build-windows-wheels.yml

name: Build Cross-Platform Wheels

on:
  push:
    tags:
      - 'v*'
  workflow_dispatch:
    inputs:
      cuda_versions:
        description: 'CUDA versions to build for (comma-separated)'
        required: false
        default: '11.8,12.1'
      pytorch_version:
        description: 'PyTorch version to install (e.g., "2.1.0", "latest")'
        required: false
        default: 'latest'
      platforms:
        description: 'Platforms to build for (comma-separated: windows,linux)'
        required: false
        default: 'windows,linux'

jobs:
  build_wheels:
    name: Build wheels on ${{ matrix.platform.name }} for CUDA ${{ matrix.cuda_version }}
    runs-on: ${{ matrix.platform.os }}
    strategy:
      fail-fast: false
      matrix:
        platform:
          - name: linux
            os: ubuntu-22.04
          - name: windows
            os: windows-2022
        cuda_version: ['11.8', '12.1', '12.4', '12.6', '12.8']

    steps:
    - name: Checkout repository
      uses: actions/checkout@v4

    - name: Install CUDA Toolkit ${{ matrix.cuda_version }} (Windows)
      if: matrix.platform.os == 'windows-2022'
      uses: Jimver/cuda-toolkit@v0.2.23
      with:
        cuda: ${{ matrix.cuda_version }}.0
        method: 'network'
        sub-packages: '["nvcc", "cudart", "cublas", "curand", "cufft", "cusparse", "cusolver"]'

    - name: Setup Visual Studio environment (Windows)
      if: matrix.platform.os == 'windows-2022'
      uses: ilammy/msvc-dev-cmd@v1
      with:
        arch: x64

    - name: Build wheels
      uses: pypa/cibuildwheel@v3.0.0
      env:
        # Pass matrix and input variables to cibuildwheel's environment
        PYTORCH_VERSION: ${{ github.event.inputs.pytorch_version || 'latest' }}
        CUDA_VERSION: ${{ matrix.cuda_version }}
        
        # Configure cibuildwheel
        CIBW_BUILD_FRONTEND: "pip; args: --no-build-isolation"
        CIBW_BUILD: "cp38-* cp39-* cp310-* cp311-* cp312-*"
        CIBW_SKIP: ${{ matrix.cuda_version == '11.8' && 'cp312-*' || '' }}
        
        CIBW_BEFORE_BUILD_LINUX: |
          set -euxo pipefail
          dnf install -y gcc-c++ sparsehash-devel
          bash .github/tools/install_pytorch.sh
          
        CIBW_BEFORE_BUILD_WINDOWS: |
          powershell -Command "Invoke-WebRequest -Uri https://github.com/sparsehash/sparsehash/archive/refs/tags/sparsehash-2.0.4.zip -OutFile sparsehash.zip"
          powershell -Command "Expand-Archive -Path sparsehash.zip -DestinationPath C:\"
          powershell -Command "Rename-Item C:\sparsehash-sparsehash-2.0.4 C:\sparsehash"
          powershell -ExecutionPolicy Bypass -File .github/tools/install_pytorch.ps1
          
        CIBW_ENVIRONMENT_LINUX: >
          CXXFLAGS="-O2 -fopenmp"
          CFLAGS="-O2"
          FORCE_CUDA=1
          TORCH_CUDA_ARCH_LIST="7.5;8.0;8.6;8.9"
          MAX_JOBS=4
          
        CIBW_ENVIRONMENT_WINDOWS: >
          CL="/O1 /MP4"
          DISTUTILS_USE_SDK=1
          MSSdk=1
          FORCE_CUDA=1
          TORCH_CUDA_ARCH_LIST="7.5;8.0;8.6;8.9"
          INCLUDE="$INCLUDE;C:\sparsehash\src"
          
        CIBW_BEFORE_TEST_LINUX: |
          bash .github/tools/install_pytorch.sh
        CIBW_BEFORE_TEST_WINDOWS: |
          powershell -ExecutionPolicy Bypass -File .github/tools/install_pytorch.ps1
          
        CIBW_TEST_COMMAND_WINDOWS: "python -c \"import torch; import torchsparse; print(f'TorchSparse version: {torchsparse.__version__}')\""
        CIBW_TEST_COMMAND_LINUX: "python -c 'import torch; import torchsparse; print(f\"TorchSparse version: {torchsparse.__version__}\")'"
        
        CIBW_BUILD_VERBOSITY: 1

    - name: Upload wheel artifacts
      uses: actions/upload-artifact@v4
      with:
        name: wheels-${{ matrix.platform.name }}-cuda${{ matrix.cuda_version }}
        path: ./wheelhouse/*.whl

  create-release:
    needs: build_wheels
    runs-on: ubuntu-latest
    if: startsWith(github.ref, 'refs/tags/')
    steps:
      - name: Download all wheel artifacts
        uses: actions/download-artifact@v4
        with:
          path: wheels
          pattern: wheels-*
          merge-multiple: true

      - name: Organize wheels and create release
        run: |
          mkdir -p release
          find wheels -name "*.whl" -exec cp {} release/ \;
          ls -la release/
          gh release create ${{ github.ref_name }} --generate-notes --title "TorchSparse ${{ github.ref_name }} - Cross-Platform Release" release/*.whl
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

  test-wheels:
    needs: build_wheels
    strategy:
      fail-fast: false
      matrix:
        platform:
          - name: linux
            os: ubuntu-22.04
          - name: windows
            os: windows-2022
        python-version: ['3.10']
        cuda-version: ['12.1']

    runs-on: ${{ matrix.platform.os }}

    steps:
    - name: Set up Python ${{ matrix.python-version }}
      uses: actions/setup-python@v5
      with:
        python-version: ${{ matrix.python-version }}
        
    - name: Set up python-version-nodot
      id: py-ver
      run: echo "nodot=$(echo ${{ matrix.python-version }} | tr -d .)" >> $GITHUB_ENV

    - name: Install CUDA Toolkit (if needed for testing runtime)
      if: matrix.platform.os == 'windows-2022'
      uses: Jimver/cuda-toolkit@v0.2.23
      with:
        cuda: ${{ matrix.cuda_version }}.0
        method: 'network'

    - name: Download wheel artifacts
      uses: actions/download-artifact@v4
      with:
        name: wheels-${{ matrix.platform.name }}-cuda${{ matrix.cuda_version }}
        path: wheels

    - name: Install PyTorch (for testing)
      run: pip install torch==2.1.0+cu121 torchvision==0.16.0+cu121 --index-url https://download.pytorch.org/whl/cu121

    - name: Test wheel installation and functionality
      shell: bash
      run: |
        wheel_file=$(find wheels -name "*cp${{ env.nodot }}*.whl" | head -1)
        pip install "$wheel_file"
        python -c "import torch; import torchsparse; print('TorchSparse version:', torchsparse.__version__); print('PyTorch version:', torch.__version__); print('CUDA available:', torch.cuda.is_available())"