Build wheels and deploy #22
Workflow file for this run
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| # This workflow will: | |
| # - Create a new Github release | |
| # - Build wheels for supported architectures | |
| # - Deploy the wheels to the Github release | |
| # - Release the static code to PyPi | |
| # For more information see: https://help.github.com/en/actions/language-and-framework-guides/using-python-with-github-actions#publishing-to-package-registries | |
| name: Build wheels and deploy | |
| on: | |
| create: | |
| tags: | |
| - v* | |
| jobs: | |
| setup_release: | |
| name: Create Release | |
| runs-on: ubuntu-latest | |
| steps: | |
| - name: Get the tag version | |
| id: extract_branch | |
| run: echo ::set-output name=branch::${GITHUB_REF#refs/tags/} | |
| shell: bash | |
| - name: Create Release | |
| id: create_release | |
| uses: actions/create-release@v1 | |
| env: | |
| GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} | |
| with: | |
| tag_name: ${{ steps.extract_branch.outputs.branch }} | |
| release_name: ${{ steps.extract_branch.outputs.branch }} | |
| build_wheels: | |
| name: Build Wheel | |
| needs: setup_release | |
| runs-on: ${{ matrix.os }} | |
| strategy: | |
| fail-fast: false | |
| matrix: | |
| # Using ubuntu-20.04 instead of 22.04 for more compatibility (glibc). Ideally we'd use the | |
| # manylinux docker image, but I haven't figured out how to install CUDA on manylinux. | |
| os: [ubuntu-20.04] | |
| python-version: ['3.8', '3.9', '3.10', '3.11', '3.12'] | |
| torch-version: ['2.0.1', '2.1.2', '2.2.2', '2.3.1', '2.4.0.dev20240505'] | |
| cuda-version: ['11.8.0', '12.2.2'] | |
| # We need separate wheels that either uses C++11 ABI (-D_GLIBCXX_USE_CXX11_ABI) or not. | |
| # Pytorch wheels currently don't use it, but nvcr images have Pytorch compiled with C++11 ABI. | |
| # Without this we get import error (undefined symbol: _ZN3c105ErrorC2ENS_14SourceLocationESs) | |
| # when building without C++11 ABI and using it on nvcr images. | |
| cxx11_abi: ['FALSE', 'TRUE'] | |
| exclude: | |
| # Pytorch < 2.2 does not support Python 3.12 | |
| - torch-version: '2.0.1' | |
| python-version: '3.12' | |
| - torch-version: '2.1.2' | |
| python-version: '3.12' | |
| # Pytorch <= 2.0 only supports CUDA <= 11.8 | |
| - torch-version: '2.0.1' | |
| cuda-version: '12.2.2' | |
| steps: | |
| - name: Checkout | |
| uses: actions/checkout@v3 | |
| - name: Set up Python | |
| uses: actions/setup-python@v4 | |
| with: | |
| python-version: ${{ matrix.python-version }} | |
| - name: Set CUDA and PyTorch versions | |
| run: | | |
| echo "MATRIX_CUDA_VERSION=$(echo ${{ matrix.cuda-version }} | awk -F \. {'print $1 $2'})" >> $GITHUB_ENV | |
| echo "MATRIX_TORCH_VERSION=$(echo ${{ matrix.torch-version }} | awk -F \. {'print $1 "." $2'})" >> $GITHUB_ENV | |
| - name: Free up disk space | |
| if: ${{ runner.os == 'Linux' }} | |
| # https://github.com/easimon/maximize-build-space/blob/master/action.yml | |
| # https://github.com/easimon/maximize-build-space/tree/test-report | |
| run: | | |
| sudo rm -rf /usr/share/dotnet | |
| sudo rm -rf /opt/ghc | |
| sudo rm -rf /opt/hostedtoolcache/CodeQL | |
| - name: Set up swap space | |
| if: runner.os == 'Linux' | |
| uses: pierotofy/[email protected] | |
| with: | |
| swap-size-gb: 10 | |
| - name: Install CUDA ${{ matrix.cuda-version }} | |
| if: ${{ matrix.cuda-version != 'cpu' }} | |
| uses: Jimver/[email protected] | |
| id: cuda-toolkit | |
| with: | |
| cuda: ${{ matrix.cuda-version }} | |
| linux-local-args: '["--toolkit"]' | |
| # default method is "local", and we're hitting some error with caching for CUDA 11.8 and 12.1 | |
| # method: ${{ (matrix.cuda-version == '11.8.0' || matrix.cuda-version == '12.1.0') && 'network' || 'local' }} | |
| method: 'network' | |
| # We need the cuda libraries (e.g. cuSparse, cuSolver) for compiling PyTorch extensions, | |
| # not just nvcc | |
| # sub-packages: '["nvcc"]' | |
| - name: Install PyTorch ${{ matrix.torch-version }}+cu${{ matrix.cuda-version }} | |
| run: | | |
| pip install --upgrade pip | |
| # If we don't install before installing Pytorch, we get error for torch 2.0.1 | |
| # ERROR: Could not find a version that satisfies the requirement setuptools>=40.8.0 (from versions: none) | |
| pip install lit | |
| # For some reason torch 2.2.0 on python 3.12 errors saying no setuptools | |
| pip install setuptools | |
| # We want to figure out the CUDA version to download pytorch | |
| # e.g. we can have system CUDA version being 11.7 but if torch==1.12 then we need to download the wheel from cu116 | |
| # This code is ugly, maybe there's a better way to do this. | |
| export TORCH_CUDA_VERSION=$(python -c "from os import environ as env; \ | |
| minv = {'2.0': 117, '2.1': 118, '2.2': 118, '2.3': 118, '2.4': 118}[env['MATRIX_TORCH_VERSION']]; \ | |
| maxv = {'2.0': 118, '2.1': 121, '2.2': 121, '2.3': 121, '2.4': 121}[env['MATRIX_TORCH_VERSION']]; \ | |
| print(max(min(int(env['MATRIX_CUDA_VERSION']), maxv), minv))" \ | |
| ) | |
| if [[ ${{ matrix.torch-version }} == *"dev"* ]]; then | |
| pip install --no-cache-dir --pre torch==${{ matrix.torch-version }} --index-url https://download.pytorch.org/whl/nightly/cu${TORCH_CUDA_VERSION} | |
| else | |
| pip install --no-cache-dir torch==${{ matrix.torch-version }} --index-url https://download.pytorch.org/whl/cu${TORCH_CUDA_VERSION} | |
| fi | |
| nvcc --version | |
| python --version | |
| python -c "import torch; print('PyTorch:', torch.__version__)" | |
| python -c "import torch; print('CUDA:', torch.version.cuda)" | |
| python -c "from torch.utils import cpp_extension; print (cpp_extension.CUDA_HOME)" | |
| shell: | |
| bash | |
| - name: Build wheel | |
| run: | | |
| # We want setuptools >= 49.6.0 otherwise we can't compile the extension if system CUDA version is 11.7 and pytorch cuda version is 11.6 | |
| # https://github.com/pytorch/pytorch/blob/664058fa83f1d8eede5d66418abff6e20bd76ca8/torch/utils/cpp_extension.py#L810 | |
| # However this still fails so I'm using a newer version of setuptools | |
| pip install setuptools==68.0.0 | |
| pip install ninja packaging wheel | |
| export PATH=/usr/local/nvidia/bin:/usr/local/nvidia/lib64:$PATH | |
| export LD_LIBRARY_PATH=/usr/local/nvidia/lib64:/usr/local/cuda/lib64:$LD_LIBRARY_PATH | |
| # Limit MAX_JOBS otherwise the github runner goes OOM | |
| MAX_JOBS=2 MAMBA_FORCE_BUILD="TRUE" MAMBA_FORCE_CXX11_ABI=${{ matrix.cxx11_abi}} python setup.py bdist_wheel --dist-dir=dist | |
| tmpname=cu${MATRIX_CUDA_VERSION}torch${MATRIX_TORCH_VERSION}cxx11abi${{ matrix.cxx11_abi }} | |
| wheel_name=$(ls dist/*whl | xargs -n 1 basename | sed "s/-/+$tmpname-/2") | |
| ls dist/*whl |xargs -I {} mv {} dist/${wheel_name} | |
| echo "wheel_name=${wheel_name}" >> $GITHUB_ENV | |
| - name: Log Built Wheels | |
| run: | | |
| ls dist | |
| - name: Get the tag version | |
| id: extract_branch | |
| run: echo ::set-output name=branch::${GITHUB_REF#refs/tags/} | |
| - name: Get Release with tag | |
| id: get_current_release | |
| uses: joutvhu/get-release@v1 | |
| with: | |
| tag_name: ${{ steps.extract_branch.outputs.branch }} | |
| env: | |
| GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} | |
| - name: Upload Release Asset | |
| id: upload_release_asset | |
| uses: actions/upload-release-asset@v1 | |
| env: | |
| GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} | |
| with: | |
| upload_url: ${{ steps.get_current_release.outputs.upload_url }} | |
| asset_path: ./dist/${{env.wheel_name}} | |
| asset_name: ${{env.wheel_name}} | |
| asset_content_type: application/* | |
| publish_package: | |
| name: Publish package | |
| needs: [build_wheels] | |
| runs-on: ubuntu-latest | |
| steps: | |
| - uses: actions/checkout@v3 | |
| - uses: actions/setup-python@v4 | |
| with: | |
| python-version: '3.10' | |
| - name: Install dependencies | |
| run: | | |
| pip install ninja packaging setuptools wheel twine | |
| # We don't want to download anything CUDA-related here | |
| pip install torch --index-url https://download.pytorch.org/whl/cpu | |
| - name: Build core package | |
| env: | |
| MAMBA_SKIP_CUDA_BUILD: "TRUE" | |
| run: | | |
| python setup.py sdist --dist-dir=dist | |
| - name: Deploy | |
| env: | |
| TWINE_USERNAME: "__token__" | |
| TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }} | |
| run: | | |
| python -m twine upload dist/* |