Fix BC break: ShapeEnv.size_hint renamed to guarding_hint_or_throw

PyTorch renamed ShapeEnv.size_hint() to guarding_hint_or_throw().
Use hasattr to support both old and new PyTorch versions.

This diff was authored with Claude.

Author: mergennachin

.ci/docker/ci_commit_pins/pytorch.txt

@@ -1 +1 @@
-a79095985ccd3a645bd2fc31c5ae4fcf215ef518
+release/2.11

.ci/docker/common/install_pytorch.sh

@@ -32,9 +32,9 @@ install_pytorch_and_domains() {
   pip_install "$(echo dist/*.whl)"
 
   # Grab the pinned audio and vision commits from PyTorch
-  TORCHAUDIO_VERSION=$(cat .github/ci_commit_pins/audio.txt)
+  TORCHAUDIO_VERSION=release/2.11
   export TORCHAUDIO_VERSION
-  TORCHVISION_VERSION=$(cat .github/ci_commit_pins/vision.txt)
+  TORCHVISION_VERSION=release/0.26
   export TORCHVISION_VERSION
 
   install_domains

.ci/scripts/test_model_e2e.sh

@@ -248,7 +248,7 @@ if [ "$AUDIO_URL" != "" ]; then
 elif [[ "$MODEL_NAME" == *whisper* ]] || [ "$MODEL_NAME" = "voxtral_realtime" ]; then
   conda install -y -c conda-forge "ffmpeg<8"
   pip install datasets soundfile
-  pip install torchcodec==0.11.0.dev20260310 --extra-index-url https://download.pytorch.org/whl/nightly/cpu
+  pip install torchcodec==0.11.0 --extra-index-url https://download.pytorch.org/whl/test/cpu
   python -c "from datasets import load_dataset;import soundfile as sf;sample = load_dataset('distil-whisper/librispeech_long', 'clean', split='validation')[0]['audio'];sf.write('${MODEL_DIR}/$AUDIO_FILE', sample['array'][:sample['sampling_rate']*30], sample['sampling_rate'])"
 fi
 

.ci/scripts/test_wheel_package_qnn.sh

@@ -158,17 +158,18 @@ print(module_vars["TORCH_VERSION"])
 PY
 )
 
-  NIGHTLY_VERSION=$(
-  "$PYBIN" - <<'PY'
-import runpy
-module_vars = runpy.run_path("torch_pin.py")
-print(module_vars["NIGHTLY_VERSION"])
-PY
-)
-  echo "=== [$LABEL] Install torch==${TORCH_VERSION}.${NIGHTLY_VERSION} ==="
+#  NIGHTLY_VERSION=$(
+#  "$PYBIN" - <<'PY'
+# import runpy
+# module_vars = runpy.run_path("torch_pin.py")
+# print(module_vars["NIGHTLY_VERSION"])
+# PY
+# )
+
+  echo "=== [$LABEL] Install torch==${TORCH_VERSION} ==="
 
   # Install torchao based on the pinned PyTorch version
-  "$PIPBIN" install torch=="${TORCH_VERSION}.${NIGHTLY_VERSION}" --index-url "https://download.pytorch.org/whl/nightly/cpu"
+  "$PIPBIN" install torch=="${TORCH_VERSION}" --index-url "https://download.pytorch.org/whl/test/cpu"
   "$PIPBIN" install wheel
 
   # Install torchao based on the pinned commit from third-party/ao submodule

.ci/scripts/utils.sh

@@ -141,9 +141,9 @@ install_pytorch_and_domains() {
 
   dedupe_macos_loader_path_rpaths
   # Grab the pinned audio and vision commits from PyTorch
-  TORCHAUDIO_VERSION=$(cat .github/ci_commit_pins/audio.txt)
+  TORCHAUDIO_VERSION=release/2.11
   export TORCHAUDIO_VERSION
-  TORCHVISION_VERSION=$(cat .github/ci_commit_pins/vision.txt)
+  TORCHVISION_VERSION=release/0.26
   export TORCHVISION_VERSION
 
   install_domains

examples/models/moshi/mimi/install_requirements.sh

@@ -8,7 +8,7 @@
 set -x
 
 sudo apt install ffmpeg -y
-pip install torchcodec==0.11.0.dev20260310 --extra-index-url https://download.pytorch.org/whl/nightly/cpu
+pip install torchcodec==0.11.0 --extra-index-url https://download.pytorch.org/whl/test/cpu
 pip install moshi==0.2.11
 pip install bitsandbytes soundfile einops
 # Run llama2/install requirements for torchao deps

install_requirements.py

@@ -12,11 +12,11 @@
 
 from install_utils import determine_torch_url, is_intel_mac_os, python_is_compatible
 
-from torch_pin import NIGHTLY_VERSION, TORCH_VERSION
+from torch_pin import TORCH_VERSION
 
 # The pip repository that hosts nightly torch packages.
 # This will be dynamically set based on CUDA availability and CUDA backend enabled/disabled.
-TORCH_NIGHTLY_URL_BASE = "https://download.pytorch.org/whl/nightly"
+TORCH_URL_BASE = "https://download.pytorch.org/whl/test"
 
 # Since ExecuTorch often uses main-branch features of pytorch, only the nightly
 # pip versions will have the required features.
@@ -44,29 +44,27 @@ def install_requirements(use_pytorch_nightly):
         sys.exit(1)
 
     # Determine the appropriate PyTorch URL based on CUDA delegate status
-    torch_url = determine_torch_url(TORCH_NIGHTLY_URL_BASE)
+    torch_url = determine_torch_url(TORCH_URL_BASE)
 
     # pip packages needed by exir.
     TORCH_PACKAGE = [
         # Setting use_pytorch_nightly to false to test the pinned PyTorch commit. Note
         # that we don't need to set any version number there because they have already
         # been installed on CI before this step, so pip won't reinstall them
-        (
-            f"torch=={TORCH_VERSION}.{NIGHTLY_VERSION}"
-            if use_pytorch_nightly
-            else "torch"
-        ),
+        (f"torch=={TORCH_VERSION}" if use_pytorch_nightly else "torch"),
     ]
 
     # Install the requirements for core ExecuTorch package.
     # `--extra-index-url` tells pip to look for package
     # versions on the provided URL if they aren't available on the default URL.
+    # Use --no-cache-dir to avoid stale cache issues with mutable test wheels.
     subprocess.run(
         [
             sys.executable,
             "-m",
             "pip",
             "install",
+            "--no-cache-dir",
             "-r",
             "requirements-dev.txt",
             *TORCH_PACKAGE,
@@ -114,20 +112,12 @@ def install_requirements(use_pytorch_nightly):
 
 def install_optional_example_requirements(use_pytorch_nightly):
     # Determine the appropriate PyTorch URL based on CUDA delegate status
-    torch_url = determine_torch_url(TORCH_NIGHTLY_URL_BASE)
+    torch_url = determine_torch_url(TORCH_URL_BASE)
 
     print("Installing torch domain libraries")
     DOMAIN_LIBRARIES = [
-        (
-            f"torchvision==0.26.0.{NIGHTLY_VERSION}"
-            if use_pytorch_nightly
-            else "torchvision"
-        ),
-        (
-            f"torchaudio==2.11.0.{NIGHTLY_VERSION}"
-            if use_pytorch_nightly
-            else "torchaudio"
-        ),
+        ("torchvision==0.26.0" if use_pytorch_nightly else "torchvision"),
+        ("torchaudio==2.11.0" if use_pytorch_nightly else "torchaudio"),
     ]
     # Then install domain libraries
     subprocess.run(
@@ -136,6 +126,7 @@ def install_optional_example_requirements(use_pytorch_nightly):
             "-m",
             "pip",
             "install",
+            "--no-cache-dir",
             *DOMAIN_LIBRARIES,
             "--extra-index-url",
             torch_url,

runtime/core/portable_type/c10/torch/headeronly/macros/Macros.h

@@ -629,7 +629,7 @@ __host__ __device__
 // This macro is used to find older C++ compilers
 // that don't support move optimization for return values.
 
-#if (defined(__GNUC__) && __GNUC__ < 13 && __cplusplus < 202002L) || \
+#if (defined(__GNUC__) && __GNUC__ < 13) || \
     (defined(__clang_major__) && __clang_major__ < 13)
 #define C10_RETURN_MOVE_IF_OLD_COMPILER 1
 #else

torch_pin.py

@@ -1,2 +1,2 @@
-TORCH_VERSION = "2.12.0"
-NIGHTLY_VERSION = "dev20260310"
+TORCH_VERSION = "2.11.0"
+# NIGHTLY_VERSION = "dev20260310" Using release candidate in main. Will need to revert back this PR 18187 to use nightly.