[Cherry-pick for 0.0.4] Let wheel names get the proper platform suffix (#366) #483
Workflow file for this run
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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: ${{ github.event_name }} | |
build-platform: "python-build-package" | |
build-command: "BUILD_AGAINST_ALL_FFMPEG_FROM_S3=1 ENABLE_CUDA=1 python -m build --wheel -vvv --no-isolation" | |
install-and-test: | |
runs-on: linux.4xlarge.nvidia.gpu | |
strategy: | |
fail-fast: false | |
matrix: | |
# 3.9 corresponds to the minimum python version for which we build | |
# the wheel unless the label cliflow/binaries/all is present in the | |
# PR. | |
# For the actual release we should add that label and change this to | |
# include more python versions. | |
python-version: ['3.9'] | |
cuda-version: ['11.8', '12.1', '12.4'] | |
ffmpeg-version-for-tests: ['5', '6', '7'] | |
container: | |
image: "pytorch/manylinux-builder:cuda${{ 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} >> $GITHUB_ENV | |
- uses: actions/download-artifact@v3 | |
with: | |
name: pytorch_torchcodec__3.9_cu${{ 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 "*.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 |