linux_cuda_wheel.yaml

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:
    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 }}
      pre-script: packaging/linux_cuda_pre_build_script.sh
      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:
        python-version: ['3.9']
        cuda-version: ['12.4']
        ffmpeg-version-for-tests: ['5', '6', '7']
    container:
      image: "pytorch/manylinux-builder:cuda${{ matrix.cuda-version }}"
    if: ${{ always() }}
    needs: build
    steps:
      - name: Setup env vars
        run: |
          cuda_version_without_periods=$(echo "${{ matrix.cuda-version }}" | sed 's/\.//g')
          echo cuda_version_without_periods=${cuda_version_without_periods} >> $GITHUB_ENV
      - uses: actions/download-artifact@v3
        with:
          name: pytorch_torchcodec__${{ 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: "3.9"
      - name: Check env
        run: |
          ${CONDA_RUN} env
          ${CONDA_RUN} conda info
      - name: Update pip
        run: ${CONDA_RUN} python -m pip install --upgrade pip
      - name: Install PyTorch
        run: |
          ${CONDA_RUN} python -m pip install --pre torch --index-url https://download.pytorch.org/whl/nightly/cu${{ env.cuda_version_without_periods }}
      - name: Install torchcodec from the wheel
        run: |
          wheel_path=`find pytorch/torchcodec/dist -type f -name "*.whl"`
          echo Installing $wheel_path
          ${CONDA_RUN} python -m pip install $wheel_path -vvv

      - name: Check out repo
        uses: actions/checkout@v3
      - name: Install ffmpeg, post build
        run: |
          # Ideally we would have checked for that before installing the wheel,
          # but we need to checkout the repo to access this file, and we don't
          # want to checkout the repo before installing the wheel to avoid any
          # side-effect. It's OK.
          source packaging/helpers.sh
          assert_ffmpeg_not_installed

          ${CONDA_RUN} conda install --yes conda-forge::ffmpeg=${{ matrix.ffmpeg-version-for-tests }}

      - name: Install cuda runtime dependencies
        run: |
          ${CONDA_RUN} conda install --yes nvidia::libnpp nvidia::cuda-nvrtc=12.4 nvidia::cuda-toolkit=12.4 nvidia::cuda-cudart=12.4 nvidia::cuda-driver-dev=12.4
      - name: Install test dependencies
        run: |
          ${CONDA_RUN} python -m pip install --pre torchvision --index-url https://download.pytorch.org/whl/nightly/cpu
          # 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: |
          find $CONDA_PREFIX -name libtorchcodec\*.so | xargs ldd
          find $CONDA_PREFIX -name libcuda\*.so\*
          echo $CONDA_PREFIX
          python test/decoders/manual_smoke_test.py
      - name: Run Python tests
        run: |
          pytest test -vvv