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[Compat] Compatible with PaddlePaddle
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‎.editorconfig‎

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# EditorConfig
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# https://editorconfig.org/
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root = true
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[*]
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indent_style = space
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indent_size = 2
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end_of_line = lf
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charset = utf-8
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trim_trailing_whitespace = true
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insert_final_newline = true
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[*.{py,sh,ipynb}]
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indent_size = 4
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[*{.md,rst}]
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indent_size = 3

‎.github/workflows/paddle_wheel.yaml‎

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name: Build Wheels for Paddle
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on:
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push:
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branches: [paddle]
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tags: ["v*"]
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pull_request:
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merge_group:
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workflow_dispatch:
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concurrency:
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group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref_name }}-${{ github.ref_type == 'branch' && github.sha }}-${{ github.event_name == 'workflow_dispatch' }}
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cancel-in-progress: true
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permissions:
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id-token: write
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contents: write
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defaults:
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run:
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shell: bash -l -eo pipefail {0}
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jobs:
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build-paddlecodec-wheel:
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runs-on: ubuntu-latest
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container:
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image: pytorch/manylinux2_28-builder:cpu
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strategy:
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fail-fast: false
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matrix:
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python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
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permissions:
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id-token: write
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contents: read
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steps:
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- name: Checkout repository
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uses: actions/checkout@v6
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- name: Setup conda environment
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uses: conda-incubator/setup-miniconda@v3
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with:
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auto-update-conda: true
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miniforge-version: latest
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activate-environment: build
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python-version: ${{ matrix.python-version }}
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- name: Install build dependencies
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run: |
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python -m pip install --upgrade pip
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pip install build wheel setuptools
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- name: Install PaddlePaddle nightly
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run: |
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pip install --pre paddlepaddle -i https://www.paddlepaddle.org.cn/packages/nightly/cpu/
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- name: Run pre-build script
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run: |
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bash packaging/pre_build_script.sh
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- name: Build wheel
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run: |
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# Use pre-built FFmpeg from PyTorch S3
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export BUILD_AGAINST_ALL_FFMPEG_FROM_S3=1
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export TORCHCODEC_CMAKE_BUILD_DIR=$(pwd)/build_cmake
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python -m build --wheel -vvv --no-isolation
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- name: Repair wheel
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run: |
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pip install auditwheel
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# 1. Extract internal libraries from the wheel to a temporary directory
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# This allows auditwheel to find them when checking dependencies
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mkdir -p temp_libs
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unzip -j dist/*.whl "torchcodec/*.so" -d temp_libs || true
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# 2. Prepare LD_LIBRARY_PATH
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# FFmpeg libraries
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FFMPEG_LIB_PATHS=$(find $(pwd)/build_cmake/_deps -type d -name "lib" | tr '\n' ':')
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# PaddlePaddle libraries
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PADDLE_PATH=$(python -c "import paddle; print(paddle.__path__[0])")
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PADDLE_LIB_PATHS="$PADDLE_PATH/base:$PADDLE_PATH/libs"
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# Wheel internal libraries
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INTERNAL_LIB_PATH=$(pwd)/temp_libs
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export LD_LIBRARY_PATH=${FFMPEG_LIB_PATHS}${PADDLE_LIB_PATHS}:${INTERNAL_LIB_PATH}:${LD_LIBRARY_PATH}
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# 3. Repair wheel with auditwheel
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# We exclude all external libraries because we want to rely on system libraries (like FFmpeg)
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# or libraries provided by other packages (like PaddlePaddle).
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# auditwheel 6.1.0+ supports wildcards in --exclude.
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auditwheel repair dist/*.whl --plat manylinux_2_28_x86_64 -w wheelhouse/ --exclude "*"
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# Cleanup
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rm -rf temp_libs
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rm dist/*.whl
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mv wheelhouse/*.whl dist/
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rmdir wheelhouse
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- name: Upload wheel artifact
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uses: actions/upload-artifact@v5
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with:
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name: paddlecodec-wheel-linux-py${{ matrix.python-version }}
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path: dist/*.whl
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- name: Run post-build script
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run: |
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bash packaging/post_build_script.sh
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- name: List wheel contents
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run: |
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wheel_path=$(find dist -type f -name "*.whl")
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echo "Wheel path: $wheel_path"
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unzip -l $wheel_path
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test-paddlecodec-wheel:
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needs: build-paddlecodec-wheel
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runs-on: ubuntu-latest
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strategy:
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fail-fast: false
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matrix:
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python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
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# FFmpeg 8.0 depends on libopenvino.so.2520, PaddlePaddle CPU depends on libopenvino.so.2500
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# There has some conflict causing test failures, but it works with PaddlePaddle GPU.
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# We skip FFmpeg 8.0 tests for PaddlePaddle CPU builds for now.
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ffmpeg-version: ["4.4.2", "5.1.2", "6.1.1", "7.0.1"]
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steps:
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- name: Checkout repository
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uses: actions/checkout@v6
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v5
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with:
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python-version: ${{ matrix.python-version }}
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- name: Download wheel artifact
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uses: actions/download-artifact@v4
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with:
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name: paddlecodec-wheel-linux-py${{ matrix.python-version }}
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path: dist/
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- name: Install FFmpeg via conda
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uses: conda-incubator/setup-miniconda@v3
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with:
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auto-update-conda: true
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miniforge-version: latest
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activate-environment: test
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python-version: ${{ matrix.python-version }}
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- name: Install FFmpeg from conda-forge
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run: |
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conda install "ffmpeg=${{ matrix.ffmpeg-version }}" -c conda-forge -y
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ffmpeg -version
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- name: Install PaddlePaddle nightly in conda env
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run: |
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pip install --pre paddlepaddle -i https://www.paddlepaddle.org.cn/packages/nightly/cpu/
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- name: Install paddlecodec from wheel
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run: |
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wheel_path=$(find dist -type f -name "*.whl")
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echo "Installing $wheel_path"
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pip install $wheel_path -vvv
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- name: Install test dependencies
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run: |
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pip install numpy pytest pillow
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- name: Delete src folder
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run: |
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# Delete src/ to ensure we're testing the installed wheel, not source code
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rm -rf src/
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ls -la
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- name: Run tests
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run: |
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pytest --override-ini="addopts=-v" -s test_paddle
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publish-pypi:
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runs-on: ubuntu-latest
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name: Publish to PyPI
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if: "startsWith(github.ref, 'refs/tags/')"
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needs:
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- test-paddlecodec-wheel
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permissions:
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id-token: write
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steps:
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- name: Retrieve release distributions
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uses: actions/download-artifact@v6
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with:
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pattern: paddlecodec-wheel-linux-*
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path: dist/
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merge-multiple: true
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- name: Publish release distributions to PyPI
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uses: pypa/gh-action-pypi-publish@release/v1
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publish-release:
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runs-on: ubuntu-latest
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name: Publish to GitHub
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if: "startsWith(github.ref, 'refs/tags/')"
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needs:
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- test-paddlecodec-wheel
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permissions:
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contents: write
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steps:
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- uses: actions/download-artifact@v6
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with:
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pattern: paddlecodec-wheel-linux-*
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path: dist/
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merge-multiple: true
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- name: Get tag name
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run: echo "RELEASE_VERSION=${GITHUB_REF#refs/*/}" >> $GITHUB_ENV
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- name: Publish to GitHub
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uses: softprops/action-gh-release@v2
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with:
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draft: true
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files: dist/*
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tag_name: ${{ env.RELEASE_VERSION }}

‎README.md‎

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[**Installation**](#installing-torchcodec) | [**Simple Example**](#using-torchcodec) | [**Detailed Example**](https://pytorch.org/torchcodec/stable/generated_examples/) | [**Documentation**](https://pytorch.org/torchcodec) | [**Contributing**](CONTRIBUTING.md) | [**License**](#license)
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# TorchCodec
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# PaddleCodec
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> [!NOTE]
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>
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> This repo is a fork of the original torchcodec project, with modifications to enhance compatibility and integration with PaddlePaddle.
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>
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> **Installation**
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>
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> ```bash
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> pip install paddlecodec
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> ```
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>
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> **Usage**
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>
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> ```python
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> import paddle
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> paddle.enable_compat(scope={"torchcodec"}) # Enable torch proxy before importing torchcodec
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> import torchcodec
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> # use torchcodec
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> ```
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The original README.md content is as follows:
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---
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TorchCodec is a Python library for decoding video and audio data into PyTorch
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tensors, on CPU and CUDA GPU. It also supports audio encoding, and video
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encoding will come soon! It aims to be fast, easy to use, and well integrated
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into the PyTorch ecosystem. If you want to use PyTorch to train ML models on
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encoding will come soon! It aims to be fast, easy to use, and well integrated
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into the PyTorch ecosystem. If you want to use PyTorch to train ML models on
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videos and audio, TorchCodec is how you turn these into data.
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We achieve these capabilities through:
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* Pythonic APIs that mirror Python and PyTorch conventions.
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* Relying on [FFmpeg](https://www.ffmpeg.org/) to do the decoding and encoding.
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TorchCodec uses the version of FFmpeg you already have installed. FFmpeg is a
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mature library with broad coverage available on most systems. It is, however,
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not easy to use. TorchCodec abstracts FFmpeg's complexity to ensure it is used
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correctly and efficiently.
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* Returning data as PyTorch tensors, ready to be fed into PyTorch transforms
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or used directly to train models.
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- Pythonic APIs that mirror Python and PyTorch conventions.
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- Relying on [FFmpeg](https://www.ffmpeg.org/) to do the decoding and encoding.
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TorchCodec uses the version of FFmpeg you already have installed. FFmpeg is a
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mature library with broad coverage available on most systems. It is, however,
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not easy to use. TorchCodec abstracts FFmpeg's complexity to ensure it is used
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correctly and efficiently.
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- Returning data as PyTorch tensors, ready to be fed into PyTorch transforms
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or used directly to train models.
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## Using TorchCodec
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```
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## Installing TorchCodec
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### Installing CPU-only TorchCodec
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1. Install the latest stable version of PyTorch following the
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The following table indicates the compatibility between versions of
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`torchcodec`, `torch` and Python.
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| `torchcodec` | `torch` | Python |
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| ------------------ | ------------------ | ------------------- |
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| `main` / `nightly` | `main` / `nightly` | `>=3.10`, `<=3.13` |
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| `0.8` | `2.9` | `>=3.10`, `<=3.13` |
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| `0.7` | `2.8` | `>=3.9`, `<=3.13` |
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| `0.6` | `2.8` | `>=3.9`, `<=3.13` |
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| `0.5` | `2.7` | `>=3.9`, `<=3.13` |
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| `0.4` | `2.7` | `>=3.9`, `<=3.13` |
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| `0.3` | `2.7` | `>=3.9`, `<=3.13` |
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| `0.2` | `2.6` | `>=3.9`, `<=3.13` |
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| `0.1` | `2.5` | `>=3.9`, `<=3.12` |
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| `0.0.3` | `2.4` | `>=3.8`, `<=3.12` |
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| `torchcodec` | `torch` | Python |
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| ------------------ | ------------------ | ------------------ |
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| `main` / `nightly` | `main` / `nightly` | `>=3.10`, `<=3.13` |
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| `0.8` | `2.9` | `>=3.10`, `<=3.13` |
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| `0.7` | `2.8` | `>=3.9`, `<=3.13` |
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| `0.6` | `2.8` | `>=3.9`, `<=3.13` |
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| `0.5` | `2.7` | `>=3.9`, `<=3.13` |
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| `0.4` | `2.7` | `>=3.9`, `<=3.13` |
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| `0.3` | `2.7` | `>=3.9`, `<=3.13` |
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| `0.2` | `2.6` | `>=3.9`, `<=3.13` |
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| `0.1` | `2.5` | `>=3.9`, `<=3.12` |
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| `0.0.3` | `2.4` | `>=3.8`, `<=3.12` |
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### Installing CUDA-enabled TorchCodec
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need the `libnpp` and `libnvrtc` CUDA libraries, which are usually part of
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the CUDA Toolkit.
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3. Install TorchCodec
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Pass in an `--index-url` parameter that corresponds to your CUDA Toolkit

‎examples/decoding/sampling.py‎

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# plotting utility. You can ignore that part and jump right below to
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# :ref:`sampling_tuto_start`.
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import paddle
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paddle.enable_compat(scope={"torchcodec"})
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from typing import Optional
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import torch
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import requests

‎pyproject.toml‎

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[project]
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name = "torchcodec"
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name = "paddlecodec"
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description = "A video decoder for PyTorch"
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readme = "README.md"
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requires-python = ">=3.8"
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license-files = ["LICENSE"]
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authors = [
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{ name = "PyTorch Team", email = "packages@pytorch.org" },
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{ name = "PaddlePaddle Team", email = "Paddle-better@baidu.com" },
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]
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dynamic = ["version"]
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‎setup.py‎

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import sys
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from pathlib import Path
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import torch
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import paddle
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from setuptools import Extension, setup
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from setuptools.command.build_ext import build_ext
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def _build_all_extensions_with_cmake(self):
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# Note that self.debug is True when you invoke setup.py like this:
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# python setup.py build_ext --debug install
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torch_dir = Path(torch.utils.cmake_prefix_path) / "Torch"
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# torch_dir = Path(torch.utils.cmake_prefix_path) / "Torch"
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cmake_build_type = os.environ.get("CMAKE_BUILD_TYPE", "Release")
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enable_cuda = os.environ.get("ENABLE_CUDA", "")
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torchcodec_disable_compile_warning_as_error = os.environ.get(
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python_version = sys.version_info
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cmake_args = [
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f"-DCMAKE_INSTALL_PREFIX={self._install_prefix}",
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f"-DTorch_DIR={torch_dir}",
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# f"-DTorch_DIR={torch_dir}",
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f"-DPADDLE_PATH={paddle.__path__[0]}",
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"-DCMAKE_VERBOSE_MAKEFILE=ON",
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f"-DCMAKE_BUILD_TYPE={cmake_build_type}",
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f"-DPYTHON_VERSION={python_version.major}.{python_version.minor}",

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