2024-12-22 nightly release (f02bd4f8bf7ee3bce9ca6200dd9998a8f5ac571a) #666
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| name: Build and test Linux CUDA wheels | |
| on: | |
| pull_request: | |
| push: | |
| branches: | |
| - nightly | |
| - main | |
| - release/* | |
| tags: | |
| - v[0-9]+.[0-9]+.[0-9]+-rc[0-9]+ | |
| workflow_dispatch: | |
| concurrency: | |
| group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref_name }}-${{ github.ref_type == 'branch' && github.sha }}-${{ github.event_name == 'workflow_dispatch' }} | |
| cancel-in-progress: true | |
| permissions: | |
| id-token: write | |
| contents: write | |
| defaults: | |
| run: | |
| shell: bash -l -eo pipefail {0} | |
| jobs: | |
| generate-matrix: | |
| uses: pytorch/test-infra/.github/workflows/generate_binary_build_matrix.yml@main | |
| with: | |
| package-type: wheel | |
| os: linux | |
| test-infra-repository: pytorch/test-infra | |
| test-infra-ref: main | |
| with-cpu: disable | |
| with-xpu: disable | |
| with-rocm: disable | |
| with-cuda: enable | |
| build-python-only: "disable" | |
| build: | |
| needs: generate-matrix | |
| strategy: | |
| fail-fast: false | |
| name: Build and Upload wheel | |
| uses: pytorch/test-infra/.github/workflows/build_wheels_linux.yml@main | |
| with: | |
| repository: pytorch/torchcodec | |
| ref: "" | |
| test-infra-repository: pytorch/test-infra | |
| test-infra-ref: main | |
| build-matrix: ${{ needs.generate-matrix.outputs.matrix }} | |
| post-script: packaging/post_build_script.sh | |
| smoke-test-script: packaging/fake_smoke_test.py | |
| package-name: torchcodec | |
| trigger-event: ${{ github.event_name }} | |
| build-platform: "python-build-package" | |
| build-command: "BUILD_AGAINST_ALL_FFMPEG_FROM_S3=1 ENABLE_CUDA=1 python -m build --wheel -vvv --no-isolation" | |
| install-and-test: | |
| runs-on: linux.4xlarge.nvidia.gpu | |
| strategy: | |
| fail-fast: false | |
| matrix: | |
| # 3.9 corresponds to the minimum python version for which we build | |
| # the wheel unless the label cliflow/binaries/all is present in the | |
| # PR. | |
| # For the actual release we should add that label and change this to | |
| # include more python versions. | |
| python-version: ['3.9'] | |
| cuda-version: ['11.8', '12.4', '12.6'] | |
| ffmpeg-version-for-tests: ['5', '6', '7'] | |
| container: | |
| image: "pytorch/manylinux2_28-builder:cuda${{ matrix.cuda-version }}" | |
| options: "--gpus all -e NVIDIA_DRIVER_CAPABILITIES=video,compute,utility" | |
| needs: build | |
| steps: | |
| - name: Setup env vars | |
| run: | | |
| cuda_version_without_periods=$(echo "${{ matrix.cuda-version }}" | sed 's/\.//g') | |
| echo cuda_version_without_periods=${cuda_version_without_periods} >> $GITHUB_ENV | |
| python_version_without_periods=$(echo "${{ matrix.python-version }}" | sed 's/\.//g') | |
| echo python_version_without_periods=${python_version_without_periods} >> $GITHUB_ENV | |
| - uses: actions/download-artifact@v3 | |
| with: | |
| name: pytorch_torchcodec__${{ matrix.python-version }}_cu${{ env.cuda_version_without_periods }}_x86_64 | |
| path: pytorch/torchcodec/dist/ | |
| - name: Setup miniconda using test-infra | |
| uses: pytorch/test-infra/.github/actions/setup-miniconda@main | |
| with: | |
| python-version: ${{ matrix.python-version }} | |
| # | |
| # For some reason nvidia::libnpp=12.4 doesn't install but nvidia/label/cuda-12.4.0::libnpp does. | |
| # So we use the latter convention for libnpp. | |
| # We install conda packages at the start because otherwise conda may have conflicts with dependencies. | |
| default-packages: "nvidia/label/cuda-${{ matrix.cuda-version }}.0::libnpp nvidia::cuda-nvrtc=${{ matrix.cuda-version }} nvidia::cuda-toolkit=${{ matrix.cuda-version }} nvidia::cuda-cudart=${{ matrix.cuda-version }} nvidia::cuda-driver-dev=${{ matrix.cuda-version }} conda-forge::ffmpeg=${{ matrix.ffmpeg-version-for-tests }}" | |
| - name: Check env | |
| run: | | |
| ${CONDA_RUN} env | |
| ${CONDA_RUN} conda info | |
| ${CONDA_RUN} nvidia-smi | |
| ${CONDA_RUN} conda list | |
| - name: Assert ffmpeg exists | |
| run: | | |
| ${CONDA_RUN} ffmpeg -buildconf | |
| - name: Update pip | |
| run: ${CONDA_RUN} python -m pip install --upgrade pip | |
| - name: Install PyTorch | |
| run: | | |
| ${CONDA_RUN} python -m pip install --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/cu${{ env.cuda_version_without_periods }} | |
| ${CONDA_RUN} python -c 'import torch; print(f"{torch.__version__}"); print(f"{torch.__file__}"); print(f"{torch.cuda.is_available()=}")' | |
| - name: Install torchcodec from the wheel | |
| run: | | |
| wheel_path=`find pytorch/torchcodec/dist -type f -name "*cu${{ env.cuda_version_without_periods }}-cp${{ env.python_version_without_periods }}*.whl"` | |
| echo Installing $wheel_path | |
| ${CONDA_RUN} python -m pip install $wheel_path -vvv | |
| - name: Check out repo | |
| uses: actions/checkout@v3 | |
| - name: Install test dependencies | |
| run: | | |
| # Ideally we would find a way to get those dependencies from pyproject.toml | |
| ${CONDA_RUN} python -m pip install numpy pytest pillow | |
| - name: Delete the src/ folder just for fun | |
| run: | | |
| # The only reason we checked-out the repo is to get access to the | |
| # tests. We don't care about the rest. Out of precaution, we delete | |
| # the src/ folder to be extra sure that we're running the code from | |
| # the installed wheel rather than from the source. | |
| # This is just to be extra cautious and very overkill because a) | |
| # there's no way the `torchcodec` package from src/ can be found from | |
| # the PythonPath: the main point of `src/` is precisely to protect | |
| # against that and b) if we ever were to execute code from | |
| # `src/torchcodec`, it would fail loudly because the built .so files | |
| # aren't present there. | |
| rm -r src/ | |
| ls | |
| - name: Smoke test | |
| run: | | |
| ${CONDA_RUN} python test/decoders/manual_smoke_test.py | |
| - name: Run Python tests | |
| run: | | |
| ${CONDA_RUN} FAIL_WITHOUT_CUDA=1 pytest test -vvv | |
| - name: Run Python benchmark | |
| run: | | |
| ${CONDA_RUN} time python benchmarks/decoders/gpu_benchmark.py --devices=cuda:0,cpu --resize_devices=none |