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Add option for the user to pass in ffmpeg thread count #158

Add option for the user to pass in ffmpeg thread count

Add option for the user to pass in ffmpeg thread count #158

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: ahmadsharif1/test-infra/.github/actions/setup-miniconda@14bc3c29f88d13b0237ab4ddf00aa409e45ade40
with:
python-version: ${{ matrix.python-version }}
default-packages: "conda-forge::ffmpeg=${{ matrix.ffmpeg-version-for-tests }}"
- name: Check env
run: |
${CONDA_RUN} env
${CONDA_RUN} conda info
${CONDA_RUN} nvidia-smi
- 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 }}
${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 cuda runtime dependencies
run: |
# 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.
${CONDA_RUN} conda install --yes nvidia/label/cuda-${{ 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 }}
- 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: |
${CONDA_RUN} python test/decoders/manual_smoke_test.py
- name: Run Python tests
run: |
# We skip test_get_ffmpeg_version because it may not have a micro version.
${CONDA_RUN} FAIL_WITHOUT_CUDA=1 pytest test -k "not test_get_ffmpeg_version" -vvv
- name: Run Python benchmark
run: |
${CONDA_RUN} time python benchmarks/decoders/gpu_benchmark.py --devices=cuda:0,cpu --resize_devices=none