Arm-Examples · MatthiasHertelArm · Jul 9, 2026
diff --git a/.github/workflows/Build_RPS_AppKit-E8.yml b/.github/workflows/Build_RPS_AppKit-E8.yml
@@ -57,7 +57,7 @@ jobs:
       - name: Add Beta packs
         working-directory: ./
         run: |
-          cpackget add ./packs/PyTorch.ExecuTorch.1.3.1-rc8/PyTorch.ExecuTorch.pdsc --agree-embedded-license
+          cpackget add ./packs/PyTorch.ExecuTorch.1.1.0-rc1-build.12/PyTorch.ExecuTorch.pdsc --agree-embedded-license
 
       - name: Build the target-set
         working-directory: ./RockPaperScissors/AppKit-E8_USB

diff --git a/.github/workflows/Build_RPS_Variants.yml b/.github/workflows/Build_RPS_Variants.yml
@@ -70,7 +70,7 @@ jobs:
       - name: Add Beta packs
         working-directory: ./
         run: |
-          cpackget add ./packs/PyTorch.ExecuTorch.1.3.1-rc8/PyTorch.ExecuTorch.pdsc --agree-embedded-license
+          cpackget add ./packs/PyTorch.ExecuTorch.1.1.0-rc1-build.12/PyTorch.ExecuTorch.pdsc --agree-embedded-license
 
       - name: ${{matrix.context.tool}} Build-Test for context ${{matrix.context.proj}}.${{matrix.context.build-type}}+${{matrix.context.target-type}}
         working-directory: ${{matrix.context.dir}}

diff --git a/.github/workflows/Test_RPS_SSE-320-U85.yml b/.github/workflows/Test_RPS_SSE-320-U85.yml
@@ -61,7 +61,7 @@ jobs:
       - name: Add Beta packs
         working-directory: ./
         run: |
-          cpackget add ./packs/PyTorch.ExecuTorch.1.3.1-rc8/PyTorch.ExecuTorch.pdsc --agree-embedded-license
+          cpackget add ./packs/PyTorch.ExecuTorch.1.1.0-rc1-build.12/PyTorch.ExecuTorch.pdsc --agree-embedded-license
 
       - name: Build the target-set
         working-directory: ./RockPaperScissors/AppKit-E8_USB

diff --git a/RockPaperScissors/AppKit-E8_USB/algorithm/ML/ai_layer/ai_layer.clayer.yml b/RockPaperScissors/AppKit-E8_USB/algorithm/ML/ai_layer/ai_layer.clayer.yml
@@ -4,24 +4,25 @@ layer:
 
   packs:
     - pack: PyTorch::ExecuTorch
-      path: ../../../../../packs/PyTorch.ExecuTorch.1.3.1-rc8
+      path: ../../../../../packs/PyTorch.ExecuTorch.1.1.0-rc1-build.12
 
   define:
     - ET_LOG_ENABLED : 0
 
   components:
-    # ExecuTorch core runtime. Runtime now ships the weak PAL (minimal.cpp),
-    # so the 1.1.0 "Platform Bare-Metal" posix stub is no longer needed.
+    # ExecuTorch core runtime
     - component: Machine Learning:ExecuTorch:Runtime
     - component: Machine Learning:ExecuTorch:Kernel Utils
     - component: Machine Learning:ExecuTorch:Kernel Registration
     # Ethos-U NPU backend
     - component: Machine Learning:ExecuTorch:Backend EthosU
-    # Quantized operators used by the RPS model. 1.3.x moves operators to the
-    # "ExecuTorch Operators" Cgroup and #ifdef-guards each registration, so the
-    # 1.1.0 "Stubs RandomOps" component is no longer needed.
-    - component: Machine Learning:ExecuTorch Operators:Quantized quantize
-    - component: Machine Learning:ExecuTorch Operators:Quantized dequantize
+    # Bare-metal PAL stubs (replaces posix.cpp)
+    - component: Machine Learning:ExecuTorch:Platform Bare-Metal
+    # Random op stubs (no std::random_device on bare-metal)
+    - component: Machine Learning:ExecuTorch:Stubs RandomOps
+    # Quantized operators used by the RPS model
+    - component: Machine Learning:ExecuTorch:Operators Quantized quantize
+    - component: Machine Learning:ExecuTorch:Operators Quantized dequantize
 
   groups:
     # AI Model - replace this group with a ModelNova-generated model pack

diff --git a/packs/PyTorch.ExecuTorch.1.1.0-rc1-build.12/Documentation/README.md b/packs/PyTorch.ExecuTorch.1.1.0-rc1-build.12/Documentation/README.md
@@ -0,0 +1,84 @@
+# ExecuTorch CMSIS Pack
+
+## Overview
+
+ExecuTorch is the PyTorch Edge Runtime, enabling efficient on-device AI inference on Arm Cortex-M processors.
+
+This pack provides:
+- **Core Runtime**: Program loading and execution
+- **Portable Operators**: Platform-independent operator implementations
+- **Quantized Operators**: Optimized quantized inference
+- **Ethos-U Backend**: Hardware acceleration for Arm Ethos-U NPU
+- **Cortex-M Backend**: CMSIS-NN optimized operators
+
+## Getting Started
+
+### Basic Usage
+
+1. Add the pack to your csolution:
+   ```yaml
+   packs:
+     - pack: PyTorch::ExecuTorch
+   ```
+
+2. Add required components:
+   ```yaml
+   components:
+     # Core runtime (always required)
+     - component: Machine Learning:ExecuTorch:Runtime
+     - component: Machine Learning:ExecuTorch:Kernel Utils
+
+     # Backend (choose one or more)
+     - component: Machine Learning:ExecuTorch:Backend::EthosU
+     # or
+     - component: Machine Learning:ExecuTorch:Backend::CortexM
+   ```
+
+3. Include ExecuTorch headers in your code:
+   ```cpp
+   #include <executorch/runtime/executor/program.h>
+   #include <executorch/runtime/executor/method.h>
+   ```
+
+### Model Integration
+
+For automatic operator selection, use a Model Pack generated from your `.pte` file. The model pack declares dependencies on required operators, which are automatically resolved.
+
+Alternatively, manually add required operators:
+```yaml
+components:
+  - component: Machine Learning:ExecuTorch:Operators::Portable::add
+  - component: Machine Learning:ExecuTorch:Operators::Portable::mul
+  # ... other operators used by your model
+```
+
+## Memory Requirements
+
+| Component | Flash (approx) | RAM (approx) |
+|-----------|----------------|--------------|
+| Runtime | 50-100 KB | 4-8 KB |
+| Per Operator | 1-10 KB | minimal |
+| Ethos-U Backend | 20-40 KB | 2-4 KB |
+
+Actual requirements depend on:
+- Selected operators
+- Model complexity
+- Tensor sizes
+
+## Compiler Support
+
+- **GCC**: arm-none-eabi-gcc 13.x+
+- **Arm Compiler 6**: armclang 6.24+
+- **LLVM/Clang**: Arm Compiler for Embedded
+
+## Dependencies
+
+- ARM::CMSIS (core headers)
+- ARM::CMSIS-NN (for Cortex-M backend)
+- ARM::ethos-u-core-driver (for Ethos-U backend)
+
+## Resources
+
+- [ExecuTorch Documentation](https://pytorch.org/executorch/)
+- [CMSIS-Pack Specification](https://open-cmsis-pack.github.io/Open-CMSIS-Pack-Spec/main/html/index.html)
+- [Issue Tracker](https://github.com/pytorch/executorch/issues)
diff --git a/packs/PyTorch.ExecuTorch.1.1.0-rc1-build.12/LICENSE b/packs/PyTorch.ExecuTorch.1.1.0-rc1-build.12/LICENSE
@@ -0,0 +1,29 @@
+BSD 3-Clause License
+
+Copyright (c) Meta Platforms, Inc. and affiliates.
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+
+3. Neither the name of the copyright holder nor the names of its
+   contributors may be used to endorse or promote products derived from
+   this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.