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| # Test ExecuTorch CUDA Build Compatibility | |
| # This workflow tests whether ExecuTorch can be successfully built with CUDA support | |
| # across different CUDA versions (12.6, 12.8, 12.9) using the command: | |
| # CMAKE_ARGS="-DEXECUTORCH_BUILD_CUDA=ON" ./install_executorch.sh | |
| # | |
| # Note: ExecuTorch automatically detects the system CUDA version using nvcc and | |
| # installs the appropriate PyTorch wheel. No manual CUDA/PyTorch installation needed. | |
| name: Test CUDA Builds | |
| on: | |
| pull_request: | |
| push: | |
| branches: | |
| - main | |
| - release/* | |
| concurrency: | |
| group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }} | |
| cancel-in-progress: false | |
| jobs: | |
| test-cuda-builds: | |
| strategy: | |
| fail-fast: false | |
| matrix: | |
| cuda-version: ["12.6", "12.8", "13.0"] | |
| name: test-executorch-cuda-build-${{ matrix.cuda-version }} | |
| uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main | |
| permissions: | |
| id-token: write | |
| contents: read | |
| with: | |
| timeout: 90 | |
| runner: linux.g5.4xlarge.nvidia.gpu | |
| gpu-arch-type: cuda | |
| gpu-arch-version: ${{ matrix.cuda-version }} | |
| use-custom-docker-registry: false | |
| submodules: recursive | |
| ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
| script: | | |
| set -eux | |
| # Test ExecuTorch CUDA build - ExecuTorch will automatically detect CUDA version | |
| # and install the appropriate PyTorch wheel when CMAKE_ARGS="-DEXECUTORCH_BUILD_CUDA=ON" | |
| source .ci/scripts/test-cuda-build.sh "${{ matrix.cuda-version }}" | |
| # This job will fail if any of the CUDA versions fail | |
| check-all-cuda-builds: | |
| needs: test-cuda-builds | |
| runs-on: ubuntu-latest | |
| if: always() | |
| steps: | |
| - name: Check if all CUDA builds succeeded | |
| run: | | |
| if [[ "${{ needs.test-cuda-builds.result }}" != "success" ]]; then | |
| echo "ERROR: One or more ExecuTorch CUDA builds failed!" | |
| echo "CUDA build results: ${{ needs.test-cuda-builds.result }}" | |
| exit 1 | |
| else | |
| echo "SUCCESS: All ExecuTorch CUDA builds (12.6, 12.8, 12.9) completed successfully!" | |
| fi | |
| test-models-cuda: | |
| name: test-models-cuda | |
| uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main | |
| permissions: | |
| id-token: write | |
| contents: read | |
| strategy: | |
| fail-fast: false | |
| matrix: | |
| model: [linear, add, add_mul, resnet18] | |
| with: | |
| timeout: 90 | |
| runner: linux.g5.4xlarge.nvidia.gpu | |
| gpu-arch-type: cuda | |
| gpu-arch-version: 12.6 | |
| use-custom-docker-registry: false | |
| submodules: recursive | |
| ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
| script: | | |
| set -eux | |
| PYTHON_EXECUTABLE=python CMAKE_ARGS="-DEXECUTORCH_BUILD_CUDA=ON" ./install_executorch.sh | |
| export LD_LIBRARY_PATH=/opt/conda/lib:$LD_LIBRARY_PATH | |
| PYTHON_EXECUTABLE=python source .ci/scripts/test_model.sh "${{ matrix.model }}" cmake cuda | |
| test-voxtral-cuda-e2e: | |
| name: test-voxtral-cuda-e2e | |
| uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main | |
| permissions: | |
| id-token: write | |
| contents: read | |
| secrets: inherit | |
| strategy: | |
| fail-fast: false | |
| with: | |
| timeout: 90 | |
| secrets-env: EXECUTORCH_HF_TOKEN | |
| runner: linux.g5.4xlarge.nvidia.gpu | |
| gpu-arch-type: cuda | |
| gpu-arch-version: 12.6 | |
| use-custom-docker-registry: false | |
| submodules: recursive | |
| ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
| script: | | |
| set -eux | |
| echo "::group::Setup ExecuTorch" | |
| CMAKE_ARGS="-DEXECUTORCH_BUILD_CUDA=ON" ./install_executorch.sh | |
| echo "::endgroup::" | |
| echo "::group::Setup Huggingface" | |
| pip install -U "huggingface_hub[cli]" accelerate | |
| huggingface-cli login --token $SECRET_EXECUTORCH_HF_TOKEN | |
| OPTIMUM_ET_VERSION=$(cat .ci/docker/ci_commit_pins/optimum-executorch.txt) | |
| pip install git+https://github.com/huggingface/optimum-executorch.git@${OPTIMUM_ET_VERSION} | |
| pip install mistral-common librosa | |
| echo "::endgroup::" | |
| echo "::group::Export Voxtral" | |
| optimum-cli export executorch \ | |
| --model "mistralai/Voxtral-Mini-3B-2507" \ | |
| --task "multimodal-text-to-text" \ | |
| --recipe "cuda" \ | |
| --dtype bfloat16 \ | |
| --device cuda \ | |
| --max_seq_len 1024 \ | |
| --output_dir ./ | |
| echo "::endgroup::" | |
| echo "::group::Build Voxtral Runner" | |
| cmake -DCMAKE_BUILD_TYPE=Release \ | |
| -DEXECUTORCH_BUILD_CUDA=ON \ | |
| -DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON \ | |
| -DEXECUTORCH_BUILD_EXTENSION_MODULE=ON \ | |
| -DEXECUTORCH_BUILD_EXTENSION_NAMED_DATA_MAP=ON \ | |
| -DEXECUTORCH_BUILD_TESTS=ON \ | |
| -Bcmake-out . | |
| cmake --build cmake-out -j$(( $(nproc) - 1 )) --target voxtral_runner | |
| echo "::endgroup::" | |
| echo "::group::Run Voxtral Runner" | |
| # Capture output and allow exit code 139 if we have the expected printout | |
| set +e | |
| export LD_LIBRARY_PATH=/opt/conda/lib:$LD_LIBRARY_PATH | |
| OUTPUT=$(cmake-out/backends/cuda/voxtral_runner model.pte aoti_cuda_blob.ptd 2>&1) | |
| EXIT_CODE=$? | |
| set -e | |
| echo "$OUTPUT" | |
| # Check if the output contains "Run latency (ms):" | |
| if echo "$OUTPUT" | grep -q "Run latency (ms):"; then | |
| echo "Found expected output: 'Run latency (ms):'" | |
| if [ $EXIT_CODE -eq 139 ]; then | |
| echo "Exit code 139 (segfault) detected, but passing since we have the expected output" | |
| exit 0 | |
| elif [ $EXIT_CODE -ne 0 ]; then | |
| echo "Unexpected exit code: $EXIT_CODE" | |
| exit $EXIT_CODE | |
| else | |
| echo "Command succeeded with exit code 0" | |
| exit 0 | |
| fi | |
| else | |
| echo "Expected output 'Run latency (ms):' not found in output" | |
| exit 1 | |
| fi | |
| echo "::endgroup::" |