FoodSeg103/Swin-Transformer-Semantic-Segmentation-main/.github/workflows/build.yml

name: build

on: [push, pull_request]

jobs:
  lint:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Set up Python 3.7
        uses: actions/setup-python@v1
        with:
          python-version: 3.7
      - name: Install pre-commit hook
        run: |
          pip install pre-commit
          pre-commit install
      - name: Linting
        run: pre-commit run --all-files
      - name: Check docstring
        run: |
          pip install interrogate
          interrogate -v --ignore-init-method --ignore-module --ignore-nested-functions --exclude mmseg/ops --ignore-regex "__repr__" --fail-under 80 mmseg

  build:
    env:
      CUDA: 10.1.105-1
      CUDA_SHORT: 10.1
      UBUNTU_VERSION: ubuntu1804
      FORCE_CUDA: 1
      MMCV_CUDA_ARGS: -gencode=arch=compute_61,code=sm_61
    runs-on: ubuntu-latest
    strategy:
      matrix:
        python-version: [3.6, 3.7]
        torch: [1.3.0+cpu, 1.5.0+cpu]
        include:
          - torch: 1.3.0+cpu
            torchvision: 0.4.1+cpu
          - torch: 1.5.0+cpu
            torchvision: 0.6.0+cpu
          - torch: 1.5.0+cpu
            torchvision: 0.6.0+cpu
            python-version: 3.8
          - torch: 1.5.0+cu101
            torchvision: 0.6.0+cu101
            python-version: 3.7
          - torch: 1.6.0+cu101
            torchvision: 0.7.0+cu101
            python-version: 3.7

    steps:
      - uses: actions/checkout@v2
      - name: Set up Python ${{ matrix.python-version }}
        uses: actions/setup-python@v2
        with:
          python-version: ${{ matrix.python-version }}
      - name: Install CUDA
        if: ${{matrix.torch == '1.5.0+cu101'}}
        run: |
          export INSTALLER=cuda-repo-${UBUNTU_VERSION}_${CUDA}_amd64.deb
          wget http://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/${INSTALLER}
          sudo dpkg -i ${INSTALLER}
          wget https://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/7fa2af80.pub
          sudo apt-key add 7fa2af80.pub
          sudo apt update -qq
          sudo apt install -y cuda-${CUDA_SHORT/./-} cuda-cufft-dev-${CUDA_SHORT/./-}
          sudo apt clean
          export CUDA_HOME=/usr/local/cuda-${CUDA_SHORT}
          export LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${CUDA_HOME}/include:${LD_LIBRARY_PATH}
          export PATH=${CUDA_HOME}/bin:${PATH}
          sudo apt-get install -y ninja-build
      - name: Install Pillow
        if: ${{matrix.torchvision == '0.4.1+cpu'}}
        run: pip install Pillow==6.2.2
      - name: Install PyTorch
        run: pip install torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
      - name: Install mmseg dependencies
        run: |
          pip install mmcv-full==latest+torch${{matrix.torch}} -f https://download.openmmlab.com/mmcv/dist/index.html --use-deprecated=legacy-resolver
          pip install -r requirements.txt
      - name: Build and install
        run: rm -rf .eggs && pip install -e .
      - name: Run unittests and generate coverage report
        run: |
          coverage run --branch --source mmseg -m pytest tests/
          coverage xml
          coverage report -m
      # Only upload coverage report for python3.7 && pytorch1.5
      - name: Upload coverage to Codecov
        if: ${{matrix.torch == '1.5.0+cu101' && matrix.python-version == '3.7'}}
        uses: codecov/codecov-action@v1.0.10
        with:
          file: ./coverage.xml
          flags: unittests
          env_vars: OS,PYTHON
          name: codecov-umbrella
          fail_ci_if_error: false