilder.java @@ -0,0 +1,176 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public interface BenchmarkEntryOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.BenchmarkEntry) + com.google.protobuf.MessageOrBuilder { + + /** + * 
    +   * The name of the specific benchmark or test
+   * (e.g. BM_AdjustContrast_gpu_B_W_H)
+   *
    + * + * string name = 1; + * @return The name. + */ + java.lang.String getName(); + /** + * 
    +   * The name of the specific benchmark or test
+   * (e.g. BM_AdjustContrast_gpu_B_W_H)
+   *
    + * + * string name = 1; + * @return The bytes for name. + */ + com.google.protobuf.ByteString + getNameBytes(); + + /** + * 
    +   * If a benchmark, how many iterations it was run for
+   *
    + * + * int64 iters = 2; + * @return The iters. + */ + long getIters(); + + /** + * 
    +   * Total cpu time used for all iterations (in seconds)
+   *
    + * + * double cpu_time = 3; + * @return The cpuTime. + */ + double getCpuTime(); + + /** + * 
    +   * Total wall time used for all iterations (in seconds)
+   *
    + * + * double wall_time = 4; + * @return The wallTime. + */ + double getWallTime(); + + /** + * 
    +   * Throughput (in MB/s)
+   *
    + * + * double throughput = 5; + * @return The throughput. + */ + double getThroughput(); + + /** + * 
    +   * Generic map from result key to value.
+   *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + int getExtrasCount(); + /** + * 
    +   * Generic map from result key to value.
+   *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + boolean containsExtras( + java.lang.String key); + /** + * Use {@link #getExtrasMap()} instead. + */ + @java.lang.Deprecated + java.util.Map + getExtras(); + /** + * 
    +   * Generic map from result key to value.
+   *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + java.util.Map + getExtrasMap(); + /** + * 
    +   * Generic map from result key to value.
+   *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + + /* nullable */ +org.tensorflow.proto.EntryValue getExtrasOrDefault( + java.lang.String key, + /* nullable */ +org.tensorflow.proto.EntryValue defaultValue); + /** + * 
    +   * Generic map from result key to value.
+   *
    + * + * map<string, .tensorflow.EntryValue> extras = 6; + */ + + org.tensorflow.proto.EntryValue getExtrasOrThrow( + java.lang.String key); + + /** + * 
    +   * Metric name, value and expected range. This can include accuracy metrics
+   * typically used to determine whether the accuracy test has passed
+   *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + java.util.List + getMetricsList(); + /** + * 
    +   * Metric name, value and expected range. This can include accuracy metrics
+   * typically used to determine whether the accuracy test has passed
+   *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + org.tensorflow.proto.MetricEntry getMetrics(int index); + /** + * 
    +   * Metric name, value and expected range. This can include accuracy metrics
+   * typically used to determine whether the accuracy test has passed
+   *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + int getMetricsCount(); + /** + * 
    +   * Metric name, value and expected range. This can include accuracy metrics
+   * typically used to determine whether the accuracy test has passed
+   *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + java.util.List + getMetricsOrBuilderList(); + /** + * 
    +   * Metric name, value and expected range. This can include accuracy metrics
+   * typically used to determine whether the accuracy test has passed
+   *
    + * + * repeated .tensorflow.MetricEntry metrics = 7; + */ + org.tensorflow.proto.MetricEntryOrBuilder getMetricsOrBuilder( + int index); +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BfcMemoryMap.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BfcMemoryMap.java new file mode 100644 index 00000000000..e894298881d --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BfcMemoryMap.java @@ -0,0 +1,5154 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/bfc_memory_map.proto + +package org.tensorflow.proto; + +public final class BfcMemoryMap { + private BfcMemoryMap() {} + public static void registerAllExtensions( + com.google.protobuf.ExtensionRegistryLite registry) { + } + + public static void registerAllExtensions( + com.google.protobuf.ExtensionRegistry registry) { + registerAllExtensions( + (com.google.protobuf.ExtensionRegistryLite) registry); + } + public interface MemAllocatorStatsOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.MemAllocatorStats) + com.google.protobuf.MessageOrBuilder { + + /** + * int64 num_allocs = 1; + * @return The numAllocs. + */ + long getNumAllocs(); + + /** + * int64 bytes_in_use = 2; + * @return The bytesInUse. + */ + long getBytesInUse(); + + /** + * int64 peak_bytes_in_use = 3; + * @return The peakBytesInUse. + */ + long getPeakBytesInUse(); + + /** + * int64 largest_alloc_size = 4; + * @return The largestAllocSize. + */ + long getLargestAllocSize(); + + /** + * float fragmentation_metric = 5; + * @return The fragmentationMetric. + */ + float getFragmentationMetric(); + } + /** + * 
    +   * Some of the data from AllocatorStats
+   *
    + * + * Protobuf type {@code tensorflow.MemAllocatorStats} + */ + public static final class MemAllocatorStats extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.MemAllocatorStats) + MemAllocatorStatsOrBuilder { + private static final long serialVersionUID = 0L; + // Use MemAllocatorStats.newBuilder() to construct. + private MemAllocatorStats(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private MemAllocatorStats() { + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new MemAllocatorStats(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemAllocatorStats_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemAllocatorStats_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.class, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.Builder.class); + } + + public static final int NUM_ALLOCS_FIELD_NUMBER = 1; + private long numAllocs_; + /** + * int64 num_allocs = 1; + * @return The numAllocs. + */ + @java.lang.Override + public long getNumAllocs() { + return numAllocs_; + } + + public static final int BYTES_IN_USE_FIELD_NUMBER = 2; + private long bytesInUse_; + /** + * int64 bytes_in_use = 2; + * @return The bytesInUse. + */ + @java.lang.Override + public long getBytesInUse() { + return bytesInUse_; + } + + public static final int PEAK_BYTES_IN_USE_FIELD_NUMBER = 3; + private long peakBytesInUse_; + /** + * int64 peak_bytes_in_use = 3; + * @return The peakBytesInUse. + */ + @java.lang.Override + public long getPeakBytesInUse() { + return peakBytesInUse_; + } + + public static final int LARGEST_ALLOC_SIZE_FIELD_NUMBER = 4; + private long largestAllocSize_; + /** + * int64 largest_alloc_size = 4; + * @return The largestAllocSize. + */ + @java.lang.Override + public long getLargestAllocSize() { + return largestAllocSize_; + } + + public static final int FRAGMENTATION_METRIC_FIELD_NUMBER = 5; + private float fragmentationMetric_; + /** + * float fragmentation_metric = 5; + * @return The fragmentationMetric. + */ + @java.lang.Override + public float getFragmentationMetric() { + return fragmentationMetric_; + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (numAllocs_ != 0L) { + output.writeInt64(1, numAllocs_); + } + if (bytesInUse_ != 0L) { + output.writeInt64(2, bytesInUse_); + } + if (peakBytesInUse_ != 0L) { + output.writeInt64(3, peakBytesInUse_); + } + if (largestAllocSize_ != 0L) { + output.writeInt64(4, largestAllocSize_); + } + if (java.lang.Float.floatToRawIntBits(fragmentationMetric_) != 0) { + output.writeFloat(5, fragmentationMetric_); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (numAllocs_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(1, numAllocs_); + } + if (bytesInUse_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(2, bytesInUse_); + } + if (peakBytesInUse_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(3, peakBytesInUse_); + } + if (largestAllocSize_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(4, largestAllocSize_); + } + if (java.lang.Float.floatToRawIntBits(fragmentationMetric_) != 0) { + size += com.google.protobuf.CodedOutputStream + .computeFloatSize(5, fragmentationMetric_); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats)) { + return super.equals(obj); + } + org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats other = (org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats) obj; + + if (getNumAllocs() + != other.getNumAllocs()) return false; + if (getBytesInUse() + != other.getBytesInUse()) return false; + if (getPeakBytesInUse() + != other.getPeakBytesInUse()) return false; + if (getLargestAllocSize() + != other.getLargestAllocSize()) return false; + if (java.lang.Float.floatToIntBits(getFragmentationMetric()) + != java.lang.Float.floatToIntBits( + other.getFragmentationMetric())) return false; + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + NUM_ALLOCS_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getNumAllocs()); + hash = (37 * hash) + BYTES_IN_USE_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getBytesInUse()); + hash = (37 * hash) + PEAK_BYTES_IN_USE_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getPeakBytesInUse()); + hash = (37 * hash) + LARGEST_ALLOC_SIZE_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getLargestAllocSize()); + hash = (37 * hash) + FRAGMENTATION_METRIC_FIELD_NUMBER; + hash = (53 * hash) + java.lang.Float.floatToIntBits( + getFragmentationMetric()); + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * 
    +     * Some of the data from AllocatorStats
+     *
    + * + * Protobuf type {@code tensorflow.MemAllocatorStats} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.MemAllocatorStats) + org.tensorflow.proto.BfcMemoryMap.MemAllocatorStatsOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemAllocatorStats_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemAllocatorStats_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.class, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.Builder.class); + } + + // Construct using org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + numAllocs_ = 0L; + + bytesInUse_ = 0L; + + peakBytesInUse_ = 0L; + + largestAllocSize_ = 0L; + + fragmentationMetric_ = 0F; + + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemAllocatorStats_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats getDefaultInstanceForType() { + return org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats build() { + org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats buildPartial() { + org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats result = new org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats(this); + result.numAllocs_ = numAllocs_; + result.bytesInUse_ = bytesInUse_; + result.peakBytesInUse_ = peakBytesInUse_; + result.largestAllocSize_ = largestAllocSize_; + result.fragmentationMetric_ = fragmentationMetric_; + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats) { + return mergeFrom((org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats other) { + if (other == org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.getDefaultInstance()) return this; + if (other.getNumAllocs() != 0L) { + setNumAllocs(other.getNumAllocs()); + } + if (other.getBytesInUse() != 0L) { + setBytesInUse(other.getBytesInUse()); + } + if (other.getPeakBytesInUse() != 0L) { + setPeakBytesInUse(other.getPeakBytesInUse()); + } + if (other.getLargestAllocSize() != 0L) { + setLargestAllocSize(other.getLargestAllocSize()); + } + if (other.getFragmentationMetric() != 0F) { + setFragmentationMetric(other.getFragmentationMetric()); + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 8: { + numAllocs_ = input.readInt64(); + + break; + } // case 8 + case 16: { + bytesInUse_ = input.readInt64(); + + break; + } // case 16 + case 24: { + peakBytesInUse_ = input.readInt64(); + + break; + } // case 24 + case 32: { + largestAllocSize_ = input.readInt64(); + + break; + } // case 32 + case 45: { + fragmentationMetric_ = input.readFloat(); + + break; + } // case 45 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + + private long numAllocs_ ; + /** + * int64 num_allocs = 1; + * @return The numAllocs. + */ + @java.lang.Override + public long getNumAllocs() { + return numAllocs_; + } + /** + * int64 num_allocs = 1; + * @param value The numAllocs to set. + * @return This builder for chaining. + */ + public Builder setNumAllocs(long value) { + + numAllocs_ = value; + onChanged(); + return this; + } + /** + * int64 num_allocs = 1; + * @return This builder for chaining. + */ + public Builder clearNumAllocs() { + + numAllocs_ = 0L; + onChanged(); + return this; + } + + private long bytesInUse_ ; + /** + * int64 bytes_in_use = 2; + * @return The bytesInUse. + */ + @java.lang.Override + public long getBytesInUse() { + return bytesInUse_; + } + /** + * int64 bytes_in_use = 2; + * @param value The bytesInUse to set. + * @return This builder for chaining. + */ + public Builder setBytesInUse(long value) { + + bytesInUse_ = value; + onChanged(); + return this; + } + /** + * int64 bytes_in_use = 2; + * @return This builder for chaining. + */ + public Builder clearBytesInUse() { + + bytesInUse_ = 0L; + onChanged(); + return this; + } + + private long peakBytesInUse_ ; + /** + * int64 peak_bytes_in_use = 3; + * @return The peakBytesInUse. + */ + @java.lang.Override + public long getPeakBytesInUse() { + return peakBytesInUse_; + } + /** + * int64 peak_bytes_in_use = 3; + * @param value The peakBytesInUse to set. + * @return This builder for chaining. + */ + public Builder setPeakBytesInUse(long value) { + + peakBytesInUse_ = value; + onChanged(); + return this; + } + /** + * int64 peak_bytes_in_use = 3; + * @return This builder for chaining. + */ + public Builder clearPeakBytesInUse() { + + peakBytesInUse_ = 0L; + onChanged(); + return this; + } + + private long largestAllocSize_ ; + /** + * int64 largest_alloc_size = 4; + * @return The largestAllocSize. + */ + @java.lang.Override + public long getLargestAllocSize() { + return largestAllocSize_; + } + /** + * int64 largest_alloc_size = 4; + * @param value The largestAllocSize to set. + * @return This builder for chaining. + */ + public Builder setLargestAllocSize(long value) { + + largestAllocSize_ = value; + onChanged(); + return this; + } + /** + * int64 largest_alloc_size = 4; + * @return This builder for chaining. + */ + public Builder clearLargestAllocSize() { + + largestAllocSize_ = 0L; + onChanged(); + return this; + } + + private float fragmentationMetric_ ; + /** + * float fragmentation_metric = 5; + * @return The fragmentationMetric. + */ + @java.lang.Override + public float getFragmentationMetric() { + return fragmentationMetric_; + } + /** + * float fragmentation_metric = 5; + * @param value The fragmentationMetric to set. + * @return This builder for chaining. + */ + public Builder setFragmentationMetric(float value) { + + fragmentationMetric_ = value; + onChanged(); + return this; + } + /** + * float fragmentation_metric = 5; + * @return This builder for chaining. + */ + public Builder clearFragmentationMetric() { + + fragmentationMetric_ = 0F; + onChanged(); + return this; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.MemAllocatorStats) + } + + // @@protoc_insertion_point(class_scope:tensorflow.MemAllocatorStats) + private static final org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats(); + } + + public static org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public MemAllocatorStats parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + + } + + public interface MemChunkOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.MemChunk) + com.google.protobuf.MessageOrBuilder { + + /** + * uint64 address = 1; + * @return The address. + */ + long getAddress(); + + /** + * int64 size = 2; + * @return The size. + */ + long getSize(); + + /** + * int64 requested_size = 3; + * @return The requestedSize. + */ + long getRequestedSize(); + + /** + * int32 bin = 4; + * @return The bin. + */ + int getBin(); + + /** + * string op_name = 5; + * @return The opName. + */ + java.lang.String getOpName(); + /** + * string op_name = 5; + * @return The bytes for opName. + */ + com.google.protobuf.ByteString + getOpNameBytes(); + + /** + * uint64 freed_at_count = 6; + * @return The freedAtCount. + */ + long getFreedAtCount(); + + /** + * uint64 action_count = 7; + * @return The actionCount. + */ + long getActionCount(); + + /** + * bool in_use = 8; + * @return The inUse. + */ + boolean getInUse(); + + /** + * uint64 step_id = 9; + * @return The stepId. + */ + long getStepId(); + } + /** + * Protobuf type {@code tensorflow.MemChunk} + */ + public static final class MemChunk extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.MemChunk) + MemChunkOrBuilder { + private static final long serialVersionUID = 0L; + // Use MemChunk.newBuilder() to construct. + private MemChunk(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private MemChunk() { + opName_ = ""; + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new MemChunk(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemChunk_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemChunk_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BfcMemoryMap.MemChunk.class, org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder.class); + } + + public static final int ADDRESS_FIELD_NUMBER = 1; + private long address_; + /** + * uint64 address = 1; + * @return The address. + */ + @java.lang.Override + public long getAddress() { + return address_; + } + + public static final int SIZE_FIELD_NUMBER = 2; + private long size_; + /** + * int64 size = 2; + * @return The size. + */ + @java.lang.Override + public long getSize() { + return size_; + } + + public static final int REQUESTED_SIZE_FIELD_NUMBER = 3; + private long requestedSize_; + /** + * int64 requested_size = 3; + * @return The requestedSize. + */ + @java.lang.Override + public long getRequestedSize() { + return requestedSize_; + } + + public static final int BIN_FIELD_NUMBER = 4; + private int bin_; + /** + * int32 bin = 4; + * @return The bin. + */ + @java.lang.Override + public int getBin() { + return bin_; + } + + public static final int OP_NAME_FIELD_NUMBER = 5; + private volatile java.lang.Object opName_; + /** + * string op_name = 5; + * @return The opName. + */ + @java.lang.Override + public java.lang.String getOpName() { + java.lang.Object ref = opName_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + opName_ = s; + return s; + } + } + /** + * string op_name = 5; + * @return The bytes for opName. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getOpNameBytes() { + java.lang.Object ref = opName_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + opName_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int FREED_AT_COUNT_FIELD_NUMBER = 6; + private long freedAtCount_; + /** + * uint64 freed_at_count = 6; + * @return The freedAtCount. + */ + @java.lang.Override + public long getFreedAtCount() { + return freedAtCount_; + } + + public static final int ACTION_COUNT_FIELD_NUMBER = 7; + private long actionCount_; + /** + * uint64 action_count = 7; + * @return The actionCount. + */ + @java.lang.Override + public long getActionCount() { + return actionCount_; + } + + public static final int IN_USE_FIELD_NUMBER = 8; + private boolean inUse_; + /** + * bool in_use = 8; + * @return The inUse. + */ + @java.lang.Override + public boolean getInUse() { + return inUse_; + } + + public static final int STEP_ID_FIELD_NUMBER = 9; + private long stepId_; + /** + * uint64 step_id = 9; + * @return The stepId. + */ + @java.lang.Override + public long getStepId() { + return stepId_; + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (address_ != 0L) { + output.writeUInt64(1, address_); + } + if (size_ != 0L) { + output.writeInt64(2, size_); + } + if (requestedSize_ != 0L) { + output.writeInt64(3, requestedSize_); + } + if (bin_ != 0) { + output.writeInt32(4, bin_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(opName_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 5, opName_); + } + if (freedAtCount_ != 0L) { + output.writeUInt64(6, freedAtCount_); + } + if (actionCount_ != 0L) { + output.writeUInt64(7, actionCount_); + } + if (inUse_ != false) { + output.writeBool(8, inUse_); + } + if (stepId_ != 0L) { + output.writeUInt64(9, stepId_); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (address_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeUInt64Size(1, address_); + } + if (size_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(2, size_); + } + if (requestedSize_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(3, requestedSize_); + } + if (bin_ != 0) { + size += com.google.protobuf.CodedOutputStream + .computeInt32Size(4, bin_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(opName_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(5, opName_); + } + if (freedAtCount_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeUInt64Size(6, freedAtCount_); + } + if (actionCount_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeUInt64Size(7, actionCount_); + } + if (inUse_ != false) { + size += com.google.protobuf.CodedOutputStream + .computeBoolSize(8, inUse_); + } + if (stepId_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeUInt64Size(9, stepId_); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.BfcMemoryMap.MemChunk)) { + return super.equals(obj); + } + org.tensorflow.proto.BfcMemoryMap.MemChunk other = (org.tensorflow.proto.BfcMemoryMap.MemChunk) obj; + + if (getAddress() + != other.getAddress()) return false; + if (getSize() + != other.getSize()) return false; + if (getRequestedSize() + != other.getRequestedSize()) return false; + if (getBin() + != other.getBin()) return false; + if (!getOpName() + .equals(other.getOpName())) return false; + if (getFreedAtCount() + != other.getFreedAtCount()) return false; + if (getActionCount() + != other.getActionCount()) return false; + if (getInUse() + != other.getInUse()) return false; + if (getStepId() + != other.getStepId()) return false; + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + ADDRESS_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getAddress()); + hash = (37 * hash) + SIZE_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getSize()); + hash = (37 * hash) + REQUESTED_SIZE_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getRequestedSize()); + hash = (37 * hash) + BIN_FIELD_NUMBER; + hash = (53 * hash) + getBin(); + hash = (37 * hash) + OP_NAME_FIELD_NUMBER; + hash = (53 * hash) + getOpName().hashCode(); + hash = (37 * hash) + FREED_AT_COUNT_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getFreedAtCount()); + hash = (37 * hash) + ACTION_COUNT_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getActionCount()); + hash = (37 * hash) + IN_USE_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashBoolean( + getInUse()); + hash = (37 * hash) + STEP_ID_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getStepId()); + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.MemChunk parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.BfcMemoryMap.MemChunk prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * Protobuf type {@code tensorflow.MemChunk} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.MemChunk) + org.tensorflow.proto.BfcMemoryMap.MemChunkOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemChunk_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemChunk_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BfcMemoryMap.MemChunk.class, org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder.class); + } + + // Construct using org.tensorflow.proto.BfcMemoryMap.MemChunk.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + address_ = 0L; + + size_ = 0L; + + requestedSize_ = 0L; + + bin_ = 0; + + opName_ = ""; + + freedAtCount_ = 0L; + + actionCount_ = 0L; + + inUse_ = false; + + stepId_ = 0L; + + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemChunk_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemChunk getDefaultInstanceForType() { + return org.tensorflow.proto.BfcMemoryMap.MemChunk.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemChunk build() { + org.tensorflow.proto.BfcMemoryMap.MemChunk result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemChunk buildPartial() { + org.tensorflow.proto.BfcMemoryMap.MemChunk result = new org.tensorflow.proto.BfcMemoryMap.MemChunk(this); + result.address_ = address_; + result.size_ = size_; + result.requestedSize_ = requestedSize_; + result.bin_ = bin_; + result.opName_ = opName_; + result.freedAtCount_ = freedAtCount_; + result.actionCount_ = actionCount_; + result.inUse_ = inUse_; + result.stepId_ = stepId_; + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.BfcMemoryMap.MemChunk) { + return mergeFrom((org.tensorflow.proto.BfcMemoryMap.MemChunk)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.BfcMemoryMap.MemChunk other) { + if (other == org.tensorflow.proto.BfcMemoryMap.MemChunk.getDefaultInstance()) return this; + if (other.getAddress() != 0L) { + setAddress(other.getAddress()); + } + if (other.getSize() != 0L) { + setSize(other.getSize()); + } + if (other.getRequestedSize() != 0L) { + setRequestedSize(other.getRequestedSize()); + } + if (other.getBin() != 0) { + setBin(other.getBin()); + } + if (!other.getOpName().isEmpty()) { + opName_ = other.opName_; + onChanged(); + } + if (other.getFreedAtCount() != 0L) { + setFreedAtCount(other.getFreedAtCount()); + } + if (other.getActionCount() != 0L) { + setActionCount(other.getActionCount()); + } + if (other.getInUse() != false) { + setInUse(other.getInUse()); + } + if (other.getStepId() != 0L) { + setStepId(other.getStepId()); + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 8: { + address_ = input.readUInt64(); + + break; + } // case 8 + case 16: { + size_ = input.readInt64(); + + break; + } // case 16 + case 24: { + requestedSize_ = input.readInt64(); + + break; + } // case 24 + case 32: { + bin_ = input.readInt32(); + + break; + } // case 32 + case 42: { + opName_ = input.readStringRequireUtf8(); + + break; + } // case 42 + case 48: { + freedAtCount_ = input.readUInt64(); + + break; + } // case 48 + case 56: { + actionCount_ = input.readUInt64(); + + break; + } // case 56 + case 64: { + inUse_ = input.readBool(); + + break; + } // case 64 + case 72: { + stepId_ = input.readUInt64(); + + break; + } // case 72 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + + private long address_ ; + /** + * uint64 address = 1; + * @return The address. + */ + @java.lang.Override + public long getAddress() { + return address_; + } + /** + * uint64 address = 1; + * @param value The address to set. + * @return This builder for chaining. + */ + public Builder setAddress(long value) { + + address_ = value; + onChanged(); + return this; + } + /** + * uint64 address = 1; + * @return This builder for chaining. + */ + public Builder clearAddress() { + + address_ = 0L; + onChanged(); + return this; + } + + private long size_ ; + /** + * int64 size = 2; + * @return The size. + */ + @java.lang.Override + public long getSize() { + return size_; + } + /** + * int64 size = 2; + * @param value The size to set. + * @return This builder for chaining. + */ + public Builder setSize(long value) { + + size_ = value; + onChanged(); + return this; + } + /** + * int64 size = 2; + * @return This builder for chaining. + */ + public Builder clearSize() { + + size_ = 0L; + onChanged(); + return this; + } + + private long requestedSize_ ; + /** + * int64 requested_size = 3; + * @return The requestedSize. + */ + @java.lang.Override + public long getRequestedSize() { + return requestedSize_; + } + /** + * int64 requested_size = 3; + * @param value The requestedSize to set. + * @return This builder for chaining. + */ + public Builder setRequestedSize(long value) { + + requestedSize_ = value; + onChanged(); + return this; + } + /** + * int64 requested_size = 3; + * @return This builder for chaining. + */ + public Builder clearRequestedSize() { + + requestedSize_ = 0L; + onChanged(); + return this; + } + + private int bin_ ; + /** + * int32 bin = 4; + * @return The bin. + */ + @java.lang.Override + public int getBin() { + return bin_; + } + /** + * int32 bin = 4; + * @param value The bin to set. + * @return This builder for chaining. + */ + public Builder setBin(int value) { + + bin_ = value; + onChanged(); + return this; + } + /** + * int32 bin = 4; + * @return This builder for chaining. + */ + public Builder clearBin() { + + bin_ = 0; + onChanged(); + return this; + } + + private java.lang.Object opName_ = ""; + /** + * string op_name = 5; + * @return The opName. + */ + public java.lang.String getOpName() { + java.lang.Object ref = opName_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + opName_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * string op_name = 5; + * @return The bytes for opName. + */ + public com.google.protobuf.ByteString + getOpNameBytes() { + java.lang.Object ref = opName_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + opName_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * string op_name = 5; + * @param value The opName to set. + * @return This builder for chaining. + */ + public Builder setOpName( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + opName_ = value; + onChanged(); + return this; + } + /** + * string op_name = 5; + * @return This builder for chaining. + */ + public Builder clearOpName() { + + opName_ = getDefaultInstance().getOpName(); + onChanged(); + return this; + } + /** + * string op_name = 5; + * @param value The bytes for opName to set. + * @return This builder for chaining. + */ + public Builder setOpNameBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + opName_ = value; + onChanged(); + return this; + } + + private long freedAtCount_ ; + /** + * uint64 freed_at_count = 6; + * @return The freedAtCount. + */ + @java.lang.Override + public long getFreedAtCount() { + return freedAtCount_; + } + /** + * uint64 freed_at_count = 6; + * @param value The freedAtCount to set. + * @return This builder for chaining. + */ + public Builder setFreedAtCount(long value) { + + freedAtCount_ = value; + onChanged(); + return this; + } + /** + * uint64 freed_at_count = 6; + * @return This builder for chaining. + */ + public Builder clearFreedAtCount() { + + freedAtCount_ = 0L; + onChanged(); + return this; + } + + private long actionCount_ ; + /** + * uint64 action_count = 7; + * @return The actionCount. + */ + @java.lang.Override + public long getActionCount() { + return actionCount_; + } + /** + * uint64 action_count = 7; + * @param value The actionCount to set. + * @return This builder for chaining. + */ + public Builder setActionCount(long value) { + + actionCount_ = value; + onChanged(); + return this; + } + /** + * uint64 action_count = 7; + * @return This builder for chaining. + */ + public Builder clearActionCount() { + + actionCount_ = 0L; + onChanged(); + return this; + } + + private boolean inUse_ ; + /** + * bool in_use = 8; + * @return The inUse. + */ + @java.lang.Override + public boolean getInUse() { + return inUse_; + } + /** + * bool in_use = 8; + * @param value The inUse to set. + * @return This builder for chaining. + */ + public Builder setInUse(boolean value) { + + inUse_ = value; + onChanged(); + return this; + } + /** + * bool in_use = 8; + * @return This builder for chaining. + */ + public Builder clearInUse() { + + inUse_ = false; + onChanged(); + return this; + } + + private long stepId_ ; + /** + * uint64 step_id = 9; + * @return The stepId. + */ + @java.lang.Override + public long getStepId() { + return stepId_; + } + /** + * uint64 step_id = 9; + * @param value The stepId to set. + * @return This builder for chaining. + */ + public Builder setStepId(long value) { + + stepId_ = value; + onChanged(); + return this; + } + /** + * uint64 step_id = 9; + * @return This builder for chaining. + */ + public Builder clearStepId() { + + stepId_ = 0L; + onChanged(); + return this; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.MemChunk) + } + + // @@protoc_insertion_point(class_scope:tensorflow.MemChunk) + private static final org.tensorflow.proto.BfcMemoryMap.MemChunk DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.BfcMemoryMap.MemChunk(); + } + + public static org.tensorflow.proto.BfcMemoryMap.MemChunk getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public MemChunk parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemChunk getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + + } + + public interface BinSummaryOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.BinSummary) + com.google.protobuf.MessageOrBuilder { + + /** + * int32 bin = 1; + * @return The bin. + */ + int getBin(); + + /** + * int64 total_bytes_in_use = 2; + * @return The totalBytesInUse. + */ + long getTotalBytesInUse(); + + /** + * int64 total_bytes_in_bin = 3; + * @return The totalBytesInBin. + */ + long getTotalBytesInBin(); + + /** + * int64 total_chunks_in_use = 4; + * @return The totalChunksInUse. + */ + long getTotalChunksInUse(); + + /** + * int64 total_chunks_in_bin = 5; + * @return The totalChunksInBin. + */ + long getTotalChunksInBin(); + } + /** + * Protobuf type {@code tensorflow.BinSummary} + */ + public static final class BinSummary extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.BinSummary) + BinSummaryOrBuilder { + private static final long serialVersionUID = 0L; + // Use BinSummary.newBuilder() to construct. + private BinSummary(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private BinSummary() { + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new BinSummary(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_BinSummary_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_BinSummary_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BfcMemoryMap.BinSummary.class, org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder.class); + } + + public static final int BIN_FIELD_NUMBER = 1; + private int bin_; + /** + * int32 bin = 1; + * @return The bin. + */ + @java.lang.Override + public int getBin() { + return bin_; + } + + public static final int TOTAL_BYTES_IN_USE_FIELD_NUMBER = 2; + private long totalBytesInUse_; + /** + * int64 total_bytes_in_use = 2; + * @return The totalBytesInUse. + */ + @java.lang.Override + public long getTotalBytesInUse() { + return totalBytesInUse_; + } + + public static final int TOTAL_BYTES_IN_BIN_FIELD_NUMBER = 3; + private long totalBytesInBin_; + /** + * int64 total_bytes_in_bin = 3; + * @return The totalBytesInBin. + */ + @java.lang.Override + public long getTotalBytesInBin() { + return totalBytesInBin_; + } + + public static final int TOTAL_CHUNKS_IN_USE_FIELD_NUMBER = 4; + private long totalChunksInUse_; + /** + * int64 total_chunks_in_use = 4; + * @return The totalChunksInUse. + */ + @java.lang.Override + public long getTotalChunksInUse() { + return totalChunksInUse_; + } + + public static final int TOTAL_CHUNKS_IN_BIN_FIELD_NUMBER = 5; + private long totalChunksInBin_; + /** + * int64 total_chunks_in_bin = 5; + * @return The totalChunksInBin. + */ + @java.lang.Override + public long getTotalChunksInBin() { + return totalChunksInBin_; + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (bin_ != 0) { + output.writeInt32(1, bin_); + } + if (totalBytesInUse_ != 0L) { + output.writeInt64(2, totalBytesInUse_); + } + if (totalBytesInBin_ != 0L) { + output.writeInt64(3, totalBytesInBin_); + } + if (totalChunksInUse_ != 0L) { + output.writeInt64(4, totalChunksInUse_); + } + if (totalChunksInBin_ != 0L) { + output.writeInt64(5, totalChunksInBin_); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (bin_ != 0) { + size += com.google.protobuf.CodedOutputStream + .computeInt32Size(1, bin_); + } + if (totalBytesInUse_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(2, totalBytesInUse_); + } + if (totalBytesInBin_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(3, totalBytesInBin_); + } + if (totalChunksInUse_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(4, totalChunksInUse_); + } + if (totalChunksInBin_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(5, totalChunksInBin_); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.BfcMemoryMap.BinSummary)) { + return super.equals(obj); + } + org.tensorflow.proto.BfcMemoryMap.BinSummary other = (org.tensorflow.proto.BfcMemoryMap.BinSummary) obj; + + if (getBin() + != other.getBin()) return false; + if (getTotalBytesInUse() + != other.getTotalBytesInUse()) return false; + if (getTotalBytesInBin() + != other.getTotalBytesInBin()) return false; + if (getTotalChunksInUse() + != other.getTotalChunksInUse()) return false; + if (getTotalChunksInBin() + != other.getTotalChunksInBin()) return false; + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + BIN_FIELD_NUMBER; + hash = (53 * hash) + getBin(); + hash = (37 * hash) + TOTAL_BYTES_IN_USE_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getTotalBytesInUse()); + hash = (37 * hash) + TOTAL_BYTES_IN_BIN_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getTotalBytesInBin()); + hash = (37 * hash) + TOTAL_CHUNKS_IN_USE_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getTotalChunksInUse()); + hash = (37 * hash) + TOTAL_CHUNKS_IN_BIN_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getTotalChunksInBin()); + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.BinSummary parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.BfcMemoryMap.BinSummary prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * Protobuf type {@code tensorflow.BinSummary} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.BinSummary) + org.tensorflow.proto.BfcMemoryMap.BinSummaryOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_BinSummary_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_BinSummary_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BfcMemoryMap.BinSummary.class, org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder.class); + } + + // Construct using org.tensorflow.proto.BfcMemoryMap.BinSummary.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + bin_ = 0; + + totalBytesInUse_ = 0L; + + totalBytesInBin_ = 0L; + + totalChunksInUse_ = 0L; + + totalChunksInBin_ = 0L; + + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_BinSummary_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.BinSummary getDefaultInstanceForType() { + return org.tensorflow.proto.BfcMemoryMap.BinSummary.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.BinSummary build() { + org.tensorflow.proto.BfcMemoryMap.BinSummary result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.BinSummary buildPartial() { + org.tensorflow.proto.BfcMemoryMap.BinSummary result = new org.tensorflow.proto.BfcMemoryMap.BinSummary(this); + result.bin_ = bin_; + result.totalBytesInUse_ = totalBytesInUse_; + result.totalBytesInBin_ = totalBytesInBin_; + result.totalChunksInUse_ = totalChunksInUse_; + result.totalChunksInBin_ = totalChunksInBin_; + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.BfcMemoryMap.BinSummary) { + return mergeFrom((org.tensorflow.proto.BfcMemoryMap.BinSummary)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.BfcMemoryMap.BinSummary other) { + if (other == org.tensorflow.proto.BfcMemoryMap.BinSummary.getDefaultInstance()) return this; + if (other.getBin() != 0) { + setBin(other.getBin()); + } + if (other.getTotalBytesInUse() != 0L) { + setTotalBytesInUse(other.getTotalBytesInUse()); + } + if (other.getTotalBytesInBin() != 0L) { + setTotalBytesInBin(other.getTotalBytesInBin()); + } + if (other.getTotalChunksInUse() != 0L) { + setTotalChunksInUse(other.getTotalChunksInUse()); + } + if (other.getTotalChunksInBin() != 0L) { + setTotalChunksInBin(other.getTotalChunksInBin()); + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 8: { + bin_ = input.readInt32(); + + break; + } // case 8 + case 16: { + totalBytesInUse_ = input.readInt64(); + + break; + } // case 16 + case 24: { + totalBytesInBin_ = input.readInt64(); + + break; + } // case 24 + case 32: { + totalChunksInUse_ = input.readInt64(); + + break; + } // case 32 + case 40: { + totalChunksInBin_ = input.readInt64(); + + break; + } // case 40 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + + private int bin_ ; + /** + * int32 bin = 1; + * @return The bin. + */ + @java.lang.Override + public int getBin() { + return bin_; + } + /** + * int32 bin = 1; + * @param value The bin to set. + * @return This builder for chaining. + */ + public Builder setBin(int value) { + + bin_ = value; + onChanged(); + return this; + } + /** + * int32 bin = 1; + * @return This builder for chaining. + */ + public Builder clearBin() { + + bin_ = 0; + onChanged(); + return this; + } + + private long totalBytesInUse_ ; + /** + * int64 total_bytes_in_use = 2; + * @return The totalBytesInUse. + */ + @java.lang.Override + public long getTotalBytesInUse() { + return totalBytesInUse_; + } + /** + * int64 total_bytes_in_use = 2; + * @param value The totalBytesInUse to set. + * @return This builder for chaining. + */ + public Builder setTotalBytesInUse(long value) { + + totalBytesInUse_ = value; + onChanged(); + return this; + } + /** + * int64 total_bytes_in_use = 2; + * @return This builder for chaining. + */ + public Builder clearTotalBytesInUse() { + + totalBytesInUse_ = 0L; + onChanged(); + return this; + } + + private long totalBytesInBin_ ; + /** + * int64 total_bytes_in_bin = 3; + * @return The totalBytesInBin. + */ + @java.lang.Override + public long getTotalBytesInBin() { + return totalBytesInBin_; + } + /** + * int64 total_bytes_in_bin = 3; + * @param value The totalBytesInBin to set. + * @return This builder for chaining. + */ + public Builder setTotalBytesInBin(long value) { + + totalBytesInBin_ = value; + onChanged(); + return this; + } + /** + * int64 total_bytes_in_bin = 3; + * @return This builder for chaining. + */ + public Builder clearTotalBytesInBin() { + + totalBytesInBin_ = 0L; + onChanged(); + return this; + } + + private long totalChunksInUse_ ; + /** + * int64 total_chunks_in_use = 4; + * @return The totalChunksInUse. + */ + @java.lang.Override + public long getTotalChunksInUse() { + return totalChunksInUse_; + } + /** + * int64 total_chunks_in_use = 4; + * @param value The totalChunksInUse to set. + * @return This builder for chaining. + */ + public Builder setTotalChunksInUse(long value) { + + totalChunksInUse_ = value; + onChanged(); + return this; + } + /** + * int64 total_chunks_in_use = 4; + * @return This builder for chaining. + */ + public Builder clearTotalChunksInUse() { + + totalChunksInUse_ = 0L; + onChanged(); + return this; + } + + private long totalChunksInBin_ ; + /** + * int64 total_chunks_in_bin = 5; + * @return The totalChunksInBin. + */ + @java.lang.Override + public long getTotalChunksInBin() { + return totalChunksInBin_; + } + /** + * int64 total_chunks_in_bin = 5; + * @param value The totalChunksInBin to set. + * @return This builder for chaining. + */ + public Builder setTotalChunksInBin(long value) { + + totalChunksInBin_ = value; + onChanged(); + return this; + } + /** + * int64 total_chunks_in_bin = 5; + * @return This builder for chaining. + */ + public Builder clearTotalChunksInBin() { + + totalChunksInBin_ = 0L; + onChanged(); + return this; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.BinSummary) + } + + // @@protoc_insertion_point(class_scope:tensorflow.BinSummary) + private static final org.tensorflow.proto.BfcMemoryMap.BinSummary DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.BfcMemoryMap.BinSummary(); + } + + public static org.tensorflow.proto.BfcMemoryMap.BinSummary getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public BinSummary parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.BinSummary getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + + } + + public interface SnapShotOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.SnapShot) + com.google.protobuf.MessageOrBuilder { + + /** + * uint64 action_count = 1; + * @return The actionCount. + */ + long getActionCount(); + + /** + * int64 size = 2; + * @return The size. + */ + long getSize(); + } + /** + * Protobuf type {@code tensorflow.SnapShot} + */ + public static final class SnapShot extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.SnapShot) + SnapShotOrBuilder { + private static final long serialVersionUID = 0L; + // Use SnapShot.newBuilder() to construct. + private SnapShot(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private SnapShot() { + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new SnapShot(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_SnapShot_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_SnapShot_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BfcMemoryMap.SnapShot.class, org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder.class); + } + + public static final int ACTION_COUNT_FIELD_NUMBER = 1; + private long actionCount_; + /** + * uint64 action_count = 1; + * @return The actionCount. + */ + @java.lang.Override + public long getActionCount() { + return actionCount_; + } + + public static final int SIZE_FIELD_NUMBER = 2; + private long size_; + /** + * int64 size = 2; + * @return The size. + */ + @java.lang.Override + public long getSize() { + return size_; + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (actionCount_ != 0L) { + output.writeUInt64(1, actionCount_); + } + if (size_ != 0L) { + output.writeInt64(2, size_); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (actionCount_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeUInt64Size(1, actionCount_); + } + if (size_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(2, size_); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.BfcMemoryMap.SnapShot)) { + return super.equals(obj); + } + org.tensorflow.proto.BfcMemoryMap.SnapShot other = (org.tensorflow.proto.BfcMemoryMap.SnapShot) obj; + + if (getActionCount() + != other.getActionCount()) return false; + if (getSize() + != other.getSize()) return false; + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + ACTION_COUNT_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getActionCount()); + hash = (37 * hash) + SIZE_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getSize()); + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.SnapShot parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.BfcMemoryMap.SnapShot prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * Protobuf type {@code tensorflow.SnapShot} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.SnapShot) + org.tensorflow.proto.BfcMemoryMap.SnapShotOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_SnapShot_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_SnapShot_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BfcMemoryMap.SnapShot.class, org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder.class); + } + + // Construct using org.tensorflow.proto.BfcMemoryMap.SnapShot.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + actionCount_ = 0L; + + size_ = 0L; + + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_SnapShot_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.SnapShot getDefaultInstanceForType() { + return org.tensorflow.proto.BfcMemoryMap.SnapShot.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.SnapShot build() { + org.tensorflow.proto.BfcMemoryMap.SnapShot result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.SnapShot buildPartial() { + org.tensorflow.proto.BfcMemoryMap.SnapShot result = new org.tensorflow.proto.BfcMemoryMap.SnapShot(this); + result.actionCount_ = actionCount_; + result.size_ = size_; + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.BfcMemoryMap.SnapShot) { + return mergeFrom((org.tensorflow.proto.BfcMemoryMap.SnapShot)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.BfcMemoryMap.SnapShot other) { + if (other == org.tensorflow.proto.BfcMemoryMap.SnapShot.getDefaultInstance()) return this; + if (other.getActionCount() != 0L) { + setActionCount(other.getActionCount()); + } + if (other.getSize() != 0L) { + setSize(other.getSize()); + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 8: { + actionCount_ = input.readUInt64(); + + break; + } // case 8 + case 16: { + size_ = input.readInt64(); + + break; + } // case 16 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + + private long actionCount_ ; + /** + * uint64 action_count = 1; + * @return The actionCount. + */ + @java.lang.Override + public long getActionCount() { + return actionCount_; + } + /** + * uint64 action_count = 1; + * @param value The actionCount to set. + * @return This builder for chaining. + */ + public Builder setActionCount(long value) { + + actionCount_ = value; + onChanged(); + return this; + } + /** + * uint64 action_count = 1; + * @return This builder for chaining. + */ + public Builder clearActionCount() { + + actionCount_ = 0L; + onChanged(); + return this; + } + + private long size_ ; + /** + * int64 size = 2; + * @return The size. + */ + @java.lang.Override + public long getSize() { + return size_; + } + /** + * int64 size = 2; + * @param value The size to set. + * @return This builder for chaining. + */ + public Builder setSize(long value) { + + size_ = value; + onChanged(); + return this; + } + /** + * int64 size = 2; + * @return This builder for chaining. + */ + public Builder clearSize() { + + size_ = 0L; + onChanged(); + return this; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.SnapShot) + } + + // @@protoc_insertion_point(class_scope:tensorflow.SnapShot) + private static final org.tensorflow.proto.BfcMemoryMap.SnapShot DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.BfcMemoryMap.SnapShot(); + } + + public static org.tensorflow.proto.BfcMemoryMap.SnapShot getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public SnapShot parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.SnapShot getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + + } + + public interface MemoryDumpOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.MemoryDump) + com.google.protobuf.MessageOrBuilder { + + /** + * string allocator_name = 1; + * @return The allocatorName. + */ + java.lang.String getAllocatorName(); + /** + * string allocator_name = 1; + * @return The bytes for allocatorName. + */ + com.google.protobuf.ByteString + getAllocatorNameBytes(); + + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + java.util.List + getBinSummaryList(); + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + org.tensorflow.proto.BfcMemoryMap.BinSummary getBinSummary(int index); + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + int getBinSummaryCount(); + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + java.util.List + getBinSummaryOrBuilderList(); + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + org.tensorflow.proto.BfcMemoryMap.BinSummaryOrBuilder getBinSummaryOrBuilder( + int index); + + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + java.util.List + getChunkList(); + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + org.tensorflow.proto.BfcMemoryMap.MemChunk getChunk(int index); + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + int getChunkCount(); + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + java.util.List + getChunkOrBuilderList(); + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + org.tensorflow.proto.BfcMemoryMap.MemChunkOrBuilder getChunkOrBuilder( + int index); + + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + java.util.List + getSnapShotList(); + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + org.tensorflow.proto.BfcMemoryMap.SnapShot getSnapShot(int index); + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + int getSnapShotCount(); + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + java.util.List + getSnapShotOrBuilderList(); + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + org.tensorflow.proto.BfcMemoryMap.SnapShotOrBuilder getSnapShotOrBuilder( + int index); + + /** + * .tensorflow.MemAllocatorStats stats = 5; + * @return Whether the stats field is set. + */ + boolean hasStats(); + /** + * .tensorflow.MemAllocatorStats stats = 5; + * @return The stats. + */ + org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats getStats(); + /** + * .tensorflow.MemAllocatorStats stats = 5; + */ + org.tensorflow.proto.BfcMemoryMap.MemAllocatorStatsOrBuilder getStatsOrBuilder(); + } + /** + * Protobuf type {@code tensorflow.MemoryDump} + */ + public static final class MemoryDump extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.MemoryDump) + MemoryDumpOrBuilder { + private static final long serialVersionUID = 0L; + // Use MemoryDump.newBuilder() to construct. + private MemoryDump(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private MemoryDump() { + allocatorName_ = ""; + binSummary_ = java.util.Collections.emptyList(); + chunk_ = java.util.Collections.emptyList(); + snapShot_ = java.util.Collections.emptyList(); + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new MemoryDump(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemoryDump_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemoryDump_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BfcMemoryMap.MemoryDump.class, org.tensorflow.proto.BfcMemoryMap.MemoryDump.Builder.class); + } + + public static final int ALLOCATOR_NAME_FIELD_NUMBER = 1; + private volatile java.lang.Object allocatorName_; + /** + * string allocator_name = 1; + * @return The allocatorName. + */ + @java.lang.Override + public java.lang.String getAllocatorName() { + java.lang.Object ref = allocatorName_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + allocatorName_ = s; + return s; + } + } + /** + * string allocator_name = 1; + * @return The bytes for allocatorName. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getAllocatorNameBytes() { + java.lang.Object ref = allocatorName_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + allocatorName_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int BIN_SUMMARY_FIELD_NUMBER = 2; + private java.util.List binSummary_; + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + @java.lang.Override + public java.util.List getBinSummaryList() { + return binSummary_; + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + @java.lang.Override + public java.util.List + getBinSummaryOrBuilderList() { + return binSummary_; + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + @java.lang.Override + public int getBinSummaryCount() { + return binSummary_.size(); + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.BinSummary getBinSummary(int index) { + return binSummary_.get(index); + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.BinSummaryOrBuilder getBinSummaryOrBuilder( + int index) { + return binSummary_.get(index); + } + + public static final int CHUNK_FIELD_NUMBER = 3; + private java.util.List chunk_; + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + @java.lang.Override + public java.util.List getChunkList() { + return chunk_; + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + @java.lang.Override + public java.util.List + getChunkOrBuilderList() { + return chunk_; + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + @java.lang.Override + public int getChunkCount() { + return chunk_.size(); + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemChunk getChunk(int index) { + return chunk_.get(index); + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemChunkOrBuilder getChunkOrBuilder( + int index) { + return chunk_.get(index); + } + + public static final int SNAP_SHOT_FIELD_NUMBER = 4; + private java.util.List snapShot_; + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + @java.lang.Override + public java.util.List getSnapShotList() { + return snapShot_; + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + @java.lang.Override + public java.util.List + getSnapShotOrBuilderList() { + return snapShot_; + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + @java.lang.Override + public int getSnapShotCount() { + return snapShot_.size(); + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.SnapShot getSnapShot(int index) { + return snapShot_.get(index); + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.SnapShotOrBuilder getSnapShotOrBuilder( + int index) { + return snapShot_.get(index); + } + + public static final int STATS_FIELD_NUMBER = 5; + private org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats stats_; + /** + * .tensorflow.MemAllocatorStats stats = 5; + * @return Whether the stats field is set. + */ + @java.lang.Override + public boolean hasStats() { + return stats_ != null; + } + /** + * .tensorflow.MemAllocatorStats stats = 5; + * @return The stats. + */ + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats getStats() { + return stats_ == null ? org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.getDefaultInstance() : stats_; + } + /** + * .tensorflow.MemAllocatorStats stats = 5; + */ + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStatsOrBuilder getStatsOrBuilder() { + return getStats(); + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(allocatorName_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 1, allocatorName_); + } + for (int i = 0; i < binSummary_.size(); i++) { + output.writeMessage(2, binSummary_.get(i)); + } + for (int i = 0; i < chunk_.size(); i++) { + output.writeMessage(3, chunk_.get(i)); + } + for (int i = 0; i < snapShot_.size(); i++) { + output.writeMessage(4, snapShot_.get(i)); + } + if (stats_ != null) { + output.writeMessage(5, getStats()); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(allocatorName_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, allocatorName_); + } + for (int i = 0; i < binSummary_.size(); i++) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(2, binSummary_.get(i)); + } + for (int i = 0; i < chunk_.size(); i++) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(3, chunk_.get(i)); + } + for (int i = 0; i < snapShot_.size(); i++) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(4, snapShot_.get(i)); + } + if (stats_ != null) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(5, getStats()); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.BfcMemoryMap.MemoryDump)) { + return super.equals(obj); + } + org.tensorflow.proto.BfcMemoryMap.MemoryDump other = (org.tensorflow.proto.BfcMemoryMap.MemoryDump) obj; + + if (!getAllocatorName() + .equals(other.getAllocatorName())) return false; + if (!getBinSummaryList() + .equals(other.getBinSummaryList())) return false; + if (!getChunkList() + .equals(other.getChunkList())) return false; + if (!getSnapShotList() + .equals(other.getSnapShotList())) return false; + if (hasStats() != other.hasStats()) return false; + if (hasStats()) { + if (!getStats() + .equals(other.getStats())) return false; + } + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + ALLOCATOR_NAME_FIELD_NUMBER; + hash = (53 * hash) + getAllocatorName().hashCode(); + if (getBinSummaryCount() > 0) { + hash = (37 * hash) + BIN_SUMMARY_FIELD_NUMBER; + hash = (53 * hash) + getBinSummaryList().hashCode(); + } + if (getChunkCount() > 0) { + hash = (37 * hash) + CHUNK_FIELD_NUMBER; + hash = (53 * hash) + getChunkList().hashCode(); + } + if (getSnapShotCount() > 0) { + hash = (37 * hash) + SNAP_SHOT_FIELD_NUMBER; + hash = (53 * hash) + getSnapShotList().hashCode(); + } + if (hasStats()) { + hash = (37 * hash) + STATS_FIELD_NUMBER; + hash = (53 * hash) + getStats().hashCode(); + } + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BfcMemoryMap.MemoryDump parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.BfcMemoryMap.MemoryDump prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * Protobuf type {@code tensorflow.MemoryDump} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.MemoryDump) + org.tensorflow.proto.BfcMemoryMap.MemoryDumpOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemoryDump_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemoryDump_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BfcMemoryMap.MemoryDump.class, org.tensorflow.proto.BfcMemoryMap.MemoryDump.Builder.class); + } + + // Construct using org.tensorflow.proto.BfcMemoryMap.MemoryDump.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + allocatorName_ = ""; + + if (binSummaryBuilder_ == null) { + binSummary_ = java.util.Collections.emptyList(); + } else { + binSummary_ = null; + binSummaryBuilder_.clear(); + } + bitField0_ = (bitField0_ & ~0x00000001); + if (chunkBuilder_ == null) { + chunk_ = java.util.Collections.emptyList(); + } else { + chunk_ = null; + chunkBuilder_.clear(); + } + bitField0_ = (bitField0_ & ~0x00000002); + if (snapShotBuilder_ == null) { + snapShot_ = java.util.Collections.emptyList(); + } else { + snapShot_ = null; + snapShotBuilder_.clear(); + } + bitField0_ = (bitField0_ & ~0x00000004); + if (statsBuilder_ == null) { + stats_ = null; + } else { + stats_ = null; + statsBuilder_ = null; + } + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.BfcMemoryMap.internal_static_tensorflow_MemoryDump_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemoryDump getDefaultInstanceForType() { + return org.tensorflow.proto.BfcMemoryMap.MemoryDump.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemoryDump build() { + org.tensorflow.proto.BfcMemoryMap.MemoryDump result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemoryDump buildPartial() { + org.tensorflow.proto.BfcMemoryMap.MemoryDump result = new org.tensorflow.proto.BfcMemoryMap.MemoryDump(this); + int from_bitField0_ = bitField0_; + result.allocatorName_ = allocatorName_; + if (binSummaryBuilder_ == null) { + if (((bitField0_ & 0x00000001) != 0)) { + binSummary_ = java.util.Collections.unmodifiableList(binSummary_); + bitField0_ = (bitField0_ & ~0x00000001); + } + result.binSummary_ = binSummary_; + } else { + result.binSummary_ = binSummaryBuilder_.build(); + } + if (chunkBuilder_ == null) { + if (((bitField0_ & 0x00000002) != 0)) { + chunk_ = java.util.Collections.unmodifiableList(chunk_); + bitField0_ = (bitField0_ & ~0x00000002); + } + result.chunk_ = chunk_; + } else { + result.chunk_ = chunkBuilder_.build(); + } + if (snapShotBuilder_ == null) { + if (((bitField0_ & 0x00000004) != 0)) { + snapShot_ = java.util.Collections.unmodifiableList(snapShot_); + bitField0_ = (bitField0_ & ~0x00000004); + } + result.snapShot_ = snapShot_; + } else { + result.snapShot_ = snapShotBuilder_.build(); + } + if (statsBuilder_ == null) { + result.stats_ = stats_; + } else { + result.stats_ = statsBuilder_.build(); + } + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.BfcMemoryMap.MemoryDump) { + return mergeFrom((org.tensorflow.proto.BfcMemoryMap.MemoryDump)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.BfcMemoryMap.MemoryDump other) { + if (other == org.tensorflow.proto.BfcMemoryMap.MemoryDump.getDefaultInstance()) return this; + if (!other.getAllocatorName().isEmpty()) { + allocatorName_ = other.allocatorName_; + onChanged(); + } + if (binSummaryBuilder_ == null) { + if (!other.binSummary_.isEmpty()) { + if (binSummary_.isEmpty()) { + binSummary_ = other.binSummary_; + bitField0_ = (bitField0_ & ~0x00000001); + } else { + ensureBinSummaryIsMutable(); + binSummary_.addAll(other.binSummary_); + } + onChanged(); + } + } else { + if (!other.binSummary_.isEmpty()) { + if (binSummaryBuilder_.isEmpty()) { + binSummaryBuilder_.dispose(); + binSummaryBuilder_ = null; + binSummary_ = other.binSummary_; + bitField0_ = (bitField0_ & ~0x00000001); + binSummaryBuilder_ = + com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ? + getBinSummaryFieldBuilder() : null; + } else { + binSummaryBuilder_.addAllMessages(other.binSummary_); + } + } + } + if (chunkBuilder_ == null) { + if (!other.chunk_.isEmpty()) { + if (chunk_.isEmpty()) { + chunk_ = other.chunk_; + bitField0_ = (bitField0_ & ~0x00000002); + } else { + ensureChunkIsMutable(); + chunk_.addAll(other.chunk_); + } + onChanged(); + } + } else { + if (!other.chunk_.isEmpty()) { + if (chunkBuilder_.isEmpty()) { + chunkBuilder_.dispose(); + chunkBuilder_ = null; + chunk_ = other.chunk_; + bitField0_ = (bitField0_ & ~0x00000002); + chunkBuilder_ = + com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ? + getChunkFieldBuilder() : null; + } else { + chunkBuilder_.addAllMessages(other.chunk_); + } + } + } + if (snapShotBuilder_ == null) { + if (!other.snapShot_.isEmpty()) { + if (snapShot_.isEmpty()) { + snapShot_ = other.snapShot_; + bitField0_ = (bitField0_ & ~0x00000004); + } else { + ensureSnapShotIsMutable(); + snapShot_.addAll(other.snapShot_); + } + onChanged(); + } + } else { + if (!other.snapShot_.isEmpty()) { + if (snapShotBuilder_.isEmpty()) { + snapShotBuilder_.dispose(); + snapShotBuilder_ = null; + snapShot_ = other.snapShot_; + bitField0_ = (bitField0_ & ~0x00000004); + snapShotBuilder_ = + com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ? + getSnapShotFieldBuilder() : null; + } else { + snapShotBuilder_.addAllMessages(other.snapShot_); + } + } + } + if (other.hasStats()) { + mergeStats(other.getStats()); + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 10: { + allocatorName_ = input.readStringRequireUtf8(); + + break; + } // case 10 + case 18: { + org.tensorflow.proto.BfcMemoryMap.BinSummary m = + input.readMessage( + org.tensorflow.proto.BfcMemoryMap.BinSummary.parser(), + extensionRegistry); + if (binSummaryBuilder_ == null) { + ensureBinSummaryIsMutable(); + binSummary_.add(m); + } else { + binSummaryBuilder_.addMessage(m); + } + break; + } // case 18 + case 26: { + org.tensorflow.proto.BfcMemoryMap.MemChunk m = + input.readMessage( + org.tensorflow.proto.BfcMemoryMap.MemChunk.parser(), + extensionRegistry); + if (chunkBuilder_ == null) { + ensureChunkIsMutable(); + chunk_.add(m); + } else { + chunkBuilder_.addMessage(m); + } + break; + } // case 26 + case 34: { + org.tensorflow.proto.BfcMemoryMap.SnapShot m = + input.readMessage( + org.tensorflow.proto.BfcMemoryMap.SnapShot.parser(), + extensionRegistry); + if (snapShotBuilder_ == null) { + ensureSnapShotIsMutable(); + snapShot_.add(m); + } else { + snapShotBuilder_.addMessage(m); + } + break; + } // case 34 + case 42: { + input.readMessage( + getStatsFieldBuilder().getBuilder(), + extensionRegistry); + + break; + } // case 42 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + private int bitField0_; + + private java.lang.Object allocatorName_ = ""; + /** + * string allocator_name = 1; + * @return The allocatorName. + */ + public java.lang.String getAllocatorName() { + java.lang.Object ref = allocatorName_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + allocatorName_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * string allocator_name = 1; + * @return The bytes for allocatorName. + */ + public com.google.protobuf.ByteString + getAllocatorNameBytes() { + java.lang.Object ref = allocatorName_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + allocatorName_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * string allocator_name = 1; + * @param value The allocatorName to set. + * @return This builder for chaining. + */ + public Builder setAllocatorName( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + allocatorName_ = value; + onChanged(); + return this; + } + /** + * string allocator_name = 1; + * @return This builder for chaining. + */ + public Builder clearAllocatorName() { + + allocatorName_ = getDefaultInstance().getAllocatorName(); + onChanged(); + return this; + } + /** + * string allocator_name = 1; + * @param value The bytes for allocatorName to set. + * @return This builder for chaining. + */ + public Builder setAllocatorNameBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + allocatorName_ = value; + onChanged(); + return this; + } + + private java.util.List binSummary_ = + java.util.Collections.emptyList(); + private void ensureBinSummaryIsMutable() { + if (!((bitField0_ & 0x00000001) != 0)) { + binSummary_ = new java.util.ArrayList(binSummary_); + bitField0_ |= 0x00000001; + } + } + + private com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.BfcMemoryMap.BinSummary, org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder, org.tensorflow.proto.BfcMemoryMap.BinSummaryOrBuilder> binSummaryBuilder_; + + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public java.util.List getBinSummaryList() { + if (binSummaryBuilder_ == null) { + return java.util.Collections.unmodifiableList(binSummary_); + } else { + return binSummaryBuilder_.getMessageList(); + } + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public int getBinSummaryCount() { + if (binSummaryBuilder_ == null) { + return binSummary_.size(); + } else { + return binSummaryBuilder_.getCount(); + } + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public org.tensorflow.proto.BfcMemoryMap.BinSummary getBinSummary(int index) { + if (binSummaryBuilder_ == null) { + return binSummary_.get(index); + } else { + return binSummaryBuilder_.getMessage(index); + } + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public Builder setBinSummary( + int index, org.tensorflow.proto.BfcMemoryMap.BinSummary value) { + if (binSummaryBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureBinSummaryIsMutable(); + binSummary_.set(index, value); + onChanged(); + } else { + binSummaryBuilder_.setMessage(index, value); + } + return this; + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public Builder setBinSummary( + int index, org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder builderForValue) { + if (binSummaryBuilder_ == null) { + ensureBinSummaryIsMutable(); + binSummary_.set(index, builderForValue.build()); + onChanged(); + } else { + binSummaryBuilder_.setMessage(index, builderForValue.build()); + } + return this; + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public Builder addBinSummary(org.tensorflow.proto.BfcMemoryMap.BinSummary value) { + if (binSummaryBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureBinSummaryIsMutable(); + binSummary_.add(value); + onChanged(); + } else { + binSummaryBuilder_.addMessage(value); + } + return this; + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public Builder addBinSummary( + int index, org.tensorflow.proto.BfcMemoryMap.BinSummary value) { + if (binSummaryBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureBinSummaryIsMutable(); + binSummary_.add(index, value); + onChanged(); + } else { + binSummaryBuilder_.addMessage(index, value); + } + return this; + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public Builder addBinSummary( + org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder builderForValue) { + if (binSummaryBuilder_ == null) { + ensureBinSummaryIsMutable(); + binSummary_.add(builderForValue.build()); + onChanged(); + } else { + binSummaryBuilder_.addMessage(builderForValue.build()); + } + return this; + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public Builder addBinSummary( + int index, org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder builderForValue) { + if (binSummaryBuilder_ == null) { + ensureBinSummaryIsMutable(); + binSummary_.add(index, builderForValue.build()); + onChanged(); + } else { + binSummaryBuilder_.addMessage(index, builderForValue.build()); + } + return this; + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public Builder addAllBinSummary( + java.lang.Iterable values) { + if (binSummaryBuilder_ == null) { + ensureBinSummaryIsMutable(); + com.google.protobuf.AbstractMessageLite.Builder.addAll( + values, binSummary_); + onChanged(); + } else { + binSummaryBuilder_.addAllMessages(values); + } + return this; + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public Builder clearBinSummary() { + if (binSummaryBuilder_ == null) { + binSummary_ = java.util.Collections.emptyList(); + bitField0_ = (bitField0_ & ~0x00000001); + onChanged(); + } else { + binSummaryBuilder_.clear(); + } + return this; + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public Builder removeBinSummary(int index) { + if (binSummaryBuilder_ == null) { + ensureBinSummaryIsMutable(); + binSummary_.remove(index); + onChanged(); + } else { + binSummaryBuilder_.remove(index); + } + return this; + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder getBinSummaryBuilder( + int index) { + return getBinSummaryFieldBuilder().getBuilder(index); + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public org.tensorflow.proto.BfcMemoryMap.BinSummaryOrBuilder getBinSummaryOrBuilder( + int index) { + if (binSummaryBuilder_ == null) { + return binSummary_.get(index); } else { + return binSummaryBuilder_.getMessageOrBuilder(index); + } + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public java.util.List + getBinSummaryOrBuilderList() { + if (binSummaryBuilder_ != null) { + return binSummaryBuilder_.getMessageOrBuilderList(); + } else { + return java.util.Collections.unmodifiableList(binSummary_); + } + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder addBinSummaryBuilder() { + return getBinSummaryFieldBuilder().addBuilder( + org.tensorflow.proto.BfcMemoryMap.BinSummary.getDefaultInstance()); + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder addBinSummaryBuilder( + int index) { + return getBinSummaryFieldBuilder().addBuilder( + index, org.tensorflow.proto.BfcMemoryMap.BinSummary.getDefaultInstance()); + } + /** + * repeated .tensorflow.BinSummary bin_summary = 2; + */ + public java.util.List + getBinSummaryBuilderList() { + return getBinSummaryFieldBuilder().getBuilderList(); + } + private com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.BfcMemoryMap.BinSummary, org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder, org.tensorflow.proto.BfcMemoryMap.BinSummaryOrBuilder> + getBinSummaryFieldBuilder() { + if (binSummaryBuilder_ == null) { + binSummaryBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.BfcMemoryMap.BinSummary, org.tensorflow.proto.BfcMemoryMap.BinSummary.Builder, org.tensorflow.proto.BfcMemoryMap.BinSummaryOrBuilder>( + binSummary_, + ((bitField0_ & 0x00000001) != 0), + getParentForChildren(), + isClean()); + binSummary_ = null; + } + return binSummaryBuilder_; + } + + private java.util.List chunk_ = + java.util.Collections.emptyList(); + private void ensureChunkIsMutable() { + if (!((bitField0_ & 0x00000002) != 0)) { + chunk_ = new java.util.ArrayList(chunk_); + bitField0_ |= 0x00000002; + } + } + + private com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.BfcMemoryMap.MemChunk, org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder, org.tensorflow.proto.BfcMemoryMap.MemChunkOrBuilder> chunkBuilder_; + + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public java.util.List getChunkList() { + if (chunkBuilder_ == null) { + return java.util.Collections.unmodifiableList(chunk_); + } else { + return chunkBuilder_.getMessageList(); + } + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public int getChunkCount() { + if (chunkBuilder_ == null) { + return chunk_.size(); + } else { + return chunkBuilder_.getCount(); + } + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public org.tensorflow.proto.BfcMemoryMap.MemChunk getChunk(int index) { + if (chunkBuilder_ == null) { + return chunk_.get(index); + } else { + return chunkBuilder_.getMessage(index); + } + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public Builder setChunk( + int index, org.tensorflow.proto.BfcMemoryMap.MemChunk value) { + if (chunkBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureChunkIsMutable(); + chunk_.set(index, value); + onChanged(); + } else { + chunkBuilder_.setMessage(index, value); + } + return this; + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public Builder setChunk( + int index, org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder builderForValue) { + if (chunkBuilder_ == null) { + ensureChunkIsMutable(); + chunk_.set(index, builderForValue.build()); + onChanged(); + } else { + chunkBuilder_.setMessage(index, builderForValue.build()); + } + return this; + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public Builder addChunk(org.tensorflow.proto.BfcMemoryMap.MemChunk value) { + if (chunkBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureChunkIsMutable(); + chunk_.add(value); + onChanged(); + } else { + chunkBuilder_.addMessage(value); + } + return this; + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public Builder addChunk( + int index, org.tensorflow.proto.BfcMemoryMap.MemChunk value) { + if (chunkBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureChunkIsMutable(); + chunk_.add(index, value); + onChanged(); + } else { + chunkBuilder_.addMessage(index, value); + } + return this; + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public Builder addChunk( + org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder builderForValue) { + if (chunkBuilder_ == null) { + ensureChunkIsMutable(); + chunk_.add(builderForValue.build()); + onChanged(); + } else { + chunkBuilder_.addMessage(builderForValue.build()); + } + return this; + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public Builder addChunk( + int index, org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder builderForValue) { + if (chunkBuilder_ == null) { + ensureChunkIsMutable(); + chunk_.add(index, builderForValue.build()); + onChanged(); + } else { + chunkBuilder_.addMessage(index, builderForValue.build()); + } + return this; + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public Builder addAllChunk( + java.lang.Iterable values) { + if (chunkBuilder_ == null) { + ensureChunkIsMutable(); + com.google.protobuf.AbstractMessageLite.Builder.addAll( + values, chunk_); + onChanged(); + } else { + chunkBuilder_.addAllMessages(values); + } + return this; + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public Builder clearChunk() { + if (chunkBuilder_ == null) { + chunk_ = java.util.Collections.emptyList(); + bitField0_ = (bitField0_ & ~0x00000002); + onChanged(); + } else { + chunkBuilder_.clear(); + } + return this; + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public Builder removeChunk(int index) { + if (chunkBuilder_ == null) { + ensureChunkIsMutable(); + chunk_.remove(index); + onChanged(); + } else { + chunkBuilder_.remove(index); + } + return this; + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder getChunkBuilder( + int index) { + return getChunkFieldBuilder().getBuilder(index); + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public org.tensorflow.proto.BfcMemoryMap.MemChunkOrBuilder getChunkOrBuilder( + int index) { + if (chunkBuilder_ == null) { + return chunk_.get(index); } else { + return chunkBuilder_.getMessageOrBuilder(index); + } + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public java.util.List + getChunkOrBuilderList() { + if (chunkBuilder_ != null) { + return chunkBuilder_.getMessageOrBuilderList(); + } else { + return java.util.Collections.unmodifiableList(chunk_); + } + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder addChunkBuilder() { + return getChunkFieldBuilder().addBuilder( + org.tensorflow.proto.BfcMemoryMap.MemChunk.getDefaultInstance()); + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder addChunkBuilder( + int index) { + return getChunkFieldBuilder().addBuilder( + index, org.tensorflow.proto.BfcMemoryMap.MemChunk.getDefaultInstance()); + } + /** + * repeated .tensorflow.MemChunk chunk = 3; + */ + public java.util.List + getChunkBuilderList() { + return getChunkFieldBuilder().getBuilderList(); + } + private com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.BfcMemoryMap.MemChunk, org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder, org.tensorflow.proto.BfcMemoryMap.MemChunkOrBuilder> + getChunkFieldBuilder() { + if (chunkBuilder_ == null) { + chunkBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.BfcMemoryMap.MemChunk, org.tensorflow.proto.BfcMemoryMap.MemChunk.Builder, org.tensorflow.proto.BfcMemoryMap.MemChunkOrBuilder>( + chunk_, + ((bitField0_ & 0x00000002) != 0), + getParentForChildren(), + isClean()); + chunk_ = null; + } + return chunkBuilder_; + } + + private java.util.List snapShot_ = + java.util.Collections.emptyList(); + private void ensureSnapShotIsMutable() { + if (!((bitField0_ & 0x00000004) != 0)) { + snapShot_ = new java.util.ArrayList(snapShot_); + bitField0_ |= 0x00000004; + } + } + + private com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.BfcMemoryMap.SnapShot, org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder, org.tensorflow.proto.BfcMemoryMap.SnapShotOrBuilder> snapShotBuilder_; + + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public java.util.List getSnapShotList() { + if (snapShotBuilder_ == null) { + return java.util.Collections.unmodifiableList(snapShot_); + } else { + return snapShotBuilder_.getMessageList(); + } + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public int getSnapShotCount() { + if (snapShotBuilder_ == null) { + return snapShot_.size(); + } else { + return snapShotBuilder_.getCount(); + } + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public org.tensorflow.proto.BfcMemoryMap.SnapShot getSnapShot(int index) { + if (snapShotBuilder_ == null) { + return snapShot_.get(index); + } else { + return snapShotBuilder_.getMessage(index); + } + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public Builder setSnapShot( + int index, org.tensorflow.proto.BfcMemoryMap.SnapShot value) { + if (snapShotBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureSnapShotIsMutable(); + snapShot_.set(index, value); + onChanged(); + } else { + snapShotBuilder_.setMessage(index, value); + } + return this; + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public Builder setSnapShot( + int index, org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder builderForValue) { + if (snapShotBuilder_ == null) { + ensureSnapShotIsMutable(); + snapShot_.set(index, builderForValue.build()); + onChanged(); + } else { + snapShotBuilder_.setMessage(index, builderForValue.build()); + } + return this; + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public Builder addSnapShot(org.tensorflow.proto.BfcMemoryMap.SnapShot value) { + if (snapShotBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureSnapShotIsMutable(); + snapShot_.add(value); + onChanged(); + } else { + snapShotBuilder_.addMessage(value); + } + return this; + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public Builder addSnapShot( + int index, org.tensorflow.proto.BfcMemoryMap.SnapShot value) { + if (snapShotBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureSnapShotIsMutable(); + snapShot_.add(index, value); + onChanged(); + } else { + snapShotBuilder_.addMessage(index, value); + } + return this; + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public Builder addSnapShot( + org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder builderForValue) { + if (snapShotBuilder_ == null) { + ensureSnapShotIsMutable(); + snapShot_.add(builderForValue.build()); + onChanged(); + } else { + snapShotBuilder_.addMessage(builderForValue.build()); + } + return this; + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public Builder addSnapShot( + int index, org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder builderForValue) { + if (snapShotBuilder_ == null) { + ensureSnapShotIsMutable(); + snapShot_.add(index, builderForValue.build()); + onChanged(); + } else { + snapShotBuilder_.addMessage(index, builderForValue.build()); + } + return this; + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public Builder addAllSnapShot( + java.lang.Iterable values) { + if (snapShotBuilder_ == null) { + ensureSnapShotIsMutable(); + com.google.protobuf.AbstractMessageLite.Builder.addAll( + values, snapShot_); + onChanged(); + } else { + snapShotBuilder_.addAllMessages(values); + } + return this; + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public Builder clearSnapShot() { + if (snapShotBuilder_ == null) { + snapShot_ = java.util.Collections.emptyList(); + bitField0_ = (bitField0_ & ~0x00000004); + onChanged(); + } else { + snapShotBuilder_.clear(); + } + return this; + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public Builder removeSnapShot(int index) { + if (snapShotBuilder_ == null) { + ensureSnapShotIsMutable(); + snapShot_.remove(index); + onChanged(); + } else { + snapShotBuilder_.remove(index); + } + return this; + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder getSnapShotBuilder( + int index) { + return getSnapShotFieldBuilder().getBuilder(index); + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public org.tensorflow.proto.BfcMemoryMap.SnapShotOrBuilder getSnapShotOrBuilder( + int index) { + if (snapShotBuilder_ == null) { + return snapShot_.get(index); } else { + return snapShotBuilder_.getMessageOrBuilder(index); + } + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public java.util.List + getSnapShotOrBuilderList() { + if (snapShotBuilder_ != null) { + return snapShotBuilder_.getMessageOrBuilderList(); + } else { + return java.util.Collections.unmodifiableList(snapShot_); + } + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder addSnapShotBuilder() { + return getSnapShotFieldBuilder().addBuilder( + org.tensorflow.proto.BfcMemoryMap.SnapShot.getDefaultInstance()); + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder addSnapShotBuilder( + int index) { + return getSnapShotFieldBuilder().addBuilder( + index, org.tensorflow.proto.BfcMemoryMap.SnapShot.getDefaultInstance()); + } + /** + * repeated .tensorflow.SnapShot snap_shot = 4; + */ + public java.util.List + getSnapShotBuilderList() { + return getSnapShotFieldBuilder().getBuilderList(); + } + private com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.BfcMemoryMap.SnapShot, org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder, org.tensorflow.proto.BfcMemoryMap.SnapShotOrBuilder> + getSnapShotFieldBuilder() { + if (snapShotBuilder_ == null) { + snapShotBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.BfcMemoryMap.SnapShot, org.tensorflow.proto.BfcMemoryMap.SnapShot.Builder, org.tensorflow.proto.BfcMemoryMap.SnapShotOrBuilder>( + snapShot_, + ((bitField0_ & 0x00000004) != 0), + getParentForChildren(), + isClean()); + snapShot_ = null; + } + return snapShotBuilder_; + } + + private org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats stats_; + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.Builder, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStatsOrBuilder> statsBuilder_; + /** + * .tensorflow.MemAllocatorStats stats = 5; + * @return Whether the stats field is set. + */ + public boolean hasStats() { + return statsBuilder_ != null || stats_ != null; + } + /** + * .tensorflow.MemAllocatorStats stats = 5; + * @return The stats. + */ + public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats getStats() { + if (statsBuilder_ == null) { + return stats_ == null ? org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.getDefaultInstance() : stats_; + } else { + return statsBuilder_.getMessage(); + } + } + /** + * .tensorflow.MemAllocatorStats stats = 5; + */ + public Builder setStats(org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats value) { + if (statsBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + stats_ = value; + onChanged(); + } else { + statsBuilder_.setMessage(value); + } + + return this; + } + /** + * .tensorflow.MemAllocatorStats stats = 5; + */ + public Builder setStats( + org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.Builder builderForValue) { + if (statsBuilder_ == null) { + stats_ = builderForValue.build(); + onChanged(); + } else { + statsBuilder_.setMessage(builderForValue.build()); + } + + return this; + } + /** + * .tensorflow.MemAllocatorStats stats = 5; + */ + public Builder mergeStats(org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats value) { + if (statsBuilder_ == null) { + if (stats_ != null) { + stats_ = + org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.newBuilder(stats_).mergeFrom(value).buildPartial(); + } else { + stats_ = value; + } + onChanged(); + } else { + statsBuilder_.mergeFrom(value); + } + + return this; + } + /** + * .tensorflow.MemAllocatorStats stats = 5; + */ + public Builder clearStats() { + if (statsBuilder_ == null) { + stats_ = null; + onChanged(); + } else { + stats_ = null; + statsBuilder_ = null; + } + + return this; + } + /** + * .tensorflow.MemAllocatorStats stats = 5; + */ + public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.Builder getStatsBuilder() { + + onChanged(); + return getStatsFieldBuilder().getBuilder(); + } + /** + * .tensorflow.MemAllocatorStats stats = 5; + */ + public org.tensorflow.proto.BfcMemoryMap.MemAllocatorStatsOrBuilder getStatsOrBuilder() { + if (statsBuilder_ != null) { + return statsBuilder_.getMessageOrBuilder(); + } else { + return stats_ == null ? + org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.getDefaultInstance() : stats_; + } + } + /** + * .tensorflow.MemAllocatorStats stats = 5; + */ + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.Builder, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStatsOrBuilder> + getStatsFieldBuilder() { + if (statsBuilder_ == null) { + statsBuilder_ = new com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStats.Builder, org.tensorflow.proto.BfcMemoryMap.MemAllocatorStatsOrBuilder>( + getStats(), + getParentForChildren(), + isClean()); + stats_ = null; + } + return statsBuilder_; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.MemoryDump) + } + + // @@protoc_insertion_point(class_scope:tensorflow.MemoryDump) + private static final org.tensorflow.proto.BfcMemoryMap.MemoryDump DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.BfcMemoryMap.MemoryDump(); + } + + public static org.tensorflow.proto.BfcMemoryMap.MemoryDump getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public MemoryDump parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.BfcMemoryMap.MemoryDump getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + + } + + private static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_MemAllocatorStats_descriptor; + private static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_MemAllocatorStats_fieldAccessorTable; + private static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_MemChunk_descriptor; + private static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_MemChunk_fieldAccessorTable; + private static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_BinSummary_descriptor; + private static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_BinSummary_fieldAccessorTable; + private static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_SnapShot_descriptor; + private static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_SnapShot_fieldAccessorTable; + private static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_MemoryDump_descriptor; + private static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_MemoryDump_fieldAccessorTable; + + public static com.google.protobuf.Descriptors.FileDescriptor + getDescriptor() { + return descriptor; + } + private static com.google.protobuf.Descriptors.FileDescriptor + descriptor; + static { + java.lang.String[] descriptorData = { + "\n%xla/tsl/protobuf/bfc_memory_map.proto\022" + + "\ntensorflow\"\222\001\n\021MemAllocatorStats\022\022\n\nnum" + + "_allocs\030\001 \001(\003\022\024\n\014bytes_in_use\030\002 \001(\003\022\031\n\021p" + + "eak_bytes_in_use\030\003 \001(\003\022\032\n\022largest_alloc_" + + "size\030\004 \001(\003\022\034\n\024fragmentation_metric\030\005 \001(\002" + + "\"\256\001\n\010MemChunk\022\017\n\007address\030\001 \001(\004\022\014\n\004size\030\002" + + " \001(\003\022\026\n\016requested_size\030\003 \001(\003\022\013\n\003bin\030\004 \001(" + + "\005\022\017\n\007op_name\030\005 \001(\t\022\026\n\016freed_at_count\030\006 \001" + + "(\004\022\024\n\014action_count\030\007 \001(\004\022\016\n\006in_use\030\010 \001(\010" + + "\022\017\n\007step_id\030\t \001(\004\"\213\001\n\nBinSummary\022\013\n\003bin\030" + + "\001 \001(\005\022\032\n\022total_bytes_in_use\030\002 \001(\003\022\032\n\022tot" + + "al_bytes_in_bin\030\003 \001(\003\022\033\n\023total_chunks_in" + + "_use\030\004 \001(\003\022\033\n\023total_chunks_in_bin\030\005 \001(\003\"" + + ".\n\010SnapShot\022\024\n\014action_count\030\001 \001(\004\022\014\n\004siz" + + "e\030\002 \001(\003\"\315\001\n\nMemoryDump\022\026\n\016allocator_name" + + "\030\001 \001(\t\022+\n\013bin_summary\030\002 \003(\0132\026.tensorflow" + + ".BinSummary\022#\n\005chunk\030\003 \003(\0132\024.tensorflow." + + "MemChunk\022\'\n\tsnap_shot\030\004 \003(\0132\024.tensorflow" + + ".SnapShot\022,\n\005stats\030\005 \001(\0132\035.tensorflow.Me" + + "mAllocatorStatsBV\n\024org.tensorflow.protoZ" + + ">github.com/google/tsl/tsl/go/protobuf/f" + + "or_core_protos_go_protob\006proto3" + }; + descriptor = com.google.protobuf.Descriptors.FileDescriptor + .internalBuildGeneratedFileFrom(descriptorData, + new com.google.protobuf.Descriptors.FileDescriptor[] { + }); + internal_static_tensorflow_MemAllocatorStats_descriptor = + getDescriptor().getMessageTypes().get(0); + internal_static_tensorflow_MemAllocatorStats_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_MemAllocatorStats_descriptor, + new java.lang.String[] { "NumAllocs", "BytesInUse", "PeakBytesInUse", "LargestAllocSize", "FragmentationMetric", }); + internal_static_tensorflow_MemChunk_descriptor = + getDescriptor().getMessageTypes().get(1); + internal_static_tensorflow_MemChunk_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_MemChunk_descriptor, + new java.lang.String[] { "Address", "Size", "RequestedSize", "Bin", "OpName", "FreedAtCount", "ActionCount", "InUse", "StepId", }); + internal_static_tensorflow_BinSummary_descriptor = + getDescriptor().getMessageTypes().get(2); + internal_static_tensorflow_BinSummary_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_BinSummary_descriptor, + new java.lang.String[] { "Bin", "TotalBytesInUse", "TotalBytesInBin", "TotalChunksInUse", "TotalChunksInBin", }); + internal_static_tensorflow_SnapShot_descriptor = + getDescriptor().getMessageTypes().get(3); + internal_static_tensorflow_SnapShot_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_SnapShot_descriptor, + new java.lang.String[] { "ActionCount", "Size", }); + internal_static_tensorflow_MemoryDump_descriptor = + getDescriptor().getMessageTypes().get(4); + internal_static_tensorflow_MemoryDump_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_MemoryDump_descriptor, + new java.lang.String[] { "AllocatorName", "BinSummary", "Chunk", "SnapShot", "Stats", }); + } + + // @@protoc_insertion_point(outer_class_scope) +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BuildConfiguration.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BuildConfiguration.java new file mode 100644 index 00000000000..19b464ffb52 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BuildConfiguration.java @@ -0,0 +1,1044 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +/** + * Protobuf type {@code tensorflow.BuildConfiguration} + */ +public final class BuildConfiguration extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.BuildConfiguration) + BuildConfigurationOrBuilder { +private static final long serialVersionUID = 0L; + // Use BuildConfiguration.newBuilder() to construct. + private BuildConfiguration(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private BuildConfiguration() { + mode_ = ""; + ccFlags_ = com.google.protobuf.LazyStringArrayList.EMPTY; + opts_ = com.google.protobuf.LazyStringArrayList.EMPTY; + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new BuildConfiguration(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BuildConfiguration_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BuildConfiguration_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BuildConfiguration.class, org.tensorflow.proto.BuildConfiguration.Builder.class); + } + + public static final int MODE_FIELD_NUMBER = 1; + private volatile java.lang.Object mode_; + /** + * 
    +   * opt, dbg, etc
+   *
    + * + * string mode = 1; + * @return The mode. + */ + @java.lang.Override + public java.lang.String getMode() { + java.lang.Object ref = mode_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + mode_ = s; + return s; + } + } + /** + * 
    +   * opt, dbg, etc
+   *
    + * + * string mode = 1; + * @return The bytes for mode. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getModeBytes() { + java.lang.Object ref = mode_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + mode_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int CC_FLAGS_FIELD_NUMBER = 2; + private com.google.protobuf.LazyStringList ccFlags_; + /** + * 
    +   * CC compiler flags, if known
+   *
    + * + * repeated string cc_flags = 2; + * @return A list containing the ccFlags. + */ + public com.google.protobuf.ProtocolStringList + getCcFlagsList() { + return ccFlags_; + } + /** + * 
    +   * CC compiler flags, if known
+   *
    + * + * repeated string cc_flags = 2; + * @return The count of ccFlags. + */ + public int getCcFlagsCount() { + return ccFlags_.size(); + } + /** + * 
    +   * CC compiler flags, if known
+   *
    + * + * repeated string cc_flags = 2; + * @param index The index of the element to return. + * @return The ccFlags at the given index. + */ + public java.lang.String getCcFlags(int index) { + return ccFlags_.get(index); + } + /** + * 
    +   * CC compiler flags, if known
+   *
    + * + * repeated string cc_flags = 2; + * @param index The index of the value to return. + * @return The bytes of the ccFlags at the given index. + */ + public com.google.protobuf.ByteString + getCcFlagsBytes(int index) { + return ccFlags_.getByteString(index); + } + + public static final int OPTS_FIELD_NUMBER = 3; + private com.google.protobuf.LazyStringList opts_; + /** + * 
    +   * Bazel compilation options, if known
+   *
    + * + * repeated string opts = 3; + * @return A list containing the opts. + */ + public com.google.protobuf.ProtocolStringList + getOptsList() { + return opts_; + } + /** + * 
    +   * Bazel compilation options, if known
+   *
    + * + * repeated string opts = 3; + * @return The count of opts. + */ + public int getOptsCount() { + return opts_.size(); + } + /** + * 
    +   * Bazel compilation options, if known
+   *
    + * + * repeated string opts = 3; + * @param index The index of the element to return. + * @return The opts at the given index. + */ + public java.lang.String getOpts(int index) { + return opts_.get(index); + } + /** + * 
    +   * Bazel compilation options, if known
+   *
    + * + * repeated string opts = 3; + * @param index The index of the value to return. + * @return The bytes of the opts at the given index. + */ + public com.google.protobuf.ByteString + getOptsBytes(int index) { + return opts_.getByteString(index); + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(mode_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 1, mode_); + } + for (int i = 0; i < ccFlags_.size(); i++) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 2, ccFlags_.getRaw(i)); + } + for (int i = 0; i < opts_.size(); i++) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 3, opts_.getRaw(i)); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(mode_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, mode_); + } + { + int dataSize = 0; + for (int i = 0; i < ccFlags_.size(); i++) { + dataSize += computeStringSizeNoTag(ccFlags_.getRaw(i)); + } + size += dataSize; + size += 1 * getCcFlagsList().size(); + } + { + int dataSize = 0; + for (int i = 0; i < opts_.size(); i++) { + dataSize += computeStringSizeNoTag(opts_.getRaw(i)); + } + size += dataSize; + size += 1 * getOptsList().size(); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.BuildConfiguration)) { + return super.equals(obj); + } + org.tensorflow.proto.BuildConfiguration other = (org.tensorflow.proto.BuildConfiguration) obj; + + if (!getMode() + .equals(other.getMode())) return false; + if (!getCcFlagsList() + .equals(other.getCcFlagsList())) return false; + if (!getOptsList() + .equals(other.getOptsList())) return false; + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + MODE_FIELD_NUMBER; + hash = (53 * hash) + getMode().hashCode(); + if (getCcFlagsCount() > 0) { + hash = (37 * hash) + CC_FLAGS_FIELD_NUMBER; + hash = (53 * hash) + getCcFlagsList().hashCode(); + } + if (getOptsCount() > 0) { + hash = (37 * hash) + OPTS_FIELD_NUMBER; + hash = (53 * hash) + getOptsList().hashCode(); + } + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.BuildConfiguration parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BuildConfiguration parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BuildConfiguration parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BuildConfiguration parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BuildConfiguration parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.BuildConfiguration parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.BuildConfiguration parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BuildConfiguration parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BuildConfiguration parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BuildConfiguration parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.BuildConfiguration parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.BuildConfiguration parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.BuildConfiguration prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * Protobuf type {@code tensorflow.BuildConfiguration} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.BuildConfiguration) + org.tensorflow.proto.BuildConfigurationOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BuildConfiguration_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BuildConfiguration_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.BuildConfiguration.class, org.tensorflow.proto.BuildConfiguration.Builder.class); + } + + // Construct using org.tensorflow.proto.BuildConfiguration.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + mode_ = ""; + + ccFlags_ = com.google.protobuf.LazyStringArrayList.EMPTY; + bitField0_ = (bitField0_ & ~0x00000001); + opts_ = com.google.protobuf.LazyStringArrayList.EMPTY; + bitField0_ = (bitField0_ & ~0x00000002); + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_BuildConfiguration_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.BuildConfiguration getDefaultInstanceForType() { + return org.tensorflow.proto.BuildConfiguration.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.BuildConfiguration build() { + org.tensorflow.proto.BuildConfiguration result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.BuildConfiguration buildPartial() { + org.tensorflow.proto.BuildConfiguration result = new org.tensorflow.proto.BuildConfiguration(this); + int from_bitField0_ = bitField0_; + result.mode_ = mode_; + if (((bitField0_ & 0x00000001) != 0)) { + ccFlags_ = ccFlags_.getUnmodifiableView(); + bitField0_ = (bitField0_ & ~0x00000001); + } + result.ccFlags_ = ccFlags_; + if (((bitField0_ & 0x00000002) != 0)) { + opts_ = opts_.getUnmodifiableView(); + bitField0_ = (bitField0_ & ~0x00000002); + } + result.opts_ = opts_; + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.BuildConfiguration) { + return mergeFrom((org.tensorflow.proto.BuildConfiguration)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.BuildConfiguration other) { + if (other == org.tensorflow.proto.BuildConfiguration.getDefaultInstance()) return this; + if (!other.getMode().isEmpty()) { + mode_ = other.mode_; + onChanged(); + } + if (!other.ccFlags_.isEmpty()) { + if (ccFlags_.isEmpty()) { + ccFlags_ = other.ccFlags_; + bitField0_ = (bitField0_ & ~0x00000001); + } else { + ensureCcFlagsIsMutable(); + ccFlags_.addAll(other.ccFlags_); + } + onChanged(); + } + if (!other.opts_.isEmpty()) { + if (opts_.isEmpty()) { + opts_ = other.opts_; + bitField0_ = (bitField0_ & ~0x00000002); + } else { + ensureOptsIsMutable(); + opts_.addAll(other.opts_); + } + onChanged(); + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 10: { + mode_ = input.readStringRequireUtf8(); + + break; + } // case 10 + case 18: { + java.lang.String s = input.readStringRequireUtf8(); + ensureCcFlagsIsMutable(); + ccFlags_.add(s); + break; + } // case 18 + case 26: { + java.lang.String s = input.readStringRequireUtf8(); + ensureOptsIsMutable(); + opts_.add(s); + break; + } // case 26 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + private int bitField0_; + + private java.lang.Object mode_ = ""; + /** + * 
    +     * opt, dbg, etc
+     *
    + * + * string mode = 1; + * @return The mode. + */ + public java.lang.String getMode() { + java.lang.Object ref = mode_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + mode_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * opt, dbg, etc
+     *
    + * + * string mode = 1; + * @return The bytes for mode. + */ + public com.google.protobuf.ByteString + getModeBytes() { + java.lang.Object ref = mode_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + mode_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * opt, dbg, etc
+     *
    + * + * string mode = 1; + * @param value The mode to set. + * @return This builder for chaining. + */ + public Builder setMode( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + mode_ = value; + onChanged(); + return this; + } + /** + * 
    +     * opt, dbg, etc
+     *
    + * + * string mode = 1; + * @return This builder for chaining. + */ + public Builder clearMode() { + + mode_ = getDefaultInstance().getMode(); + onChanged(); + return this; + } + /** + * 
    +     * opt, dbg, etc
+     *
    + * + * string mode = 1; + * @param value The bytes for mode to set. + * @return This builder for chaining. + */ + public Builder setModeBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + mode_ = value; + onChanged(); + return this; + } + + private com.google.protobuf.LazyStringList ccFlags_ = com.google.protobuf.LazyStringArrayList.EMPTY; + private void ensureCcFlagsIsMutable() { + if (!((bitField0_ & 0x00000001) != 0)) { + ccFlags_ = new com.google.protobuf.LazyStringArrayList(ccFlags_); + bitField0_ |= 0x00000001; + } + } + /** + * 
    +     * CC compiler flags, if known
+     *
    + * + * repeated string cc_flags = 2; + * @return A list containing the ccFlags. + */ + public com.google.protobuf.ProtocolStringList + getCcFlagsList() { + return ccFlags_.getUnmodifiableView(); + } + /** + * 
    +     * CC compiler flags, if known
+     *
    + * + * repeated string cc_flags = 2; + * @return The count of ccFlags. + */ + public int getCcFlagsCount() { + return ccFlags_.size(); + } + /** + * 
    +     * CC compiler flags, if known
+     *
    + * + * repeated string cc_flags = 2; + * @param index The index of the element to return. + * @return The ccFlags at the given index. + */ + public java.lang.String getCcFlags(int index) { + return ccFlags_.get(index); + } + /** + * 
    +     * CC compiler flags, if known
+     *
    + * + * repeated string cc_flags = 2; + * @param index The index of the value to return. + * @return The bytes of the ccFlags at the given index. + */ + public com.google.protobuf.ByteString + getCcFlagsBytes(int index) { + return ccFlags_.getByteString(index); + } + /** + * 
    +     * CC compiler flags, if known
+     *
    + * + * repeated string cc_flags = 2; + * @param index The index to set the value at. + * @param value The ccFlags to set. + * @return This builder for chaining. + */ + public Builder setCcFlags( + int index, java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + ensureCcFlagsIsMutable(); + ccFlags_.set(index, value); + onChanged(); + return this; + } + /** + * 
    +     * CC compiler flags, if known
+     *
    + * + * repeated string cc_flags = 2; + * @param value The ccFlags to add. + * @return This builder for chaining. + */ + public Builder addCcFlags( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + ensureCcFlagsIsMutable(); + ccFlags_.add(value); + onChanged(); + return this; + } + /** + * 
    +     * CC compiler flags, if known
+     *
    + * + * repeated string cc_flags = 2; + * @param values The ccFlags to add. + * @return This builder for chaining. + */ + public Builder addAllCcFlags( + java.lang.Iterable values) { + ensureCcFlagsIsMutable(); + com.google.protobuf.AbstractMessageLite.Builder.addAll( + values, ccFlags_); + onChanged(); + return this; + } + /** + * 
    +     * CC compiler flags, if known
+     *
    + * + * repeated string cc_flags = 2; + * @return This builder for chaining. + */ + public Builder clearCcFlags() { + ccFlags_ = com.google.protobuf.LazyStringArrayList.EMPTY; + bitField0_ = (bitField0_ & ~0x00000001); + onChanged(); + return this; + } + /** + * 
    +     * CC compiler flags, if known
+     *
    + * + * repeated string cc_flags = 2; + * @param value The bytes of the ccFlags to add. + * @return This builder for chaining. + */ + public Builder addCcFlagsBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + ensureCcFlagsIsMutable(); + ccFlags_.add(value); + onChanged(); + return this; + } + + private com.google.protobuf.LazyStringList opts_ = com.google.protobuf.LazyStringArrayList.EMPTY; + private void ensureOptsIsMutable() { + if (!((bitField0_ & 0x00000002) != 0)) { + opts_ = new com.google.protobuf.LazyStringArrayList(opts_); + bitField0_ |= 0x00000002; + } + } + /** + * 
    +     * Bazel compilation options, if known
+     *
    + * + * repeated string opts = 3; + * @return A list containing the opts. + */ + public com.google.protobuf.ProtocolStringList + getOptsList() { + return opts_.getUnmodifiableView(); + } + /** + * 
    +     * Bazel compilation options, if known
+     *
    + * + * repeated string opts = 3; + * @return The count of opts. + */ + public int getOptsCount() { + return opts_.size(); + } + /** + * 
    +     * Bazel compilation options, if known
+     *
    + * + * repeated string opts = 3; + * @param index The index of the element to return. + * @return The opts at the given index. + */ + public java.lang.String getOpts(int index) { + return opts_.get(index); + } + /** + * 
    +     * Bazel compilation options, if known
+     *
    + * + * repeated string opts = 3; + * @param index The index of the value to return. + * @return The bytes of the opts at the given index. + */ + public com.google.protobuf.ByteString + getOptsBytes(int index) { + return opts_.getByteString(index); + } + /** + * 
    +     * Bazel compilation options, if known
+     *
    + * + * repeated string opts = 3; + * @param index The index to set the value at. + * @param value The opts to set. + * @return This builder for chaining. + */ + public Builder setOpts( + int index, java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + ensureOptsIsMutable(); + opts_.set(index, value); + onChanged(); + return this; + } + /** + * 
    +     * Bazel compilation options, if known
+     *
    + * + * repeated string opts = 3; + * @param value The opts to add. + * @return This builder for chaining. + */ + public Builder addOpts( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + ensureOptsIsMutable(); + opts_.add(value); + onChanged(); + return this; + } + /** + * 
    +     * Bazel compilation options, if known
+     *
    + * + * repeated string opts = 3; + * @param values The opts to add. + * @return This builder for chaining. + */ + public Builder addAllOpts( + java.lang.Iterable values) { + ensureOptsIsMutable(); + com.google.protobuf.AbstractMessageLite.Builder.addAll( + values, opts_); + onChanged(); + return this; + } + /** + * 
    +     * Bazel compilation options, if known
+     *
    + * + * repeated string opts = 3; + * @return This builder for chaining. + */ + public Builder clearOpts() { + opts_ = com.google.protobuf.LazyStringArrayList.EMPTY; + bitField0_ = (bitField0_ & ~0x00000002); + onChanged(); + return this; + } + /** + * 
    +     * Bazel compilation options, if known
+     *
    + * + * repeated string opts = 3; + * @param value The bytes of the opts to add. + * @return This builder for chaining. + */ + public Builder addOptsBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + ensureOptsIsMutable(); + opts_.add(value); + onChanged(); + return this; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.BuildConfiguration) + } + + // @@protoc_insertion_point(class_scope:tensorflow.BuildConfiguration) + private static final org.tensorflow.proto.BuildConfiguration DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.BuildConfiguration(); + } + + public static org.tensorflow.proto.BuildConfiguration getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public BuildConfiguration parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.BuildConfiguration getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + +} + diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BuildConfigurationOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BuildConfigurationOrBuilder.java new file mode 100644 index 00000000000..112534dc95a --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/BuildConfigurationOrBuilder.java @@ -0,0 +1,111 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public interface BuildConfigurationOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.BuildConfiguration) + com.google.protobuf.MessageOrBuilder { + + /** + * 
    +   * opt, dbg, etc
+   *
    + * + * string mode = 1; + * @return The mode. + */ + java.lang.String getMode(); + /** + * 
    +   * opt, dbg, etc
+   *
    + * + * string mode = 1; + * @return The bytes for mode. + */ + com.google.protobuf.ByteString + getModeBytes(); + + /** + * 
    +   * CC compiler flags, if known
+   *
    + * + * repeated string cc_flags = 2; + * @return A list containing the ccFlags. + */ + java.util.List + getCcFlagsList(); + /** + * 
    +   * CC compiler flags, if known
+   *
    + * + * repeated string cc_flags = 2; + * @return The count of ccFlags. + */ + int getCcFlagsCount(); + /** + * 
    +   * CC compiler flags, if known
+   *
    + * + * repeated string cc_flags = 2; + * @param index The index of the element to return. + * @return The ccFlags at the given index. + */ + java.lang.String getCcFlags(int index); + /** + * 
    +   * CC compiler flags, if known
+   *
    + * + * repeated string cc_flags = 2; + * @param index The index of the value to return. + * @return The bytes of the ccFlags at the given index. + */ + com.google.protobuf.ByteString + getCcFlagsBytes(int index); + + /** + * 
    +   * Bazel compilation options, if known
+   *
    + * + * repeated string opts = 3; + * @return A list containing the opts. + */ + java.util.List + getOptsList(); + /** + * 
    +   * Bazel compilation options, if known
+   *
    + * + * repeated string opts = 3; + * @return The count of opts. + */ + int getOptsCount(); + /** + * 
    +   * Bazel compilation options, if known
+   *
    + * + * repeated string opts = 3; + * @param index The index of the element to return. + * @return The opts at the given index. + */ + java.lang.String getOpts(int index); + /** + * 
    +   * Bazel compilation options, if known
+   *
    + * + * repeated string opts = 3; + * @param index The index of the value to return. + * @return The bytes of the opts at the given index. + */ + com.google.protobuf.ByteString + getOptsBytes(int index); +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CPUInfo.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CPUInfo.java new file mode 100644 index 00000000000..3816e55e459 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CPUInfo.java @@ -0,0 +1,1281 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +/** + * Protobuf type {@code tensorflow.CPUInfo} + */ +public final class CPUInfo extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.CPUInfo) + CPUInfoOrBuilder { +private static final long serialVersionUID = 0L; + // Use CPUInfo.newBuilder() to construct. + private CPUInfo(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private CPUInfo() { + cpuInfo_ = ""; + cpuGovernor_ = ""; + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new CPUInfo(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CPUInfo_descriptor; + } + + @SuppressWarnings({"rawtypes"}) + @java.lang.Override + protected com.google.protobuf.MapField internalGetMapField( + int number) { + switch (number) { + case 6: + return internalGetCacheSize(); + default: + throw new RuntimeException( + "Invalid map field number: " + number); + } + } + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CPUInfo_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.CPUInfo.class, org.tensorflow.proto.CPUInfo.Builder.class); + } + + public static final int NUM_CORES_FIELD_NUMBER = 1; + private long numCores_; + /** + * int64 num_cores = 1; + * @return The numCores. + */ + @java.lang.Override + public long getNumCores() { + return numCores_; + } + + public static final int NUM_CORES_ALLOWED_FIELD_NUMBER = 2; + private long numCoresAllowed_; + /** + * int64 num_cores_allowed = 2; + * @return The numCoresAllowed. + */ + @java.lang.Override + public long getNumCoresAllowed() { + return numCoresAllowed_; + } + + public static final int MHZ_PER_CPU_FIELD_NUMBER = 3; + private double mhzPerCpu_; + /** + * 
    +   * How fast are these cpus?
+   *
    + * + * double mhz_per_cpu = 3; + * @return The mhzPerCpu. + */ + @java.lang.Override + public double getMhzPerCpu() { + return mhzPerCpu_; + } + + public static final int CPU_INFO_FIELD_NUMBER = 4; + private volatile java.lang.Object cpuInfo_; + /** + * 
    +   * Additional cpu information. For example,
+   * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
+   *
    + * + * string cpu_info = 4; + * @return The cpuInfo. + */ + @java.lang.Override + public java.lang.String getCpuInfo() { + java.lang.Object ref = cpuInfo_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + cpuInfo_ = s; + return s; + } + } + /** + * 
    +   * Additional cpu information. For example,
+   * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
+   *
    + * + * string cpu_info = 4; + * @return The bytes for cpuInfo. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getCpuInfoBytes() { + java.lang.Object ref = cpuInfo_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + cpuInfo_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int CPU_GOVERNOR_FIELD_NUMBER = 5; + private volatile java.lang.Object cpuGovernor_; + /** + * 
    +   * What kind of cpu scaling is enabled on the host.
+   * Examples include "performance", "ondemand", "conservative", "mixed".
+   *
    + * + * string cpu_governor = 5; + * @return The cpuGovernor. + */ + @java.lang.Override + public java.lang.String getCpuGovernor() { + java.lang.Object ref = cpuGovernor_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + cpuGovernor_ = s; + return s; + } + } + /** + * 
    +   * What kind of cpu scaling is enabled on the host.
+   * Examples include "performance", "ondemand", "conservative", "mixed".
+   *
    + * + * string cpu_governor = 5; + * @return The bytes for cpuGovernor. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getCpuGovernorBytes() { + java.lang.Object ref = cpuGovernor_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + cpuGovernor_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int CACHE_SIZE_FIELD_NUMBER = 6; + private static final class CacheSizeDefaultEntryHolder { + static final com.google.protobuf.MapEntry< + java.lang.String, java.lang.Long> defaultEntry = + com.google.protobuf.MapEntry + .newDefaultInstance( + org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CPUInfo_CacheSizeEntry_descriptor, + com.google.protobuf.WireFormat.FieldType.STRING, + "", + com.google.protobuf.WireFormat.FieldType.INT64, + 0L); + } + private com.google.protobuf.MapField< + java.lang.String, java.lang.Long> cacheSize_; + private com.google.protobuf.MapField + internalGetCacheSize() { + if (cacheSize_ == null) { + return com.google.protobuf.MapField.emptyMapField( + CacheSizeDefaultEntryHolder.defaultEntry); + } + return cacheSize_; + } + + public int getCacheSizeCount() { + return internalGetCacheSize().getMap().size(); + } + /** + * 
    +   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+   *
    + * + * map<string, int64> cache_size = 6; + */ + + @java.lang.Override + public boolean containsCacheSize( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + return internalGetCacheSize().getMap().containsKey(key); + } + /** + * Use {@link #getCacheSizeMap()} instead. + */ + @java.lang.Override + @java.lang.Deprecated + public java.util.Map getCacheSize() { + return getCacheSizeMap(); + } + /** + * 
    +   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+   *
    + * + * map<string, int64> cache_size = 6; + */ + @java.lang.Override + + public java.util.Map getCacheSizeMap() { + return internalGetCacheSize().getMap(); + } + /** + * 
    +   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+   *
    + * + * map<string, int64> cache_size = 6; + */ + @java.lang.Override + + public long getCacheSizeOrDefault( + java.lang.String key, + long defaultValue) { + if (key == null) { throw new NullPointerException("map key"); } + java.util.Map map = + internalGetCacheSize().getMap(); + return map.containsKey(key) ? map.get(key) : defaultValue; + } + /** + * 
    +   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+   *
    + * + * map<string, int64> cache_size = 6; + */ + @java.lang.Override + + public long getCacheSizeOrThrow( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + java.util.Map map = + internalGetCacheSize().getMap(); + if (!map.containsKey(key)) { + throw new java.lang.IllegalArgumentException(); + } + return map.get(key); + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (numCores_ != 0L) { + output.writeInt64(1, numCores_); + } + if (numCoresAllowed_ != 0L) { + output.writeInt64(2, numCoresAllowed_); + } + if (java.lang.Double.doubleToRawLongBits(mhzPerCpu_) != 0) { + output.writeDouble(3, mhzPerCpu_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(cpuInfo_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 4, cpuInfo_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(cpuGovernor_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 5, cpuGovernor_); + } + com.google.protobuf.GeneratedMessageV3 + .serializeStringMapTo( + output, + internalGetCacheSize(), + CacheSizeDefaultEntryHolder.defaultEntry, + 6); + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (numCores_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(1, numCores_); + } + if (numCoresAllowed_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(2, numCoresAllowed_); + } + if (java.lang.Double.doubleToRawLongBits(mhzPerCpu_) != 0) { + size += com.google.protobuf.CodedOutputStream + .computeDoubleSize(3, mhzPerCpu_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(cpuInfo_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(4, cpuInfo_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(cpuGovernor_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(5, cpuGovernor_); + } + for (java.util.Map.Entry entry + : internalGetCacheSize().getMap().entrySet()) { + com.google.protobuf.MapEntry + cacheSize__ = CacheSizeDefaultEntryHolder.defaultEntry.newBuilderForType() + .setKey(entry.getKey()) + .setValue(entry.getValue()) + .build(); + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(6, cacheSize__); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.CPUInfo)) { + return super.equals(obj); + } + org.tensorflow.proto.CPUInfo other = (org.tensorflow.proto.CPUInfo) obj; + + if (getNumCores() + != other.getNumCores()) return false; + if (getNumCoresAllowed() + != other.getNumCoresAllowed()) return false; + if (java.lang.Double.doubleToLongBits(getMhzPerCpu()) + != java.lang.Double.doubleToLongBits( + other.getMhzPerCpu())) return false; + if (!getCpuInfo() + .equals(other.getCpuInfo())) return false; + if (!getCpuGovernor() + .equals(other.getCpuGovernor())) return false; + if (!internalGetCacheSize().equals( + other.internalGetCacheSize())) return false; + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + NUM_CORES_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getNumCores()); + hash = (37 * hash) + NUM_CORES_ALLOWED_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getNumCoresAllowed()); + hash = (37 * hash) + MHZ_PER_CPU_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + java.lang.Double.doubleToLongBits(getMhzPerCpu())); + hash = (37 * hash) + CPU_INFO_FIELD_NUMBER; + hash = (53 * hash) + getCpuInfo().hashCode(); + hash = (37 * hash) + CPU_GOVERNOR_FIELD_NUMBER; + hash = (53 * hash) + getCpuGovernor().hashCode(); + if (!internalGetCacheSize().getMap().isEmpty()) { + hash = (37 * hash) + CACHE_SIZE_FIELD_NUMBER; + hash = (53 * hash) + internalGetCacheSize().hashCode(); + } + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.CPUInfo parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.CPUInfo parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.CPUInfo parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.CPUInfo parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.CPUInfo parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.CPUInfo parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.CPUInfo parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.CPUInfo parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.CPUInfo parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.CPUInfo parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.CPUInfo parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.CPUInfo parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.CPUInfo prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * Protobuf type {@code tensorflow.CPUInfo} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.CPUInfo) + org.tensorflow.proto.CPUInfoOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CPUInfo_descriptor; + } + + @SuppressWarnings({"rawtypes"}) + protected com.google.protobuf.MapField internalGetMapField( + int number) { + switch (number) { + case 6: + return internalGetCacheSize(); + default: + throw new RuntimeException( + "Invalid map field number: " + number); + } + } + @SuppressWarnings({"rawtypes"}) + protected com.google.protobuf.MapField internalGetMutableMapField( + int number) { + switch (number) { + case 6: + return internalGetMutableCacheSize(); + default: + throw new RuntimeException( + "Invalid map field number: " + number); + } + } + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CPUInfo_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.CPUInfo.class, org.tensorflow.proto.CPUInfo.Builder.class); + } + + // Construct using org.tensorflow.proto.CPUInfo.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + numCores_ = 0L; + + numCoresAllowed_ = 0L; + + mhzPerCpu_ = 0D; + + cpuInfo_ = ""; + + cpuGovernor_ = ""; + + internalGetMutableCacheSize().clear(); + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CPUInfo_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.CPUInfo getDefaultInstanceForType() { + return org.tensorflow.proto.CPUInfo.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.CPUInfo build() { + org.tensorflow.proto.CPUInfo result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.CPUInfo buildPartial() { + org.tensorflow.proto.CPUInfo result = new org.tensorflow.proto.CPUInfo(this); + int from_bitField0_ = bitField0_; + result.numCores_ = numCores_; + result.numCoresAllowed_ = numCoresAllowed_; + result.mhzPerCpu_ = mhzPerCpu_; + result.cpuInfo_ = cpuInfo_; + result.cpuGovernor_ = cpuGovernor_; + result.cacheSize_ = internalGetCacheSize(); + result.cacheSize_.makeImmutable(); + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.CPUInfo) { + return mergeFrom((org.tensorflow.proto.CPUInfo)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.CPUInfo other) { + if (other == org.tensorflow.proto.CPUInfo.getDefaultInstance()) return this; + if (other.getNumCores() != 0L) { + setNumCores(other.getNumCores()); + } + if (other.getNumCoresAllowed() != 0L) { + setNumCoresAllowed(other.getNumCoresAllowed()); + } + if (other.getMhzPerCpu() != 0D) { + setMhzPerCpu(other.getMhzPerCpu()); + } + if (!other.getCpuInfo().isEmpty()) { + cpuInfo_ = other.cpuInfo_; + onChanged(); + } + if (!other.getCpuGovernor().isEmpty()) { + cpuGovernor_ = other.cpuGovernor_; + onChanged(); + } + internalGetMutableCacheSize().mergeFrom( + other.internalGetCacheSize()); + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 8: { + numCores_ = input.readInt64(); + + break; + } // case 8 + case 16: { + numCoresAllowed_ = input.readInt64(); + + break; + } // case 16 + case 25: { + mhzPerCpu_ = input.readDouble(); + + break; + } // case 25 + case 34: { + cpuInfo_ = input.readStringRequireUtf8(); + + break; + } // case 34 + case 42: { + cpuGovernor_ = input.readStringRequireUtf8(); + + break; + } // case 42 + case 50: { + com.google.protobuf.MapEntry + cacheSize__ = input.readMessage( + CacheSizeDefaultEntryHolder.defaultEntry.getParserForType(), extensionRegistry); + internalGetMutableCacheSize().getMutableMap().put( + cacheSize__.getKey(), cacheSize__.getValue()); + break; + } // case 50 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + private int bitField0_; + + private long numCores_ ; + /** + * int64 num_cores = 1; + * @return The numCores. + */ + @java.lang.Override + public long getNumCores() { + return numCores_; + } + /** + * int64 num_cores = 1; + * @param value The numCores to set. + * @return This builder for chaining. + */ + public Builder setNumCores(long value) { + + numCores_ = value; + onChanged(); + return this; + } + /** + * int64 num_cores = 1; + * @return This builder for chaining. + */ + public Builder clearNumCores() { + + numCores_ = 0L; + onChanged(); + return this; + } + + private long numCoresAllowed_ ; + /** + * int64 num_cores_allowed = 2; + * @return The numCoresAllowed. + */ + @java.lang.Override + public long getNumCoresAllowed() { + return numCoresAllowed_; + } + /** + * int64 num_cores_allowed = 2; + * @param value The numCoresAllowed to set. + * @return This builder for chaining. + */ + public Builder setNumCoresAllowed(long value) { + + numCoresAllowed_ = value; + onChanged(); + return this; + } + /** + * int64 num_cores_allowed = 2; + * @return This builder for chaining. + */ + public Builder clearNumCoresAllowed() { + + numCoresAllowed_ = 0L; + onChanged(); + return this; + } + + private double mhzPerCpu_ ; + /** + * 
    +     * How fast are these cpus?
+     *
    + * + * double mhz_per_cpu = 3; + * @return The mhzPerCpu. + */ + @java.lang.Override + public double getMhzPerCpu() { + return mhzPerCpu_; + } + /** + * 
    +     * How fast are these cpus?
+     *
    + * + * double mhz_per_cpu = 3; + * @param value The mhzPerCpu to set. + * @return This builder for chaining. + */ + public Builder setMhzPerCpu(double value) { + + mhzPerCpu_ = value; + onChanged(); + return this; + } + /** + * 
    +     * How fast are these cpus?
+     *
    + * + * double mhz_per_cpu = 3; + * @return This builder for chaining. + */ + public Builder clearMhzPerCpu() { + + mhzPerCpu_ = 0D; + onChanged(); + return this; + } + + private java.lang.Object cpuInfo_ = ""; + /** + * 
    +     * Additional cpu information. For example,
+     * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
+     *
    + * + * string cpu_info = 4; + * @return The cpuInfo. + */ + public java.lang.String getCpuInfo() { + java.lang.Object ref = cpuInfo_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + cpuInfo_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * Additional cpu information. For example,
+     * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
+     *
    + * + * string cpu_info = 4; + * @return The bytes for cpuInfo. + */ + public com.google.protobuf.ByteString + getCpuInfoBytes() { + java.lang.Object ref = cpuInfo_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + cpuInfo_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * Additional cpu information. For example,
+     * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
+     *
    + * + * string cpu_info = 4; + * @param value The cpuInfo to set. + * @return This builder for chaining. + */ + public Builder setCpuInfo( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + cpuInfo_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Additional cpu information. For example,
+     * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
+     *
    + * + * string cpu_info = 4; + * @return This builder for chaining. + */ + public Builder clearCpuInfo() { + + cpuInfo_ = getDefaultInstance().getCpuInfo(); + onChanged(); + return this; + } + /** + * 
    +     * Additional cpu information. For example,
+     * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
+     *
    + * + * string cpu_info = 4; + * @param value The bytes for cpuInfo to set. + * @return This builder for chaining. + */ + public Builder setCpuInfoBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + cpuInfo_ = value; + onChanged(); + return this; + } + + private java.lang.Object cpuGovernor_ = ""; + /** + * 
    +     * What kind of cpu scaling is enabled on the host.
+     * Examples include "performance", "ondemand", "conservative", "mixed".
+     *
    + * + * string cpu_governor = 5; + * @return The cpuGovernor. + */ + public java.lang.String getCpuGovernor() { + java.lang.Object ref = cpuGovernor_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + cpuGovernor_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * What kind of cpu scaling is enabled on the host.
+     * Examples include "performance", "ondemand", "conservative", "mixed".
+     *
    + * + * string cpu_governor = 5; + * @return The bytes for cpuGovernor. + */ + public com.google.protobuf.ByteString + getCpuGovernorBytes() { + java.lang.Object ref = cpuGovernor_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + cpuGovernor_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * What kind of cpu scaling is enabled on the host.
+     * Examples include "performance", "ondemand", "conservative", "mixed".
+     *
    + * + * string cpu_governor = 5; + * @param value The cpuGovernor to set. + * @return This builder for chaining. + */ + public Builder setCpuGovernor( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + cpuGovernor_ = value; + onChanged(); + return this; + } + /** + * 
    +     * What kind of cpu scaling is enabled on the host.
+     * Examples include "performance", "ondemand", "conservative", "mixed".
+     *
    + * + * string cpu_governor = 5; + * @return This builder for chaining. + */ + public Builder clearCpuGovernor() { + + cpuGovernor_ = getDefaultInstance().getCpuGovernor(); + onChanged(); + return this; + } + /** + * 
    +     * What kind of cpu scaling is enabled on the host.
+     * Examples include "performance", "ondemand", "conservative", "mixed".
+     *
    + * + * string cpu_governor = 5; + * @param value The bytes for cpuGovernor to set. + * @return This builder for chaining. + */ + public Builder setCpuGovernorBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + cpuGovernor_ = value; + onChanged(); + return this; + } + + private com.google.protobuf.MapField< + java.lang.String, java.lang.Long> cacheSize_; + private com.google.protobuf.MapField + internalGetCacheSize() { + if (cacheSize_ == null) { + return com.google.protobuf.MapField.emptyMapField( + CacheSizeDefaultEntryHolder.defaultEntry); + } + return cacheSize_; + } + private com.google.protobuf.MapField + internalGetMutableCacheSize() { + onChanged();; + if (cacheSize_ == null) { + cacheSize_ = com.google.protobuf.MapField.newMapField( + CacheSizeDefaultEntryHolder.defaultEntry); + } + if (!cacheSize_.isMutable()) { + cacheSize_ = cacheSize_.copy(); + } + return cacheSize_; + } + + public int getCacheSizeCount() { + return internalGetCacheSize().getMap().size(); + } + /** + * 
    +     * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+     *
    + * + * map<string, int64> cache_size = 6; + */ + + @java.lang.Override + public boolean containsCacheSize( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + return internalGetCacheSize().getMap().containsKey(key); + } + /** + * Use {@link #getCacheSizeMap()} instead. + */ + @java.lang.Override + @java.lang.Deprecated + public java.util.Map getCacheSize() { + return getCacheSizeMap(); + } + /** + * 
    +     * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+     *
    + * + * map<string, int64> cache_size = 6; + */ + @java.lang.Override + + public java.util.Map getCacheSizeMap() { + return internalGetCacheSize().getMap(); + } + /** + * 
    +     * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+     *
    + * + * map<string, int64> cache_size = 6; + */ + @java.lang.Override + + public long getCacheSizeOrDefault( + java.lang.String key, + long defaultValue) { + if (key == null) { throw new NullPointerException("map key"); } + java.util.Map map = + internalGetCacheSize().getMap(); + return map.containsKey(key) ? map.get(key) : defaultValue; + } + /** + * 
    +     * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+     *
    + * + * map<string, int64> cache_size = 6; + */ + @java.lang.Override + + public long getCacheSizeOrThrow( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + java.util.Map map = + internalGetCacheSize().getMap(); + if (!map.containsKey(key)) { + throw new java.lang.IllegalArgumentException(); + } + return map.get(key); + } + + public Builder clearCacheSize() { + internalGetMutableCacheSize().getMutableMap() + .clear(); + return this; + } + /** + * 
    +     * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+     *
    + * + * map<string, int64> cache_size = 6; + */ + + public Builder removeCacheSize( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + internalGetMutableCacheSize().getMutableMap() + .remove(key); + return this; + } + /** + * Use alternate mutation accessors instead. + */ + @java.lang.Deprecated + public java.util.Map + getMutableCacheSize() { + return internalGetMutableCacheSize().getMutableMap(); + } + /** + * 
    +     * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+     *
    + * + * map<string, int64> cache_size = 6; + */ + public Builder putCacheSize( + java.lang.String key, + long value) { + if (key == null) { throw new NullPointerException("map key"); } + + internalGetMutableCacheSize().getMutableMap() + .put(key, value); + return this; + } + /** + * 
    +     * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+     *
    + * + * map<string, int64> cache_size = 6; + */ + + public Builder putAllCacheSize( + java.util.Map values) { + internalGetMutableCacheSize().getMutableMap() + .putAll(values); + return this; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.CPUInfo) + } + + // @@protoc_insertion_point(class_scope:tensorflow.CPUInfo) + private static final org.tensorflow.proto.CPUInfo DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.CPUInfo(); + } + + public static org.tensorflow.proto.CPUInfo getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public CPUInfo parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.CPUInfo getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + +} + diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CPUInfoOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CPUInfoOrBuilder.java new file mode 100644 index 00000000000..9ede760853d --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CPUInfoOrBuilder.java @@ -0,0 +1,129 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public interface CPUInfoOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.CPUInfo) + com.google.protobuf.MessageOrBuilder { + + /** + * int64 num_cores = 1; + * @return The numCores. + */ + long getNumCores(); + + /** + * int64 num_cores_allowed = 2; + * @return The numCoresAllowed. + */ + long getNumCoresAllowed(); + + /** + * 
    +   * How fast are these cpus?
+   *
    + * + * double mhz_per_cpu = 3; + * @return The mhzPerCpu. + */ + double getMhzPerCpu(); + + /** + * 
    +   * Additional cpu information. For example,
+   * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
+   *
    + * + * string cpu_info = 4; + * @return The cpuInfo. + */ + java.lang.String getCpuInfo(); + /** + * 
    +   * Additional cpu information. For example,
+   * Intel Ivybridge with HyperThreading (24 cores) dL1:32KB dL2:256KB dL3:30MB
+   *
    + * + * string cpu_info = 4; + * @return The bytes for cpuInfo. + */ + com.google.protobuf.ByteString + getCpuInfoBytes(); + + /** + * 
    +   * What kind of cpu scaling is enabled on the host.
+   * Examples include "performance", "ondemand", "conservative", "mixed".
+   *
    + * + * string cpu_governor = 5; + * @return The cpuGovernor. + */ + java.lang.String getCpuGovernor(); + /** + * 
    +   * What kind of cpu scaling is enabled on the host.
+   * Examples include "performance", "ondemand", "conservative", "mixed".
+   *
    + * + * string cpu_governor = 5; + * @return The bytes for cpuGovernor. + */ + com.google.protobuf.ByteString + getCpuGovernorBytes(); + + /** + * 
    +   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+   *
    + * + * map<string, int64> cache_size = 6; + */ + int getCacheSizeCount(); + /** + * 
    +   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+   *
    + * + * map<string, int64> cache_size = 6; + */ + boolean containsCacheSize( + java.lang.String key); + /** + * Use {@link #getCacheSizeMap()} instead. + */ + @java.lang.Deprecated + java.util.Map + getCacheSize(); + /** + * 
    +   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+   *
    + * + * map<string, int64> cache_size = 6; + */ + java.util.Map + getCacheSizeMap(); + /** + * 
    +   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+   *
    + * + * map<string, int64> cache_size = 6; + */ + + long getCacheSizeOrDefault( + java.lang.String key, + long defaultValue); + /** + * 
    +   * Cache sizes (in bytes), e.g. "L2": 262144 (for 256KB)
+   *
    + * + * map<string, int64> cache_size = 6; + */ + + long getCacheSizeOrThrow( + java.lang.String key); +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CommitId.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CommitId.java new file mode 100644 index 00000000000..9f6ad5f08bc --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CommitId.java @@ -0,0 +1,1021 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +/** + * Protobuf type {@code tensorflow.CommitId} + */ +public final class CommitId extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.CommitId) + CommitIdOrBuilder { +private static final long serialVersionUID = 0L; + // Use CommitId.newBuilder() to construct. + private CommitId(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private CommitId() { + snapshot_ = ""; + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new CommitId(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CommitId_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CommitId_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.CommitId.class, org.tensorflow.proto.CommitId.Builder.class); + } + + private int kindCase_ = 0; + private java.lang.Object kind_; + public enum KindCase + implements com.google.protobuf.Internal.EnumLite, + com.google.protobuf.AbstractMessage.InternalOneOfEnum { + CHANGELIST(1), + HASH(2), + KIND_NOT_SET(0); + private final int value; + private KindCase(int value) { + this.value = value; + } + /** + * @param value The number of the enum to look for. + * @return The enum associated with the given number. + * @deprecated Use {@link #forNumber(int)} instead. + */ + @java.lang.Deprecated + public static KindCase valueOf(int value) { + return forNumber(value); + } + + public static KindCase forNumber(int value) { + switch (value) { + case 1: return CHANGELIST; + case 2: return HASH; + case 0: return KIND_NOT_SET; + default: return null; + } + } + public int getNumber() { + return this.value; + } + }; + + public KindCase + getKindCase() { + return KindCase.forNumber( + kindCase_); + } + + public static final int CHANGELIST_FIELD_NUMBER = 1; + /** + * 
    +   * Submitted changelist.
+   *
    + * + * int64 changelist = 1; + * @return Whether the changelist field is set. + */ + @java.lang.Override + public boolean hasChangelist() { + return kindCase_ == 1; + } + /** + * 
    +   * Submitted changelist.
+   *
    + * + * int64 changelist = 1; + * @return The changelist. + */ + @java.lang.Override + public long getChangelist() { + if (kindCase_ == 1) { + return (java.lang.Long) kind_; + } + return 0L; + } + + public static final int HASH_FIELD_NUMBER = 2; + /** + * string hash = 2; + * @return Whether the hash field is set. + */ + public boolean hasHash() { + return kindCase_ == 2; + } + /** + * string hash = 2; + * @return The hash. + */ + public java.lang.String getHash() { + java.lang.Object ref = ""; + if (kindCase_ == 2) { + ref = kind_; + } + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + if (kindCase_ == 2) { + kind_ = s; + } + return s; + } + } + /** + * string hash = 2; + * @return The bytes for hash. + */ + public com.google.protobuf.ByteString + getHashBytes() { + java.lang.Object ref = ""; + if (kindCase_ == 2) { + ref = kind_; + } + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + if (kindCase_ == 2) { + kind_ = b; + } + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int SNAPSHOT_FIELD_NUMBER = 3; + private volatile java.lang.Object snapshot_; + /** + * 
    +   * Hash of intermediate change between hash/changelist and what was tested.
+   * Not used if the build is from a commit without modifications.
+   *
    + * + * string snapshot = 3; + * @return The snapshot. + */ + @java.lang.Override + public java.lang.String getSnapshot() { + java.lang.Object ref = snapshot_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + snapshot_ = s; + return s; + } + } + /** + * 
    +   * Hash of intermediate change between hash/changelist and what was tested.
+   * Not used if the build is from a commit without modifications.
+   *
    + * + * string snapshot = 3; + * @return The bytes for snapshot. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getSnapshotBytes() { + java.lang.Object ref = snapshot_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + snapshot_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int PENDING_CHANGELIST_FIELD_NUMBER = 4; + private long pendingChangelist_; + /** + * 
    +   * Changelist tested if the change list is not already submitted.
+   *
    + * + * int64 pending_changelist = 4; + * @return The pendingChangelist. + */ + @java.lang.Override + public long getPendingChangelist() { + return pendingChangelist_; + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (kindCase_ == 1) { + output.writeInt64( + 1, (long)((java.lang.Long) kind_)); + } + if (kindCase_ == 2) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 2, kind_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(snapshot_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 3, snapshot_); + } + if (pendingChangelist_ != 0L) { + output.writeInt64(4, pendingChangelist_); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (kindCase_ == 1) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size( + 1, (long)((java.lang.Long) kind_)); + } + if (kindCase_ == 2) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(2, kind_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(snapshot_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(3, snapshot_); + } + if (pendingChangelist_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(4, pendingChangelist_); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.CommitId)) { + return super.equals(obj); + } + org.tensorflow.proto.CommitId other = (org.tensorflow.proto.CommitId) obj; + + if (!getSnapshot() + .equals(other.getSnapshot())) return false; + if (getPendingChangelist() + != other.getPendingChangelist()) return false; + if (!getKindCase().equals(other.getKindCase())) return false; + switch (kindCase_) { + case 1: + if (getChangelist() + != other.getChangelist()) return false; + break; + case 2: + if (!getHash() + .equals(other.getHash())) return false; + break; + case 0: + default: + } + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + SNAPSHOT_FIELD_NUMBER; + hash = (53 * hash) + getSnapshot().hashCode(); + hash = (37 * hash) + PENDING_CHANGELIST_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getPendingChangelist()); + switch (kindCase_) { + case 1: + hash = (37 * hash) + CHANGELIST_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getChangelist()); + break; + case 2: + hash = (37 * hash) + HASH_FIELD_NUMBER; + hash = (53 * hash) + getHash().hashCode(); + break; + case 0: + default: + } + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.CommitId parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.CommitId parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.CommitId parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.CommitId parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.CommitId parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.CommitId parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.CommitId parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.CommitId parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.CommitId parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.CommitId parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.CommitId parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.CommitId parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.CommitId prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * Protobuf type {@code tensorflow.CommitId} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.CommitId) + org.tensorflow.proto.CommitIdOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CommitId_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CommitId_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.CommitId.class, org.tensorflow.proto.CommitId.Builder.class); + } + + // Construct using org.tensorflow.proto.CommitId.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + snapshot_ = ""; + + pendingChangelist_ = 0L; + + kindCase_ = 0; + kind_ = null; + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_CommitId_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.CommitId getDefaultInstanceForType() { + return org.tensorflow.proto.CommitId.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.CommitId build() { + org.tensorflow.proto.CommitId result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.CommitId buildPartial() { + org.tensorflow.proto.CommitId result = new org.tensorflow.proto.CommitId(this); + if (kindCase_ == 1) { + result.kind_ = kind_; + } + if (kindCase_ == 2) { + result.kind_ = kind_; + } + result.snapshot_ = snapshot_; + result.pendingChangelist_ = pendingChangelist_; + result.kindCase_ = kindCase_; + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.CommitId) { + return mergeFrom((org.tensorflow.proto.CommitId)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.CommitId other) { + if (other == org.tensorflow.proto.CommitId.getDefaultInstance()) return this; + if (!other.getSnapshot().isEmpty()) { + snapshot_ = other.snapshot_; + onChanged(); + } + if (other.getPendingChangelist() != 0L) { + setPendingChangelist(other.getPendingChangelist()); + } + switch (other.getKindCase()) { + case CHANGELIST: { + setChangelist(other.getChangelist()); + break; + } + case HASH: { + kindCase_ = 2; + kind_ = other.kind_; + onChanged(); + break; + } + case KIND_NOT_SET: { + break; + } + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 8: { + kind_ = input.readInt64(); + kindCase_ = 1; + break; + } // case 8 + case 18: { + java.lang.String s = input.readStringRequireUtf8(); + kindCase_ = 2; + kind_ = s; + break; + } // case 18 + case 26: { + snapshot_ = input.readStringRequireUtf8(); + + break; + } // case 26 + case 32: { + pendingChangelist_ = input.readInt64(); + + break; + } // case 32 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + private int kindCase_ = 0; + private java.lang.Object kind_; + public KindCase + getKindCase() { + return KindCase.forNumber( + kindCase_); + } + + public Builder clearKind() { + kindCase_ = 0; + kind_ = null; + onChanged(); + return this; + } + + + /** + * 
    +     * Submitted changelist.
+     *
    + * + * int64 changelist = 1; + * @return Whether the changelist field is set. + */ + public boolean hasChangelist() { + return kindCase_ == 1; + } + /** + * 
    +     * Submitted changelist.
+     *
    + * + * int64 changelist = 1; + * @return The changelist. + */ + public long getChangelist() { + if (kindCase_ == 1) { + return (java.lang.Long) kind_; + } + return 0L; + } + /** + * 
    +     * Submitted changelist.
+     *
    + * + * int64 changelist = 1; + * @param value The changelist to set. + * @return This builder for chaining. + */ + public Builder setChangelist(long value) { + kindCase_ = 1; + kind_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Submitted changelist.
+     *
    + * + * int64 changelist = 1; + * @return This builder for chaining. + */ + public Builder clearChangelist() { + if (kindCase_ == 1) { + kindCase_ = 0; + kind_ = null; + onChanged(); + } + return this; + } + + /** + * string hash = 2; + * @return Whether the hash field is set. + */ + @java.lang.Override + public boolean hasHash() { + return kindCase_ == 2; + } + /** + * string hash = 2; + * @return The hash. + */ + @java.lang.Override + public java.lang.String getHash() { + java.lang.Object ref = ""; + if (kindCase_ == 2) { + ref = kind_; + } + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + if (kindCase_ == 2) { + kind_ = s; + } + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * string hash = 2; + * @return The bytes for hash. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getHashBytes() { + java.lang.Object ref = ""; + if (kindCase_ == 2) { + ref = kind_; + } + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + if (kindCase_ == 2) { + kind_ = b; + } + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * string hash = 2; + * @param value The hash to set. + * @return This builder for chaining. + */ + public Builder setHash( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + kindCase_ = 2; + kind_ = value; + onChanged(); + return this; + } + /** + * string hash = 2; + * @return This builder for chaining. + */ + public Builder clearHash() { + if (kindCase_ == 2) { + kindCase_ = 0; + kind_ = null; + onChanged(); + } + return this; + } + /** + * string hash = 2; + * @param value The bytes for hash to set. + * @return This builder for chaining. + */ + public Builder setHashBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + kindCase_ = 2; + kind_ = value; + onChanged(); + return this; + } + + private java.lang.Object snapshot_ = ""; + /** + * 
    +     * Hash of intermediate change between hash/changelist and what was tested.
+     * Not used if the build is from a commit without modifications.
+     *
    + * + * string snapshot = 3; + * @return The snapshot. + */ + public java.lang.String getSnapshot() { + java.lang.Object ref = snapshot_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + snapshot_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * Hash of intermediate change between hash/changelist and what was tested.
+     * Not used if the build is from a commit without modifications.
+     *
    + * + * string snapshot = 3; + * @return The bytes for snapshot. + */ + public com.google.protobuf.ByteString + getSnapshotBytes() { + java.lang.Object ref = snapshot_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + snapshot_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * Hash of intermediate change between hash/changelist and what was tested.
+     * Not used if the build is from a commit without modifications.
+     *
    + * + * string snapshot = 3; + * @param value The snapshot to set. + * @return This builder for chaining. + */ + public Builder setSnapshot( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + snapshot_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Hash of intermediate change between hash/changelist and what was tested.
+     * Not used if the build is from a commit without modifications.
+     *
    + * + * string snapshot = 3; + * @return This builder for chaining. + */ + public Builder clearSnapshot() { + + snapshot_ = getDefaultInstance().getSnapshot(); + onChanged(); + return this; + } + /** + * 
    +     * Hash of intermediate change between hash/changelist and what was tested.
+     * Not used if the build is from a commit without modifications.
+     *
    + * + * string snapshot = 3; + * @param value The bytes for snapshot to set. + * @return This builder for chaining. + */ + public Builder setSnapshotBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + snapshot_ = value; + onChanged(); + return this; + } + + private long pendingChangelist_ ; + /** + * 
    +     * Changelist tested if the change list is not already submitted.
+     *
    + * + * int64 pending_changelist = 4; + * @return The pendingChangelist. + */ + @java.lang.Override + public long getPendingChangelist() { + return pendingChangelist_; + } + /** + * 
    +     * Changelist tested if the change list is not already submitted.
+     *
    + * + * int64 pending_changelist = 4; + * @param value The pendingChangelist to set. + * @return This builder for chaining. + */ + public Builder setPendingChangelist(long value) { + + pendingChangelist_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Changelist tested if the change list is not already submitted.
+     *
    + * + * int64 pending_changelist = 4; + * @return This builder for chaining. + */ + public Builder clearPendingChangelist() { + + pendingChangelist_ = 0L; + onChanged(); + return this; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.CommitId) + } + + // @@protoc_insertion_point(class_scope:tensorflow.CommitId) + private static final org.tensorflow.proto.CommitId DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.CommitId(); + } + + public static org.tensorflow.proto.CommitId getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public CommitId parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.CommitId getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + +} + diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CommitIdOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CommitIdOrBuilder.java new file mode 100644 index 00000000000..cb78f3bd9d2 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/CommitIdOrBuilder.java @@ -0,0 +1,79 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public interface CommitIdOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.CommitId) + com.google.protobuf.MessageOrBuilder { + + /** + * 
    +   * Submitted changelist.
+   *
    + * + * int64 changelist = 1; + * @return Whether the changelist field is set. + */ + boolean hasChangelist(); + /** + * 
    +   * Submitted changelist.
+   *
    + * + * int64 changelist = 1; + * @return The changelist. + */ + long getChangelist(); + + /** + * string hash = 2; + * @return Whether the hash field is set. + */ + boolean hasHash(); + /** + * string hash = 2; + * @return The hash. + */ + java.lang.String getHash(); + /** + * string hash = 2; + * @return The bytes for hash. + */ + com.google.protobuf.ByteString + getHashBytes(); + + /** + * 
    +   * Hash of intermediate change between hash/changelist and what was tested.
+   * Not used if the build is from a commit without modifications.
+   *
    + * + * string snapshot = 3; + * @return The snapshot. + */ + java.lang.String getSnapshot(); + /** + * 
    +   * Hash of intermediate change between hash/changelist and what was tested.
+   * Not used if the build is from a commit without modifications.
+   *
    + * + * string snapshot = 3; + * @return The bytes for snapshot. + */ + com.google.protobuf.ByteString + getSnapshotBytes(); + + /** + * 
    +   * Changelist tested if the change list is not already submitted.
+   *
    + * + * int64 pending_changelist = 4; + * @return The pendingChangelist. + */ + long getPendingChangelist(); + + public org.tensorflow.proto.CommitId.KindCase getKindCase(); +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/EntryValue.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/EntryValue.java new file mode 100644 index 00000000000..0b6ce2fef52 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/EntryValue.java @@ -0,0 +1,745 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +/** + * Protobuf type {@code tensorflow.EntryValue} + */ +public final class EntryValue extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.EntryValue) + EntryValueOrBuilder { +private static final long serialVersionUID = 0L; + // Use EntryValue.newBuilder() to construct. + private EntryValue(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private EntryValue() { + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new EntryValue(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_EntryValue_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_EntryValue_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.EntryValue.class, org.tensorflow.proto.EntryValue.Builder.class); + } + + private int kindCase_ = 0; + private java.lang.Object kind_; + public enum KindCase + implements com.google.protobuf.Internal.EnumLite, + com.google.protobuf.AbstractMessage.InternalOneOfEnum { + DOUBLE_VALUE(1), + STRING_VALUE(2), + KIND_NOT_SET(0); + private final int value; + private KindCase(int value) { + this.value = value; + } + /** + * @param value The number of the enum to look for. + * @return The enum associated with the given number. + * @deprecated Use {@link #forNumber(int)} instead. + */ + @java.lang.Deprecated + public static KindCase valueOf(int value) { + return forNumber(value); + } + + public static KindCase forNumber(int value) { + switch (value) { + case 1: return DOUBLE_VALUE; + case 2: return STRING_VALUE; + case 0: return KIND_NOT_SET; + default: return null; + } + } + public int getNumber() { + return this.value; + } + }; + + public KindCase + getKindCase() { + return KindCase.forNumber( + kindCase_); + } + + public static final int DOUBLE_VALUE_FIELD_NUMBER = 1; + /** + * double double_value = 1; + * @return Whether the doubleValue field is set. + */ + @java.lang.Override + public boolean hasDoubleValue() { + return kindCase_ == 1; + } + /** + * double double_value = 1; + * @return The doubleValue. + */ + @java.lang.Override + public double getDoubleValue() { + if (kindCase_ == 1) { + return (java.lang.Double) kind_; + } + return 0D; + } + + public static final int STRING_VALUE_FIELD_NUMBER = 2; + /** + * string string_value = 2; + * @return Whether the stringValue field is set. + */ + public boolean hasStringValue() { + return kindCase_ == 2; + } + /** + * string string_value = 2; + * @return The stringValue. + */ + public java.lang.String getStringValue() { + java.lang.Object ref = ""; + if (kindCase_ == 2) { + ref = kind_; + } + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + if (kindCase_ == 2) { + kind_ = s; + } + return s; + } + } + /** + * string string_value = 2; + * @return The bytes for stringValue. + */ + public com.google.protobuf.ByteString + getStringValueBytes() { + java.lang.Object ref = ""; + if (kindCase_ == 2) { + ref = kind_; + } + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + if (kindCase_ == 2) { + kind_ = b; + } + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (kindCase_ == 1) { + output.writeDouble( + 1, (double)((java.lang.Double) kind_)); + } + if (kindCase_ == 2) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 2, kind_); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (kindCase_ == 1) { + size += com.google.protobuf.CodedOutputStream + .computeDoubleSize( + 1, (double)((java.lang.Double) kind_)); + } + if (kindCase_ == 2) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(2, kind_); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.EntryValue)) { + return super.equals(obj); + } + org.tensorflow.proto.EntryValue other = (org.tensorflow.proto.EntryValue) obj; + + if (!getKindCase().equals(other.getKindCase())) return false; + switch (kindCase_) { + case 1: + if (java.lang.Double.doubleToLongBits(getDoubleValue()) + != java.lang.Double.doubleToLongBits( + other.getDoubleValue())) return false; + break; + case 2: + if (!getStringValue() + .equals(other.getStringValue())) return false; + break; + case 0: + default: + } + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + switch (kindCase_) { + case 1: + hash = (37 * hash) + DOUBLE_VALUE_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + java.lang.Double.doubleToLongBits(getDoubleValue())); + break; + case 2: + hash = (37 * hash) + STRING_VALUE_FIELD_NUMBER; + hash = (53 * hash) + getStringValue().hashCode(); + break; + case 0: + default: + } + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.EntryValue parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.EntryValue parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.EntryValue parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.EntryValue parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.EntryValue parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.EntryValue parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.EntryValue parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.EntryValue parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.EntryValue parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.EntryValue parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.EntryValue parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.EntryValue parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.EntryValue prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * Protobuf type {@code tensorflow.EntryValue} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.EntryValue) + org.tensorflow.proto.EntryValueOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_EntryValue_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_EntryValue_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.EntryValue.class, org.tensorflow.proto.EntryValue.Builder.class); + } + + // Construct using org.tensorflow.proto.EntryValue.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + kindCase_ = 0; + kind_ = null; + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_EntryValue_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.EntryValue getDefaultInstanceForType() { + return org.tensorflow.proto.EntryValue.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.EntryValue build() { + org.tensorflow.proto.EntryValue result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.EntryValue buildPartial() { + org.tensorflow.proto.EntryValue result = new org.tensorflow.proto.EntryValue(this); + if (kindCase_ == 1) { + result.kind_ = kind_; + } + if (kindCase_ == 2) { + result.kind_ = kind_; + } + result.kindCase_ = kindCase_; + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.EntryValue) { + return mergeFrom((org.tensorflow.proto.EntryValue)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.EntryValue other) { + if (other == org.tensorflow.proto.EntryValue.getDefaultInstance()) return this; + switch (other.getKindCase()) { + case DOUBLE_VALUE: { + setDoubleValue(other.getDoubleValue()); + break; + } + case STRING_VALUE: { + kindCase_ = 2; + kind_ = other.kind_; + onChanged(); + break; + } + case KIND_NOT_SET: { + break; + } + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 9: { + kind_ = input.readDouble(); + kindCase_ = 1; + break; + } // case 9 + case 18: { + java.lang.String s = input.readStringRequireUtf8(); + kindCase_ = 2; + kind_ = s; + break; + } // case 18 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + private int kindCase_ = 0; + private java.lang.Object kind_; + public KindCase + getKindCase() { + return KindCase.forNumber( + kindCase_); + } + + public Builder clearKind() { + kindCase_ = 0; + kind_ = null; + onChanged(); + return this; + } + + + /** + * double double_value = 1; + * @return Whether the doubleValue field is set. + */ + public boolean hasDoubleValue() { + return kindCase_ == 1; + } + /** + * double double_value = 1; + * @return The doubleValue. + */ + public double getDoubleValue() { + if (kindCase_ == 1) { + return (java.lang.Double) kind_; + } + return 0D; + } + /** + * double double_value = 1; + * @param value The doubleValue to set. + * @return This builder for chaining. + */ + public Builder setDoubleValue(double value) { + kindCase_ = 1; + kind_ = value; + onChanged(); + return this; + } + /** + * double double_value = 1; + * @return This builder for chaining. + */ + public Builder clearDoubleValue() { + if (kindCase_ == 1) { + kindCase_ = 0; + kind_ = null; + onChanged(); + } + return this; + } + + /** + * string string_value = 2; + * @return Whether the stringValue field is set. + */ + @java.lang.Override + public boolean hasStringValue() { + return kindCase_ == 2; + } + /** + * string string_value = 2; + * @return The stringValue. + */ + @java.lang.Override + public java.lang.String getStringValue() { + java.lang.Object ref = ""; + if (kindCase_ == 2) { + ref = kind_; + } + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + if (kindCase_ == 2) { + kind_ = s; + } + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * string string_value = 2; + * @return The bytes for stringValue. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getStringValueBytes() { + java.lang.Object ref = ""; + if (kindCase_ == 2) { + ref = kind_; + } + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + if (kindCase_ == 2) { + kind_ = b; + } + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * string string_value = 2; + * @param value The stringValue to set. + * @return This builder for chaining. + */ + public Builder setStringValue( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + kindCase_ = 2; + kind_ = value; + onChanged(); + return this; + } + /** + * string string_value = 2; + * @return This builder for chaining. + */ + public Builder clearStringValue() { + if (kindCase_ == 2) { + kindCase_ = 0; + kind_ = null; + onChanged(); + } + return this; + } + /** + * string string_value = 2; + * @param value The bytes for stringValue to set. + * @return This builder for chaining. + */ + public Builder setStringValueBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + kindCase_ = 2; + kind_ = value; + onChanged(); + return this; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.EntryValue) + } + + // @@protoc_insertion_point(class_scope:tensorflow.EntryValue) + private static final org.tensorflow.proto.EntryValue DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.EntryValue(); + } + + public static org.tensorflow.proto.EntryValue getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public EntryValue parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.EntryValue getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + +} + diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/EntryValueOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/EntryValueOrBuilder.java new file mode 100644 index 00000000000..6338554d477 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/EntryValueOrBuilder.java @@ -0,0 +1,39 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public interface EntryValueOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.EntryValue) + com.google.protobuf.MessageOrBuilder { + + /** + * double double_value = 1; + * @return Whether the doubleValue field is set. + */ + boolean hasDoubleValue(); + /** + * double double_value = 1; + * @return The doubleValue. + */ + double getDoubleValue(); + + /** + * string string_value = 2; + * @return Whether the stringValue field is set. + */ + boolean hasStringValue(); + /** + * string string_value = 2; + * @return The stringValue. + */ + java.lang.String getStringValue(); + /** + * string string_value = 2; + * @return The bytes for stringValue. + */ + com.google.protobuf.ByteString + getStringValueBytes(); + + public org.tensorflow.proto.EntryValue.KindCase getKindCase(); +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/GPUInfo.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/GPUInfo.java new file mode 100644 index 00000000000..858f216fb45 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/GPUInfo.java @@ -0,0 +1,896 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +/** + * Protobuf type {@code tensorflow.GPUInfo} + */ +public final class GPUInfo extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.GPUInfo) + GPUInfoOrBuilder { +private static final long serialVersionUID = 0L; + // Use GPUInfo.newBuilder() to construct. + private GPUInfo(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private GPUInfo() { + model_ = ""; + uuid_ = ""; + busId_ = ""; + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new GPUInfo(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_GPUInfo_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_GPUInfo_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.GPUInfo.class, org.tensorflow.proto.GPUInfo.Builder.class); + } + + public static final int MODEL_FIELD_NUMBER = 1; + private volatile java.lang.Object model_; + /** + * 
    +   * e.g. "Tesla K40c"
+   *
    + * + * string model = 1; + * @return The model. + */ + @java.lang.Override + public java.lang.String getModel() { + java.lang.Object ref = model_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + model_ = s; + return s; + } + } + /** + * 
    +   * e.g. "Tesla K40c"
+   *
    + * + * string model = 1; + * @return The bytes for model. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getModelBytes() { + java.lang.Object ref = model_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + model_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int UUID_FIELD_NUMBER = 2; + private volatile java.lang.Object uuid_; + /** + * 
    +   * Final entry in output of "nvidia-smi -L"
+   *
    + * + * string uuid = 2; + * @return The uuid. + */ + @java.lang.Override + public java.lang.String getUuid() { + java.lang.Object ref = uuid_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + uuid_ = s; + return s; + } + } + /** + * 
    +   * Final entry in output of "nvidia-smi -L"
+   *
    + * + * string uuid = 2; + * @return The bytes for uuid. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getUuidBytes() { + java.lang.Object ref = uuid_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + uuid_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int BUS_ID_FIELD_NUMBER = 3; + private volatile java.lang.Object busId_; + /** + * 
    +   * e.g. "0000:04:00.0"
+   *
    + * + * string bus_id = 3; + * @return The busId. + */ + @java.lang.Override + public java.lang.String getBusId() { + java.lang.Object ref = busId_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + busId_ = s; + return s; + } + } + /** + * 
    +   * e.g. "0000:04:00.0"
+   *
    + * + * string bus_id = 3; + * @return The bytes for busId. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getBusIdBytes() { + java.lang.Object ref = busId_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + busId_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(model_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 1, model_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(uuid_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 2, uuid_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(busId_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 3, busId_); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(model_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, model_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(uuid_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(2, uuid_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(busId_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(3, busId_); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.GPUInfo)) { + return super.equals(obj); + } + org.tensorflow.proto.GPUInfo other = (org.tensorflow.proto.GPUInfo) obj; + + if (!getModel() + .equals(other.getModel())) return false; + if (!getUuid() + .equals(other.getUuid())) return false; + if (!getBusId() + .equals(other.getBusId())) return false; + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + MODEL_FIELD_NUMBER; + hash = (53 * hash) + getModel().hashCode(); + hash = (37 * hash) + UUID_FIELD_NUMBER; + hash = (53 * hash) + getUuid().hashCode(); + hash = (37 * hash) + BUS_ID_FIELD_NUMBER; + hash = (53 * hash) + getBusId().hashCode(); + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.GPUInfo parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.GPUInfo parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.GPUInfo parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.GPUInfo parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.GPUInfo parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.GPUInfo parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.GPUInfo parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.GPUInfo parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.GPUInfo parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.GPUInfo parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.GPUInfo parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.GPUInfo parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.GPUInfo prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * Protobuf type {@code tensorflow.GPUInfo} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.GPUInfo) + org.tensorflow.proto.GPUInfoOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_GPUInfo_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_GPUInfo_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.GPUInfo.class, org.tensorflow.proto.GPUInfo.Builder.class); + } + + // Construct using org.tensorflow.proto.GPUInfo.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + model_ = ""; + + uuid_ = ""; + + busId_ = ""; + + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_GPUInfo_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.GPUInfo getDefaultInstanceForType() { + return org.tensorflow.proto.GPUInfo.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.GPUInfo build() { + org.tensorflow.proto.GPUInfo result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.GPUInfo buildPartial() { + org.tensorflow.proto.GPUInfo result = new org.tensorflow.proto.GPUInfo(this); + result.model_ = model_; + result.uuid_ = uuid_; + result.busId_ = busId_; + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.GPUInfo) { + return mergeFrom((org.tensorflow.proto.GPUInfo)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.GPUInfo other) { + if (other == org.tensorflow.proto.GPUInfo.getDefaultInstance()) return this; + if (!other.getModel().isEmpty()) { + model_ = other.model_; + onChanged(); + } + if (!other.getUuid().isEmpty()) { + uuid_ = other.uuid_; + onChanged(); + } + if (!other.getBusId().isEmpty()) { + busId_ = other.busId_; + onChanged(); + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 10: { + model_ = input.readStringRequireUtf8(); + + break; + } // case 10 + case 18: { + uuid_ = input.readStringRequireUtf8(); + + break; + } // case 18 + case 26: { + busId_ = input.readStringRequireUtf8(); + + break; + } // case 26 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + + private java.lang.Object model_ = ""; + /** + * 
    +     * e.g. "Tesla K40c"
+     *
    + * + * string model = 1; + * @return The model. + */ + public java.lang.String getModel() { + java.lang.Object ref = model_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + model_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * e.g. "Tesla K40c"
+     *
    + * + * string model = 1; + * @return The bytes for model. + */ + public com.google.protobuf.ByteString + getModelBytes() { + java.lang.Object ref = model_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + model_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * e.g. "Tesla K40c"
+     *
    + * + * string model = 1; + * @param value The model to set. + * @return This builder for chaining. + */ + public Builder setModel( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + model_ = value; + onChanged(); + return this; + } + /** + * 
    +     * e.g. "Tesla K40c"
+     *
    + * + * string model = 1; + * @return This builder for chaining. + */ + public Builder clearModel() { + + model_ = getDefaultInstance().getModel(); + onChanged(); + return this; + } + /** + * 
    +     * e.g. "Tesla K40c"
+     *
    + * + * string model = 1; + * @param value The bytes for model to set. + * @return This builder for chaining. + */ + public Builder setModelBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + model_ = value; + onChanged(); + return this; + } + + private java.lang.Object uuid_ = ""; + /** + * 
    +     * Final entry in output of "nvidia-smi -L"
+     *
    + * + * string uuid = 2; + * @return The uuid. + */ + public java.lang.String getUuid() { + java.lang.Object ref = uuid_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + uuid_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * Final entry in output of "nvidia-smi -L"
+     *
    + * + * string uuid = 2; + * @return The bytes for uuid. + */ + public com.google.protobuf.ByteString + getUuidBytes() { + java.lang.Object ref = uuid_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + uuid_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * Final entry in output of "nvidia-smi -L"
+     *
    + * + * string uuid = 2; + * @param value The uuid to set. + * @return This builder for chaining. + */ + public Builder setUuid( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + uuid_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Final entry in output of "nvidia-smi -L"
+     *
    + * + * string uuid = 2; + * @return This builder for chaining. + */ + public Builder clearUuid() { + + uuid_ = getDefaultInstance().getUuid(); + onChanged(); + return this; + } + /** + * 
    +     * Final entry in output of "nvidia-smi -L"
+     *
    + * + * string uuid = 2; + * @param value The bytes for uuid to set. + * @return This builder for chaining. + */ + public Builder setUuidBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + uuid_ = value; + onChanged(); + return this; + } + + private java.lang.Object busId_ = ""; + /** + * 
    +     * e.g. "0000:04:00.0"
+     *
    + * + * string bus_id = 3; + * @return The busId. + */ + public java.lang.String getBusId() { + java.lang.Object ref = busId_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + busId_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * e.g. "0000:04:00.0"
+     *
    + * + * string bus_id = 3; + * @return The bytes for busId. + */ + public com.google.protobuf.ByteString + getBusIdBytes() { + java.lang.Object ref = busId_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + busId_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * e.g. "0000:04:00.0"
+     *
    + * + * string bus_id = 3; + * @param value The busId to set. + * @return This builder for chaining. + */ + public Builder setBusId( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + busId_ = value; + onChanged(); + return this; + } + /** + * 
    +     * e.g. "0000:04:00.0"
+     *
    + * + * string bus_id = 3; + * @return This builder for chaining. + */ + public Builder clearBusId() { + + busId_ = getDefaultInstance().getBusId(); + onChanged(); + return this; + } + /** + * 
    +     * e.g. "0000:04:00.0"
+     *
    + * + * string bus_id = 3; + * @param value The bytes for busId to set. + * @return This builder for chaining. + */ + public Builder setBusIdBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + busId_ = value; + onChanged(); + return this; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.GPUInfo) + } + + // @@protoc_insertion_point(class_scope:tensorflow.GPUInfo) + private static final org.tensorflow.proto.GPUInfo DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.GPUInfo(); + } + + public static org.tensorflow.proto.GPUInfo getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public GPUInfo parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.GPUInfo getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + +} + diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/GPUInfoOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/GPUInfoOrBuilder.java new file mode 100644 index 00000000000..02d2cc61740 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/GPUInfoOrBuilder.java @@ -0,0 +1,69 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public interface GPUInfoOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.GPUInfo) + com.google.protobuf.MessageOrBuilder { + + /** + * 
    +   * e.g. "Tesla K40c"
+   *
    + * + * string model = 1; + * @return The model. + */ + java.lang.String getModel(); + /** + * 
    +   * e.g. "Tesla K40c"
+   *
    + * + * string model = 1; + * @return The bytes for model. + */ + com.google.protobuf.ByteString + getModelBytes(); + + /** + * 
    +   * Final entry in output of "nvidia-smi -L"
+   *
    + * + * string uuid = 2; + * @return The uuid. + */ + java.lang.String getUuid(); + /** + * 
    +   * Final entry in output of "nvidia-smi -L"
+   *
    + * + * string uuid = 2; + * @return The bytes for uuid. + */ + com.google.protobuf.ByteString + getUuidBytes(); + + /** + * 
    +   * e.g. "0000:04:00.0"
+   *
    + * + * string bus_id = 3; + * @return The busId. + */ + java.lang.String getBusId(); + /** + * 
    +   * e.g. "0000:04:00.0"
+   *
    + * + * string bus_id = 3; + * @return The bytes for busId. + */ + com.google.protobuf.ByteString + getBusIdBytes(); +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MachineConfiguration.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MachineConfiguration.java new file mode 100644 index 00000000000..6dbc6ce6f3b --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MachineConfiguration.java @@ -0,0 +1,2257 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +/** + * Protobuf type {@code tensorflow.MachineConfiguration} + */ +public final class MachineConfiguration extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.MachineConfiguration) + MachineConfigurationOrBuilder { +private static final long serialVersionUID = 0L; + // Use MachineConfiguration.newBuilder() to construct. + private MachineConfiguration(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private MachineConfiguration() { + hostname_ = ""; + serialIdentifier_ = ""; + deviceInfo_ = java.util.Collections.emptyList(); + availableDeviceInfo_ = java.util.Collections.emptyList(); + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new MachineConfiguration(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MachineConfiguration_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MachineConfiguration_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.MachineConfiguration.class, org.tensorflow.proto.MachineConfiguration.Builder.class); + } + + public static final int HOSTNAME_FIELD_NUMBER = 1; + private volatile java.lang.Object hostname_; + /** + * 
    +   * Host name of machine that ran the benchmark.
+   *
    + * + * string hostname = 1; + * @return The hostname. + */ + @java.lang.Override + public java.lang.String getHostname() { + java.lang.Object ref = hostname_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + hostname_ = s; + return s; + } + } + /** + * 
    +   * Host name of machine that ran the benchmark.
+   *
    + * + * string hostname = 1; + * @return The bytes for hostname. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getHostnameBytes() { + java.lang.Object ref = hostname_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + hostname_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int SERIAL_IDENTIFIER_FIELD_NUMBER = 7; + private volatile java.lang.Object serialIdentifier_; + /** + * 
    +   * Unique serial number of the machine.
+   *
    + * + * string serial_identifier = 7; + * @return The serialIdentifier. + */ + @java.lang.Override + public java.lang.String getSerialIdentifier() { + java.lang.Object ref = serialIdentifier_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + serialIdentifier_ = s; + return s; + } + } + /** + * 
    +   * Unique serial number of the machine.
+   *
    + * + * string serial_identifier = 7; + * @return The bytes for serialIdentifier. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getSerialIdentifierBytes() { + java.lang.Object ref = serialIdentifier_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + serialIdentifier_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int PLATFORM_INFO_FIELD_NUMBER = 2; + private org.tensorflow.proto.PlatformInfo platformInfo_; + /** + * 
    +   * Additional platform information.
+   *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + * @return Whether the platformInfo field is set. + */ + @java.lang.Override + public boolean hasPlatformInfo() { + return platformInfo_ != null; + } + /** + * 
    +   * Additional platform information.
+   *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + * @return The platformInfo. + */ + @java.lang.Override + public org.tensorflow.proto.PlatformInfo getPlatformInfo() { + return platformInfo_ == null ? org.tensorflow.proto.PlatformInfo.getDefaultInstance() : platformInfo_; + } + /** + * 
    +   * Additional platform information.
+   *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + */ + @java.lang.Override + public org.tensorflow.proto.PlatformInfoOrBuilder getPlatformInfoOrBuilder() { + return getPlatformInfo(); + } + + public static final int CPU_INFO_FIELD_NUMBER = 3; + private org.tensorflow.proto.CPUInfo cpuInfo_; + /** + * 
    +   * CPU Information.
+   *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + * @return Whether the cpuInfo field is set. + */ + @java.lang.Override + public boolean hasCpuInfo() { + return cpuInfo_ != null; + } + /** + * 
    +   * CPU Information.
+   *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + * @return The cpuInfo. + */ + @java.lang.Override + public org.tensorflow.proto.CPUInfo getCpuInfo() { + return cpuInfo_ == null ? org.tensorflow.proto.CPUInfo.getDefaultInstance() : cpuInfo_; + } + /** + * 
    +   * CPU Information.
+   *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + */ + @java.lang.Override + public org.tensorflow.proto.CPUInfoOrBuilder getCpuInfoOrBuilder() { + return getCpuInfo(); + } + + public static final int DEVICE_INFO_FIELD_NUMBER = 4; + private java.util.List deviceInfo_; + /** + * 
    +   * Other devices that are attached and relevant (e.g. GPUInfo).
+   *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + @java.lang.Override + public java.util.List getDeviceInfoList() { + return deviceInfo_; + } + /** + * 
    +   * Other devices that are attached and relevant (e.g. GPUInfo).
+   *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + @java.lang.Override + public java.util.List + getDeviceInfoOrBuilderList() { + return deviceInfo_; + } + /** + * 
    +   * Other devices that are attached and relevant (e.g. GPUInfo).
+   *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + @java.lang.Override + public int getDeviceInfoCount() { + return deviceInfo_.size(); + } + /** + * 
    +   * Other devices that are attached and relevant (e.g. GPUInfo).
+   *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + @java.lang.Override + public com.google.protobuf.Any getDeviceInfo(int index) { + return deviceInfo_.get(index); + } + /** + * 
    +   * Other devices that are attached and relevant (e.g. GPUInfo).
+   *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + @java.lang.Override + public com.google.protobuf.AnyOrBuilder getDeviceInfoOrBuilder( + int index) { + return deviceInfo_.get(index); + } + + public static final int AVAILABLE_DEVICE_INFO_FIELD_NUMBER = 5; + private java.util.List availableDeviceInfo_; + /** + * 
    +   * Devices accessible to the test (e.g. as given by list_local_devices).
+   *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + @java.lang.Override + public java.util.List getAvailableDeviceInfoList() { + return availableDeviceInfo_; + } + /** + * 
    +   * Devices accessible to the test (e.g. as given by list_local_devices).
+   *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + @java.lang.Override + public java.util.List + getAvailableDeviceInfoOrBuilderList() { + return availableDeviceInfo_; + } + /** + * 
    +   * Devices accessible to the test (e.g. as given by list_local_devices).
+   *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + @java.lang.Override + public int getAvailableDeviceInfoCount() { + return availableDeviceInfo_.size(); + } + /** + * 
    +   * Devices accessible to the test (e.g. as given by list_local_devices).
+   *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + @java.lang.Override + public org.tensorflow.proto.AvailableDeviceInfo getAvailableDeviceInfo(int index) { + return availableDeviceInfo_.get(index); + } + /** + * 
    +   * Devices accessible to the test (e.g. as given by list_local_devices).
+   *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + @java.lang.Override + public org.tensorflow.proto.AvailableDeviceInfoOrBuilder getAvailableDeviceInfoOrBuilder( + int index) { + return availableDeviceInfo_.get(index); + } + + public static final int MEMORY_INFO_FIELD_NUMBER = 6; + private org.tensorflow.proto.MemoryInfo memoryInfo_; + /** + * .tensorflow.MemoryInfo memory_info = 6; + * @return Whether the memoryInfo field is set. + */ + @java.lang.Override + public boolean hasMemoryInfo() { + return memoryInfo_ != null; + } + /** + * .tensorflow.MemoryInfo memory_info = 6; + * @return The memoryInfo. + */ + @java.lang.Override + public org.tensorflow.proto.MemoryInfo getMemoryInfo() { + return memoryInfo_ == null ? org.tensorflow.proto.MemoryInfo.getDefaultInstance() : memoryInfo_; + } + /** + * .tensorflow.MemoryInfo memory_info = 6; + */ + @java.lang.Override + public org.tensorflow.proto.MemoryInfoOrBuilder getMemoryInfoOrBuilder() { + return getMemoryInfo(); + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(hostname_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 1, hostname_); + } + if (platformInfo_ != null) { + output.writeMessage(2, getPlatformInfo()); + } + if (cpuInfo_ != null) { + output.writeMessage(3, getCpuInfo()); + } + for (int i = 0; i < deviceInfo_.size(); i++) { + output.writeMessage(4, deviceInfo_.get(i)); + } + for (int i = 0; i < availableDeviceInfo_.size(); i++) { + output.writeMessage(5, availableDeviceInfo_.get(i)); + } + if (memoryInfo_ != null) { + output.writeMessage(6, getMemoryInfo()); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(serialIdentifier_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 7, serialIdentifier_); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(hostname_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, hostname_); + } + if (platformInfo_ != null) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(2, getPlatformInfo()); + } + if (cpuInfo_ != null) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(3, getCpuInfo()); + } + for (int i = 0; i < deviceInfo_.size(); i++) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(4, deviceInfo_.get(i)); + } + for (int i = 0; i < availableDeviceInfo_.size(); i++) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(5, availableDeviceInfo_.get(i)); + } + if (memoryInfo_ != null) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(6, getMemoryInfo()); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(serialIdentifier_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(7, serialIdentifier_); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.MachineConfiguration)) { + return super.equals(obj); + } + org.tensorflow.proto.MachineConfiguration other = (org.tensorflow.proto.MachineConfiguration) obj; + + if (!getHostname() + .equals(other.getHostname())) return false; + if (!getSerialIdentifier() + .equals(other.getSerialIdentifier())) return false; + if (hasPlatformInfo() != other.hasPlatformInfo()) return false; + if (hasPlatformInfo()) { + if (!getPlatformInfo() + .equals(other.getPlatformInfo())) return false; + } + if (hasCpuInfo() != other.hasCpuInfo()) return false; + if (hasCpuInfo()) { + if (!getCpuInfo() + .equals(other.getCpuInfo())) return false; + } + if (!getDeviceInfoList() + .equals(other.getDeviceInfoList())) return false; + if (!getAvailableDeviceInfoList() + .equals(other.getAvailableDeviceInfoList())) return false; + if (hasMemoryInfo() != other.hasMemoryInfo()) return false; + if (hasMemoryInfo()) { + if (!getMemoryInfo() + .equals(other.getMemoryInfo())) return false; + } + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + HOSTNAME_FIELD_NUMBER; + hash = (53 * hash) + getHostname().hashCode(); + hash = (37 * hash) + SERIAL_IDENTIFIER_FIELD_NUMBER; + hash = (53 * hash) + getSerialIdentifier().hashCode(); + if (hasPlatformInfo()) { + hash = (37 * hash) + PLATFORM_INFO_FIELD_NUMBER; + hash = (53 * hash) + getPlatformInfo().hashCode(); + } + if (hasCpuInfo()) { + hash = (37 * hash) + CPU_INFO_FIELD_NUMBER; + hash = (53 * hash) + getCpuInfo().hashCode(); + } + if (getDeviceInfoCount() > 0) { + hash = (37 * hash) + DEVICE_INFO_FIELD_NUMBER; + hash = (53 * hash) + getDeviceInfoList().hashCode(); + } + if (getAvailableDeviceInfoCount() > 0) { + hash = (37 * hash) + AVAILABLE_DEVICE_INFO_FIELD_NUMBER; + hash = (53 * hash) + getAvailableDeviceInfoList().hashCode(); + } + if (hasMemoryInfo()) { + hash = (37 * hash) + MEMORY_INFO_FIELD_NUMBER; + hash = (53 * hash) + getMemoryInfo().hashCode(); + } + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.MachineConfiguration parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.MachineConfiguration parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.MachineConfiguration parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.MachineConfiguration parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.MachineConfiguration parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.MachineConfiguration parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.MachineConfiguration parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.MachineConfiguration parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.MachineConfiguration parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.MachineConfiguration parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.MachineConfiguration parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.MachineConfiguration parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.MachineConfiguration prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * Protobuf type {@code tensorflow.MachineConfiguration} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.MachineConfiguration) + org.tensorflow.proto.MachineConfigurationOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MachineConfiguration_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MachineConfiguration_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.MachineConfiguration.class, org.tensorflow.proto.MachineConfiguration.Builder.class); + } + + // Construct using org.tensorflow.proto.MachineConfiguration.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + hostname_ = ""; + + serialIdentifier_ = ""; + + if (platformInfoBuilder_ == null) { + platformInfo_ = null; + } else { + platformInfo_ = null; + platformInfoBuilder_ = null; + } + if (cpuInfoBuilder_ == null) { + cpuInfo_ = null; + } else { + cpuInfo_ = null; + cpuInfoBuilder_ = null; + } + if (deviceInfoBuilder_ == null) { + deviceInfo_ = java.util.Collections.emptyList(); + } else { + deviceInfo_ = null; + deviceInfoBuilder_.clear(); + } + bitField0_ = (bitField0_ & ~0x00000001); + if (availableDeviceInfoBuilder_ == null) { + availableDeviceInfo_ = java.util.Collections.emptyList(); + } else { + availableDeviceInfo_ = null; + availableDeviceInfoBuilder_.clear(); + } + bitField0_ = (bitField0_ & ~0x00000002); + if (memoryInfoBuilder_ == null) { + memoryInfo_ = null; + } else { + memoryInfo_ = null; + memoryInfoBuilder_ = null; + } + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MachineConfiguration_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.MachineConfiguration getDefaultInstanceForType() { + return org.tensorflow.proto.MachineConfiguration.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.MachineConfiguration build() { + org.tensorflow.proto.MachineConfiguration result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.MachineConfiguration buildPartial() { + org.tensorflow.proto.MachineConfiguration result = new org.tensorflow.proto.MachineConfiguration(this); + int from_bitField0_ = bitField0_; + result.hostname_ = hostname_; + result.serialIdentifier_ = serialIdentifier_; + if (platformInfoBuilder_ == null) { + result.platformInfo_ = platformInfo_; + } else { + result.platformInfo_ = platformInfoBuilder_.build(); + } + if (cpuInfoBuilder_ == null) { + result.cpuInfo_ = cpuInfo_; + } else { + result.cpuInfo_ = cpuInfoBuilder_.build(); + } + if (deviceInfoBuilder_ == null) { + if (((bitField0_ & 0x00000001) != 0)) { + deviceInfo_ = java.util.Collections.unmodifiableList(deviceInfo_); + bitField0_ = (bitField0_ & ~0x00000001); + } + result.deviceInfo_ = deviceInfo_; + } else { + result.deviceInfo_ = deviceInfoBuilder_.build(); + } + if (availableDeviceInfoBuilder_ == null) { + if (((bitField0_ & 0x00000002) != 0)) { + availableDeviceInfo_ = java.util.Collections.unmodifiableList(availableDeviceInfo_); + bitField0_ = (bitField0_ & ~0x00000002); + } + result.availableDeviceInfo_ = availableDeviceInfo_; + } else { + result.availableDeviceInfo_ = availableDeviceInfoBuilder_.build(); + } + if (memoryInfoBuilder_ == null) { + result.memoryInfo_ = memoryInfo_; + } else { + result.memoryInfo_ = memoryInfoBuilder_.build(); + } + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.MachineConfiguration) { + return mergeFrom((org.tensorflow.proto.MachineConfiguration)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.MachineConfiguration other) { + if (other == org.tensorflow.proto.MachineConfiguration.getDefaultInstance()) return this; + if (!other.getHostname().isEmpty()) { + hostname_ = other.hostname_; + onChanged(); + } + if (!other.getSerialIdentifier().isEmpty()) { + serialIdentifier_ = other.serialIdentifier_; + onChanged(); + } + if (other.hasPlatformInfo()) { + mergePlatformInfo(other.getPlatformInfo()); + } + if (other.hasCpuInfo()) { + mergeCpuInfo(other.getCpuInfo()); + } + if (deviceInfoBuilder_ == null) { + if (!other.deviceInfo_.isEmpty()) { + if (deviceInfo_.isEmpty()) { + deviceInfo_ = other.deviceInfo_; + bitField0_ = (bitField0_ & ~0x00000001); + } else { + ensureDeviceInfoIsMutable(); + deviceInfo_.addAll(other.deviceInfo_); + } + onChanged(); + } + } else { + if (!other.deviceInfo_.isEmpty()) { + if (deviceInfoBuilder_.isEmpty()) { + deviceInfoBuilder_.dispose(); + deviceInfoBuilder_ = null; + deviceInfo_ = other.deviceInfo_; + bitField0_ = (bitField0_ & ~0x00000001); + deviceInfoBuilder_ = + com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ? + getDeviceInfoFieldBuilder() : null; + } else { + deviceInfoBuilder_.addAllMessages(other.deviceInfo_); + } + } + } + if (availableDeviceInfoBuilder_ == null) { + if (!other.availableDeviceInfo_.isEmpty()) { + if (availableDeviceInfo_.isEmpty()) { + availableDeviceInfo_ = other.availableDeviceInfo_; + bitField0_ = (bitField0_ & ~0x00000002); + } else { + ensureAvailableDeviceInfoIsMutable(); + availableDeviceInfo_.addAll(other.availableDeviceInfo_); + } + onChanged(); + } + } else { + if (!other.availableDeviceInfo_.isEmpty()) { + if (availableDeviceInfoBuilder_.isEmpty()) { + availableDeviceInfoBuilder_.dispose(); + availableDeviceInfoBuilder_ = null; + availableDeviceInfo_ = other.availableDeviceInfo_; + bitField0_ = (bitField0_ & ~0x00000002); + availableDeviceInfoBuilder_ = + com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ? + getAvailableDeviceInfoFieldBuilder() : null; + } else { + availableDeviceInfoBuilder_.addAllMessages(other.availableDeviceInfo_); + } + } + } + if (other.hasMemoryInfo()) { + mergeMemoryInfo(other.getMemoryInfo()); + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 10: { + hostname_ = input.readStringRequireUtf8(); + + break; + } // case 10 + case 18: { + input.readMessage( + getPlatformInfoFieldBuilder().getBuilder(), + extensionRegistry); + + break; + } // case 18 + case 26: { + input.readMessage( + getCpuInfoFieldBuilder().getBuilder(), + extensionRegistry); + + break; + } // case 26 + case 34: { + com.google.protobuf.Any m = + input.readMessage( + com.google.protobuf.Any.parser(), + extensionRegistry); + if (deviceInfoBuilder_ == null) { + ensureDeviceInfoIsMutable(); + deviceInfo_.add(m); + } else { + deviceInfoBuilder_.addMessage(m); + } + break; + } // case 34 + case 42: { + org.tensorflow.proto.AvailableDeviceInfo m = + input.readMessage( + org.tensorflow.proto.AvailableDeviceInfo.parser(), + extensionRegistry); + if (availableDeviceInfoBuilder_ == null) { + ensureAvailableDeviceInfoIsMutable(); + availableDeviceInfo_.add(m); + } else { + availableDeviceInfoBuilder_.addMessage(m); + } + break; + } // case 42 + case 50: { + input.readMessage( + getMemoryInfoFieldBuilder().getBuilder(), + extensionRegistry); + + break; + } // case 50 + case 58: { + serialIdentifier_ = input.readStringRequireUtf8(); + + break; + } // case 58 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + private int bitField0_; + + private java.lang.Object hostname_ = ""; + /** + * 
    +     * Host name of machine that ran the benchmark.
+     *
    + * + * string hostname = 1; + * @return The hostname. + */ + public java.lang.String getHostname() { + java.lang.Object ref = hostname_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + hostname_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * Host name of machine that ran the benchmark.
+     *
    + * + * string hostname = 1; + * @return The bytes for hostname. + */ + public com.google.protobuf.ByteString + getHostnameBytes() { + java.lang.Object ref = hostname_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + hostname_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * Host name of machine that ran the benchmark.
+     *
    + * + * string hostname = 1; + * @param value The hostname to set. + * @return This builder for chaining. + */ + public Builder setHostname( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + hostname_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Host name of machine that ran the benchmark.
+     *
    + * + * string hostname = 1; + * @return This builder for chaining. + */ + public Builder clearHostname() { + + hostname_ = getDefaultInstance().getHostname(); + onChanged(); + return this; + } + /** + * 
    +     * Host name of machine that ran the benchmark.
+     *
    + * + * string hostname = 1; + * @param value The bytes for hostname to set. + * @return This builder for chaining. + */ + public Builder setHostnameBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + hostname_ = value; + onChanged(); + return this; + } + + private java.lang.Object serialIdentifier_ = ""; + /** + * 
    +     * Unique serial number of the machine.
+     *
    + * + * string serial_identifier = 7; + * @return The serialIdentifier. + */ + public java.lang.String getSerialIdentifier() { + java.lang.Object ref = serialIdentifier_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + serialIdentifier_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * Unique serial number of the machine.
+     *
    + * + * string serial_identifier = 7; + * @return The bytes for serialIdentifier. + */ + public com.google.protobuf.ByteString + getSerialIdentifierBytes() { + java.lang.Object ref = serialIdentifier_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + serialIdentifier_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * Unique serial number of the machine.
+     *
    + * + * string serial_identifier = 7; + * @param value The serialIdentifier to set. + * @return This builder for chaining. + */ + public Builder setSerialIdentifier( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + serialIdentifier_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Unique serial number of the machine.
+     *
    + * + * string serial_identifier = 7; + * @return This builder for chaining. + */ + public Builder clearSerialIdentifier() { + + serialIdentifier_ = getDefaultInstance().getSerialIdentifier(); + onChanged(); + return this; + } + /** + * 
    +     * Unique serial number of the machine.
+     *
    + * + * string serial_identifier = 7; + * @param value The bytes for serialIdentifier to set. + * @return This builder for chaining. + */ + public Builder setSerialIdentifierBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + serialIdentifier_ = value; + onChanged(); + return this; + } + + private org.tensorflow.proto.PlatformInfo platformInfo_; + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.PlatformInfo, org.tensorflow.proto.PlatformInfo.Builder, org.tensorflow.proto.PlatformInfoOrBuilder> platformInfoBuilder_; + /** + * 
    +     * Additional platform information.
+     *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + * @return Whether the platformInfo field is set. + */ + public boolean hasPlatformInfo() { + return platformInfoBuilder_ != null || platformInfo_ != null; + } + /** + * 
    +     * Additional platform information.
+     *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + * @return The platformInfo. + */ + public org.tensorflow.proto.PlatformInfo getPlatformInfo() { + if (platformInfoBuilder_ == null) { + return platformInfo_ == null ? org.tensorflow.proto.PlatformInfo.getDefaultInstance() : platformInfo_; + } else { + return platformInfoBuilder_.getMessage(); + } + } + /** + * 
    +     * Additional platform information.
+     *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + */ + public Builder setPlatformInfo(org.tensorflow.proto.PlatformInfo value) { + if (platformInfoBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + platformInfo_ = value; + onChanged(); + } else { + platformInfoBuilder_.setMessage(value); + } + + return this; + } + /** + * 
    +     * Additional platform information.
+     *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + */ + public Builder setPlatformInfo( + org.tensorflow.proto.PlatformInfo.Builder builderForValue) { + if (platformInfoBuilder_ == null) { + platformInfo_ = builderForValue.build(); + onChanged(); + } else { + platformInfoBuilder_.setMessage(builderForValue.build()); + } + + return this; + } + /** + * 
    +     * Additional platform information.
+     *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + */ + public Builder mergePlatformInfo(org.tensorflow.proto.PlatformInfo value) { + if (platformInfoBuilder_ == null) { + if (platformInfo_ != null) { + platformInfo_ = + org.tensorflow.proto.PlatformInfo.newBuilder(platformInfo_).mergeFrom(value).buildPartial(); + } else { + platformInfo_ = value; + } + onChanged(); + } else { + platformInfoBuilder_.mergeFrom(value); + } + + return this; + } + /** + * 
    +     * Additional platform information.
+     *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + */ + public Builder clearPlatformInfo() { + if (platformInfoBuilder_ == null) { + platformInfo_ = null; + onChanged(); + } else { + platformInfo_ = null; + platformInfoBuilder_ = null; + } + + return this; + } + /** + * 
    +     * Additional platform information.
+     *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + */ + public org.tensorflow.proto.PlatformInfo.Builder getPlatformInfoBuilder() { + + onChanged(); + return getPlatformInfoFieldBuilder().getBuilder(); + } + /** + * 
    +     * Additional platform information.
+     *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + */ + public org.tensorflow.proto.PlatformInfoOrBuilder getPlatformInfoOrBuilder() { + if (platformInfoBuilder_ != null) { + return platformInfoBuilder_.getMessageOrBuilder(); + } else { + return platformInfo_ == null ? + org.tensorflow.proto.PlatformInfo.getDefaultInstance() : platformInfo_; + } + } + /** + * 
    +     * Additional platform information.
+     *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + */ + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.PlatformInfo, org.tensorflow.proto.PlatformInfo.Builder, org.tensorflow.proto.PlatformInfoOrBuilder> + getPlatformInfoFieldBuilder() { + if (platformInfoBuilder_ == null) { + platformInfoBuilder_ = new com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.PlatformInfo, org.tensorflow.proto.PlatformInfo.Builder, org.tensorflow.proto.PlatformInfoOrBuilder>( + getPlatformInfo(), + getParentForChildren(), + isClean()); + platformInfo_ = null; + } + return platformInfoBuilder_; + } + + private org.tensorflow.proto.CPUInfo cpuInfo_; + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.CPUInfo, org.tensorflow.proto.CPUInfo.Builder, org.tensorflow.proto.CPUInfoOrBuilder> cpuInfoBuilder_; + /** + * 
    +     * CPU Information.
+     *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + * @return Whether the cpuInfo field is set. + */ + public boolean hasCpuInfo() { + return cpuInfoBuilder_ != null || cpuInfo_ != null; + } + /** + * 
    +     * CPU Information.
+     *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + * @return The cpuInfo. + */ + public org.tensorflow.proto.CPUInfo getCpuInfo() { + if (cpuInfoBuilder_ == null) { + return cpuInfo_ == null ? org.tensorflow.proto.CPUInfo.getDefaultInstance() : cpuInfo_; + } else { + return cpuInfoBuilder_.getMessage(); + } + } + /** + * 
    +     * CPU Information.
+     *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + */ + public Builder setCpuInfo(org.tensorflow.proto.CPUInfo value) { + if (cpuInfoBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + cpuInfo_ = value; + onChanged(); + } else { + cpuInfoBuilder_.setMessage(value); + } + + return this; + } + /** + * 
    +     * CPU Information.
+     *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + */ + public Builder setCpuInfo( + org.tensorflow.proto.CPUInfo.Builder builderForValue) { + if (cpuInfoBuilder_ == null) { + cpuInfo_ = builderForValue.build(); + onChanged(); + } else { + cpuInfoBuilder_.setMessage(builderForValue.build()); + } + + return this; + } + /** + * 
    +     * CPU Information.
+     *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + */ + public Builder mergeCpuInfo(org.tensorflow.proto.CPUInfo value) { + if (cpuInfoBuilder_ == null) { + if (cpuInfo_ != null) { + cpuInfo_ = + org.tensorflow.proto.CPUInfo.newBuilder(cpuInfo_).mergeFrom(value).buildPartial(); + } else { + cpuInfo_ = value; + } + onChanged(); + } else { + cpuInfoBuilder_.mergeFrom(value); + } + + return this; + } + /** + * 
    +     * CPU Information.
+     *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + */ + public Builder clearCpuInfo() { + if (cpuInfoBuilder_ == null) { + cpuInfo_ = null; + onChanged(); + } else { + cpuInfo_ = null; + cpuInfoBuilder_ = null; + } + + return this; + } + /** + * 
    +     * CPU Information.
+     *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + */ + public org.tensorflow.proto.CPUInfo.Builder getCpuInfoBuilder() { + + onChanged(); + return getCpuInfoFieldBuilder().getBuilder(); + } + /** + * 
    +     * CPU Information.
+     *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + */ + public org.tensorflow.proto.CPUInfoOrBuilder getCpuInfoOrBuilder() { + if (cpuInfoBuilder_ != null) { + return cpuInfoBuilder_.getMessageOrBuilder(); + } else { + return cpuInfo_ == null ? + org.tensorflow.proto.CPUInfo.getDefaultInstance() : cpuInfo_; + } + } + /** + * 
    +     * CPU Information.
+     *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + */ + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.CPUInfo, org.tensorflow.proto.CPUInfo.Builder, org.tensorflow.proto.CPUInfoOrBuilder> + getCpuInfoFieldBuilder() { + if (cpuInfoBuilder_ == null) { + cpuInfoBuilder_ = new com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.CPUInfo, org.tensorflow.proto.CPUInfo.Builder, org.tensorflow.proto.CPUInfoOrBuilder>( + getCpuInfo(), + getParentForChildren(), + isClean()); + cpuInfo_ = null; + } + return cpuInfoBuilder_; + } + + private java.util.List deviceInfo_ = + java.util.Collections.emptyList(); + private void ensureDeviceInfoIsMutable() { + if (!((bitField0_ & 0x00000001) != 0)) { + deviceInfo_ = new java.util.ArrayList(deviceInfo_); + bitField0_ |= 0x00000001; + } + } + + private com.google.protobuf.RepeatedFieldBuilderV3< + com.google.protobuf.Any, com.google.protobuf.Any.Builder, com.google.protobuf.AnyOrBuilder> deviceInfoBuilder_; + + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public java.util.List getDeviceInfoList() { + if (deviceInfoBuilder_ == null) { + return java.util.Collections.unmodifiableList(deviceInfo_); + } else { + return deviceInfoBuilder_.getMessageList(); + } + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public int getDeviceInfoCount() { + if (deviceInfoBuilder_ == null) { + return deviceInfo_.size(); + } else { + return deviceInfoBuilder_.getCount(); + } + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public com.google.protobuf.Any getDeviceInfo(int index) { + if (deviceInfoBuilder_ == null) { + return deviceInfo_.get(index); + } else { + return deviceInfoBuilder_.getMessage(index); + } + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public Builder setDeviceInfo( + int index, com.google.protobuf.Any value) { + if (deviceInfoBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureDeviceInfoIsMutable(); + deviceInfo_.set(index, value); + onChanged(); + } else { + deviceInfoBuilder_.setMessage(index, value); + } + return this; + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public Builder setDeviceInfo( + int index, com.google.protobuf.Any.Builder builderForValue) { + if (deviceInfoBuilder_ == null) { + ensureDeviceInfoIsMutable(); + deviceInfo_.set(index, builderForValue.build()); + onChanged(); + } else { + deviceInfoBuilder_.setMessage(index, builderForValue.build()); + } + return this; + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public Builder addDeviceInfo(com.google.protobuf.Any value) { + if (deviceInfoBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureDeviceInfoIsMutable(); + deviceInfo_.add(value); + onChanged(); + } else { + deviceInfoBuilder_.addMessage(value); + } + return this; + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public Builder addDeviceInfo( + int index, com.google.protobuf.Any value) { + if (deviceInfoBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureDeviceInfoIsMutable(); + deviceInfo_.add(index, value); + onChanged(); + } else { + deviceInfoBuilder_.addMessage(index, value); + } + return this; + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public Builder addDeviceInfo( + com.google.protobuf.Any.Builder builderForValue) { + if (deviceInfoBuilder_ == null) { + ensureDeviceInfoIsMutable(); + deviceInfo_.add(builderForValue.build()); + onChanged(); + } else { + deviceInfoBuilder_.addMessage(builderForValue.build()); + } + return this; + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public Builder addDeviceInfo( + int index, com.google.protobuf.Any.Builder builderForValue) { + if (deviceInfoBuilder_ == null) { + ensureDeviceInfoIsMutable(); + deviceInfo_.add(index, builderForValue.build()); + onChanged(); + } else { + deviceInfoBuilder_.addMessage(index, builderForValue.build()); + } + return this; + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public Builder addAllDeviceInfo( + java.lang.Iterable values) { + if (deviceInfoBuilder_ == null) { + ensureDeviceInfoIsMutable(); + com.google.protobuf.AbstractMessageLite.Builder.addAll( + values, deviceInfo_); + onChanged(); + } else { + deviceInfoBuilder_.addAllMessages(values); + } + return this; + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public Builder clearDeviceInfo() { + if (deviceInfoBuilder_ == null) { + deviceInfo_ = java.util.Collections.emptyList(); + bitField0_ = (bitField0_ & ~0x00000001); + onChanged(); + } else { + deviceInfoBuilder_.clear(); + } + return this; + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public Builder removeDeviceInfo(int index) { + if (deviceInfoBuilder_ == null) { + ensureDeviceInfoIsMutable(); + deviceInfo_.remove(index); + onChanged(); + } else { + deviceInfoBuilder_.remove(index); + } + return this; + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public com.google.protobuf.Any.Builder getDeviceInfoBuilder( + int index) { + return getDeviceInfoFieldBuilder().getBuilder(index); + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public com.google.protobuf.AnyOrBuilder getDeviceInfoOrBuilder( + int index) { + if (deviceInfoBuilder_ == null) { + return deviceInfo_.get(index); } else { + return deviceInfoBuilder_.getMessageOrBuilder(index); + } + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public java.util.List + getDeviceInfoOrBuilderList() { + if (deviceInfoBuilder_ != null) { + return deviceInfoBuilder_.getMessageOrBuilderList(); + } else { + return java.util.Collections.unmodifiableList(deviceInfo_); + } + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public com.google.protobuf.Any.Builder addDeviceInfoBuilder() { + return getDeviceInfoFieldBuilder().addBuilder( + com.google.protobuf.Any.getDefaultInstance()); + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public com.google.protobuf.Any.Builder addDeviceInfoBuilder( + int index) { + return getDeviceInfoFieldBuilder().addBuilder( + index, com.google.protobuf.Any.getDefaultInstance()); + } + /** + * 
    +     * Other devices that are attached and relevant (e.g. GPUInfo).
+     *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + public java.util.List + getDeviceInfoBuilderList() { + return getDeviceInfoFieldBuilder().getBuilderList(); + } + private com.google.protobuf.RepeatedFieldBuilderV3< + com.google.protobuf.Any, com.google.protobuf.Any.Builder, com.google.protobuf.AnyOrBuilder> + getDeviceInfoFieldBuilder() { + if (deviceInfoBuilder_ == null) { + deviceInfoBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3< + com.google.protobuf.Any, com.google.protobuf.Any.Builder, com.google.protobuf.AnyOrBuilder>( + deviceInfo_, + ((bitField0_ & 0x00000001) != 0), + getParentForChildren(), + isClean()); + deviceInfo_ = null; + } + return deviceInfoBuilder_; + } + + private java.util.List availableDeviceInfo_ = + java.util.Collections.emptyList(); + private void ensureAvailableDeviceInfoIsMutable() { + if (!((bitField0_ & 0x00000002) != 0)) { + availableDeviceInfo_ = new java.util.ArrayList(availableDeviceInfo_); + bitField0_ |= 0x00000002; + } + } + + private com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.AvailableDeviceInfo, org.tensorflow.proto.AvailableDeviceInfo.Builder, org.tensorflow.proto.AvailableDeviceInfoOrBuilder> availableDeviceInfoBuilder_; + + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public java.util.List getAvailableDeviceInfoList() { + if (availableDeviceInfoBuilder_ == null) { + return java.util.Collections.unmodifiableList(availableDeviceInfo_); + } else { + return availableDeviceInfoBuilder_.getMessageList(); + } + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public int getAvailableDeviceInfoCount() { + if (availableDeviceInfoBuilder_ == null) { + return availableDeviceInfo_.size(); + } else { + return availableDeviceInfoBuilder_.getCount(); + } + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public org.tensorflow.proto.AvailableDeviceInfo getAvailableDeviceInfo(int index) { + if (availableDeviceInfoBuilder_ == null) { + return availableDeviceInfo_.get(index); + } else { + return availableDeviceInfoBuilder_.getMessage(index); + } + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public Builder setAvailableDeviceInfo( + int index, org.tensorflow.proto.AvailableDeviceInfo value) { + if (availableDeviceInfoBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureAvailableDeviceInfoIsMutable(); + availableDeviceInfo_.set(index, value); + onChanged(); + } else { + availableDeviceInfoBuilder_.setMessage(index, value); + } + return this; + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public Builder setAvailableDeviceInfo( + int index, org.tensorflow.proto.AvailableDeviceInfo.Builder builderForValue) { + if (availableDeviceInfoBuilder_ == null) { + ensureAvailableDeviceInfoIsMutable(); + availableDeviceInfo_.set(index, builderForValue.build()); + onChanged(); + } else { + availableDeviceInfoBuilder_.setMessage(index, builderForValue.build()); + } + return this; + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public Builder addAvailableDeviceInfo(org.tensorflow.proto.AvailableDeviceInfo value) { + if (availableDeviceInfoBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureAvailableDeviceInfoIsMutable(); + availableDeviceInfo_.add(value); + onChanged(); + } else { + availableDeviceInfoBuilder_.addMessage(value); + } + return this; + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public Builder addAvailableDeviceInfo( + int index, org.tensorflow.proto.AvailableDeviceInfo value) { + if (availableDeviceInfoBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + ensureAvailableDeviceInfoIsMutable(); + availableDeviceInfo_.add(index, value); + onChanged(); + } else { + availableDeviceInfoBuilder_.addMessage(index, value); + } + return this; + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public Builder addAvailableDeviceInfo( + org.tensorflow.proto.AvailableDeviceInfo.Builder builderForValue) { + if (availableDeviceInfoBuilder_ == null) { + ensureAvailableDeviceInfoIsMutable(); + availableDeviceInfo_.add(builderForValue.build()); + onChanged(); + } else { + availableDeviceInfoBuilder_.addMessage(builderForValue.build()); + } + return this; + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public Builder addAvailableDeviceInfo( + int index, org.tensorflow.proto.AvailableDeviceInfo.Builder builderForValue) { + if (availableDeviceInfoBuilder_ == null) { + ensureAvailableDeviceInfoIsMutable(); + availableDeviceInfo_.add(index, builderForValue.build()); + onChanged(); + } else { + availableDeviceInfoBuilder_.addMessage(index, builderForValue.build()); + } + return this; + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public Builder addAllAvailableDeviceInfo( + java.lang.Iterable values) { + if (availableDeviceInfoBuilder_ == null) { + ensureAvailableDeviceInfoIsMutable(); + com.google.protobuf.AbstractMessageLite.Builder.addAll( + values, availableDeviceInfo_); + onChanged(); + } else { + availableDeviceInfoBuilder_.addAllMessages(values); + } + return this; + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public Builder clearAvailableDeviceInfo() { + if (availableDeviceInfoBuilder_ == null) { + availableDeviceInfo_ = java.util.Collections.emptyList(); + bitField0_ = (bitField0_ & ~0x00000002); + onChanged(); + } else { + availableDeviceInfoBuilder_.clear(); + } + return this; + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public Builder removeAvailableDeviceInfo(int index) { + if (availableDeviceInfoBuilder_ == null) { + ensureAvailableDeviceInfoIsMutable(); + availableDeviceInfo_.remove(index); + onChanged(); + } else { + availableDeviceInfoBuilder_.remove(index); + } + return this; + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public org.tensorflow.proto.AvailableDeviceInfo.Builder getAvailableDeviceInfoBuilder( + int index) { + return getAvailableDeviceInfoFieldBuilder().getBuilder(index); + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public org.tensorflow.proto.AvailableDeviceInfoOrBuilder getAvailableDeviceInfoOrBuilder( + int index) { + if (availableDeviceInfoBuilder_ == null) { + return availableDeviceInfo_.get(index); } else { + return availableDeviceInfoBuilder_.getMessageOrBuilder(index); + } + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public java.util.List + getAvailableDeviceInfoOrBuilderList() { + if (availableDeviceInfoBuilder_ != null) { + return availableDeviceInfoBuilder_.getMessageOrBuilderList(); + } else { + return java.util.Collections.unmodifiableList(availableDeviceInfo_); + } + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public org.tensorflow.proto.AvailableDeviceInfo.Builder addAvailableDeviceInfoBuilder() { + return getAvailableDeviceInfoFieldBuilder().addBuilder( + org.tensorflow.proto.AvailableDeviceInfo.getDefaultInstance()); + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public org.tensorflow.proto.AvailableDeviceInfo.Builder addAvailableDeviceInfoBuilder( + int index) { + return getAvailableDeviceInfoFieldBuilder().addBuilder( + index, org.tensorflow.proto.AvailableDeviceInfo.getDefaultInstance()); + } + /** + * 
    +     * Devices accessible to the test (e.g. as given by list_local_devices).
+     *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + public java.util.List + getAvailableDeviceInfoBuilderList() { + return getAvailableDeviceInfoFieldBuilder().getBuilderList(); + } + private com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.AvailableDeviceInfo, org.tensorflow.proto.AvailableDeviceInfo.Builder, org.tensorflow.proto.AvailableDeviceInfoOrBuilder> + getAvailableDeviceInfoFieldBuilder() { + if (availableDeviceInfoBuilder_ == null) { + availableDeviceInfoBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3< + org.tensorflow.proto.AvailableDeviceInfo, org.tensorflow.proto.AvailableDeviceInfo.Builder, org.tensorflow.proto.AvailableDeviceInfoOrBuilder>( + availableDeviceInfo_, + ((bitField0_ & 0x00000002) != 0), + getParentForChildren(), + isClean()); + availableDeviceInfo_ = null; + } + return availableDeviceInfoBuilder_; + } + + private org.tensorflow.proto.MemoryInfo memoryInfo_; + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.MemoryInfo, org.tensorflow.proto.MemoryInfo.Builder, org.tensorflow.proto.MemoryInfoOrBuilder> memoryInfoBuilder_; + /** + * .tensorflow.MemoryInfo memory_info = 6; + * @return Whether the memoryInfo field is set. + */ + public boolean hasMemoryInfo() { + return memoryInfoBuilder_ != null || memoryInfo_ != null; + } + /** + * .tensorflow.MemoryInfo memory_info = 6; + * @return The memoryInfo. + */ + public org.tensorflow.proto.MemoryInfo getMemoryInfo() { + if (memoryInfoBuilder_ == null) { + return memoryInfo_ == null ? org.tensorflow.proto.MemoryInfo.getDefaultInstance() : memoryInfo_; + } else { + return memoryInfoBuilder_.getMessage(); + } + } + /** + * .tensorflow.MemoryInfo memory_info = 6; + */ + public Builder setMemoryInfo(org.tensorflow.proto.MemoryInfo value) { + if (memoryInfoBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + memoryInfo_ = value; + onChanged(); + } else { + memoryInfoBuilder_.setMessage(value); + } + + return this; + } + /** + * .tensorflow.MemoryInfo memory_info = 6; + */ + public Builder setMemoryInfo( + org.tensorflow.proto.MemoryInfo.Builder builderForValue) { + if (memoryInfoBuilder_ == null) { + memoryInfo_ = builderForValue.build(); + onChanged(); + } else { + memoryInfoBuilder_.setMessage(builderForValue.build()); + } + + return this; + } + /** + * .tensorflow.MemoryInfo memory_info = 6; + */ + public Builder mergeMemoryInfo(org.tensorflow.proto.MemoryInfo value) { + if (memoryInfoBuilder_ == null) { + if (memoryInfo_ != null) { + memoryInfo_ = + org.tensorflow.proto.MemoryInfo.newBuilder(memoryInfo_).mergeFrom(value).buildPartial(); + } else { + memoryInfo_ = value; + } + onChanged(); + } else { + memoryInfoBuilder_.mergeFrom(value); + } + + return this; + } + /** + * .tensorflow.MemoryInfo memory_info = 6; + */ + public Builder clearMemoryInfo() { + if (memoryInfoBuilder_ == null) { + memoryInfo_ = null; + onChanged(); + } else { + memoryInfo_ = null; + memoryInfoBuilder_ = null; + } + + return this; + } + /** + * .tensorflow.MemoryInfo memory_info = 6; + */ + public org.tensorflow.proto.MemoryInfo.Builder getMemoryInfoBuilder() { + + onChanged(); + return getMemoryInfoFieldBuilder().getBuilder(); + } + /** + * .tensorflow.MemoryInfo memory_info = 6; + */ + public org.tensorflow.proto.MemoryInfoOrBuilder getMemoryInfoOrBuilder() { + if (memoryInfoBuilder_ != null) { + return memoryInfoBuilder_.getMessageOrBuilder(); + } else { + return memoryInfo_ == null ? + org.tensorflow.proto.MemoryInfo.getDefaultInstance() : memoryInfo_; + } + } + /** + * .tensorflow.MemoryInfo memory_info = 6; + */ + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.MemoryInfo, org.tensorflow.proto.MemoryInfo.Builder, org.tensorflow.proto.MemoryInfoOrBuilder> + getMemoryInfoFieldBuilder() { + if (memoryInfoBuilder_ == null) { + memoryInfoBuilder_ = new com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.MemoryInfo, org.tensorflow.proto.MemoryInfo.Builder, org.tensorflow.proto.MemoryInfoOrBuilder>( + getMemoryInfo(), + getParentForChildren(), + isClean()); + memoryInfo_ = null; + } + return memoryInfoBuilder_; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.MachineConfiguration) + } + + // @@protoc_insertion_point(class_scope:tensorflow.MachineConfiguration) + private static final org.tensorflow.proto.MachineConfiguration DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.MachineConfiguration(); + } + + public static org.tensorflow.proto.MachineConfiguration getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public MachineConfiguration parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.MachineConfiguration getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + +} + diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MachineConfigurationOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MachineConfigurationOrBuilder.java new file mode 100644 index 00000000000..e3c944d06be --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MachineConfigurationOrBuilder.java @@ -0,0 +1,206 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public interface MachineConfigurationOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.MachineConfiguration) + com.google.protobuf.MessageOrBuilder { + + /** + * 
    +   * Host name of machine that ran the benchmark.
+   *
    + * + * string hostname = 1; + * @return The hostname. + */ + java.lang.String getHostname(); + /** + * 
    +   * Host name of machine that ran the benchmark.
+   *
    + * + * string hostname = 1; + * @return The bytes for hostname. + */ + com.google.protobuf.ByteString + getHostnameBytes(); + + /** + * 
    +   * Unique serial number of the machine.
+   *
    + * + * string serial_identifier = 7; + * @return The serialIdentifier. + */ + java.lang.String getSerialIdentifier(); + /** + * 
    +   * Unique serial number of the machine.
+   *
    + * + * string serial_identifier = 7; + * @return The bytes for serialIdentifier. + */ + com.google.protobuf.ByteString + getSerialIdentifierBytes(); + + /** + * 
    +   * Additional platform information.
+   *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + * @return Whether the platformInfo field is set. + */ + boolean hasPlatformInfo(); + /** + * 
    +   * Additional platform information.
+   *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + * @return The platformInfo. + */ + org.tensorflow.proto.PlatformInfo getPlatformInfo(); + /** + * 
    +   * Additional platform information.
+   *
    + * + * .tensorflow.PlatformInfo platform_info = 2; + */ + org.tensorflow.proto.PlatformInfoOrBuilder getPlatformInfoOrBuilder(); + + /** + * 
    +   * CPU Information.
+   *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + * @return Whether the cpuInfo field is set. + */ + boolean hasCpuInfo(); + /** + * 
    +   * CPU Information.
+   *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + * @return The cpuInfo. + */ + org.tensorflow.proto.CPUInfo getCpuInfo(); + /** + * 
    +   * CPU Information.
+   *
    + * + * .tensorflow.CPUInfo cpu_info = 3; + */ + org.tensorflow.proto.CPUInfoOrBuilder getCpuInfoOrBuilder(); + + /** + * 
    +   * Other devices that are attached and relevant (e.g. GPUInfo).
+   *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + java.util.List + getDeviceInfoList(); + /** + * 
    +   * Other devices that are attached and relevant (e.g. GPUInfo).
+   *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + com.google.protobuf.Any getDeviceInfo(int index); + /** + * 
    +   * Other devices that are attached and relevant (e.g. GPUInfo).
+   *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + int getDeviceInfoCount(); + /** + * 
    +   * Other devices that are attached and relevant (e.g. GPUInfo).
+   *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + java.util.List + getDeviceInfoOrBuilderList(); + /** + * 
    +   * Other devices that are attached and relevant (e.g. GPUInfo).
+   *
    + * + * repeated .google.protobuf.Any device_info = 4; + */ + com.google.protobuf.AnyOrBuilder getDeviceInfoOrBuilder( + int index); + + /** + * 
    +   * Devices accessible to the test (e.g. as given by list_local_devices).
+   *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + java.util.List + getAvailableDeviceInfoList(); + /** + * 
    +   * Devices accessible to the test (e.g. as given by list_local_devices).
+   *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + org.tensorflow.proto.AvailableDeviceInfo getAvailableDeviceInfo(int index); + /** + * 
    +   * Devices accessible to the test (e.g. as given by list_local_devices).
+   *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + int getAvailableDeviceInfoCount(); + /** + * 
    +   * Devices accessible to the test (e.g. as given by list_local_devices).
+   *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + java.util.List + getAvailableDeviceInfoOrBuilderList(); + /** + * 
    +   * Devices accessible to the test (e.g. as given by list_local_devices).
+   *
    + * + * repeated .tensorflow.AvailableDeviceInfo available_device_info = 5; + */ + org.tensorflow.proto.AvailableDeviceInfoOrBuilder getAvailableDeviceInfoOrBuilder( + int index); + + /** + * .tensorflow.MemoryInfo memory_info = 6; + * @return Whether the memoryInfo field is set. + */ + boolean hasMemoryInfo(); + /** + * .tensorflow.MemoryInfo memory_info = 6; + * @return The memoryInfo. + */ + org.tensorflow.proto.MemoryInfo getMemoryInfo(); + /** + * .tensorflow.MemoryInfo memory_info = 6; + */ + org.tensorflow.proto.MemoryInfoOrBuilder getMemoryInfoOrBuilder(); +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MemoryInfo.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MemoryInfo.java new file mode 100644 index 00000000000..d351a728e2a --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MemoryInfo.java @@ -0,0 +1,563 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +/** + * Protobuf type {@code tensorflow.MemoryInfo} + */ +public final class MemoryInfo extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.MemoryInfo) + MemoryInfoOrBuilder { +private static final long serialVersionUID = 0L; + // Use MemoryInfo.newBuilder() to construct. + private MemoryInfo(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private MemoryInfo() { + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new MemoryInfo(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MemoryInfo_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MemoryInfo_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.MemoryInfo.class, org.tensorflow.proto.MemoryInfo.Builder.class); + } + + public static final int TOTAL_FIELD_NUMBER = 1; + private long total_; + /** + * 
    +   * Total virtual memory in bytes
+   *
    + * + * int64 total = 1; + * @return The total. + */ + @java.lang.Override + public long getTotal() { + return total_; + } + + public static final int AVAILABLE_FIELD_NUMBER = 2; + private long available_; + /** + * 
    +   * Immediately available memory in bytes
+   *
    + * + * int64 available = 2; + * @return The available. + */ + @java.lang.Override + public long getAvailable() { + return available_; + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (total_ != 0L) { + output.writeInt64(1, total_); + } + if (available_ != 0L) { + output.writeInt64(2, available_); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (total_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(1, total_); + } + if (available_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(2, available_); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.MemoryInfo)) { + return super.equals(obj); + } + org.tensorflow.proto.MemoryInfo other = (org.tensorflow.proto.MemoryInfo) obj; + + if (getTotal() + != other.getTotal()) return false; + if (getAvailable() + != other.getAvailable()) return false; + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + TOTAL_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getTotal()); + hash = (37 * hash) + AVAILABLE_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getAvailable()); + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.MemoryInfo parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.MemoryInfo parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.MemoryInfo parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.MemoryInfo parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.MemoryInfo parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.MemoryInfo parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.MemoryInfo parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.MemoryInfo parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.MemoryInfo parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.MemoryInfo parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.MemoryInfo parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.MemoryInfo parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.MemoryInfo prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * Protobuf type {@code tensorflow.MemoryInfo} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.MemoryInfo) + org.tensorflow.proto.MemoryInfoOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MemoryInfo_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MemoryInfo_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.MemoryInfo.class, org.tensorflow.proto.MemoryInfo.Builder.class); + } + + // Construct using org.tensorflow.proto.MemoryInfo.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + total_ = 0L; + + available_ = 0L; + + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MemoryInfo_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.MemoryInfo getDefaultInstanceForType() { + return org.tensorflow.proto.MemoryInfo.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.MemoryInfo build() { + org.tensorflow.proto.MemoryInfo result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.MemoryInfo buildPartial() { + org.tensorflow.proto.MemoryInfo result = new org.tensorflow.proto.MemoryInfo(this); + result.total_ = total_; + result.available_ = available_; + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.MemoryInfo) { + return mergeFrom((org.tensorflow.proto.MemoryInfo)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.MemoryInfo other) { + if (other == org.tensorflow.proto.MemoryInfo.getDefaultInstance()) return this; + if (other.getTotal() != 0L) { + setTotal(other.getTotal()); + } + if (other.getAvailable() != 0L) { + setAvailable(other.getAvailable()); + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 8: { + total_ = input.readInt64(); + + break; + } // case 8 + case 16: { + available_ = input.readInt64(); + + break; + } // case 16 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + + private long total_ ; + /** + * 
    +     * Total virtual memory in bytes
+     *
    + * + * int64 total = 1; + * @return The total. + */ + @java.lang.Override + public long getTotal() { + return total_; + } + /** + * 
    +     * Total virtual memory in bytes
+     *
    + * + * int64 total = 1; + * @param value The total to set. + * @return This builder for chaining. + */ + public Builder setTotal(long value) { + + total_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Total virtual memory in bytes
+     *
    + * + * int64 total = 1; + * @return This builder for chaining. + */ + public Builder clearTotal() { + + total_ = 0L; + onChanged(); + return this; + } + + private long available_ ; + /** + * 
    +     * Immediately available memory in bytes
+     *
    + * + * int64 available = 2; + * @return The available. + */ + @java.lang.Override + public long getAvailable() { + return available_; + } + /** + * 
    +     * Immediately available memory in bytes
+     *
    + * + * int64 available = 2; + * @param value The available to set. + * @return This builder for chaining. + */ + public Builder setAvailable(long value) { + + available_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Immediately available memory in bytes
+     *
    + * + * int64 available = 2; + * @return This builder for chaining. + */ + public Builder clearAvailable() { + + available_ = 0L; + onChanged(); + return this; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.MemoryInfo) + } + + // @@protoc_insertion_point(class_scope:tensorflow.MemoryInfo) + private static final org.tensorflow.proto.MemoryInfo DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.MemoryInfo(); + } + + public static org.tensorflow.proto.MemoryInfo getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public MemoryInfo parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.MemoryInfo getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + +} + diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MemoryInfoOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MemoryInfoOrBuilder.java new file mode 100644 index 00000000000..6a2f7e6c9e8 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MemoryInfoOrBuilder.java @@ -0,0 +1,29 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public interface MemoryInfoOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.MemoryInfo) + com.google.protobuf.MessageOrBuilder { + + /** + * 
    +   * Total virtual memory in bytes
+   *
    + * + * int64 total = 1; + * @return The total. + */ + long getTotal(); + + /** + * 
    +   * Immediately available memory in bytes
+   *
    + * + * int64 available = 2; + * @return The available. + */ + long getAvailable(); +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MetricEntry.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MetricEntry.java new file mode 100644 index 00000000000..d9454e9bc70 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MetricEntry.java @@ -0,0 +1,1108 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +/** + * Protobuf type {@code tensorflow.MetricEntry} + */ +public final class MetricEntry extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.MetricEntry) + MetricEntryOrBuilder { +private static final long serialVersionUID = 0L; + // Use MetricEntry.newBuilder() to construct. + private MetricEntry(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private MetricEntry() { + name_ = ""; + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new MetricEntry(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MetricEntry_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MetricEntry_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.MetricEntry.class, org.tensorflow.proto.MetricEntry.Builder.class); + } + + public static final int NAME_FIELD_NUMBER = 1; + private volatile java.lang.Object name_; + /** + * 
    +   * Metric name
+   *
    + * + * string name = 1; + * @return The name. + */ + @java.lang.Override + public java.lang.String getName() { + java.lang.Object ref = name_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + name_ = s; + return s; + } + } + /** + * 
    +   * Metric name
+   *
    + * + * string name = 1; + * @return The bytes for name. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getNameBytes() { + java.lang.Object ref = name_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + name_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int VALUE_FIELD_NUMBER = 2; + private double value_; + /** + * 
    +   * Metric value
+   *
    + * + * double value = 2; + * @return The value. + */ + @java.lang.Override + public double getValue() { + return value_; + } + + public static final int MIN_VALUE_FIELD_NUMBER = 3; + private com.google.protobuf.DoubleValue minValue_; + /** + * 
    +   * The minimum acceptable value for the metric if specified
+   *
    + * + * .google.protobuf.DoubleValue min_value = 3; + * @return Whether the minValue field is set. + */ + @java.lang.Override + public boolean hasMinValue() { + return minValue_ != null; + } + /** + * 
    +   * The minimum acceptable value for the metric if specified
+   *
    + * + * .google.protobuf.DoubleValue min_value = 3; + * @return The minValue. + */ + @java.lang.Override + public com.google.protobuf.DoubleValue getMinValue() { + return minValue_ == null ? com.google.protobuf.DoubleValue.getDefaultInstance() : minValue_; + } + /** + * 
    +   * The minimum acceptable value for the metric if specified
+   *
    + * + * .google.protobuf.DoubleValue min_value = 3; + */ + @java.lang.Override + public com.google.protobuf.DoubleValueOrBuilder getMinValueOrBuilder() { + return getMinValue(); + } + + public static final int MAX_VALUE_FIELD_NUMBER = 4; + private com.google.protobuf.DoubleValue maxValue_; + /** + * 
    +   * The maximum acceptable value for the metric if specified
+   *
    + * + * .google.protobuf.DoubleValue max_value = 4; + * @return Whether the maxValue field is set. + */ + @java.lang.Override + public boolean hasMaxValue() { + return maxValue_ != null; + } + /** + * 
    +   * The maximum acceptable value for the metric if specified
+   *
    + * + * .google.protobuf.DoubleValue max_value = 4; + * @return The maxValue. + */ + @java.lang.Override + public com.google.protobuf.DoubleValue getMaxValue() { + return maxValue_ == null ? com.google.protobuf.DoubleValue.getDefaultInstance() : maxValue_; + } + /** + * 
    +   * The maximum acceptable value for the metric if specified
+   *
    + * + * .google.protobuf.DoubleValue max_value = 4; + */ + @java.lang.Override + public com.google.protobuf.DoubleValueOrBuilder getMaxValueOrBuilder() { + return getMaxValue(); + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 1, name_); + } + if (java.lang.Double.doubleToRawLongBits(value_) != 0) { + output.writeDouble(2, value_); + } + if (minValue_ != null) { + output.writeMessage(3, getMinValue()); + } + if (maxValue_ != null) { + output.writeMessage(4, getMaxValue()); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, name_); + } + if (java.lang.Double.doubleToRawLongBits(value_) != 0) { + size += com.google.protobuf.CodedOutputStream + .computeDoubleSize(2, value_); + } + if (minValue_ != null) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(3, getMinValue()); + } + if (maxValue_ != null) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(4, getMaxValue()); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.MetricEntry)) { + return super.equals(obj); + } + org.tensorflow.proto.MetricEntry other = (org.tensorflow.proto.MetricEntry) obj; + + if (!getName() + .equals(other.getName())) return false; + if (java.lang.Double.doubleToLongBits(getValue()) + != java.lang.Double.doubleToLongBits( + other.getValue())) return false; + if (hasMinValue() != other.hasMinValue()) return false; + if (hasMinValue()) { + if (!getMinValue() + .equals(other.getMinValue())) return false; + } + if (hasMaxValue() != other.hasMaxValue()) return false; + if (hasMaxValue()) { + if (!getMaxValue() + .equals(other.getMaxValue())) return false; + } + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + NAME_FIELD_NUMBER; + hash = (53 * hash) + getName().hashCode(); + hash = (37 * hash) + VALUE_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + java.lang.Double.doubleToLongBits(getValue())); + if (hasMinValue()) { + hash = (37 * hash) + MIN_VALUE_FIELD_NUMBER; + hash = (53 * hash) + getMinValue().hashCode(); + } + if (hasMaxValue()) { + hash = (37 * hash) + MAX_VALUE_FIELD_NUMBER; + hash = (53 * hash) + getMaxValue().hashCode(); + } + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.MetricEntry parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.MetricEntry parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.MetricEntry parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.MetricEntry parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.MetricEntry parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.MetricEntry parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.MetricEntry parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.MetricEntry parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.MetricEntry parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.MetricEntry parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.MetricEntry parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.MetricEntry parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.MetricEntry prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * Protobuf type {@code tensorflow.MetricEntry} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.MetricEntry) + org.tensorflow.proto.MetricEntryOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MetricEntry_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MetricEntry_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.MetricEntry.class, org.tensorflow.proto.MetricEntry.Builder.class); + } + + // Construct using org.tensorflow.proto.MetricEntry.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + name_ = ""; + + value_ = 0D; + + if (minValueBuilder_ == null) { + minValue_ = null; + } else { + minValue_ = null; + minValueBuilder_ = null; + } + if (maxValueBuilder_ == null) { + maxValue_ = null; + } else { + maxValue_ = null; + maxValueBuilder_ = null; + } + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_MetricEntry_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.MetricEntry getDefaultInstanceForType() { + return org.tensorflow.proto.MetricEntry.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.MetricEntry build() { + org.tensorflow.proto.MetricEntry result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.MetricEntry buildPartial() { + org.tensorflow.proto.MetricEntry result = new org.tensorflow.proto.MetricEntry(this); + result.name_ = name_; + result.value_ = value_; + if (minValueBuilder_ == null) { + result.minValue_ = minValue_; + } else { + result.minValue_ = minValueBuilder_.build(); + } + if (maxValueBuilder_ == null) { + result.maxValue_ = maxValue_; + } else { + result.maxValue_ = maxValueBuilder_.build(); + } + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.MetricEntry) { + return mergeFrom((org.tensorflow.proto.MetricEntry)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.MetricEntry other) { + if (other == org.tensorflow.proto.MetricEntry.getDefaultInstance()) return this; + if (!other.getName().isEmpty()) { + name_ = other.name_; + onChanged(); + } + if (other.getValue() != 0D) { + setValue(other.getValue()); + } + if (other.hasMinValue()) { + mergeMinValue(other.getMinValue()); + } + if (other.hasMaxValue()) { + mergeMaxValue(other.getMaxValue()); + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 10: { + name_ = input.readStringRequireUtf8(); + + break; + } // case 10 + case 17: { + value_ = input.readDouble(); + + break; + } // case 17 + case 26: { + input.readMessage( + getMinValueFieldBuilder().getBuilder(), + extensionRegistry); + + break; + } // case 26 + case 34: { + input.readMessage( + getMaxValueFieldBuilder().getBuilder(), + extensionRegistry); + + break; + } // case 34 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + + private java.lang.Object name_ = ""; + /** + * 
    +     * Metric name
+     *
    + * + * string name = 1; + * @return The name. + */ + public java.lang.String getName() { + java.lang.Object ref = name_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + name_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * Metric name
+     *
    + * + * string name = 1; + * @return The bytes for name. + */ + public com.google.protobuf.ByteString + getNameBytes() { + java.lang.Object ref = name_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + name_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * Metric name
+     *
    + * + * string name = 1; + * @param value The name to set. + * @return This builder for chaining. + */ + public Builder setName( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + name_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Metric name
+     *
    + * + * string name = 1; + * @return This builder for chaining. + */ + public Builder clearName() { + + name_ = getDefaultInstance().getName(); + onChanged(); + return this; + } + /** + * 
    +     * Metric name
+     *
    + * + * string name = 1; + * @param value The bytes for name to set. + * @return This builder for chaining. + */ + public Builder setNameBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + name_ = value; + onChanged(); + return this; + } + + private double value_ ; + /** + * 
    +     * Metric value
+     *
    + * + * double value = 2; + * @return The value. + */ + @java.lang.Override + public double getValue() { + return value_; + } + /** + * 
    +     * Metric value
+     *
    + * + * double value = 2; + * @param value The value to set. + * @return This builder for chaining. + */ + public Builder setValue(double value) { + + value_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Metric value
+     *
    + * + * double value = 2; + * @return This builder for chaining. + */ + public Builder clearValue() { + + value_ = 0D; + onChanged(); + return this; + } + + private com.google.protobuf.DoubleValue minValue_; + private com.google.protobuf.SingleFieldBuilderV3< + com.google.protobuf.DoubleValue, com.google.protobuf.DoubleValue.Builder, com.google.protobuf.DoubleValueOrBuilder> minValueBuilder_; + /** + * 
    +     * The minimum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue min_value = 3; + * @return Whether the minValue field is set. + */ + public boolean hasMinValue() { + return minValueBuilder_ != null || minValue_ != null; + } + /** + * 
    +     * The minimum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue min_value = 3; + * @return The minValue. + */ + public com.google.protobuf.DoubleValue getMinValue() { + if (minValueBuilder_ == null) { + return minValue_ == null ? com.google.protobuf.DoubleValue.getDefaultInstance() : minValue_; + } else { + return minValueBuilder_.getMessage(); + } + } + /** + * 
    +     * The minimum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue min_value = 3; + */ + public Builder setMinValue(com.google.protobuf.DoubleValue value) { + if (minValueBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + minValue_ = value; + onChanged(); + } else { + minValueBuilder_.setMessage(value); + } + + return this; + } + /** + * 
    +     * The minimum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue min_value = 3; + */ + public Builder setMinValue( + com.google.protobuf.DoubleValue.Builder builderForValue) { + if (minValueBuilder_ == null) { + minValue_ = builderForValue.build(); + onChanged(); + } else { + minValueBuilder_.setMessage(builderForValue.build()); + } + + return this; + } + /** + * 
    +     * The minimum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue min_value = 3; + */ + public Builder mergeMinValue(com.google.protobuf.DoubleValue value) { + if (minValueBuilder_ == null) { + if (minValue_ != null) { + minValue_ = + com.google.protobuf.DoubleValue.newBuilder(minValue_).mergeFrom(value).buildPartial(); + } else { + minValue_ = value; + } + onChanged(); + } else { + minValueBuilder_.mergeFrom(value); + } + + return this; + } + /** + * 
    +     * The minimum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue min_value = 3; + */ + public Builder clearMinValue() { + if (minValueBuilder_ == null) { + minValue_ = null; + onChanged(); + } else { + minValue_ = null; + minValueBuilder_ = null; + } + + return this; + } + /** + * 
    +     * The minimum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue min_value = 3; + */ + public com.google.protobuf.DoubleValue.Builder getMinValueBuilder() { + + onChanged(); + return getMinValueFieldBuilder().getBuilder(); + } + /** + * 
    +     * The minimum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue min_value = 3; + */ + public com.google.protobuf.DoubleValueOrBuilder getMinValueOrBuilder() { + if (minValueBuilder_ != null) { + return minValueBuilder_.getMessageOrBuilder(); + } else { + return minValue_ == null ? + com.google.protobuf.DoubleValue.getDefaultInstance() : minValue_; + } + } + /** + * 
    +     * The minimum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue min_value = 3; + */ + private com.google.protobuf.SingleFieldBuilderV3< + com.google.protobuf.DoubleValue, com.google.protobuf.DoubleValue.Builder, com.google.protobuf.DoubleValueOrBuilder> + getMinValueFieldBuilder() { + if (minValueBuilder_ == null) { + minValueBuilder_ = new com.google.protobuf.SingleFieldBuilderV3< + com.google.protobuf.DoubleValue, com.google.protobuf.DoubleValue.Builder, com.google.protobuf.DoubleValueOrBuilder>( + getMinValue(), + getParentForChildren(), + isClean()); + minValue_ = null; + } + return minValueBuilder_; + } + + private com.google.protobuf.DoubleValue maxValue_; + private com.google.protobuf.SingleFieldBuilderV3< + com.google.protobuf.DoubleValue, com.google.protobuf.DoubleValue.Builder, com.google.protobuf.DoubleValueOrBuilder> maxValueBuilder_; + /** + * 
    +     * The maximum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue max_value = 4; + * @return Whether the maxValue field is set. + */ + public boolean hasMaxValue() { + return maxValueBuilder_ != null || maxValue_ != null; + } + /** + * 
    +     * The maximum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue max_value = 4; + * @return The maxValue. + */ + public com.google.protobuf.DoubleValue getMaxValue() { + if (maxValueBuilder_ == null) { + return maxValue_ == null ? com.google.protobuf.DoubleValue.getDefaultInstance() : maxValue_; + } else { + return maxValueBuilder_.getMessage(); + } + } + /** + * 
    +     * The maximum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue max_value = 4; + */ + public Builder setMaxValue(com.google.protobuf.DoubleValue value) { + if (maxValueBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + maxValue_ = value; + onChanged(); + } else { + maxValueBuilder_.setMessage(value); + } + + return this; + } + /** + * 
    +     * The maximum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue max_value = 4; + */ + public Builder setMaxValue( + com.google.protobuf.DoubleValue.Builder builderForValue) { + if (maxValueBuilder_ == null) { + maxValue_ = builderForValue.build(); + onChanged(); + } else { + maxValueBuilder_.setMessage(builderForValue.build()); + } + + return this; + } + /** + * 
    +     * The maximum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue max_value = 4; + */ + public Builder mergeMaxValue(com.google.protobuf.DoubleValue value) { + if (maxValueBuilder_ == null) { + if (maxValue_ != null) { + maxValue_ = + com.google.protobuf.DoubleValue.newBuilder(maxValue_).mergeFrom(value).buildPartial(); + } else { + maxValue_ = value; + } + onChanged(); + } else { + maxValueBuilder_.mergeFrom(value); + } + + return this; + } + /** + * 
    +     * The maximum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue max_value = 4; + */ + public Builder clearMaxValue() { + if (maxValueBuilder_ == null) { + maxValue_ = null; + onChanged(); + } else { + maxValue_ = null; + maxValueBuilder_ = null; + } + + return this; + } + /** + * 
    +     * The maximum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue max_value = 4; + */ + public com.google.protobuf.DoubleValue.Builder getMaxValueBuilder() { + + onChanged(); + return getMaxValueFieldBuilder().getBuilder(); + } + /** + * 
    +     * The maximum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue max_value = 4; + */ + public com.google.protobuf.DoubleValueOrBuilder getMaxValueOrBuilder() { + if (maxValueBuilder_ != null) { + return maxValueBuilder_.getMessageOrBuilder(); + } else { + return maxValue_ == null ? + com.google.protobuf.DoubleValue.getDefaultInstance() : maxValue_; + } + } + /** + * 
    +     * The maximum acceptable value for the metric if specified
+     *
    + * + * .google.protobuf.DoubleValue max_value = 4; + */ + private com.google.protobuf.SingleFieldBuilderV3< + com.google.protobuf.DoubleValue, com.google.protobuf.DoubleValue.Builder, com.google.protobuf.DoubleValueOrBuilder> + getMaxValueFieldBuilder() { + if (maxValueBuilder_ == null) { + maxValueBuilder_ = new com.google.protobuf.SingleFieldBuilderV3< + com.google.protobuf.DoubleValue, com.google.protobuf.DoubleValue.Builder, com.google.protobuf.DoubleValueOrBuilder>( + getMaxValue(), + getParentForChildren(), + isClean()); + maxValue_ = null; + } + return maxValueBuilder_; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.MetricEntry) + } + + // @@protoc_insertion_point(class_scope:tensorflow.MetricEntry) + private static final org.tensorflow.proto.MetricEntry DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.MetricEntry(); + } + + public static org.tensorflow.proto.MetricEntry getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public MetricEntry parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.MetricEntry getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + +} + diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MetricEntryOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MetricEntryOrBuilder.java new file mode 100644 index 00000000000..e8f2867a14a --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/MetricEntryOrBuilder.java @@ -0,0 +1,93 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public interface MetricEntryOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.MetricEntry) + com.google.protobuf.MessageOrBuilder { + + /** + * 
    +   * Metric name
+   *
    + * + * string name = 1; + * @return The name. + */ + java.lang.String getName(); + /** + * 
    +   * Metric name
+   *
    + * + * string name = 1; + * @return The bytes for name. + */ + com.google.protobuf.ByteString + getNameBytes(); + + /** + * 
    +   * Metric value
+   *
    + * + * double value = 2; + * @return The value. + */ + double getValue(); + + /** + * 
    +   * The minimum acceptable value for the metric if specified
+   *
    + * + * .google.protobuf.DoubleValue min_value = 3; + * @return Whether the minValue field is set. + */ + boolean hasMinValue(); + /** + * 
    +   * The minimum acceptable value for the metric if specified
+   *
    + * + * .google.protobuf.DoubleValue min_value = 3; + * @return The minValue. + */ + com.google.protobuf.DoubleValue getMinValue(); + /** + * 
    +   * The minimum acceptable value for the metric if specified
+   *
    + * + * .google.protobuf.DoubleValue min_value = 3; + */ + com.google.protobuf.DoubleValueOrBuilder getMinValueOrBuilder(); + + /** + * 
    +   * The maximum acceptable value for the metric if specified
+   *
    + * + * .google.protobuf.DoubleValue max_value = 4; + * @return Whether the maxValue field is set. + */ + boolean hasMaxValue(); + /** + * 
    +   * The maximum acceptable value for the metric if specified
+   *
    + * + * .google.protobuf.DoubleValue max_value = 4; + * @return The maxValue. + */ + com.google.protobuf.DoubleValue getMaxValue(); + /** + * 
    +   * The maximum acceptable value for the metric if specified
+   *
    + * + * .google.protobuf.DoubleValue max_value = 4; + */ + com.google.protobuf.DoubleValueOrBuilder getMaxValueOrBuilder(); +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/PlatformInfo.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/PlatformInfo.java new file mode 100644 index 00000000000..d2875cf5041 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/PlatformInfo.java @@ -0,0 +1,1391 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +/** + * Protobuf type {@code tensorflow.PlatformInfo} + */ +public final class PlatformInfo extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.PlatformInfo) + PlatformInfoOrBuilder { +private static final long serialVersionUID = 0L; + // Use PlatformInfo.newBuilder() to construct. + private PlatformInfo(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private PlatformInfo() { + bits_ = ""; + linkage_ = ""; + machine_ = ""; + release_ = ""; + system_ = ""; + version_ = ""; + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new PlatformInfo(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_PlatformInfo_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_PlatformInfo_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.PlatformInfo.class, org.tensorflow.proto.PlatformInfo.Builder.class); + } + + public static final int BITS_FIELD_NUMBER = 1; + private volatile java.lang.Object bits_; + /** + * 
    +   * e.g. '64bit'
+   *
    + * + * string bits = 1; + * @return The bits. + */ + @java.lang.Override + public java.lang.String getBits() { + java.lang.Object ref = bits_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + bits_ = s; + return s; + } + } + /** + * 
    +   * e.g. '64bit'
+   *
    + * + * string bits = 1; + * @return The bytes for bits. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getBitsBytes() { + java.lang.Object ref = bits_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + bits_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int LINKAGE_FIELD_NUMBER = 2; + private volatile java.lang.Object linkage_; + /** + * 
    +   * e.g. 'ELF'
+   *
    + * + * string linkage = 2; + * @return The linkage. + */ + @java.lang.Override + public java.lang.String getLinkage() { + java.lang.Object ref = linkage_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + linkage_ = s; + return s; + } + } + /** + * 
    +   * e.g. 'ELF'
+   *
    + * + * string linkage = 2; + * @return The bytes for linkage. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getLinkageBytes() { + java.lang.Object ref = linkage_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + linkage_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int MACHINE_FIELD_NUMBER = 3; + private volatile java.lang.Object machine_; + /** + * 
    +   * e.g. 'i386'
+   *
    + * + * string machine = 3; + * @return The machine. + */ + @java.lang.Override + public java.lang.String getMachine() { + java.lang.Object ref = machine_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + machine_ = s; + return s; + } + } + /** + * 
    +   * e.g. 'i386'
+   *
    + * + * string machine = 3; + * @return The bytes for machine. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getMachineBytes() { + java.lang.Object ref = machine_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + machine_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int RELEASE_FIELD_NUMBER = 4; + private volatile java.lang.Object release_; + /** + * 
    +   * e.g. '3.13.0-76-generic'
+   *
    + * + * string release = 4; + * @return The release. + */ + @java.lang.Override + public java.lang.String getRelease() { + java.lang.Object ref = release_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + release_ = s; + return s; + } + } + /** + * 
    +   * e.g. '3.13.0-76-generic'
+   *
    + * + * string release = 4; + * @return The bytes for release. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getReleaseBytes() { + java.lang.Object ref = release_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + release_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int SYSTEM_FIELD_NUMBER = 5; + private volatile java.lang.Object system_; + /** + * 
    +   * e.g. 'Linux'
+   *
    + * + * string system = 5; + * @return The system. + */ + @java.lang.Override + public java.lang.String getSystem() { + java.lang.Object ref = system_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + system_ = s; + return s; + } + } + /** + * 
    +   * e.g. 'Linux'
+   *
    + * + * string system = 5; + * @return The bytes for system. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getSystemBytes() { + java.lang.Object ref = system_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + system_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int VERSION_FIELD_NUMBER = 6; + private volatile java.lang.Object version_; + /** + * 
    +   * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
+   *
    + * + * string version = 6; + * @return The version. + */ + @java.lang.Override + public java.lang.String getVersion() { + java.lang.Object ref = version_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + version_ = s; + return s; + } + } + /** + * 
    +   * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
+   *
    + * + * string version = 6; + * @return The bytes for version. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getVersionBytes() { + java.lang.Object ref = version_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + version_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(bits_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 1, bits_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(linkage_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 2, linkage_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(machine_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 3, machine_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(release_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 4, release_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(system_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 5, system_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(version_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 6, version_); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(bits_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, bits_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(linkage_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(2, linkage_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(machine_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(3, machine_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(release_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(4, release_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(system_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(5, system_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(version_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(6, version_); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.PlatformInfo)) { + return super.equals(obj); + } + org.tensorflow.proto.PlatformInfo other = (org.tensorflow.proto.PlatformInfo) obj; + + if (!getBits() + .equals(other.getBits())) return false; + if (!getLinkage() + .equals(other.getLinkage())) return false; + if (!getMachine() + .equals(other.getMachine())) return false; + if (!getRelease() + .equals(other.getRelease())) return false; + if (!getSystem() + .equals(other.getSystem())) return false; + if (!getVersion() + .equals(other.getVersion())) return false; + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + BITS_FIELD_NUMBER; + hash = (53 * hash) + getBits().hashCode(); + hash = (37 * hash) + LINKAGE_FIELD_NUMBER; + hash = (53 * hash) + getLinkage().hashCode(); + hash = (37 * hash) + MACHINE_FIELD_NUMBER; + hash = (53 * hash) + getMachine().hashCode(); + hash = (37 * hash) + RELEASE_FIELD_NUMBER; + hash = (53 * hash) + getRelease().hashCode(); + hash = (37 * hash) + SYSTEM_FIELD_NUMBER; + hash = (53 * hash) + getSystem().hashCode(); + hash = (37 * hash) + VERSION_FIELD_NUMBER; + hash = (53 * hash) + getVersion().hashCode(); + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.PlatformInfo parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.PlatformInfo parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.PlatformInfo parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.PlatformInfo parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.PlatformInfo parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.PlatformInfo parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.PlatformInfo parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.PlatformInfo parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.PlatformInfo parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.PlatformInfo parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.PlatformInfo parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.PlatformInfo parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.PlatformInfo prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * Protobuf type {@code tensorflow.PlatformInfo} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.PlatformInfo) + org.tensorflow.proto.PlatformInfoOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_PlatformInfo_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_PlatformInfo_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.PlatformInfo.class, org.tensorflow.proto.PlatformInfo.Builder.class); + } + + // Construct using org.tensorflow.proto.PlatformInfo.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + bits_ = ""; + + linkage_ = ""; + + machine_ = ""; + + release_ = ""; + + system_ = ""; + + version_ = ""; + + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_PlatformInfo_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.PlatformInfo getDefaultInstanceForType() { + return org.tensorflow.proto.PlatformInfo.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.PlatformInfo build() { + org.tensorflow.proto.PlatformInfo result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.PlatformInfo buildPartial() { + org.tensorflow.proto.PlatformInfo result = new org.tensorflow.proto.PlatformInfo(this); + result.bits_ = bits_; + result.linkage_ = linkage_; + result.machine_ = machine_; + result.release_ = release_; + result.system_ = system_; + result.version_ = version_; + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.PlatformInfo) { + return mergeFrom((org.tensorflow.proto.PlatformInfo)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.PlatformInfo other) { + if (other == org.tensorflow.proto.PlatformInfo.getDefaultInstance()) return this; + if (!other.getBits().isEmpty()) { + bits_ = other.bits_; + onChanged(); + } + if (!other.getLinkage().isEmpty()) { + linkage_ = other.linkage_; + onChanged(); + } + if (!other.getMachine().isEmpty()) { + machine_ = other.machine_; + onChanged(); + } + if (!other.getRelease().isEmpty()) { + release_ = other.release_; + onChanged(); + } + if (!other.getSystem().isEmpty()) { + system_ = other.system_; + onChanged(); + } + if (!other.getVersion().isEmpty()) { + version_ = other.version_; + onChanged(); + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 10: { + bits_ = input.readStringRequireUtf8(); + + break; + } // case 10 + case 18: { + linkage_ = input.readStringRequireUtf8(); + + break; + } // case 18 + case 26: { + machine_ = input.readStringRequireUtf8(); + + break; + } // case 26 + case 34: { + release_ = input.readStringRequireUtf8(); + + break; + } // case 34 + case 42: { + system_ = input.readStringRequireUtf8(); + + break; + } // case 42 + case 50: { + version_ = input.readStringRequireUtf8(); + + break; + } // case 50 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + + private java.lang.Object bits_ = ""; + /** + * 
    +     * e.g. '64bit'
+     *
    + * + * string bits = 1; + * @return The bits. + */ + public java.lang.String getBits() { + java.lang.Object ref = bits_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + bits_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * e.g. '64bit'
+     *
    + * + * string bits = 1; + * @return The bytes for bits. + */ + public com.google.protobuf.ByteString + getBitsBytes() { + java.lang.Object ref = bits_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + bits_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * e.g. '64bit'
+     *
    + * + * string bits = 1; + * @param value The bits to set. + * @return This builder for chaining. + */ + public Builder setBits( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + bits_ = value; + onChanged(); + return this; + } + /** + * 
    +     * e.g. '64bit'
+     *
    + * + * string bits = 1; + * @return This builder for chaining. + */ + public Builder clearBits() { + + bits_ = getDefaultInstance().getBits(); + onChanged(); + return this; + } + /** + * 
    +     * e.g. '64bit'
+     *
    + * + * string bits = 1; + * @param value The bytes for bits to set. + * @return This builder for chaining. + */ + public Builder setBitsBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + bits_ = value; + onChanged(); + return this; + } + + private java.lang.Object linkage_ = ""; + /** + * 
    +     * e.g. 'ELF'
+     *
    + * + * string linkage = 2; + * @return The linkage. + */ + public java.lang.String getLinkage() { + java.lang.Object ref = linkage_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + linkage_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * e.g. 'ELF'
+     *
    + * + * string linkage = 2; + * @return The bytes for linkage. + */ + public com.google.protobuf.ByteString + getLinkageBytes() { + java.lang.Object ref = linkage_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + linkage_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * e.g. 'ELF'
+     *
    + * + * string linkage = 2; + * @param value The linkage to set. + * @return This builder for chaining. + */ + public Builder setLinkage( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + linkage_ = value; + onChanged(); + return this; + } + /** + * 
    +     * e.g. 'ELF'
+     *
    + * + * string linkage = 2; + * @return This builder for chaining. + */ + public Builder clearLinkage() { + + linkage_ = getDefaultInstance().getLinkage(); + onChanged(); + return this; + } + /** + * 
    +     * e.g. 'ELF'
+     *
    + * + * string linkage = 2; + * @param value The bytes for linkage to set. + * @return This builder for chaining. + */ + public Builder setLinkageBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + linkage_ = value; + onChanged(); + return this; + } + + private java.lang.Object machine_ = ""; + /** + * 
    +     * e.g. 'i386'
+     *
    + * + * string machine = 3; + * @return The machine. + */ + public java.lang.String getMachine() { + java.lang.Object ref = machine_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + machine_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * e.g. 'i386'
+     *
    + * + * string machine = 3; + * @return The bytes for machine. + */ + public com.google.protobuf.ByteString + getMachineBytes() { + java.lang.Object ref = machine_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + machine_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * e.g. 'i386'
+     *
    + * + * string machine = 3; + * @param value The machine to set. + * @return This builder for chaining. + */ + public Builder setMachine( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + machine_ = value; + onChanged(); + return this; + } + /** + * 
    +     * e.g. 'i386'
+     *
    + * + * string machine = 3; + * @return This builder for chaining. + */ + public Builder clearMachine() { + + machine_ = getDefaultInstance().getMachine(); + onChanged(); + return this; + } + /** + * 
    +     * e.g. 'i386'
+     *
    + * + * string machine = 3; + * @param value The bytes for machine to set. + * @return This builder for chaining. + */ + public Builder setMachineBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + machine_ = value; + onChanged(); + return this; + } + + private java.lang.Object release_ = ""; + /** + * 
    +     * e.g. '3.13.0-76-generic'
+     *
    + * + * string release = 4; + * @return The release. + */ + public java.lang.String getRelease() { + java.lang.Object ref = release_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + release_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * e.g. '3.13.0-76-generic'
+     *
    + * + * string release = 4; + * @return The bytes for release. + */ + public com.google.protobuf.ByteString + getReleaseBytes() { + java.lang.Object ref = release_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + release_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * e.g. '3.13.0-76-generic'
+     *
    + * + * string release = 4; + * @param value The release to set. + * @return This builder for chaining. + */ + public Builder setRelease( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + release_ = value; + onChanged(); + return this; + } + /** + * 
    +     * e.g. '3.13.0-76-generic'
+     *
    + * + * string release = 4; + * @return This builder for chaining. + */ + public Builder clearRelease() { + + release_ = getDefaultInstance().getRelease(); + onChanged(); + return this; + } + /** + * 
    +     * e.g. '3.13.0-76-generic'
+     *
    + * + * string release = 4; + * @param value The bytes for release to set. + * @return This builder for chaining. + */ + public Builder setReleaseBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + release_ = value; + onChanged(); + return this; + } + + private java.lang.Object system_ = ""; + /** + * 
    +     * e.g. 'Linux'
+     *
    + * + * string system = 5; + * @return The system. + */ + public java.lang.String getSystem() { + java.lang.Object ref = system_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + system_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * e.g. 'Linux'
+     *
    + * + * string system = 5; + * @return The bytes for system. + */ + public com.google.protobuf.ByteString + getSystemBytes() { + java.lang.Object ref = system_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + system_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * e.g. 'Linux'
+     *
    + * + * string system = 5; + * @param value The system to set. + * @return This builder for chaining. + */ + public Builder setSystem( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + system_ = value; + onChanged(); + return this; + } + /** + * 
    +     * e.g. 'Linux'
+     *
    + * + * string system = 5; + * @return This builder for chaining. + */ + public Builder clearSystem() { + + system_ = getDefaultInstance().getSystem(); + onChanged(); + return this; + } + /** + * 
    +     * e.g. 'Linux'
+     *
    + * + * string system = 5; + * @param value The bytes for system to set. + * @return This builder for chaining. + */ + public Builder setSystemBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + system_ = value; + onChanged(); + return this; + } + + private java.lang.Object version_ = ""; + /** + * 
    +     * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
+     *
    + * + * string version = 6; + * @return The version. + */ + public java.lang.String getVersion() { + java.lang.Object ref = version_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + version_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
+     *
    + * + * string version = 6; + * @return The bytes for version. + */ + public com.google.protobuf.ByteString + getVersionBytes() { + java.lang.Object ref = version_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + version_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
+     *
    + * + * string version = 6; + * @param value The version to set. + * @return This builder for chaining. + */ + public Builder setVersion( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + version_ = value; + onChanged(); + return this; + } + /** + * 
    +     * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
+     *
    + * + * string version = 6; + * @return This builder for chaining. + */ + public Builder clearVersion() { + + version_ = getDefaultInstance().getVersion(); + onChanged(); + return this; + } + /** + * 
    +     * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
+     *
    + * + * string version = 6; + * @param value The bytes for version to set. + * @return This builder for chaining. + */ + public Builder setVersionBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + version_ = value; + onChanged(); + return this; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.PlatformInfo) + } + + // @@protoc_insertion_point(class_scope:tensorflow.PlatformInfo) + private static final org.tensorflow.proto.PlatformInfo DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.PlatformInfo(); + } + + public static org.tensorflow.proto.PlatformInfo getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public PlatformInfo parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.PlatformInfo getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + +} + diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/PlatformInfoOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/PlatformInfoOrBuilder.java new file mode 100644 index 00000000000..caade7d2f32 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/PlatformInfoOrBuilder.java @@ -0,0 +1,129 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public interface PlatformInfoOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.PlatformInfo) + com.google.protobuf.MessageOrBuilder { + + /** + * 
    +   * e.g. '64bit'
+   *
    + * + * string bits = 1; + * @return The bits. + */ + java.lang.String getBits(); + /** + * 
    +   * e.g. '64bit'
+   *
    + * + * string bits = 1; + * @return The bytes for bits. + */ + com.google.protobuf.ByteString + getBitsBytes(); + + /** + * 
    +   * e.g. 'ELF'
+   *
    + * + * string linkage = 2; + * @return The linkage. + */ + java.lang.String getLinkage(); + /** + * 
    +   * e.g. 'ELF'
+   *
    + * + * string linkage = 2; + * @return The bytes for linkage. + */ + com.google.protobuf.ByteString + getLinkageBytes(); + + /** + * 
    +   * e.g. 'i386'
+   *
    + * + * string machine = 3; + * @return The machine. + */ + java.lang.String getMachine(); + /** + * 
    +   * e.g. 'i386'
+   *
    + * + * string machine = 3; + * @return The bytes for machine. + */ + com.google.protobuf.ByteString + getMachineBytes(); + + /** + * 
    +   * e.g. '3.13.0-76-generic'
+   *
    + * + * string release = 4; + * @return The release. + */ + java.lang.String getRelease(); + /** + * 
    +   * e.g. '3.13.0-76-generic'
+   *
    + * + * string release = 4; + * @return The bytes for release. + */ + com.google.protobuf.ByteString + getReleaseBytes(); + + /** + * 
    +   * e.g. 'Linux'
+   *
    + * + * string system = 5; + * @return The system. + */ + java.lang.String getSystem(); + /** + * 
    +   * e.g. 'Linux'
+   *
    + * + * string system = 5; + * @return The bytes for system. + */ + com.google.protobuf.ByteString + getSystemBytes(); + + /** + * 
    +   * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
+   *
    + * + * string version = 6; + * @return The version. + */ + java.lang.String getVersion(); + /** + * 
    +   * e.g. '#120-Ubuntu SMP Mon Jan 18 15:59:10 UTC 2016'
+   *
    + * + * string version = 6; + * @return The bytes for version. + */ + com.google.protobuf.ByteString + getVersionBytes(); +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RunConfiguration.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RunConfiguration.java new file mode 100644 index 00000000000..f8f244b522c --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RunConfiguration.java @@ -0,0 +1,922 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +/** + * 
    + * Run-specific items such as arguments to the test / benchmark.
+ *
    + * + * Protobuf type {@code tensorflow.RunConfiguration} + */ +public final class RunConfiguration extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.RunConfiguration) + RunConfigurationOrBuilder { +private static final long serialVersionUID = 0L; + // Use RunConfiguration.newBuilder() to construct. + private RunConfiguration(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private RunConfiguration() { + argument_ = com.google.protobuf.LazyStringArrayList.EMPTY; + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new RunConfiguration(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_RunConfiguration_descriptor; + } + + @SuppressWarnings({"rawtypes"}) + @java.lang.Override + protected com.google.protobuf.MapField internalGetMapField( + int number) { + switch (number) { + case 2: + return internalGetEnvVars(); + default: + throw new RuntimeException( + "Invalid map field number: " + number); + } + } + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_RunConfiguration_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.RunConfiguration.class, org.tensorflow.proto.RunConfiguration.Builder.class); + } + + public static final int ARGUMENT_FIELD_NUMBER = 1; + private com.google.protobuf.LazyStringList argument_; + /** + * repeated string argument = 1; + * @return A list containing the argument. + */ + public com.google.protobuf.ProtocolStringList + getArgumentList() { + return argument_; + } + /** + * repeated string argument = 1; + * @return The count of argument. + */ + public int getArgumentCount() { + return argument_.size(); + } + /** + * repeated string argument = 1; + * @param index The index of the element to return. + * @return The argument at the given index. + */ + public java.lang.String getArgument(int index) { + return argument_.get(index); + } + /** + * repeated string argument = 1; + * @param index The index of the value to return. + * @return The bytes of the argument at the given index. + */ + public com.google.protobuf.ByteString + getArgumentBytes(int index) { + return argument_.getByteString(index); + } + + public static final int ENV_VARS_FIELD_NUMBER = 2; + private static final class EnvVarsDefaultEntryHolder { + static final com.google.protobuf.MapEntry< + java.lang.String, java.lang.String> defaultEntry = + com.google.protobuf.MapEntry + .newDefaultInstance( + org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_RunConfiguration_EnvVarsEntry_descriptor, + com.google.protobuf.WireFormat.FieldType.STRING, + "", + com.google.protobuf.WireFormat.FieldType.STRING, + ""); + } + private com.google.protobuf.MapField< + java.lang.String, java.lang.String> envVars_; + private com.google.protobuf.MapField + internalGetEnvVars() { + if (envVars_ == null) { + return com.google.protobuf.MapField.emptyMapField( + EnvVarsDefaultEntryHolder.defaultEntry); + } + return envVars_; + } + + public int getEnvVarsCount() { + return internalGetEnvVars().getMap().size(); + } + /** + * 
    +   * Environment variables used to run the test/benchmark.
+   *
    + * + * map<string, string> env_vars = 2; + */ + + @java.lang.Override + public boolean containsEnvVars( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + return internalGetEnvVars().getMap().containsKey(key); + } + /** + * Use {@link #getEnvVarsMap()} instead. + */ + @java.lang.Override + @java.lang.Deprecated + public java.util.Map getEnvVars() { + return getEnvVarsMap(); + } + /** + * 
    +   * Environment variables used to run the test/benchmark.
+   *
    + * + * map<string, string> env_vars = 2; + */ + @java.lang.Override + + public java.util.Map getEnvVarsMap() { + return internalGetEnvVars().getMap(); + } + /** + * 
    +   * Environment variables used to run the test/benchmark.
+   *
    + * + * map<string, string> env_vars = 2; + */ + @java.lang.Override + + public java.lang.String getEnvVarsOrDefault( + java.lang.String key, + java.lang.String defaultValue) { + if (key == null) { throw new NullPointerException("map key"); } + java.util.Map map = + internalGetEnvVars().getMap(); + return map.containsKey(key) ? map.get(key) : defaultValue; + } + /** + * 
    +   * Environment variables used to run the test/benchmark.
+   *
    + * + * map<string, string> env_vars = 2; + */ + @java.lang.Override + + public java.lang.String getEnvVarsOrThrow( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + java.util.Map map = + internalGetEnvVars().getMap(); + if (!map.containsKey(key)) { + throw new java.lang.IllegalArgumentException(); + } + return map.get(key); + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + for (int i = 0; i < argument_.size(); i++) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 1, argument_.getRaw(i)); + } + com.google.protobuf.GeneratedMessageV3 + .serializeStringMapTo( + output, + internalGetEnvVars(), + EnvVarsDefaultEntryHolder.defaultEntry, + 2); + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + { + int dataSize = 0; + for (int i = 0; i < argument_.size(); i++) { + dataSize += computeStringSizeNoTag(argument_.getRaw(i)); + } + size += dataSize; + size += 1 * getArgumentList().size(); + } + for (java.util.Map.Entry entry + : internalGetEnvVars().getMap().entrySet()) { + com.google.protobuf.MapEntry + envVars__ = EnvVarsDefaultEntryHolder.defaultEntry.newBuilderForType() + .setKey(entry.getKey()) + .setValue(entry.getValue()) + .build(); + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(2, envVars__); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.RunConfiguration)) { + return super.equals(obj); + } + org.tensorflow.proto.RunConfiguration other = (org.tensorflow.proto.RunConfiguration) obj; + + if (!getArgumentList() + .equals(other.getArgumentList())) return false; + if (!internalGetEnvVars().equals( + other.internalGetEnvVars())) return false; + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + if (getArgumentCount() > 0) { + hash = (37 * hash) + ARGUMENT_FIELD_NUMBER; + hash = (53 * hash) + getArgumentList().hashCode(); + } + if (!internalGetEnvVars().getMap().isEmpty()) { + hash = (37 * hash) + ENV_VARS_FIELD_NUMBER; + hash = (53 * hash) + internalGetEnvVars().hashCode(); + } + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.RunConfiguration parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.RunConfiguration parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.RunConfiguration parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.RunConfiguration parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.RunConfiguration parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.RunConfiguration parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.RunConfiguration parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.RunConfiguration parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.RunConfiguration parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.RunConfiguration parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.RunConfiguration parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.RunConfiguration parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.RunConfiguration prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * 
    +   * Run-specific items such as arguments to the test / benchmark.
+   *
    + * + * Protobuf type {@code tensorflow.RunConfiguration} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.RunConfiguration) + org.tensorflow.proto.RunConfigurationOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_RunConfiguration_descriptor; + } + + @SuppressWarnings({"rawtypes"}) + protected com.google.protobuf.MapField internalGetMapField( + int number) { + switch (number) { + case 2: + return internalGetEnvVars(); + default: + throw new RuntimeException( + "Invalid map field number: " + number); + } + } + @SuppressWarnings({"rawtypes"}) + protected com.google.protobuf.MapField internalGetMutableMapField( + int number) { + switch (number) { + case 2: + return internalGetMutableEnvVars(); + default: + throw new RuntimeException( + "Invalid map field number: " + number); + } + } + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_RunConfiguration_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.RunConfiguration.class, org.tensorflow.proto.RunConfiguration.Builder.class); + } + + // Construct using org.tensorflow.proto.RunConfiguration.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + argument_ = com.google.protobuf.LazyStringArrayList.EMPTY; + bitField0_ = (bitField0_ & ~0x00000001); + internalGetMutableEnvVars().clear(); + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_RunConfiguration_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.RunConfiguration getDefaultInstanceForType() { + return org.tensorflow.proto.RunConfiguration.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.RunConfiguration build() { + org.tensorflow.proto.RunConfiguration result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.RunConfiguration buildPartial() { + org.tensorflow.proto.RunConfiguration result = new org.tensorflow.proto.RunConfiguration(this); + int from_bitField0_ = bitField0_; + if (((bitField0_ & 0x00000001) != 0)) { + argument_ = argument_.getUnmodifiableView(); + bitField0_ = (bitField0_ & ~0x00000001); + } + result.argument_ = argument_; + result.envVars_ = internalGetEnvVars(); + result.envVars_.makeImmutable(); + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.RunConfiguration) { + return mergeFrom((org.tensorflow.proto.RunConfiguration)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.RunConfiguration other) { + if (other == org.tensorflow.proto.RunConfiguration.getDefaultInstance()) return this; + if (!other.argument_.isEmpty()) { + if (argument_.isEmpty()) { + argument_ = other.argument_; + bitField0_ = (bitField0_ & ~0x00000001); + } else { + ensureArgumentIsMutable(); + argument_.addAll(other.argument_); + } + onChanged(); + } + internalGetMutableEnvVars().mergeFrom( + other.internalGetEnvVars()); + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 10: { + java.lang.String s = input.readStringRequireUtf8(); + ensureArgumentIsMutable(); + argument_.add(s); + break; + } // case 10 + case 18: { + com.google.protobuf.MapEntry + envVars__ = input.readMessage( + EnvVarsDefaultEntryHolder.defaultEntry.getParserForType(), extensionRegistry); + internalGetMutableEnvVars().getMutableMap().put( + envVars__.getKey(), envVars__.getValue()); + break; + } // case 18 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + private int bitField0_; + + private com.google.protobuf.LazyStringList argument_ = com.google.protobuf.LazyStringArrayList.EMPTY; + private void ensureArgumentIsMutable() { + if (!((bitField0_ & 0x00000001) != 0)) { + argument_ = new com.google.protobuf.LazyStringArrayList(argument_); + bitField0_ |= 0x00000001; + } + } + /** + * repeated string argument = 1; + * @return A list containing the argument. + */ + public com.google.protobuf.ProtocolStringList + getArgumentList() { + return argument_.getUnmodifiableView(); + } + /** + * repeated string argument = 1; + * @return The count of argument. + */ + public int getArgumentCount() { + return argument_.size(); + } + /** + * repeated string argument = 1; + * @param index The index of the element to return. + * @return The argument at the given index. + */ + public java.lang.String getArgument(int index) { + return argument_.get(index); + } + /** + * repeated string argument = 1; + * @param index The index of the value to return. + * @return The bytes of the argument at the given index. + */ + public com.google.protobuf.ByteString + getArgumentBytes(int index) { + return argument_.getByteString(index); + } + /** + * repeated string argument = 1; + * @param index The index to set the value at. + * @param value The argument to set. + * @return This builder for chaining. + */ + public Builder setArgument( + int index, java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + ensureArgumentIsMutable(); + argument_.set(index, value); + onChanged(); + return this; + } + /** + * repeated string argument = 1; + * @param value The argument to add. + * @return This builder for chaining. + */ + public Builder addArgument( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + ensureArgumentIsMutable(); + argument_.add(value); + onChanged(); + return this; + } + /** + * repeated string argument = 1; + * @param values The argument to add. + * @return This builder for chaining. + */ + public Builder addAllArgument( + java.lang.Iterable values) { + ensureArgumentIsMutable(); + com.google.protobuf.AbstractMessageLite.Builder.addAll( + values, argument_); + onChanged(); + return this; + } + /** + * repeated string argument = 1; + * @return This builder for chaining. + */ + public Builder clearArgument() { + argument_ = com.google.protobuf.LazyStringArrayList.EMPTY; + bitField0_ = (bitField0_ & ~0x00000001); + onChanged(); + return this; + } + /** + * repeated string argument = 1; + * @param value The bytes of the argument to add. + * @return This builder for chaining. + */ + public Builder addArgumentBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + ensureArgumentIsMutable(); + argument_.add(value); + onChanged(); + return this; + } + + private com.google.protobuf.MapField< + java.lang.String, java.lang.String> envVars_; + private com.google.protobuf.MapField + internalGetEnvVars() { + if (envVars_ == null) { + return com.google.protobuf.MapField.emptyMapField( + EnvVarsDefaultEntryHolder.defaultEntry); + } + return envVars_; + } + private com.google.protobuf.MapField + internalGetMutableEnvVars() { + onChanged();; + if (envVars_ == null) { + envVars_ = com.google.protobuf.MapField.newMapField( + EnvVarsDefaultEntryHolder.defaultEntry); + } + if (!envVars_.isMutable()) { + envVars_ = envVars_.copy(); + } + return envVars_; + } + + public int getEnvVarsCount() { + return internalGetEnvVars().getMap().size(); + } + /** + * 
    +     * Environment variables used to run the test/benchmark.
+     *
    + * + * map<string, string> env_vars = 2; + */ + + @java.lang.Override + public boolean containsEnvVars( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + return internalGetEnvVars().getMap().containsKey(key); + } + /** + * Use {@link #getEnvVarsMap()} instead. + */ + @java.lang.Override + @java.lang.Deprecated + public java.util.Map getEnvVars() { + return getEnvVarsMap(); + } + /** + * 
    +     * Environment variables used to run the test/benchmark.
+     *
    + * + * map<string, string> env_vars = 2; + */ + @java.lang.Override + + public java.util.Map getEnvVarsMap() { + return internalGetEnvVars().getMap(); + } + /** + * 
    +     * Environment variables used to run the test/benchmark.
+     *
    + * + * map<string, string> env_vars = 2; + */ + @java.lang.Override + + public java.lang.String getEnvVarsOrDefault( + java.lang.String key, + java.lang.String defaultValue) { + if (key == null) { throw new NullPointerException("map key"); } + java.util.Map map = + internalGetEnvVars().getMap(); + return map.containsKey(key) ? map.get(key) : defaultValue; + } + /** + * 
    +     * Environment variables used to run the test/benchmark.
+     *
    + * + * map<string, string> env_vars = 2; + */ + @java.lang.Override + + public java.lang.String getEnvVarsOrThrow( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + java.util.Map map = + internalGetEnvVars().getMap(); + if (!map.containsKey(key)) { + throw new java.lang.IllegalArgumentException(); + } + return map.get(key); + } + + public Builder clearEnvVars() { + internalGetMutableEnvVars().getMutableMap() + .clear(); + return this; + } + /** + * 
    +     * Environment variables used to run the test/benchmark.
+     *
    + * + * map<string, string> env_vars = 2; + */ + + public Builder removeEnvVars( + java.lang.String key) { + if (key == null) { throw new NullPointerException("map key"); } + internalGetMutableEnvVars().getMutableMap() + .remove(key); + return this; + } + /** + * Use alternate mutation accessors instead. + */ + @java.lang.Deprecated + public java.util.Map + getMutableEnvVars() { + return internalGetMutableEnvVars().getMutableMap(); + } + /** + * 
    +     * Environment variables used to run the test/benchmark.
+     *
    + * + * map<string, string> env_vars = 2; + */ + public Builder putEnvVars( + java.lang.String key, + java.lang.String value) { + if (key == null) { throw new NullPointerException("map key"); } + if (value == null) { + throw new NullPointerException("map value"); +} + + internalGetMutableEnvVars().getMutableMap() + .put(key, value); + return this; + } + /** + * 
    +     * Environment variables used to run the test/benchmark.
+     *
    + * + * map<string, string> env_vars = 2; + */ + + public Builder putAllEnvVars( + java.util.Map values) { + internalGetMutableEnvVars().getMutableMap() + .putAll(values); + return this; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.RunConfiguration) + } + + // @@protoc_insertion_point(class_scope:tensorflow.RunConfiguration) + private static final org.tensorflow.proto.RunConfiguration DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.RunConfiguration(); + } + + public static org.tensorflow.proto.RunConfiguration getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public RunConfiguration parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.RunConfiguration getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + +} + diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RunConfigurationOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RunConfigurationOrBuilder.java new file mode 100644 index 00000000000..4f2ef9a6b2c --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/RunConfigurationOrBuilder.java @@ -0,0 +1,90 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public interface RunConfigurationOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.RunConfiguration) + com.google.protobuf.MessageOrBuilder { + + /** + * repeated string argument = 1; + * @return A list containing the argument. + */ + java.util.List + getArgumentList(); + /** + * repeated string argument = 1; + * @return The count of argument. + */ + int getArgumentCount(); + /** + * repeated string argument = 1; + * @param index The index of the element to return. + * @return The argument at the given index. + */ + java.lang.String getArgument(int index); + /** + * repeated string argument = 1; + * @param index The index of the value to return. + * @return The bytes of the argument at the given index. + */ + com.google.protobuf.ByteString + getArgumentBytes(int index); + + /** + * 
    +   * Environment variables used to run the test/benchmark.
+   *
    + * + * map<string, string> env_vars = 2; + */ + int getEnvVarsCount(); + /** + * 
    +   * Environment variables used to run the test/benchmark.
+   *
    + * + * map<string, string> env_vars = 2; + */ + boolean containsEnvVars( + java.lang.String key); + /** + * Use {@link #getEnvVarsMap()} instead. + */ + @java.lang.Deprecated + java.util.Map + getEnvVars(); + /** + * 
    +   * Environment variables used to run the test/benchmark.
+   *
    + * + * map<string, string> env_vars = 2; + */ + java.util.Map + getEnvVarsMap(); + /** + * 
    +   * Environment variables used to run the test/benchmark.
+   *
    + * + * map<string, string> env_vars = 2; + */ + + /* nullable */ +java.lang.String getEnvVarsOrDefault( + java.lang.String key, + /* nullable */ +java.lang.String defaultValue); + /** + * 
    +   * Environment variables used to run the test/benchmark.
+   *
    + * + * map<string, string> env_vars = 2; + */ + + java.lang.String getEnvVarsOrThrow( + java.lang.String key); +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestLogProtos.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestLogProtos.java new file mode 100644 index 00000000000..f56cbf6b82b --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestLogProtos.java @@ -0,0 +1,287 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public final class TestLogProtos { + private TestLogProtos() {} + public static void registerAllExtensions( + com.google.protobuf.ExtensionRegistryLite registry) { + } + + public static void registerAllExtensions( + com.google.protobuf.ExtensionRegistry registry) { + registerAllExtensions( + (com.google.protobuf.ExtensionRegistryLite) registry); + } + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_EntryValue_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_EntryValue_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_MetricEntry_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_MetricEntry_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_BenchmarkEntry_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_BenchmarkEntry_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_BenchmarkEntry_ExtrasEntry_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_BenchmarkEntry_ExtrasEntry_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_BenchmarkEntries_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_BenchmarkEntries_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_BuildConfiguration_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_BuildConfiguration_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_CommitId_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_CommitId_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_CPUInfo_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_CPUInfo_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_CPUInfo_CacheSizeEntry_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_CPUInfo_CacheSizeEntry_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_MemoryInfo_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_MemoryInfo_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_GPUInfo_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_GPUInfo_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_PlatformInfo_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_PlatformInfo_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_AvailableDeviceInfo_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_AvailableDeviceInfo_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_MachineConfiguration_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_MachineConfiguration_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_RunConfiguration_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_RunConfiguration_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_RunConfiguration_EnvVarsEntry_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_RunConfiguration_EnvVarsEntry_fieldAccessorTable; + static final com.google.protobuf.Descriptors.Descriptor + internal_static_tensorflow_TestResults_descriptor; + static final + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internal_static_tensorflow_TestResults_fieldAccessorTable; + + public static com.google.protobuf.Descriptors.FileDescriptor + getDescriptor() { + return descriptor; + } + private static com.google.protobuf.Descriptors.FileDescriptor + descriptor; + static { + 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"\032E\n\013ExtrasEntry\022\013\n\003key\030\001 \001(\t\022%\n\005value\030\002 " + + "\001(\0132\026.tensorflow.EntryValue:\0028\001\"=\n\020Bench" + + "markEntries\022)\n\005entry\030\001 \003(\0132\032.tensorflow." + + "BenchmarkEntry\"B\n\022BuildConfiguration\022\014\n\004" + + "mode\030\001 \001(\t\022\020\n\010cc_flags\030\002 \003(\t\022\014\n\004opts\030\003 \003" + + "(\t\"f\n\010CommitId\022\024\n\nchangelist\030\001 \001(\003H\000\022\016\n\004" + + "hash\030\002 \001(\tH\000\022\020\n\010snapshot\030\003 \001(\t\022\032\n\022pendin" + + "g_changelist\030\004 \001(\003B\006\n\004kind\"\336\001\n\007CPUInfo\022\021" + + "\n\tnum_cores\030\001 \001(\003\022\031\n\021num_cores_allowed\030\002" + + " \001(\003\022\023\n\013mhz_per_cpu\030\003 \001(\001\022\020\n\010cpu_info\030\004 " + + "\001(\t\022\024\n\014cpu_governor\030\005 \001(\t\0226\n\ncache_size\030" + + "\006 \003(\0132\".tensorflow.CPUInfo.CacheSizeEntr" + + "y\0320\n\016CacheSizeEntry\022\013\n\003key\030\001 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\001(\013" + + "2 .tensorflow.MachineConfiguration\0227\n\021ru" + + "n_configuration\030\010 \001(\0132\034.tensorflow.RunCo" + + "nfiguration\022\014\n\004name\030\t \001(\t\022=\n\016benchmark_t" + + "ype\030\n \001(\0162%.tensorflow.TestResults.Bench" + + "markType\022\020\n\010run_mode\030\013 \001(\t\022\022\n\ntf_version" + + "\030\014 \001(\t\"\210\001\n\rBenchmarkType\022\013\n\007UNKNOWN\020\000\022\026\n" + + "\022CPP_MICROBENCHMARK\020\001\022\024\n\020PYTHON_BENCHMAR" + + "K\020\002\022\025\n\021ANDROID_BENCHMARK\020\003\022\022\n\016EDGE_BENCH" + + "MARK\020\004\022\021\n\rIOS_BENCHMARK\020\005B*\n\024org.tensorf" + + "low.protoB\rTestLogProtosP\001\370\001\001b\006proto3" + }; + descriptor = com.google.protobuf.Descriptors.FileDescriptor + .internalBuildGeneratedFileFrom(descriptorData, + new com.google.protobuf.Descriptors.FileDescriptor[] { + com.google.protobuf.AnyProto.getDescriptor(), + com.google.protobuf.WrappersProto.getDescriptor(), + }); + internal_static_tensorflow_EntryValue_descriptor = + getDescriptor().getMessageTypes().get(0); + internal_static_tensorflow_EntryValue_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_EntryValue_descriptor, + new java.lang.String[] { "DoubleValue", "StringValue", "Kind", }); + internal_static_tensorflow_MetricEntry_descriptor = + getDescriptor().getMessageTypes().get(1); + internal_static_tensorflow_MetricEntry_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_MetricEntry_descriptor, + new java.lang.String[] { "Name", "Value", "MinValue", "MaxValue", }); + internal_static_tensorflow_BenchmarkEntry_descriptor = + getDescriptor().getMessageTypes().get(2); + internal_static_tensorflow_BenchmarkEntry_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_BenchmarkEntry_descriptor, + new java.lang.String[] { "Name", "Iters", "CpuTime", "WallTime", "Throughput", "Extras", "Metrics", }); + internal_static_tensorflow_BenchmarkEntry_ExtrasEntry_descriptor = + internal_static_tensorflow_BenchmarkEntry_descriptor.getNestedTypes().get(0); + internal_static_tensorflow_BenchmarkEntry_ExtrasEntry_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_BenchmarkEntry_ExtrasEntry_descriptor, + new java.lang.String[] { "Key", "Value", }); + internal_static_tensorflow_BenchmarkEntries_descriptor = + getDescriptor().getMessageTypes().get(3); + internal_static_tensorflow_BenchmarkEntries_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_BenchmarkEntries_descriptor, + new java.lang.String[] { "Entry", }); + internal_static_tensorflow_BuildConfiguration_descriptor = + getDescriptor().getMessageTypes().get(4); + internal_static_tensorflow_BuildConfiguration_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_BuildConfiguration_descriptor, + new java.lang.String[] { "Mode", "CcFlags", "Opts", }); + internal_static_tensorflow_CommitId_descriptor = + getDescriptor().getMessageTypes().get(5); + internal_static_tensorflow_CommitId_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_CommitId_descriptor, + new java.lang.String[] { "Changelist", "Hash", "Snapshot", "PendingChangelist", "Kind", }); + internal_static_tensorflow_CPUInfo_descriptor = + getDescriptor().getMessageTypes().get(6); + internal_static_tensorflow_CPUInfo_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_CPUInfo_descriptor, + new java.lang.String[] { "NumCores", "NumCoresAllowed", "MhzPerCpu", "CpuInfo", "CpuGovernor", "CacheSize", }); + internal_static_tensorflow_CPUInfo_CacheSizeEntry_descriptor = + internal_static_tensorflow_CPUInfo_descriptor.getNestedTypes().get(0); + internal_static_tensorflow_CPUInfo_CacheSizeEntry_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_CPUInfo_CacheSizeEntry_descriptor, + new java.lang.String[] { "Key", "Value", }); + internal_static_tensorflow_MemoryInfo_descriptor = + getDescriptor().getMessageTypes().get(7); + internal_static_tensorflow_MemoryInfo_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_MemoryInfo_descriptor, + new java.lang.String[] { "Total", "Available", }); + internal_static_tensorflow_GPUInfo_descriptor = + getDescriptor().getMessageTypes().get(8); + internal_static_tensorflow_GPUInfo_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_GPUInfo_descriptor, + new java.lang.String[] { "Model", "Uuid", "BusId", }); + internal_static_tensorflow_PlatformInfo_descriptor = + getDescriptor().getMessageTypes().get(9); + internal_static_tensorflow_PlatformInfo_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_PlatformInfo_descriptor, + new java.lang.String[] { "Bits", "Linkage", "Machine", "Release", "System", "Version", }); + internal_static_tensorflow_AvailableDeviceInfo_descriptor = + getDescriptor().getMessageTypes().get(10); + internal_static_tensorflow_AvailableDeviceInfo_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_AvailableDeviceInfo_descriptor, + new java.lang.String[] { "Name", "Type", "MemoryLimit", "PhysicalDescription", }); + internal_static_tensorflow_MachineConfiguration_descriptor = + getDescriptor().getMessageTypes().get(11); + internal_static_tensorflow_MachineConfiguration_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_MachineConfiguration_descriptor, + new java.lang.String[] { "Hostname", "SerialIdentifier", "PlatformInfo", "CpuInfo", "DeviceInfo", "AvailableDeviceInfo", "MemoryInfo", }); + internal_static_tensorflow_RunConfiguration_descriptor = + getDescriptor().getMessageTypes().get(12); + internal_static_tensorflow_RunConfiguration_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_RunConfiguration_descriptor, + new java.lang.String[] { "Argument", "EnvVars", }); + internal_static_tensorflow_RunConfiguration_EnvVarsEntry_descriptor = + internal_static_tensorflow_RunConfiguration_descriptor.getNestedTypes().get(0); + internal_static_tensorflow_RunConfiguration_EnvVarsEntry_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_RunConfiguration_EnvVarsEntry_descriptor, + new java.lang.String[] { "Key", "Value", }); + internal_static_tensorflow_TestResults_descriptor = + getDescriptor().getMessageTypes().get(13); + internal_static_tensorflow_TestResults_fieldAccessorTable = new + com.google.protobuf.GeneratedMessageV3.FieldAccessorTable( + internal_static_tensorflow_TestResults_descriptor, + new java.lang.String[] { "Target", "Entries", "BuildConfiguration", "CommitId", "StartTime", "RunTime", "MachineConfiguration", "RunConfiguration", "Name", "BenchmarkType", "RunMode", "TfVersion", }); + com.google.protobuf.AnyProto.getDescriptor(); + com.google.protobuf.WrappersProto.getDescriptor(); + } + + // @@protoc_insertion_point(outer_class_scope) +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestResults.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestResults.java new file mode 100644 index 00000000000..4bc27cbdde7 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestResults.java @@ -0,0 +1,2685 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +/** + * 
    + * The output of one benchmark / test run.  Each run contains a list of
+ * tests or benchmarks, stored as BenchmarkEntry messages.
+ * This message should be emitted by the reporter (which runs the
+ * test / BM in a subprocess and then reads the emitted BenchmarkEntry messages;
+ * usually from a serialized json file, finally collecting them along
+ * with additional information about the test run.
+ *
    + * + * Protobuf type {@code tensorflow.TestResults} + */ +public final class TestResults extends + com.google.protobuf.GeneratedMessageV3 implements + // @@protoc_insertion_point(message_implements:tensorflow.TestResults) + TestResultsOrBuilder { +private static final long serialVersionUID = 0L; + // Use TestResults.newBuilder() to construct. + private TestResults(com.google.protobuf.GeneratedMessageV3.Builder builder) { + super(builder); + } + private TestResults() { + target_ = ""; + name_ = ""; + benchmarkType_ = 0; + runMode_ = ""; + tfVersion_ = ""; + } + + @java.lang.Override + @SuppressWarnings({"unused"}) + protected java.lang.Object newInstance( + UnusedPrivateParameter unused) { + return new TestResults(); + } + + @java.lang.Override + public final com.google.protobuf.UnknownFieldSet + getUnknownFields() { + return this.unknownFields; + } + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_TestResults_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_TestResults_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.TestResults.class, org.tensorflow.proto.TestResults.Builder.class); + } + + /** + * 
    +   * The type of benchmark.
+   *
    + * + * Protobuf enum {@code tensorflow.TestResults.BenchmarkType} + */ + public enum BenchmarkType + implements com.google.protobuf.ProtocolMessageEnum { + /** + * 
    +     * Fallback for protos written before Type was introduced.
+     *
    + * + * UNKNOWN = 0; + */ + UNKNOWN(0), + /** + * CPP_MICROBENCHMARK = 1; + */ + CPP_MICROBENCHMARK(1), + /** + * PYTHON_BENCHMARK = 2; + */ + PYTHON_BENCHMARK(2), + /** + * ANDROID_BENCHMARK = 3; + */ + ANDROID_BENCHMARK(3), + /** + * EDGE_BENCHMARK = 4; + */ + EDGE_BENCHMARK(4), + /** + * IOS_BENCHMARK = 5; + */ + IOS_BENCHMARK(5), + UNRECOGNIZED(-1), + ; + + /** + * 
    +     * Fallback for protos written before Type was introduced.
+     *
    + * + * UNKNOWN = 0; + */ + public static final int UNKNOWN_VALUE = 0; + /** + * CPP_MICROBENCHMARK = 1; + */ + public static final int CPP_MICROBENCHMARK_VALUE = 1; + /** + * PYTHON_BENCHMARK = 2; + */ + public static final int PYTHON_BENCHMARK_VALUE = 2; + /** + * ANDROID_BENCHMARK = 3; + */ + public static final int ANDROID_BENCHMARK_VALUE = 3; + /** + * EDGE_BENCHMARK = 4; + */ + public static final int EDGE_BENCHMARK_VALUE = 4; + /** + * IOS_BENCHMARK = 5; + */ + public static final int IOS_BENCHMARK_VALUE = 5; + + + public final int getNumber() { + if (this == UNRECOGNIZED) { + throw new java.lang.IllegalArgumentException( + "Can't get the number of an unknown enum value."); + } + return value; + } + + /** + * @param value The numeric wire value of the corresponding enum entry. + * @return The enum associated with the given numeric wire value. + * @deprecated Use {@link #forNumber(int)} instead. + */ + @java.lang.Deprecated + public static BenchmarkType valueOf(int value) { + return forNumber(value); + } + + /** + * @param value The numeric wire value of the corresponding enum entry. + * @return The enum associated with the given numeric wire value. + */ + public static BenchmarkType forNumber(int value) { + switch (value) { + case 0: return UNKNOWN; + case 1: return CPP_MICROBENCHMARK; + case 2: return PYTHON_BENCHMARK; + case 3: return ANDROID_BENCHMARK; + case 4: return EDGE_BENCHMARK; + case 5: return IOS_BENCHMARK; + default: return null; + } + } + + public static com.google.protobuf.Internal.EnumLiteMap + internalGetValueMap() { + return internalValueMap; + } + private static final com.google.protobuf.Internal.EnumLiteMap< + BenchmarkType> internalValueMap = + new com.google.protobuf.Internal.EnumLiteMap() { + public BenchmarkType findValueByNumber(int number) { + return BenchmarkType.forNumber(number); + } + }; + + public final com.google.protobuf.Descriptors.EnumValueDescriptor + getValueDescriptor() { + if (this == UNRECOGNIZED) { + throw new java.lang.IllegalStateException( + "Can't get the descriptor of an unrecognized enum value."); + } + return getDescriptor().getValues().get(ordinal()); + } + public final com.google.protobuf.Descriptors.EnumDescriptor + getDescriptorForType() { + return getDescriptor(); + } + public static final com.google.protobuf.Descriptors.EnumDescriptor + getDescriptor() { + return org.tensorflow.proto.TestResults.getDescriptor().getEnumTypes().get(0); + } + + private static final BenchmarkType[] VALUES = values(); + + public static BenchmarkType valueOf( + com.google.protobuf.Descriptors.EnumValueDescriptor desc) { + if (desc.getType() != getDescriptor()) { + throw new java.lang.IllegalArgumentException( + "EnumValueDescriptor is not for this type."); + } + if (desc.getIndex() == -1) { + return UNRECOGNIZED; + } + return VALUES[desc.getIndex()]; + } + + private final int value; + + private BenchmarkType(int value) { + this.value = value; + } + + // @@protoc_insertion_point(enum_scope:tensorflow.TestResults.BenchmarkType) + } + + public static final int TARGET_FIELD_NUMBER = 1; + private volatile java.lang.Object target_; + /** + * 
    +   * The target of the run, e.g.:
+   *  //tensorflow/core:kernels_adjust_contrast_op_benchmark_test
+   *
    + * + * string target = 1; + * @return The target. + */ + @java.lang.Override + public java.lang.String getTarget() { + java.lang.Object ref = target_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + target_ = s; + return s; + } + } + /** + * 
    +   * The target of the run, e.g.:
+   *  //tensorflow/core:kernels_adjust_contrast_op_benchmark_test
+   *
    + * + * string target = 1; + * @return The bytes for target. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getTargetBytes() { + java.lang.Object ref = target_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + target_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int ENTRIES_FIELD_NUMBER = 2; + private org.tensorflow.proto.BenchmarkEntries entries_; + /** + * 
    +   * The list of tests or benchmarks in this run.
+   *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + * @return Whether the entries field is set. + */ + @java.lang.Override + public boolean hasEntries() { + return entries_ != null; + } + /** + * 
    +   * The list of tests or benchmarks in this run.
+   *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + * @return The entries. + */ + @java.lang.Override + public org.tensorflow.proto.BenchmarkEntries getEntries() { + return entries_ == null ? org.tensorflow.proto.BenchmarkEntries.getDefaultInstance() : entries_; + } + /** + * 
    +   * The list of tests or benchmarks in this run.
+   *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + */ + @java.lang.Override + public org.tensorflow.proto.BenchmarkEntriesOrBuilder getEntriesOrBuilder() { + return getEntries(); + } + + public static final int BUILD_CONFIGURATION_FIELD_NUMBER = 3; + private org.tensorflow.proto.BuildConfiguration buildConfiguration_; + /** + * 
    +   * The configuration of the build (compiled opt? with cuda? any copts?)
+   *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + * @return Whether the buildConfiguration field is set. + */ + @java.lang.Override + public boolean hasBuildConfiguration() { + return buildConfiguration_ != null; + } + /** + * 
    +   * The configuration of the build (compiled opt? with cuda? any copts?)
+   *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + * @return The buildConfiguration. + */ + @java.lang.Override + public org.tensorflow.proto.BuildConfiguration getBuildConfiguration() { + return buildConfiguration_ == null ? org.tensorflow.proto.BuildConfiguration.getDefaultInstance() : buildConfiguration_; + } + /** + * 
    +   * The configuration of the build (compiled opt? with cuda? any copts?)
+   *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + */ + @java.lang.Override + public org.tensorflow.proto.BuildConfigurationOrBuilder getBuildConfigurationOrBuilder() { + return getBuildConfiguration(); + } + + public static final int COMMIT_ID_FIELD_NUMBER = 4; + private org.tensorflow.proto.CommitId commitId_; + /** + * 
    +   * The commit id (git hash or changelist)
+   *
    + * + * .tensorflow.CommitId commit_id = 4; + * @return Whether the commitId field is set. + */ + @java.lang.Override + public boolean hasCommitId() { + return commitId_ != null; + } + /** + * 
    +   * The commit id (git hash or changelist)
+   *
    + * + * .tensorflow.CommitId commit_id = 4; + * @return The commitId. + */ + @java.lang.Override + public org.tensorflow.proto.CommitId getCommitId() { + return commitId_ == null ? org.tensorflow.proto.CommitId.getDefaultInstance() : commitId_; + } + /** + * 
    +   * The commit id (git hash or changelist)
+   *
    + * + * .tensorflow.CommitId commit_id = 4; + */ + @java.lang.Override + public org.tensorflow.proto.CommitIdOrBuilder getCommitIdOrBuilder() { + return getCommitId(); + } + + public static final int START_TIME_FIELD_NUMBER = 5; + private long startTime_; + /** + * 
    +   * The time the run started (in seconds of UTC time since Unix epoch)
+   *
    + * + * int64 start_time = 5; + * @return The startTime. + */ + @java.lang.Override + public long getStartTime() { + return startTime_; + } + + public static final int RUN_TIME_FIELD_NUMBER = 6; + private double runTime_; + /** + * 
    +   * The amount of time the total run took (wall time in seconds)
+   *
    + * + * double run_time = 6; + * @return The runTime. + */ + @java.lang.Override + public double getRunTime() { + return runTime_; + } + + public static final int MACHINE_CONFIGURATION_FIELD_NUMBER = 7; + private org.tensorflow.proto.MachineConfiguration machineConfiguration_; + /** + * 
    +   * Machine-specific parameters (Platform and CPU info)
+   *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + * @return Whether the machineConfiguration field is set. + */ + @java.lang.Override + public boolean hasMachineConfiguration() { + return machineConfiguration_ != null; + } + /** + * 
    +   * Machine-specific parameters (Platform and CPU info)
+   *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + * @return The machineConfiguration. + */ + @java.lang.Override + public org.tensorflow.proto.MachineConfiguration getMachineConfiguration() { + return machineConfiguration_ == null ? org.tensorflow.proto.MachineConfiguration.getDefaultInstance() : machineConfiguration_; + } + /** + * 
    +   * Machine-specific parameters (Platform and CPU info)
+   *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + */ + @java.lang.Override + public org.tensorflow.proto.MachineConfigurationOrBuilder getMachineConfigurationOrBuilder() { + return getMachineConfiguration(); + } + + public static final int RUN_CONFIGURATION_FIELD_NUMBER = 8; + private org.tensorflow.proto.RunConfiguration runConfiguration_; + /** + * 
    +   * Run-specific parameters (arguments, etc)
+   *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + * @return Whether the runConfiguration field is set. + */ + @java.lang.Override + public boolean hasRunConfiguration() { + return runConfiguration_ != null; + } + /** + * 
    +   * Run-specific parameters (arguments, etc)
+   *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + * @return The runConfiguration. + */ + @java.lang.Override + public org.tensorflow.proto.RunConfiguration getRunConfiguration() { + return runConfiguration_ == null ? org.tensorflow.proto.RunConfiguration.getDefaultInstance() : runConfiguration_; + } + /** + * 
    +   * Run-specific parameters (arguments, etc)
+   *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + */ + @java.lang.Override + public org.tensorflow.proto.RunConfigurationOrBuilder getRunConfigurationOrBuilder() { + return getRunConfiguration(); + } + + public static final int NAME_FIELD_NUMBER = 9; + private volatile java.lang.Object name_; + /** + * 
    +   * Benchmark target identifier.
+   *
    + * + * string name = 9; + * @return The name. + */ + @java.lang.Override + public java.lang.String getName() { + java.lang.Object ref = name_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + name_ = s; + return s; + } + } + /** + * 
    +   * Benchmark target identifier.
+   *
    + * + * string name = 9; + * @return The bytes for name. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getNameBytes() { + java.lang.Object ref = name_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + name_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int BENCHMARK_TYPE_FIELD_NUMBER = 10; + private int benchmarkType_; + /** + * .tensorflow.TestResults.BenchmarkType benchmark_type = 10; + * @return The enum numeric value on the wire for benchmarkType. + */ + @java.lang.Override public int getBenchmarkTypeValue() { + return benchmarkType_; + } + /** + * .tensorflow.TestResults.BenchmarkType benchmark_type = 10; + * @return The benchmarkType. + */ + @java.lang.Override public org.tensorflow.proto.TestResults.BenchmarkType getBenchmarkType() { + @SuppressWarnings("deprecation") + org.tensorflow.proto.TestResults.BenchmarkType result = org.tensorflow.proto.TestResults.BenchmarkType.valueOf(benchmarkType_); + return result == null ? org.tensorflow.proto.TestResults.BenchmarkType.UNRECOGNIZED : result; + } + + public static final int RUN_MODE_FIELD_NUMBER = 11; + private volatile java.lang.Object runMode_; + /** + * 
    +   * Used for differentiating between continuous and debug builds.
+   * Must be one of:
+   * * cbuild: results from continuous build.
+   * * presubmit: results from oneshot requests.
+   * * culprit: results from culprit finder rerun.
+   *
    + * + * string run_mode = 11; + * @return The runMode. + */ + @java.lang.Override + public java.lang.String getRunMode() { + java.lang.Object ref = runMode_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + runMode_ = s; + return s; + } + } + /** + * 
    +   * Used for differentiating between continuous and debug builds.
+   * Must be one of:
+   * * cbuild: results from continuous build.
+   * * presubmit: results from oneshot requests.
+   * * culprit: results from culprit finder rerun.
+   *
    + * + * string run_mode = 11; + * @return The bytes for runMode. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getRunModeBytes() { + java.lang.Object ref = runMode_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + runMode_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + public static final int TF_VERSION_FIELD_NUMBER = 12; + private volatile java.lang.Object tfVersion_; + /** + * 
    +   * TensorFlow version this benchmark runs against.
+   * This can be either set to full version or just the major version.
+   *
    + * + * string tf_version = 12; + * @return The tfVersion. + */ + @java.lang.Override + public java.lang.String getTfVersion() { + java.lang.Object ref = tfVersion_; + if (ref instanceof java.lang.String) { + return (java.lang.String) ref; + } else { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + tfVersion_ = s; + return s; + } + } + /** + * 
    +   * TensorFlow version this benchmark runs against.
+   * This can be either set to full version or just the major version.
+   *
    + * + * string tf_version = 12; + * @return The bytes for tfVersion. + */ + @java.lang.Override + public com.google.protobuf.ByteString + getTfVersionBytes() { + java.lang.Object ref = tfVersion_; + if (ref instanceof java.lang.String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + tfVersion_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + + private byte memoizedIsInitialized = -1; + @java.lang.Override + public final boolean isInitialized() { + byte isInitialized = memoizedIsInitialized; + if (isInitialized == 1) return true; + if (isInitialized == 0) return false; + + memoizedIsInitialized = 1; + return true; + } + + @java.lang.Override + public void writeTo(com.google.protobuf.CodedOutputStream output) + throws java.io.IOException { + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(target_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 1, target_); + } + if (entries_ != null) { + output.writeMessage(2, getEntries()); + } + if (buildConfiguration_ != null) { + output.writeMessage(3, getBuildConfiguration()); + } + if (commitId_ != null) { + output.writeMessage(4, getCommitId()); + } + if (startTime_ != 0L) { + output.writeInt64(5, startTime_); + } + if (java.lang.Double.doubleToRawLongBits(runTime_) != 0) { + output.writeDouble(6, runTime_); + } + if (machineConfiguration_ != null) { + output.writeMessage(7, getMachineConfiguration()); + } + if (runConfiguration_ != null) { + output.writeMessage(8, getRunConfiguration()); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 9, name_); + } + if (benchmarkType_ != org.tensorflow.proto.TestResults.BenchmarkType.UNKNOWN.getNumber()) { + output.writeEnum(10, benchmarkType_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(runMode_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 11, runMode_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(tfVersion_)) { + com.google.protobuf.GeneratedMessageV3.writeString(output, 12, tfVersion_); + } + getUnknownFields().writeTo(output); + } + + @java.lang.Override + public int getSerializedSize() { + int size = memoizedSize; + if (size != -1) return size; + + size = 0; + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(target_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, target_); + } + if (entries_ != null) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(2, getEntries()); + } + if (buildConfiguration_ != null) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(3, getBuildConfiguration()); + } + if (commitId_ != null) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(4, getCommitId()); + } + if (startTime_ != 0L) { + size += com.google.protobuf.CodedOutputStream + .computeInt64Size(5, startTime_); + } + if (java.lang.Double.doubleToRawLongBits(runTime_) != 0) { + size += com.google.protobuf.CodedOutputStream + .computeDoubleSize(6, runTime_); + } + if (machineConfiguration_ != null) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(7, getMachineConfiguration()); + } + if (runConfiguration_ != null) { + size += com.google.protobuf.CodedOutputStream + .computeMessageSize(8, getRunConfiguration()); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(name_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(9, name_); + } + if (benchmarkType_ != org.tensorflow.proto.TestResults.BenchmarkType.UNKNOWN.getNumber()) { + size += com.google.protobuf.CodedOutputStream + .computeEnumSize(10, benchmarkType_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(runMode_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(11, runMode_); + } + if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(tfVersion_)) { + size += com.google.protobuf.GeneratedMessageV3.computeStringSize(12, tfVersion_); + } + size += getUnknownFields().getSerializedSize(); + memoizedSize = size; + return size; + } + + @java.lang.Override + public boolean equals(final java.lang.Object obj) { + if (obj == this) { + return true; + } + if (!(obj instanceof org.tensorflow.proto.TestResults)) { + return super.equals(obj); + } + org.tensorflow.proto.TestResults other = (org.tensorflow.proto.TestResults) obj; + + if (!getTarget() + .equals(other.getTarget())) return false; + if (hasEntries() != other.hasEntries()) return false; + if (hasEntries()) { + if (!getEntries() + .equals(other.getEntries())) return false; + } + if (hasBuildConfiguration() != other.hasBuildConfiguration()) return false; + if (hasBuildConfiguration()) { + if (!getBuildConfiguration() + .equals(other.getBuildConfiguration())) return false; + } + if (hasCommitId() != other.hasCommitId()) return false; + if (hasCommitId()) { + if (!getCommitId() + .equals(other.getCommitId())) return false; + } + if (getStartTime() + != other.getStartTime()) return false; + if (java.lang.Double.doubleToLongBits(getRunTime()) + != java.lang.Double.doubleToLongBits( + other.getRunTime())) return false; + if (hasMachineConfiguration() != other.hasMachineConfiguration()) return false; + if (hasMachineConfiguration()) { + if (!getMachineConfiguration() + .equals(other.getMachineConfiguration())) return false; + } + if (hasRunConfiguration() != other.hasRunConfiguration()) return false; + if (hasRunConfiguration()) { + if (!getRunConfiguration() + .equals(other.getRunConfiguration())) return false; + } + if (!getName() + .equals(other.getName())) return false; + if (benchmarkType_ != other.benchmarkType_) return false; + if (!getRunMode() + .equals(other.getRunMode())) return false; + if (!getTfVersion() + .equals(other.getTfVersion())) return false; + if (!getUnknownFields().equals(other.getUnknownFields())) return false; + return true; + } + + @java.lang.Override + public int hashCode() { + if (memoizedHashCode != 0) { + return memoizedHashCode; + } + int hash = 41; + hash = (19 * hash) + getDescriptor().hashCode(); + hash = (37 * hash) + TARGET_FIELD_NUMBER; + hash = (53 * hash) + getTarget().hashCode(); + if (hasEntries()) { + hash = (37 * hash) + ENTRIES_FIELD_NUMBER; + hash = (53 * hash) + getEntries().hashCode(); + } + if (hasBuildConfiguration()) { + hash = (37 * hash) + BUILD_CONFIGURATION_FIELD_NUMBER; + hash = (53 * hash) + getBuildConfiguration().hashCode(); + } + if (hasCommitId()) { + hash = (37 * hash) + COMMIT_ID_FIELD_NUMBER; + hash = (53 * hash) + getCommitId().hashCode(); + } + hash = (37 * hash) + START_TIME_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + getStartTime()); + hash = (37 * hash) + RUN_TIME_FIELD_NUMBER; + hash = (53 * hash) + com.google.protobuf.Internal.hashLong( + java.lang.Double.doubleToLongBits(getRunTime())); + if (hasMachineConfiguration()) { + hash = (37 * hash) + MACHINE_CONFIGURATION_FIELD_NUMBER; + hash = (53 * hash) + getMachineConfiguration().hashCode(); + } + if (hasRunConfiguration()) { + hash = (37 * hash) + RUN_CONFIGURATION_FIELD_NUMBER; + hash = (53 * hash) + getRunConfiguration().hashCode(); + } + hash = (37 * hash) + NAME_FIELD_NUMBER; + hash = (53 * hash) + getName().hashCode(); + hash = (37 * hash) + BENCHMARK_TYPE_FIELD_NUMBER; + hash = (53 * hash) + benchmarkType_; + hash = (37 * hash) + RUN_MODE_FIELD_NUMBER; + hash = (53 * hash) + getRunMode().hashCode(); + hash = (37 * hash) + TF_VERSION_FIELD_NUMBER; + hash = (53 * hash) + getTfVersion().hashCode(); + hash = (29 * hash) + getUnknownFields().hashCode(); + memoizedHashCode = hash; + return hash; + } + + public static org.tensorflow.proto.TestResults parseFrom( + java.nio.ByteBuffer data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.TestResults parseFrom( + java.nio.ByteBuffer data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.TestResults parseFrom( + com.google.protobuf.ByteString data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.TestResults parseFrom( + com.google.protobuf.ByteString data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.TestResults parseFrom(byte[] data) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data); + } + public static org.tensorflow.proto.TestResults parseFrom( + byte[] data, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + return PARSER.parseFrom(data, extensionRegistry); + } + public static org.tensorflow.proto.TestResults parseFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.TestResults parseFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.TestResults parseDelimitedFrom(java.io.InputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input); + } + public static org.tensorflow.proto.TestResults parseDelimitedFrom( + java.io.InputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseDelimitedWithIOException(PARSER, input, extensionRegistry); + } + public static org.tensorflow.proto.TestResults parseFrom( + com.google.protobuf.CodedInputStream input) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input); + } + public static org.tensorflow.proto.TestResults parseFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + return com.google.protobuf.GeneratedMessageV3 + .parseWithIOException(PARSER, input, extensionRegistry); + } + + @java.lang.Override + public Builder newBuilderForType() { return newBuilder(); } + public static Builder newBuilder() { + return DEFAULT_INSTANCE.toBuilder(); + } + public static Builder newBuilder(org.tensorflow.proto.TestResults prototype) { + return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); + } + @java.lang.Override + public Builder toBuilder() { + return this == DEFAULT_INSTANCE + ? new Builder() : new Builder().mergeFrom(this); + } + + @java.lang.Override + protected Builder newBuilderForType( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + Builder builder = new Builder(parent); + return builder; + } + /** + * 
    +   * The output of one benchmark / test run.  Each run contains a list of
+   * tests or benchmarks, stored as BenchmarkEntry messages.
+   * This message should be emitted by the reporter (which runs the
+   * test / BM in a subprocess and then reads the emitted BenchmarkEntry messages;
+   * usually from a serialized json file, finally collecting them along
+   * with additional information about the test run.
+   *
    + * + * Protobuf type {@code tensorflow.TestResults} + */ + public static final class Builder extends + com.google.protobuf.GeneratedMessageV3.Builder implements + // @@protoc_insertion_point(builder_implements:tensorflow.TestResults) + org.tensorflow.proto.TestResultsOrBuilder { + public static final com.google.protobuf.Descriptors.Descriptor + getDescriptor() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_TestResults_descriptor; + } + + @java.lang.Override + protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable + internalGetFieldAccessorTable() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_TestResults_fieldAccessorTable + .ensureFieldAccessorsInitialized( + org.tensorflow.proto.TestResults.class, org.tensorflow.proto.TestResults.Builder.class); + } + + // Construct using org.tensorflow.proto.TestResults.newBuilder() + private Builder() { + + } + + private Builder( + com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { + super(parent); + + } + @java.lang.Override + public Builder clear() { + super.clear(); + target_ = ""; + + if (entriesBuilder_ == null) { + entries_ = null; + } else { + entries_ = null; + entriesBuilder_ = null; + } + if (buildConfigurationBuilder_ == null) { + buildConfiguration_ = null; + } else { + buildConfiguration_ = null; + buildConfigurationBuilder_ = null; + } + if (commitIdBuilder_ == null) { + commitId_ = null; + } else { + commitId_ = null; + commitIdBuilder_ = null; + } + startTime_ = 0L; + + runTime_ = 0D; + + if (machineConfigurationBuilder_ == null) { + machineConfiguration_ = null; + } else { + machineConfiguration_ = null; + machineConfigurationBuilder_ = null; + } + if (runConfigurationBuilder_ == null) { + runConfiguration_ = null; + } else { + runConfiguration_ = null; + runConfigurationBuilder_ = null; + } + name_ = ""; + + benchmarkType_ = 0; + + runMode_ = ""; + + tfVersion_ = ""; + + return this; + } + + @java.lang.Override + public com.google.protobuf.Descriptors.Descriptor + getDescriptorForType() { + return org.tensorflow.proto.TestLogProtos.internal_static_tensorflow_TestResults_descriptor; + } + + @java.lang.Override + public org.tensorflow.proto.TestResults getDefaultInstanceForType() { + return org.tensorflow.proto.TestResults.getDefaultInstance(); + } + + @java.lang.Override + public org.tensorflow.proto.TestResults build() { + org.tensorflow.proto.TestResults result = buildPartial(); + if (!result.isInitialized()) { + throw newUninitializedMessageException(result); + } + return result; + } + + @java.lang.Override + public org.tensorflow.proto.TestResults buildPartial() { + org.tensorflow.proto.TestResults result = new org.tensorflow.proto.TestResults(this); + result.target_ = target_; + if (entriesBuilder_ == null) { + result.entries_ = entries_; + } else { + result.entries_ = entriesBuilder_.build(); + } + if (buildConfigurationBuilder_ == null) { + result.buildConfiguration_ = buildConfiguration_; + } else { + result.buildConfiguration_ = buildConfigurationBuilder_.build(); + } + if (commitIdBuilder_ == null) { + result.commitId_ = commitId_; + } else { + result.commitId_ = commitIdBuilder_.build(); + } + result.startTime_ = startTime_; + result.runTime_ = runTime_; + if (machineConfigurationBuilder_ == null) { + result.machineConfiguration_ = machineConfiguration_; + } else { + result.machineConfiguration_ = machineConfigurationBuilder_.build(); + } + if (runConfigurationBuilder_ == null) { + result.runConfiguration_ = runConfiguration_; + } else { + result.runConfiguration_ = runConfigurationBuilder_.build(); + } + result.name_ = name_; + result.benchmarkType_ = benchmarkType_; + result.runMode_ = runMode_; + result.tfVersion_ = tfVersion_; + onBuilt(); + return result; + } + + @java.lang.Override + public Builder clone() { + return super.clone(); + } + @java.lang.Override + public Builder setField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.setField(field, value); + } + @java.lang.Override + public Builder clearField( + com.google.protobuf.Descriptors.FieldDescriptor field) { + return super.clearField(field); + } + @java.lang.Override + public Builder clearOneof( + com.google.protobuf.Descriptors.OneofDescriptor oneof) { + return super.clearOneof(oneof); + } + @java.lang.Override + public Builder setRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + int index, java.lang.Object value) { + return super.setRepeatedField(field, index, value); + } + @java.lang.Override + public Builder addRepeatedField( + com.google.protobuf.Descriptors.FieldDescriptor field, + java.lang.Object value) { + return super.addRepeatedField(field, value); + } + @java.lang.Override + public Builder mergeFrom(com.google.protobuf.Message other) { + if (other instanceof org.tensorflow.proto.TestResults) { + return mergeFrom((org.tensorflow.proto.TestResults)other); + } else { + super.mergeFrom(other); + return this; + } + } + + public Builder mergeFrom(org.tensorflow.proto.TestResults other) { + if (other == org.tensorflow.proto.TestResults.getDefaultInstance()) return this; + if (!other.getTarget().isEmpty()) { + target_ = other.target_; + onChanged(); + } + if (other.hasEntries()) { + mergeEntries(other.getEntries()); + } + if (other.hasBuildConfiguration()) { + mergeBuildConfiguration(other.getBuildConfiguration()); + } + if (other.hasCommitId()) { + mergeCommitId(other.getCommitId()); + } + if (other.getStartTime() != 0L) { + setStartTime(other.getStartTime()); + } + if (other.getRunTime() != 0D) { + setRunTime(other.getRunTime()); + } + if (other.hasMachineConfiguration()) { + mergeMachineConfiguration(other.getMachineConfiguration()); + } + if (other.hasRunConfiguration()) { + mergeRunConfiguration(other.getRunConfiguration()); + } + if (!other.getName().isEmpty()) { + name_ = other.name_; + onChanged(); + } + if (other.benchmarkType_ != 0) { + setBenchmarkTypeValue(other.getBenchmarkTypeValue()); + } + if (!other.getRunMode().isEmpty()) { + runMode_ = other.runMode_; + onChanged(); + } + if (!other.getTfVersion().isEmpty()) { + tfVersion_ = other.tfVersion_; + onChanged(); + } + this.mergeUnknownFields(other.getUnknownFields()); + onChanged(); + return this; + } + + @java.lang.Override + public final boolean isInitialized() { + return true; + } + + @java.lang.Override + public Builder mergeFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws java.io.IOException { + if (extensionRegistry == null) { + throw new java.lang.NullPointerException(); + } + try { + boolean done = false; + while (!done) { + int tag = input.readTag(); + switch (tag) { + case 0: + done = true; + break; + case 10: { + target_ = input.readStringRequireUtf8(); + + break; + } // case 10 + case 18: { + input.readMessage( + getEntriesFieldBuilder().getBuilder(), + extensionRegistry); + + break; + } // case 18 + case 26: { + input.readMessage( + getBuildConfigurationFieldBuilder().getBuilder(), + extensionRegistry); + + break; + } // case 26 + case 34: { + input.readMessage( + getCommitIdFieldBuilder().getBuilder(), + extensionRegistry); + + break; + } // case 34 + case 40: { + startTime_ = input.readInt64(); + + break; + } // case 40 + case 49: { + runTime_ = input.readDouble(); + + break; + } // case 49 + case 58: { + input.readMessage( + getMachineConfigurationFieldBuilder().getBuilder(), + extensionRegistry); + + break; + } // case 58 + case 66: { + input.readMessage( + getRunConfigurationFieldBuilder().getBuilder(), + extensionRegistry); + + break; + } // case 66 + case 74: { + name_ = input.readStringRequireUtf8(); + + break; + } // case 74 + case 80: { + benchmarkType_ = input.readEnum(); + + break; + } // case 80 + case 90: { + runMode_ = input.readStringRequireUtf8(); + + break; + } // case 90 + case 98: { + tfVersion_ = input.readStringRequireUtf8(); + + break; + } // case 98 + default: { + if (!super.parseUnknownField(input, extensionRegistry, tag)) { + done = true; // was an endgroup tag + } + break; + } // default: + } // switch (tag) + } // while (!done) + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.unwrapIOException(); + } finally { + onChanged(); + } // finally + return this; + } + + private java.lang.Object target_ = ""; + /** + * 
    +     * The target of the run, e.g.:
+     *  //tensorflow/core:kernels_adjust_contrast_op_benchmark_test
+     *
    + * + * string target = 1; + * @return The target. + */ + public java.lang.String getTarget() { + java.lang.Object ref = target_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + target_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * The target of the run, e.g.:
+     *  //tensorflow/core:kernels_adjust_contrast_op_benchmark_test
+     *
    + * + * string target = 1; + * @return The bytes for target. + */ + public com.google.protobuf.ByteString + getTargetBytes() { + java.lang.Object ref = target_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + target_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * The target of the run, e.g.:
+     *  //tensorflow/core:kernels_adjust_contrast_op_benchmark_test
+     *
    + * + * string target = 1; + * @param value The target to set. + * @return This builder for chaining. + */ + public Builder setTarget( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + target_ = value; + onChanged(); + return this; + } + /** + * 
    +     * The target of the run, e.g.:
+     *  //tensorflow/core:kernels_adjust_contrast_op_benchmark_test
+     *
    + * + * string target = 1; + * @return This builder for chaining. + */ + public Builder clearTarget() { + + target_ = getDefaultInstance().getTarget(); + onChanged(); + return this; + } + /** + * 
    +     * The target of the run, e.g.:
+     *  //tensorflow/core:kernels_adjust_contrast_op_benchmark_test
+     *
    + * + * string target = 1; + * @param value The bytes for target to set. + * @return This builder for chaining. + */ + public Builder setTargetBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + target_ = value; + onChanged(); + return this; + } + + private org.tensorflow.proto.BenchmarkEntries entries_; + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.BenchmarkEntries, org.tensorflow.proto.BenchmarkEntries.Builder, org.tensorflow.proto.BenchmarkEntriesOrBuilder> entriesBuilder_; + /** + * 
    +     * The list of tests or benchmarks in this run.
+     *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + * @return Whether the entries field is set. + */ + public boolean hasEntries() { + return entriesBuilder_ != null || entries_ != null; + } + /** + * 
    +     * The list of tests or benchmarks in this run.
+     *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + * @return The entries. + */ + public org.tensorflow.proto.BenchmarkEntries getEntries() { + if (entriesBuilder_ == null) { + return entries_ == null ? org.tensorflow.proto.BenchmarkEntries.getDefaultInstance() : entries_; + } else { + return entriesBuilder_.getMessage(); + } + } + /** + * 
    +     * The list of tests or benchmarks in this run.
+     *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + */ + public Builder setEntries(org.tensorflow.proto.BenchmarkEntries value) { + if (entriesBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + entries_ = value; + onChanged(); + } else { + entriesBuilder_.setMessage(value); + } + + return this; + } + /** + * 
    +     * The list of tests or benchmarks in this run.
+     *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + */ + public Builder setEntries( + org.tensorflow.proto.BenchmarkEntries.Builder builderForValue) { + if (entriesBuilder_ == null) { + entries_ = builderForValue.build(); + onChanged(); + } else { + entriesBuilder_.setMessage(builderForValue.build()); + } + + return this; + } + /** + * 
    +     * The list of tests or benchmarks in this run.
+     *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + */ + public Builder mergeEntries(org.tensorflow.proto.BenchmarkEntries value) { + if (entriesBuilder_ == null) { + if (entries_ != null) { + entries_ = + org.tensorflow.proto.BenchmarkEntries.newBuilder(entries_).mergeFrom(value).buildPartial(); + } else { + entries_ = value; + } + onChanged(); + } else { + entriesBuilder_.mergeFrom(value); + } + + return this; + } + /** + * 
    +     * The list of tests or benchmarks in this run.
+     *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + */ + public Builder clearEntries() { + if (entriesBuilder_ == null) { + entries_ = null; + onChanged(); + } else { + entries_ = null; + entriesBuilder_ = null; + } + + return this; + } + /** + * 
    +     * The list of tests or benchmarks in this run.
+     *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + */ + public org.tensorflow.proto.BenchmarkEntries.Builder getEntriesBuilder() { + + onChanged(); + return getEntriesFieldBuilder().getBuilder(); + } + /** + * 
    +     * The list of tests or benchmarks in this run.
+     *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + */ + public org.tensorflow.proto.BenchmarkEntriesOrBuilder getEntriesOrBuilder() { + if (entriesBuilder_ != null) { + return entriesBuilder_.getMessageOrBuilder(); + } else { + return entries_ == null ? + org.tensorflow.proto.BenchmarkEntries.getDefaultInstance() : entries_; + } + } + /** + * 
    +     * The list of tests or benchmarks in this run.
+     *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + */ + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.BenchmarkEntries, org.tensorflow.proto.BenchmarkEntries.Builder, org.tensorflow.proto.BenchmarkEntriesOrBuilder> + getEntriesFieldBuilder() { + if (entriesBuilder_ == null) { + entriesBuilder_ = new com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.BenchmarkEntries, org.tensorflow.proto.BenchmarkEntries.Builder, org.tensorflow.proto.BenchmarkEntriesOrBuilder>( + getEntries(), + getParentForChildren(), + isClean()); + entries_ = null; + } + return entriesBuilder_; + } + + private org.tensorflow.proto.BuildConfiguration buildConfiguration_; + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.BuildConfiguration, org.tensorflow.proto.BuildConfiguration.Builder, org.tensorflow.proto.BuildConfigurationOrBuilder> buildConfigurationBuilder_; + /** + * 
    +     * The configuration of the build (compiled opt? with cuda? any copts?)
+     *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + * @return Whether the buildConfiguration field is set. + */ + public boolean hasBuildConfiguration() { + return buildConfigurationBuilder_ != null || buildConfiguration_ != null; + } + /** + * 
    +     * The configuration of the build (compiled opt? with cuda? any copts?)
+     *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + * @return The buildConfiguration. + */ + public org.tensorflow.proto.BuildConfiguration getBuildConfiguration() { + if (buildConfigurationBuilder_ == null) { + return buildConfiguration_ == null ? org.tensorflow.proto.BuildConfiguration.getDefaultInstance() : buildConfiguration_; + } else { + return buildConfigurationBuilder_.getMessage(); + } + } + /** + * 
    +     * The configuration of the build (compiled opt? with cuda? any copts?)
+     *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + */ + public Builder setBuildConfiguration(org.tensorflow.proto.BuildConfiguration value) { + if (buildConfigurationBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + buildConfiguration_ = value; + onChanged(); + } else { + buildConfigurationBuilder_.setMessage(value); + } + + return this; + } + /** + * 
    +     * The configuration of the build (compiled opt? with cuda? any copts?)
+     *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + */ + public Builder setBuildConfiguration( + org.tensorflow.proto.BuildConfiguration.Builder builderForValue) { + if (buildConfigurationBuilder_ == null) { + buildConfiguration_ = builderForValue.build(); + onChanged(); + } else { + buildConfigurationBuilder_.setMessage(builderForValue.build()); + } + + return this; + } + /** + * 
    +     * The configuration of the build (compiled opt? with cuda? any copts?)
+     *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + */ + public Builder mergeBuildConfiguration(org.tensorflow.proto.BuildConfiguration value) { + if (buildConfigurationBuilder_ == null) { + if (buildConfiguration_ != null) { + buildConfiguration_ = + org.tensorflow.proto.BuildConfiguration.newBuilder(buildConfiguration_).mergeFrom(value).buildPartial(); + } else { + buildConfiguration_ = value; + } + onChanged(); + } else { + buildConfigurationBuilder_.mergeFrom(value); + } + + return this; + } + /** + * 
    +     * The configuration of the build (compiled opt? with cuda? any copts?)
+     *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + */ + public Builder clearBuildConfiguration() { + if (buildConfigurationBuilder_ == null) { + buildConfiguration_ = null; + onChanged(); + } else { + buildConfiguration_ = null; + buildConfigurationBuilder_ = null; + } + + return this; + } + /** + * 
    +     * The configuration of the build (compiled opt? with cuda? any copts?)
+     *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + */ + public org.tensorflow.proto.BuildConfiguration.Builder getBuildConfigurationBuilder() { + + onChanged(); + return getBuildConfigurationFieldBuilder().getBuilder(); + } + /** + * 
    +     * The configuration of the build (compiled opt? with cuda? any copts?)
+     *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + */ + public org.tensorflow.proto.BuildConfigurationOrBuilder getBuildConfigurationOrBuilder() { + if (buildConfigurationBuilder_ != null) { + return buildConfigurationBuilder_.getMessageOrBuilder(); + } else { + return buildConfiguration_ == null ? + org.tensorflow.proto.BuildConfiguration.getDefaultInstance() : buildConfiguration_; + } + } + /** + * 
    +     * The configuration of the build (compiled opt? with cuda? any copts?)
+     *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + */ + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.BuildConfiguration, org.tensorflow.proto.BuildConfiguration.Builder, org.tensorflow.proto.BuildConfigurationOrBuilder> + getBuildConfigurationFieldBuilder() { + if (buildConfigurationBuilder_ == null) { + buildConfigurationBuilder_ = new com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.BuildConfiguration, org.tensorflow.proto.BuildConfiguration.Builder, org.tensorflow.proto.BuildConfigurationOrBuilder>( + getBuildConfiguration(), + getParentForChildren(), + isClean()); + buildConfiguration_ = null; + } + return buildConfigurationBuilder_; + } + + private org.tensorflow.proto.CommitId commitId_; + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.CommitId, org.tensorflow.proto.CommitId.Builder, org.tensorflow.proto.CommitIdOrBuilder> commitIdBuilder_; + /** + * 
    +     * The commit id (git hash or changelist)
+     *
    + * + * .tensorflow.CommitId commit_id = 4; + * @return Whether the commitId field is set. + */ + public boolean hasCommitId() { + return commitIdBuilder_ != null || commitId_ != null; + } + /** + * 
    +     * The commit id (git hash or changelist)
+     *
    + * + * .tensorflow.CommitId commit_id = 4; + * @return The commitId. + */ + public org.tensorflow.proto.CommitId getCommitId() { + if (commitIdBuilder_ == null) { + return commitId_ == null ? org.tensorflow.proto.CommitId.getDefaultInstance() : commitId_; + } else { + return commitIdBuilder_.getMessage(); + } + } + /** + * 
    +     * The commit id (git hash or changelist)
+     *
    + * + * .tensorflow.CommitId commit_id = 4; + */ + public Builder setCommitId(org.tensorflow.proto.CommitId value) { + if (commitIdBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + commitId_ = value; + onChanged(); + } else { + commitIdBuilder_.setMessage(value); + } + + return this; + } + /** + * 
    +     * The commit id (git hash or changelist)
+     *
    + * + * .tensorflow.CommitId commit_id = 4; + */ + public Builder setCommitId( + org.tensorflow.proto.CommitId.Builder builderForValue) { + if (commitIdBuilder_ == null) { + commitId_ = builderForValue.build(); + onChanged(); + } else { + commitIdBuilder_.setMessage(builderForValue.build()); + } + + return this; + } + /** + * 
    +     * The commit id (git hash or changelist)
+     *
    + * + * .tensorflow.CommitId commit_id = 4; + */ + public Builder mergeCommitId(org.tensorflow.proto.CommitId value) { + if (commitIdBuilder_ == null) { + if (commitId_ != null) { + commitId_ = + org.tensorflow.proto.CommitId.newBuilder(commitId_).mergeFrom(value).buildPartial(); + } else { + commitId_ = value; + } + onChanged(); + } else { + commitIdBuilder_.mergeFrom(value); + } + + return this; + } + /** + * 
    +     * The commit id (git hash or changelist)
+     *
    + * + * .tensorflow.CommitId commit_id = 4; + */ + public Builder clearCommitId() { + if (commitIdBuilder_ == null) { + commitId_ = null; + onChanged(); + } else { + commitId_ = null; + commitIdBuilder_ = null; + } + + return this; + } + /** + * 
    +     * The commit id (git hash or changelist)
+     *
    + * + * .tensorflow.CommitId commit_id = 4; + */ + public org.tensorflow.proto.CommitId.Builder getCommitIdBuilder() { + + onChanged(); + return getCommitIdFieldBuilder().getBuilder(); + } + /** + * 
    +     * The commit id (git hash or changelist)
+     *
    + * + * .tensorflow.CommitId commit_id = 4; + */ + public org.tensorflow.proto.CommitIdOrBuilder getCommitIdOrBuilder() { + if (commitIdBuilder_ != null) { + return commitIdBuilder_.getMessageOrBuilder(); + } else { + return commitId_ == null ? + org.tensorflow.proto.CommitId.getDefaultInstance() : commitId_; + } + } + /** + * 
    +     * The commit id (git hash or changelist)
+     *
    + * + * .tensorflow.CommitId commit_id = 4; + */ + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.CommitId, org.tensorflow.proto.CommitId.Builder, org.tensorflow.proto.CommitIdOrBuilder> + getCommitIdFieldBuilder() { + if (commitIdBuilder_ == null) { + commitIdBuilder_ = new com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.CommitId, org.tensorflow.proto.CommitId.Builder, org.tensorflow.proto.CommitIdOrBuilder>( + getCommitId(), + getParentForChildren(), + isClean()); + commitId_ = null; + } + return commitIdBuilder_; + } + + private long startTime_ ; + /** + * 
    +     * The time the run started (in seconds of UTC time since Unix epoch)
+     *
    + * + * int64 start_time = 5; + * @return The startTime. + */ + @java.lang.Override + public long getStartTime() { + return startTime_; + } + /** + * 
    +     * The time the run started (in seconds of UTC time since Unix epoch)
+     *
    + * + * int64 start_time = 5; + * @param value The startTime to set. + * @return This builder for chaining. + */ + public Builder setStartTime(long value) { + + startTime_ = value; + onChanged(); + return this; + } + /** + * 
    +     * The time the run started (in seconds of UTC time since Unix epoch)
+     *
    + * + * int64 start_time = 5; + * @return This builder for chaining. + */ + public Builder clearStartTime() { + + startTime_ = 0L; + onChanged(); + return this; + } + + private double runTime_ ; + /** + * 
    +     * The amount of time the total run took (wall time in seconds)
+     *
    + * + * double run_time = 6; + * @return The runTime. + */ + @java.lang.Override + public double getRunTime() { + return runTime_; + } + /** + * 
    +     * The amount of time the total run took (wall time in seconds)
+     *
    + * + * double run_time = 6; + * @param value The runTime to set. + * @return This builder for chaining. + */ + public Builder setRunTime(double value) { + + runTime_ = value; + onChanged(); + return this; + } + /** + * 
    +     * The amount of time the total run took (wall time in seconds)
+     *
    + * + * double run_time = 6; + * @return This builder for chaining. + */ + public Builder clearRunTime() { + + runTime_ = 0D; + onChanged(); + return this; + } + + private org.tensorflow.proto.MachineConfiguration machineConfiguration_; + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.MachineConfiguration, org.tensorflow.proto.MachineConfiguration.Builder, org.tensorflow.proto.MachineConfigurationOrBuilder> machineConfigurationBuilder_; + /** + * 
    +     * Machine-specific parameters (Platform and CPU info)
+     *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + * @return Whether the machineConfiguration field is set. + */ + public boolean hasMachineConfiguration() { + return machineConfigurationBuilder_ != null || machineConfiguration_ != null; + } + /** + * 
    +     * Machine-specific parameters (Platform and CPU info)
+     *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + * @return The machineConfiguration. + */ + public org.tensorflow.proto.MachineConfiguration getMachineConfiguration() { + if (machineConfigurationBuilder_ == null) { + return machineConfiguration_ == null ? org.tensorflow.proto.MachineConfiguration.getDefaultInstance() : machineConfiguration_; + } else { + return machineConfigurationBuilder_.getMessage(); + } + } + /** + * 
    +     * Machine-specific parameters (Platform and CPU info)
+     *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + */ + public Builder setMachineConfiguration(org.tensorflow.proto.MachineConfiguration value) { + if (machineConfigurationBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + machineConfiguration_ = value; + onChanged(); + } else { + machineConfigurationBuilder_.setMessage(value); + } + + return this; + } + /** + * 
    +     * Machine-specific parameters (Platform and CPU info)
+     *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + */ + public Builder setMachineConfiguration( + org.tensorflow.proto.MachineConfiguration.Builder builderForValue) { + if (machineConfigurationBuilder_ == null) { + machineConfiguration_ = builderForValue.build(); + onChanged(); + } else { + machineConfigurationBuilder_.setMessage(builderForValue.build()); + } + + return this; + } + /** + * 
    +     * Machine-specific parameters (Platform and CPU info)
+     *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + */ + public Builder mergeMachineConfiguration(org.tensorflow.proto.MachineConfiguration value) { + if (machineConfigurationBuilder_ == null) { + if (machineConfiguration_ != null) { + machineConfiguration_ = + org.tensorflow.proto.MachineConfiguration.newBuilder(machineConfiguration_).mergeFrom(value).buildPartial(); + } else { + machineConfiguration_ = value; + } + onChanged(); + } else { + machineConfigurationBuilder_.mergeFrom(value); + } + + return this; + } + /** + * 
    +     * Machine-specific parameters (Platform and CPU info)
+     *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + */ + public Builder clearMachineConfiguration() { + if (machineConfigurationBuilder_ == null) { + machineConfiguration_ = null; + onChanged(); + } else { + machineConfiguration_ = null; + machineConfigurationBuilder_ = null; + } + + return this; + } + /** + * 
    +     * Machine-specific parameters (Platform and CPU info)
+     *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + */ + public org.tensorflow.proto.MachineConfiguration.Builder getMachineConfigurationBuilder() { + + onChanged(); + return getMachineConfigurationFieldBuilder().getBuilder(); + } + /** + * 
    +     * Machine-specific parameters (Platform and CPU info)
+     *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + */ + public org.tensorflow.proto.MachineConfigurationOrBuilder getMachineConfigurationOrBuilder() { + if (machineConfigurationBuilder_ != null) { + return machineConfigurationBuilder_.getMessageOrBuilder(); + } else { + return machineConfiguration_ == null ? + org.tensorflow.proto.MachineConfiguration.getDefaultInstance() : machineConfiguration_; + } + } + /** + * 
    +     * Machine-specific parameters (Platform and CPU info)
+     *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + */ + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.MachineConfiguration, org.tensorflow.proto.MachineConfiguration.Builder, org.tensorflow.proto.MachineConfigurationOrBuilder> + getMachineConfigurationFieldBuilder() { + if (machineConfigurationBuilder_ == null) { + machineConfigurationBuilder_ = new com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.MachineConfiguration, org.tensorflow.proto.MachineConfiguration.Builder, org.tensorflow.proto.MachineConfigurationOrBuilder>( + getMachineConfiguration(), + getParentForChildren(), + isClean()); + machineConfiguration_ = null; + } + return machineConfigurationBuilder_; + } + + private org.tensorflow.proto.RunConfiguration runConfiguration_; + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.RunConfiguration, org.tensorflow.proto.RunConfiguration.Builder, org.tensorflow.proto.RunConfigurationOrBuilder> runConfigurationBuilder_; + /** + * 
    +     * Run-specific parameters (arguments, etc)
+     *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + * @return Whether the runConfiguration field is set. + */ + public boolean hasRunConfiguration() { + return runConfigurationBuilder_ != null || runConfiguration_ != null; + } + /** + * 
    +     * Run-specific parameters (arguments, etc)
+     *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + * @return The runConfiguration. + */ + public org.tensorflow.proto.RunConfiguration getRunConfiguration() { + if (runConfigurationBuilder_ == null) { + return runConfiguration_ == null ? org.tensorflow.proto.RunConfiguration.getDefaultInstance() : runConfiguration_; + } else { + return runConfigurationBuilder_.getMessage(); + } + } + /** + * 
    +     * Run-specific parameters (arguments, etc)
+     *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + */ + public Builder setRunConfiguration(org.tensorflow.proto.RunConfiguration value) { + if (runConfigurationBuilder_ == null) { + if (value == null) { + throw new NullPointerException(); + } + runConfiguration_ = value; + onChanged(); + } else { + runConfigurationBuilder_.setMessage(value); + } + + return this; + } + /** + * 
    +     * Run-specific parameters (arguments, etc)
+     *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + */ + public Builder setRunConfiguration( + org.tensorflow.proto.RunConfiguration.Builder builderForValue) { + if (runConfigurationBuilder_ == null) { + runConfiguration_ = builderForValue.build(); + onChanged(); + } else { + runConfigurationBuilder_.setMessage(builderForValue.build()); + } + + return this; + } + /** + * 
    +     * Run-specific parameters (arguments, etc)
+     *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + */ + public Builder mergeRunConfiguration(org.tensorflow.proto.RunConfiguration value) { + if (runConfigurationBuilder_ == null) { + if (runConfiguration_ != null) { + runConfiguration_ = + org.tensorflow.proto.RunConfiguration.newBuilder(runConfiguration_).mergeFrom(value).buildPartial(); + } else { + runConfiguration_ = value; + } + onChanged(); + } else { + runConfigurationBuilder_.mergeFrom(value); + } + + return this; + } + /** + * 
    +     * Run-specific parameters (arguments, etc)
+     *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + */ + public Builder clearRunConfiguration() { + if (runConfigurationBuilder_ == null) { + runConfiguration_ = null; + onChanged(); + } else { + runConfiguration_ = null; + runConfigurationBuilder_ = null; + } + + return this; + } + /** + * 
    +     * Run-specific parameters (arguments, etc)
+     *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + */ + public org.tensorflow.proto.RunConfiguration.Builder getRunConfigurationBuilder() { + + onChanged(); + return getRunConfigurationFieldBuilder().getBuilder(); + } + /** + * 
    +     * Run-specific parameters (arguments, etc)
+     *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + */ + public org.tensorflow.proto.RunConfigurationOrBuilder getRunConfigurationOrBuilder() { + if (runConfigurationBuilder_ != null) { + return runConfigurationBuilder_.getMessageOrBuilder(); + } else { + return runConfiguration_ == null ? + org.tensorflow.proto.RunConfiguration.getDefaultInstance() : runConfiguration_; + } + } + /** + * 
    +     * Run-specific parameters (arguments, etc)
+     *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + */ + private com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.RunConfiguration, org.tensorflow.proto.RunConfiguration.Builder, org.tensorflow.proto.RunConfigurationOrBuilder> + getRunConfigurationFieldBuilder() { + if (runConfigurationBuilder_ == null) { + runConfigurationBuilder_ = new com.google.protobuf.SingleFieldBuilderV3< + org.tensorflow.proto.RunConfiguration, org.tensorflow.proto.RunConfiguration.Builder, org.tensorflow.proto.RunConfigurationOrBuilder>( + getRunConfiguration(), + getParentForChildren(), + isClean()); + runConfiguration_ = null; + } + return runConfigurationBuilder_; + } + + private java.lang.Object name_ = ""; + /** + * 
    +     * Benchmark target identifier.
+     *
    + * + * string name = 9; + * @return The name. + */ + public java.lang.String getName() { + java.lang.Object ref = name_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + name_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * Benchmark target identifier.
+     *
    + * + * string name = 9; + * @return The bytes for name. + */ + public com.google.protobuf.ByteString + getNameBytes() { + java.lang.Object ref = name_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + name_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * Benchmark target identifier.
+     *
    + * + * string name = 9; + * @param value The name to set. + * @return This builder for chaining. + */ + public Builder setName( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + name_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Benchmark target identifier.
+     *
    + * + * string name = 9; + * @return This builder for chaining. + */ + public Builder clearName() { + + name_ = getDefaultInstance().getName(); + onChanged(); + return this; + } + /** + * 
    +     * Benchmark target identifier.
+     *
    + * + * string name = 9; + * @param value The bytes for name to set. + * @return This builder for chaining. + */ + public Builder setNameBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + name_ = value; + onChanged(); + return this; + } + + private int benchmarkType_ = 0; + /** + * .tensorflow.TestResults.BenchmarkType benchmark_type = 10; + * @return The enum numeric value on the wire for benchmarkType. + */ + @java.lang.Override public int getBenchmarkTypeValue() { + return benchmarkType_; + } + /** + * .tensorflow.TestResults.BenchmarkType benchmark_type = 10; + * @param value The enum numeric value on the wire for benchmarkType to set. + * @return This builder for chaining. + */ + public Builder setBenchmarkTypeValue(int value) { + + benchmarkType_ = value; + onChanged(); + return this; + } + /** + * .tensorflow.TestResults.BenchmarkType benchmark_type = 10; + * @return The benchmarkType. + */ + @java.lang.Override + public org.tensorflow.proto.TestResults.BenchmarkType getBenchmarkType() { + @SuppressWarnings("deprecation") + org.tensorflow.proto.TestResults.BenchmarkType result = org.tensorflow.proto.TestResults.BenchmarkType.valueOf(benchmarkType_); + return result == null ? org.tensorflow.proto.TestResults.BenchmarkType.UNRECOGNIZED : result; + } + /** + * .tensorflow.TestResults.BenchmarkType benchmark_type = 10; + * @param value The benchmarkType to set. + * @return This builder for chaining. + */ + public Builder setBenchmarkType(org.tensorflow.proto.TestResults.BenchmarkType value) { + if (value == null) { + throw new NullPointerException(); + } + + benchmarkType_ = value.getNumber(); + onChanged(); + return this; + } + /** + * .tensorflow.TestResults.BenchmarkType benchmark_type = 10; + * @return This builder for chaining. + */ + public Builder clearBenchmarkType() { + + benchmarkType_ = 0; + onChanged(); + return this; + } + + private java.lang.Object runMode_ = ""; + /** + * 
    +     * Used for differentiating between continuous and debug builds.
+     * Must be one of:
+     * * cbuild: results from continuous build.
+     * * presubmit: results from oneshot requests.
+     * * culprit: results from culprit finder rerun.
+     *
    + * + * string run_mode = 11; + * @return The runMode. + */ + public java.lang.String getRunMode() { + java.lang.Object ref = runMode_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + runMode_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * Used for differentiating between continuous and debug builds.
+     * Must be one of:
+     * * cbuild: results from continuous build.
+     * * presubmit: results from oneshot requests.
+     * * culprit: results from culprit finder rerun.
+     *
    + * + * string run_mode = 11; + * @return The bytes for runMode. + */ + public com.google.protobuf.ByteString + getRunModeBytes() { + java.lang.Object ref = runMode_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + runMode_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * Used for differentiating between continuous and debug builds.
+     * Must be one of:
+     * * cbuild: results from continuous build.
+     * * presubmit: results from oneshot requests.
+     * * culprit: results from culprit finder rerun.
+     *
    + * + * string run_mode = 11; + * @param value The runMode to set. + * @return This builder for chaining. + */ + public Builder setRunMode( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + runMode_ = value; + onChanged(); + return this; + } + /** + * 
    +     * Used for differentiating between continuous and debug builds.
+     * Must be one of:
+     * * cbuild: results from continuous build.
+     * * presubmit: results from oneshot requests.
+     * * culprit: results from culprit finder rerun.
+     *
    + * + * string run_mode = 11; + * @return This builder for chaining. + */ + public Builder clearRunMode() { + + runMode_ = getDefaultInstance().getRunMode(); + onChanged(); + return this; + } + /** + * 
    +     * Used for differentiating between continuous and debug builds.
+     * Must be one of:
+     * * cbuild: results from continuous build.
+     * * presubmit: results from oneshot requests.
+     * * culprit: results from culprit finder rerun.
+     *
    + * + * string run_mode = 11; + * @param value The bytes for runMode to set. + * @return This builder for chaining. + */ + public Builder setRunModeBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + runMode_ = value; + onChanged(); + return this; + } + + private java.lang.Object tfVersion_ = ""; + /** + * 
    +     * TensorFlow version this benchmark runs against.
+     * This can be either set to full version or just the major version.
+     *
    + * + * string tf_version = 12; + * @return The tfVersion. + */ + public java.lang.String getTfVersion() { + java.lang.Object ref = tfVersion_; + if (!(ref instanceof java.lang.String)) { + com.google.protobuf.ByteString bs = + (com.google.protobuf.ByteString) ref; + java.lang.String s = bs.toStringUtf8(); + tfVersion_ = s; + return s; + } else { + return (java.lang.String) ref; + } + } + /** + * 
    +     * TensorFlow version this benchmark runs against.
+     * This can be either set to full version or just the major version.
+     *
    + * + * string tf_version = 12; + * @return The bytes for tfVersion. + */ + public com.google.protobuf.ByteString + getTfVersionBytes() { + java.lang.Object ref = tfVersion_; + if (ref instanceof String) { + com.google.protobuf.ByteString b = + com.google.protobuf.ByteString.copyFromUtf8( + (java.lang.String) ref); + tfVersion_ = b; + return b; + } else { + return (com.google.protobuf.ByteString) ref; + } + } + /** + * 
    +     * TensorFlow version this benchmark runs against.
+     * This can be either set to full version or just the major version.
+     *
    + * + * string tf_version = 12; + * @param value The tfVersion to set. + * @return This builder for chaining. + */ + public Builder setTfVersion( + java.lang.String value) { + if (value == null) { + throw new NullPointerException(); + } + + tfVersion_ = value; + onChanged(); + return this; + } + /** + * 
    +     * TensorFlow version this benchmark runs against.
+     * This can be either set to full version or just the major version.
+     *
    + * + * string tf_version = 12; + * @return This builder for chaining. + */ + public Builder clearTfVersion() { + + tfVersion_ = getDefaultInstance().getTfVersion(); + onChanged(); + return this; + } + /** + * 
    +     * TensorFlow version this benchmark runs against.
+     * This can be either set to full version or just the major version.
+     *
    + * + * string tf_version = 12; + * @param value The bytes for tfVersion to set. + * @return This builder for chaining. + */ + public Builder setTfVersionBytes( + com.google.protobuf.ByteString value) { + if (value == null) { + throw new NullPointerException(); + } + checkByteStringIsUtf8(value); + + tfVersion_ = value; + onChanged(); + return this; + } + @java.lang.Override + public final Builder setUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.setUnknownFields(unknownFields); + } + + @java.lang.Override + public final Builder mergeUnknownFields( + final com.google.protobuf.UnknownFieldSet unknownFields) { + return super.mergeUnknownFields(unknownFields); + } + + + // @@protoc_insertion_point(builder_scope:tensorflow.TestResults) + } + + // @@protoc_insertion_point(class_scope:tensorflow.TestResults) + private static final org.tensorflow.proto.TestResults DEFAULT_INSTANCE; + static { + DEFAULT_INSTANCE = new org.tensorflow.proto.TestResults(); + } + + public static org.tensorflow.proto.TestResults getDefaultInstance() { + return DEFAULT_INSTANCE; + } + + private static final com.google.protobuf.Parser + PARSER = new com.google.protobuf.AbstractParser() { + @java.lang.Override + public TestResults parsePartialFrom( + com.google.protobuf.CodedInputStream input, + com.google.protobuf.ExtensionRegistryLite extensionRegistry) + throws com.google.protobuf.InvalidProtocolBufferException { + Builder builder = newBuilder(); + try { + builder.mergeFrom(input, extensionRegistry); + } catch (com.google.protobuf.InvalidProtocolBufferException e) { + throw e.setUnfinishedMessage(builder.buildPartial()); + } catch (com.google.protobuf.UninitializedMessageException e) { + throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); + } catch (java.io.IOException e) { + throw new com.google.protobuf.InvalidProtocolBufferException(e) + .setUnfinishedMessage(builder.buildPartial()); + } + return builder.buildPartial(); + } + }; + + public static com.google.protobuf.Parser parser() { + return PARSER; + } + + @java.lang.Override + public com.google.protobuf.Parser getParserForType() { + return PARSER; + } + + @java.lang.Override + public org.tensorflow.proto.TestResults getDefaultInstanceForType() { + return DEFAULT_INSTANCE; + } + +} + diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestResultsOrBuilder.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestResultsOrBuilder.java new file mode 100644 index 00000000000..1d6f1545988 --- /dev/null +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/TestResultsOrBuilder.java @@ -0,0 +1,267 @@ +// Generated by the protocol buffer compiler. DO NOT EDIT! +// source: xla/tsl/protobuf/test_log.proto + +package org.tensorflow.proto; + +public interface TestResultsOrBuilder extends + // @@protoc_insertion_point(interface_extends:tensorflow.TestResults) + com.google.protobuf.MessageOrBuilder { + + /** + * 
    +   * The target of the run, e.g.:
+   *  //tensorflow/core:kernels_adjust_contrast_op_benchmark_test
+   *
    + * + * string target = 1; + * @return The target. + */ + java.lang.String getTarget(); + /** + * 
    +   * The target of the run, e.g.:
+   *  //tensorflow/core:kernels_adjust_contrast_op_benchmark_test
+   *
    + * + * string target = 1; + * @return The bytes for target. + */ + com.google.protobuf.ByteString + getTargetBytes(); + + /** + * 
    +   * The list of tests or benchmarks in this run.
+   *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + * @return Whether the entries field is set. + */ + boolean hasEntries(); + /** + * 
    +   * The list of tests or benchmarks in this run.
+   *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + * @return The entries. + */ + org.tensorflow.proto.BenchmarkEntries getEntries(); + /** + * 
    +   * The list of tests or benchmarks in this run.
+   *
    + * + * .tensorflow.BenchmarkEntries entries = 2; + */ + org.tensorflow.proto.BenchmarkEntriesOrBuilder getEntriesOrBuilder(); + + /** + * 
    +   * The configuration of the build (compiled opt? with cuda? any copts?)
+   *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + * @return Whether the buildConfiguration field is set. + */ + boolean hasBuildConfiguration(); + /** + * 
    +   * The configuration of the build (compiled opt? with cuda? any copts?)
+   *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + * @return The buildConfiguration. + */ + org.tensorflow.proto.BuildConfiguration getBuildConfiguration(); + /** + * 
    +   * The configuration of the build (compiled opt? with cuda? any copts?)
+   *
    + * + * .tensorflow.BuildConfiguration build_configuration = 3; + */ + org.tensorflow.proto.BuildConfigurationOrBuilder getBuildConfigurationOrBuilder(); + + /** + * 
    +   * The commit id (git hash or changelist)
+   *
    + * + * .tensorflow.CommitId commit_id = 4; + * @return Whether the commitId field is set. + */ + boolean hasCommitId(); + /** + * 
    +   * The commit id (git hash or changelist)
+   *
    + * + * .tensorflow.CommitId commit_id = 4; + * @return The commitId. + */ + org.tensorflow.proto.CommitId getCommitId(); + /** + * 
    +   * The commit id (git hash or changelist)
+   *
    + * + * .tensorflow.CommitId commit_id = 4; + */ + org.tensorflow.proto.CommitIdOrBuilder getCommitIdOrBuilder(); + + /** + * 
    +   * The time the run started (in seconds of UTC time since Unix epoch)
+   *
    + * + * int64 start_time = 5; + * @return The startTime. + */ + long getStartTime(); + + /** + * 
    +   * The amount of time the total run took (wall time in seconds)
+   *
    + * + * double run_time = 6; + * @return The runTime. + */ + double getRunTime(); + + /** + * 
    +   * Machine-specific parameters (Platform and CPU info)
+   *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + * @return Whether the machineConfiguration field is set. + */ + boolean hasMachineConfiguration(); + /** + * 
    +   * Machine-specific parameters (Platform and CPU info)
+   *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + * @return The machineConfiguration. + */ + org.tensorflow.proto.MachineConfiguration getMachineConfiguration(); + /** + * 
    +   * Machine-specific parameters (Platform and CPU info)
+   *
    + * + * .tensorflow.MachineConfiguration machine_configuration = 7; + */ + org.tensorflow.proto.MachineConfigurationOrBuilder getMachineConfigurationOrBuilder(); + + /** + * 
    +   * Run-specific parameters (arguments, etc)
+   *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + * @return Whether the runConfiguration field is set. + */ + boolean hasRunConfiguration(); + /** + * 
    +   * Run-specific parameters (arguments, etc)
+   *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + * @return The runConfiguration. + */ + org.tensorflow.proto.RunConfiguration getRunConfiguration(); + /** + * 
    +   * Run-specific parameters (arguments, etc)
+   *
    + * + * .tensorflow.RunConfiguration run_configuration = 8; + */ + org.tensorflow.proto.RunConfigurationOrBuilder getRunConfigurationOrBuilder(); + + /** + * 
    +   * Benchmark target identifier.
+   *
    + * + * string name = 9; + * @return The name. + */ + java.lang.String getName(); + /** + * 
    +   * Benchmark target identifier.
+   *
    + * + * string name = 9; + * @return The bytes for name. + */ + com.google.protobuf.ByteString + getNameBytes(); + + /** + * .tensorflow.TestResults.BenchmarkType benchmark_type = 10; + * @return The enum numeric value on the wire for benchmarkType. + */ + int getBenchmarkTypeValue(); + /** + * .tensorflow.TestResults.BenchmarkType benchmark_type = 10; + * @return The benchmarkType. + */ + org.tensorflow.proto.TestResults.BenchmarkType getBenchmarkType(); + + /** + * 
    +   * Used for differentiating between continuous and debug builds.
+   * Must be one of:
+   * * cbuild: results from continuous build.
+   * * presubmit: results from oneshot requests.
+   * * culprit: results from culprit finder rerun.
+   *
    + * + * string run_mode = 11; + * @return The runMode. + */ + java.lang.String getRunMode(); + /** + * 
    +   * Used for differentiating between continuous and debug builds.
+   * Must be one of:
+   * * cbuild: results from continuous build.
+   * * presubmit: results from oneshot requests.
+   * * culprit: results from culprit finder rerun.
+   *
    + * + * string run_mode = 11; + * @return The bytes for runMode. + */ + com.google.protobuf.ByteString + getRunModeBytes(); + + /** + * 
    +   * TensorFlow version this benchmark runs against.
+   * This can be either set to full version or just the major version.
+   *
    + * + * string tf_version = 12; + * @return The tfVersion. + */ + java.lang.String getTfVersion(); + /** + * 
    +   * TensorFlow version this benchmark runs against.
+   * This can be either set to full version or just the major version.
+   *
    + * + * string tf_version = 12; + * @return The bytes for tfVersion. + */ + com.google.protobuf.ByteString + getTfVersionBytes(); +} diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/BfcMemoryMap.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/BfcMemoryMap.java index e957b7817fb..38f0ce96ef4 100644 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/BfcMemoryMap.java +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/BfcMemoryMap.java @@ -33,9 +33,9 @@ public static void registerAllExtensions( descriptor = com.google.protobuf.Descriptors.FileDescriptor .internalBuildGeneratedFileFrom(descriptorData, new com.google.protobuf.Descriptors.FileDescriptor[] { - tensorflow.BfcMemoryMap.getDescriptor(), + org.tensorflow.proto.BfcMemoryMap.getDescriptor(), }); - tensorflow.BfcMemoryMap.getDescriptor(); + org.tensorflow.proto.BfcMemoryMap.getDescriptor(); } // @@protoc_insertion_point(outer_class_scope) diff --git a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/TestLog.java b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/TestLog.java index 73eae05fd2f..95f0ab4c9c2 100644 --- a/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/TestLog.java +++ b/tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto/dummy/TestLog.java @@ -31,9 +31,9 @@ public static void registerAllExtensions( descriptor = com.google.protobuf.Descriptors.FileDescriptor .internalBuildGeneratedFileFrom(descriptorData, new com.google.protobuf.Descriptors.FileDescriptor[] { - org.tensorflow.util.testlog.TestLogProtos.getDescriptor(), + org.tensorflow.proto.TestLogProtos.getDescriptor(), }); - org.tensorflow.util.testlog.TestLogProtos.getDescriptor(); + org.tensorflow.proto.TestLogProtos.getDescriptor(); } // @@protoc_insertion_point(outer_class_scope) From 8f6db1bc0aaef4f300b03ad2175db5cf43acc650 Mon Sep 17 00:00:00 2001 From: Adam Pocock Date: Fri, 16 May 2025 14:55:22 -0400 Subject: [PATCH 05/11] Bumping versions to 1.1.0-SNAPSHOT. --- README.md | 19 ++++++++++--------- docs/install.md | 8 ++++---- pom.xml | 2 +- tensorflow-core/pom.xml | 2 +- tensorflow-core/tensorflow-core-api/pom.xml | 2 +- .../tensorflow-core-generator/pom.xml | 2 +- .../tensorflow-core-native/pom.xml | 2 +- .../tensorflow-core-platform/pom.xml | 2 +- tensorflow-framework/pom.xml | 2 +- 9 files changed, 21 insertions(+), 20 deletions(-) diff --git a/README.md b/README.md index e48ba72e656..1b33f042b25 100644 --- a/README.md +++ b/README.md @@ -69,12 +69,12 @@ systems with no GPU support, you should add the following dependencies: org.tensorflow tensorflow-core-api - 1.0.0-rc.2 + 1.0.0 org.tensorflow tensorflow-core-native - 1.0.0-rc.2 + 1.0.0 linux-x86_64 ``` @@ -85,24 +85,24 @@ native dependencies as follows: org.tensorflow tensorflow-core-api - 1.0.0-rc.2 + 1.0.0 org.tensorflow tensorflow-core-native - 1.0.0-rc.2 + 1.0.0 linux-x86_64-gpu org.tensorflow tensorflow-core-native - 1.0.0-rc.2 + 1.0.0 macosx-arm64 org.tensorflow tensorflow-core-native - 1.0.0-rc.2 + 1.0.0 windows-x86_64 ``` @@ -123,7 +123,7 @@ simply add this dependency to your application: org.tensorflow tensorflow-core-platform - 1.0.0-rc.2 + 1.0.0 ``` @@ -153,7 +153,7 @@ to add Sonatype OSS repository in your pom.xml, like the following org.tensorflow tensorflow-core-platform - 1.0.0-SNAPSHOT + 1.1.0-SNAPSHOT ``` @@ -175,7 +175,8 @@ This table shows the mapping between TensorFlow, TensorFlow Java and minimum sup | 0.5.0 | 2.10.1 | 11 | | 1.0.0-rc.1 | 2.16.1 | 11 | | 1.0.0-rc.2 | 2.16.2 | 11 | -| 1.0.0-SNAPSHOT | 2.16.2 | 11 | +| 1.0.0 | 2.16.2 | 11 | +| 1.1.0-SNAPSHOT | 2.18.0 | 11 | ## How to Contribute? diff --git a/docs/install.md b/docs/install.md index 2dc2601b0e5..3c969c433dc 100644 --- a/docs/install.md +++ b/docs/install.md @@ -59,7 +59,7 @@ For example, org.tensorflow tensorflow-core-platform - 1.0.0-rc.2 + 1.0.0 ``` @@ -102,7 +102,7 @@ snapshots repository in your `pom.xml`. org.tensorflow tensorflow-core-platform - 1.0.0-SNAPSHOT + 1.1.0-SNAPSHOT ``` @@ -119,7 +119,7 @@ repositories { } dependencies { - compile group: 'org.tensorflow', name: 'tensorflow-core-platform', version: '1.0.0-rc.2' + compile group: 'org.tensorflow', name: 'tensorflow-core-platform', version: '1.0.0' } ``` @@ -165,7 +165,7 @@ add the TensorFlow dependency to the project's `pom.xml` file: org.tensorflow tensorflow-core-platform - 1.0.0-rc.2 + 1.0.0 diff --git a/pom.xml b/pom.xml index e5ddc337a97..a65a232cada 100644 --- a/pom.xml +++ b/pom.xml @@ -7,7 +7,7 @@ org.tensorflow tensorflow-java - 1.0.0-SNAPSHOT + 1.1.0-SNAPSHOT pom TensorFlow Java Parent diff --git a/tensorflow-core/pom.xml b/tensorflow-core/pom.xml index 2813ad72a09..5b378653ba8 100644 --- a/tensorflow-core/pom.xml +++ b/tensorflow-core/pom.xml @@ -22,7 +22,7 @@ org.tensorflow tensorflow-java - 1.0.0-SNAPSHOT + 1.1.0-SNAPSHOT tensorflow-core pom diff --git a/tensorflow-core/tensorflow-core-api/pom.xml b/tensorflow-core/tensorflow-core-api/pom.xml index d08f7733cba..077977144dc 100644 --- a/tensorflow-core/tensorflow-core-api/pom.xml +++ b/tensorflow-core/tensorflow-core-api/pom.xml @@ -6,7 +6,7 @@ org.tensorflow tensorflow-core - 1.0.0-SNAPSHOT + 1.1.0-SNAPSHOT tensorflow-core-api jar diff --git a/tensorflow-core/tensorflow-core-generator/pom.xml b/tensorflow-core/tensorflow-core-generator/pom.xml index a90d85a1d4b..923bd52b4e6 100644 --- a/tensorflow-core/tensorflow-core-generator/pom.xml +++ b/tensorflow-core/tensorflow-core-generator/pom.xml @@ -5,7 +5,7 @@ org.tensorflow tensorflow-core - 1.0.0-SNAPSHOT + 1.1.0-SNAPSHOT tensorflow-core-generator jar diff --git a/tensorflow-core/tensorflow-core-native/pom.xml b/tensorflow-core/tensorflow-core-native/pom.xml index 3c77906c0e5..ec42150271e 100644 --- a/tensorflow-core/tensorflow-core-native/pom.xml +++ b/tensorflow-core/tensorflow-core-native/pom.xml @@ -6,7 +6,7 @@ org.tensorflow tensorflow-core - 1.0.0-SNAPSHOT + 1.1.0-SNAPSHOT tensorflow-core-native jar diff --git a/tensorflow-core/tensorflow-core-platform/pom.xml b/tensorflow-core/tensorflow-core-platform/pom.xml index 0d43c7fc4b3..9ce366bca21 100644 --- a/tensorflow-core/tensorflow-core-platform/pom.xml +++ b/tensorflow-core/tensorflow-core-platform/pom.xml @@ -22,7 +22,7 @@ org.tensorflow tensorflow-core - 1.0.0-SNAPSHOT + 1.1.0-SNAPSHOT tensorflow-core-platform TensorFlow API Platform diff --git a/tensorflow-framework/pom.xml b/tensorflow-framework/pom.xml index 982bf78e118..ed64855877d 100644 --- a/tensorflow-framework/pom.xml +++ b/tensorflow-framework/pom.xml @@ -22,7 +22,7 @@ org.tensorflow tensorflow-java - 1.0.0-SNAPSHOT + 1.1.0-SNAPSHOT tensorflow-framework jar From 184782894c84d97d3d03e199a4301ac1bfda9dc1 Mon Sep 17 00:00:00 2001 From: Adam Pocock Date: Fri, 16 May 2025 14:57:42 -0400 Subject: [PATCH 06/11] Bumping the CI to Ubuntu 22.04 --- .github/workflows/build.yml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 28e9cda7d4c..0ef75b40f35 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -17,7 +17,7 @@ env: jobs: check-format: if: github.event_name == 'pull_request' - runs-on: ubuntu-20.04 + runs-on: ubuntu-22.04 steps: - name: Configure Java uses: actions/setup-java@v2 @@ -35,7 +35,7 @@ jobs: run: | mvn spotless:check -Pjdk17 -B -U -e prepare: - runs-on: ubuntu-20.04 + runs-on: ubuntu-22.04 outputs: repositoryUrl: ${{ steps.repository.outputs.repositoryUrl }} steps: @@ -91,7 +91,7 @@ jobs: if: env.DEPLOY_RELEASE == 'true' || env.DEPLOY_SNAPSHOT == 'true' run: mvn -f tensorflow-core/tensorflow-core-native/pom.xml deploy:deploy-file@native-only -B -e -Djavacpp.platform=${{ github.job }} -Djavacpp.platform.extension=${{ matrix.ext }} -Durl=${{ needs.prepare.outputs.repositoryUrl }} linux-x86_64: - runs-on: ubuntu-20.04 + runs-on: ubuntu-22.04 needs: prepare strategy: matrix: @@ -209,7 +209,7 @@ jobs: deploy: if: ${{ github.event_name == 'push' && (github.ref == 'refs/heads/master' || github.ref == 'refs/heads/staging') }} # DEPLOY_SNAPSHOT (releases should be signed and deployed manually from local machine) needs: [linux-x86_64, macosx-x86_64, windows-x86_64, macosx-arm64, linux-arm64] - runs-on: ubuntu-20.04 + runs-on: ubuntu-22.04 steps: - name: Configure Java uses: actions/setup-java@v2 From 3102cc015cac038f89e261514c9b17fcad921873 Mon Sep 17 00:00:00 2001 From: Adam Pocock Date: Fri, 23 May 2025 15:19:50 -0400 Subject: [PATCH 07/11] Fixes for CI. --- .github/workflows/build.yml | 1 + .../java/org/tensorflow/internal/c_api/presets/tensorflow.java | 3 --- 2 files changed, 1 insertion(+), 3 deletions(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 0ef75b40f35..e9e7d82cdfb 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -138,6 +138,7 @@ jobs: if: env.DEPLOY_RELEASE == 'true' || env.DEPLOY_SNAPSHOT == 'true' run: mvn -f tensorflow-core/tensorflow-core-native/pom.xml deploy:deploy-file@native-only -B -e -Djavacpp.platform=${{ github.job }} -Djavacpp.platform.extension=${{ matrix.ext }} -Durl=${{ needs.prepare.outputs.repositoryUrl }} macosx-x86_64: + if: startsWith(github.ref, 'refs/heads/r1.0') runs-on: macos-12 needs: prepare strategy: diff --git a/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java b/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java index 54c2fb1c827..c9c0024f354 100644 --- a/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java +++ b/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java @@ -62,9 +62,6 @@ }, link = {"tensorflow_cc@.2", "tensorflow_framework@.2"}, resource = {"LICENSE", "THIRD_PARTY_TF_JNI_LICENSES"}), - @Platform( - value = {"linux-arm64"}, - link = {"tensorflow_cc@.2", "tensorflow_framework@.2", "omp-e9212f90@.5"}), @Platform( value = "windows", preload = { From a60b826428292ff917b2d98439f5da348c62ef4c Mon Sep 17 00:00:00 2001 From: Adam Pocock Date: Fri, 23 May 2025 15:22:52 -0400 Subject: [PATCH 08/11] Removing macOS x86_64 from the CI. --- .github/workflows/build.yml | 26 +------------------------- 1 file changed, 1 insertion(+), 25 deletions(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 0947efe245b..c48921c272d 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -137,30 +137,6 @@ jobs: - name: Deploy native artifact if: env.DEPLOY_RELEASE == 'true' || env.DEPLOY_SNAPSHOT == 'true' run: mvn -f tensorflow-core/tensorflow-core-native/pom.xml deploy:deploy-file@native-only -B -e -Djavacpp.platform=${{ github.job }} -Djavacpp.platform.extension=${{ matrix.ext }} -Durl=${{ needs.prepare.outputs.repositoryUrl }} - macosx-x86_64: - if: ${{ github.base_ref == 'r1.0' }} - runs-on: macos-13 - needs: prepare - strategy: - matrix: - ext: [""] - steps: - - name: Configure Java - uses: actions/setup-java@v2 - with: - distribution: 'adopt' - java-version: '11' - - name: Checkout repository - uses: actions/checkout@v1 - - name: Build project - run: | - clang --version - mvn -version - echo "ossrh${{ secrets.CI_DEPLOY_USERNAME }}${{ secrets.CI_DEPLOY_PASSWORD }}" > $HOME/.m2/settings.xml - mvn clean install -pl '!tensorflow-framework' -B -U -e -Djavacpp.platform=${{ github.job }} -Djavacpp.platform.extension=${{ matrix.ext }} - - name: Deploy native artifact - if: env.DEPLOY_RELEASE == 'true' || env.DEPLOY_SNAPSHOT == 'true' - run: mvn -f tensorflow-core/tensorflow-core-native/pom.xml deploy:deploy-file@native-only -B -e -Djavacpp.platform=${{ github.job }} -Djavacpp.platform.extension=${{ matrix.ext }} -Durl=${{ needs.prepare.outputs.repositoryUrl }} windows-x86_64: runs-on: windows-2019 needs: prepare @@ -209,7 +185,7 @@ jobs: if ERRORLEVEL 1 exit /b deploy: if: ${{ github.event_name == 'push' && (github.ref == 'refs/heads/master' || github.ref == 'refs/heads/staging') }} # DEPLOY_SNAPSHOT (releases should be signed and deployed manually from local machine) - needs: [linux-x86_64, macosx-x86_64, windows-x86_64, macosx-arm64, linux-arm64] + needs: [linux-x86_64, windows-x86_64, macosx-arm64, linux-arm64] runs-on: ubuntu-22.04 steps: - name: Configure Java From 6b736ca50232886ffc639641cbb377faffc7f4b5 Mon Sep 17 00:00:00 2001 From: Adam Pocock Date: Fri, 23 May 2025 15:30:26 -0400 Subject: [PATCH 09/11] Docs and pom updates for dropping macos x86_64. --- README.md | 6 ++++-- docs/install.md | 5 ++++- tensorflow-core/tensorflow-core-native/pom.xml | 10 ---------- tensorflow-core/tensorflow-core-platform/pom.xml | 8 +------- 4 files changed, 9 insertions(+), 20 deletions(-) diff --git a/README.md b/README.md index c3931f2a5b7..00cacf870c4 100644 --- a/README.md +++ b/README.md @@ -59,10 +59,12 @@ only binaries for the followings are being **supported and distributed** by this - `linux-x86_64`: Linux platforms on Intel/AMD chips - `linux-x86_64-gpu`: Linux platforms on Intel/AMD chips with Cuda GPU support - `linux-arm64`: Linux platforms on Arm chips -- `macosx-x86_64`: MacOS X platforms on Intel/AMD chips - `macosx-arm64`: MacOS X platforms on Apple Silicon chips - `windows-x86_64`: Windows platforms on Intel/AMD chips +Binaries for `macosx-x86_64` are available for TF-Java 1.0 series releases and earlier, they were dropped from +TF-Java 1.1 and newer as they are no longer supported or released by Google. + For example, for building a JAR that uses TensorFlow and is targeted to be deployed only on Linux systems with no GPU support, you should add the following dependencies: ```xml @@ -119,7 +121,7 @@ For Ubuntu 24.04, you can install them with the following command: In some cases, it might be preferable to add a single dependency that includes transitively all the artifacts required to run TensorFlow Java on any [supported platforms](README.md#individual-dependencies) -- `tensorflow-core-platform`: Includes `tensorflow-core-api`, plus native artifacts for `linux-x86_64`, `linux-x86_64-arm64`, `macosx-arm64`, `macosx-x86_64` and `windows-x86_64` +- `tensorflow-core-platform`: Includes `tensorflow-core-api`, plus native artifacts for `linux-x86_64`, `linux-x86_64-arm64`, `macosx-arm64` and `windows-x86_64` For example, to run TensorFlow Java on any CPU platform for which a binary is being distributed by this project, you can simply add this dependency to your application: diff --git a/docs/install.md b/docs/install.md index 3c969c433dc..cfffe9959a5 100644 --- a/docs/install.md +++ b/docs/install.md @@ -18,10 +18,13 @@ following platforms: * Ubuntu 20.04 or higher; 64-bit, x86 * Ubuntu 22.04 or higher; 64-bit, arm -* macOS 12 or higher; 64-bit, x86 * macOS 14 or higher; 64-bit, arm * Windows 10 or higher; 64-bit, x86 +TensorFlow Java 1.0 series and earlier releases also have binaries for: + +* macOS 12 or higher; 64-bit, x86 + *Note: To use TensorFlow on Android, see [TensorFlow Lite](https://tensorflow.org/lite)* diff --git a/tensorflow-core/tensorflow-core-native/pom.xml b/tensorflow-core/tensorflow-core-native/pom.xml index ec42150271e..3814864439a 100644 --- a/tensorflow-core/tensorflow-core-native/pom.xml +++ b/tensorflow-core/tensorflow-core-native/pom.xml @@ -113,12 +113,6 @@ ${project.version} ${javacpp.platform.linux-x86_64}-gpu - - ${project.groupId} - ${project.artifactId} - ${project.version} - ${javacpp.platform.macosx-x86_64} - ${project.groupId} ${project.artifactId} @@ -167,10 +161,6 @@ ${project.build.directory}/${project.artifactId}-${project.version}-${javacpp.platform.macosx-arm64}.jar ${javacpp.platform.macosx-arm64} - - ${project.build.directory}/${project.artifactId}-${project.version}-${javacpp.platform.macosx-x86_64}.jar - ${javacpp.platform.macosx-x86_64} - ${project.build.directory}/${project.artifactId}-${project.version}-${javacpp.platform.windows-x86_64}.jar ${javacpp.platform.windows-x86_64} diff --git a/tensorflow-core/tensorflow-core-platform/pom.xml b/tensorflow-core/tensorflow-core-platform/pom.xml index 9ce366bca21..ec19cf501f1 100644 --- a/tensorflow-core/tensorflow-core-platform/pom.xml +++ b/tensorflow-core/tensorflow-core-platform/pom.xml @@ -55,12 +55,6 @@ ${project.version} macosx-arm64 - - org.tensorflow - tensorflow-core-native - ${project.version} - macosx-x86_64 - org.tensorflow tensorflow-core-native @@ -79,7 +73,7 @@ - tensorflow-core-api.jar tensorflow-core-native.jar tensorflow-core-native-linux-x86_64.jar tensorflow-core-native-macosx-arm64.jar tensorflow-core-native-macosx-x86_64.jar tensorflow-core-native-windows-x86_64.jar tensorflow-core-native-linux-arm64.jar + tensorflow-core-api.jar tensorflow-core-native.jar tensorflow-core-native-linux-x86_64.jar tensorflow-core-native-macosx-arm64.jar tensorflow-core-native-windows-x86_64.jar tensorflow-core-native-linux-arm64.jar ${java.module.name} From d806ccdebd9ec6b97e24a7d3bf7e655fc16ae47c Mon Sep 17 00:00:00 2001 From: Adam Pocock Date: Fri, 23 May 2025 15:43:49 -0400 Subject: [PATCH 10/11] Fix libomp path on Linux arm64. --- .../tensorflow-core-native/scripts/dist_download.sh | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh b/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh index 2cc3a49dec0..acf28b9391d 100755 --- a/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh +++ b/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh @@ -52,7 +52,8 @@ if [[ "$PLATFORM" =~ "linux" ]]; then ln -fs libtensorflow_cc.so.2 libtensorflow_cc.so ln -fs libtensorflow_framework.so.2 libtensorflow_framework.so if [[ "$PLATFORM" == "linux-arm64" ]]; then - ln -fs libomp-e9212f90.so.5 libomp-e9212f90.so + cp ../tensorflow.libs/libomp-6196b3b5.so.5 libomp-6196b3b5.so.5 + ln -fs libomp-6196b3b5.so.5 libomp-6196b3b5.so fi elif [[ "$PLATFORM" =~ "macosx" ]]; then ln -fs libtensorflow_cc.2.dylib libtensorflow_cc.dylib From 1c03e7c19f33fce4e7d0562d564604e399769b1b Mon Sep 17 00:00:00 2001 From: Adam Pocock Date: Fri, 23 May 2025 15:49:24 -0400 Subject: [PATCH 11/11] Adding back the libomp link. --- .../java/org/tensorflow/internal/c_api/presets/tensorflow.java | 3 +++ 1 file changed, 3 insertions(+) diff --git a/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java b/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java index c9c0024f354..969c2ae0e80 100644 --- a/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java +++ b/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java @@ -62,6 +62,9 @@ }, link = {"tensorflow_cc@.2", "tensorflow_framework@.2"}, resource = {"LICENSE", "THIRD_PARTY_TF_JNI_LICENSES"}), + @Platform( + value = {"linux-arm64"}, + link = {"tensorflow_cc@.2", "tensorflow_framework@.2", "omp-6196b3b5@.5"}), @Platform( value = "windows", preload = {