FoodSeg103/demo/mmcv/.circleci/test.yml

version: 2.1

# the default pipeline parameters, which will be updated according to
# the results of the path-filtering orb
parameters:
  lint_only:
    type: boolean
    default: true

jobs:
  lint:
    docker:
      - image: cimg/python:3.7.4
    steps:
      - checkout
      - run:
          name: Install pre-commit hook
          command: |
            pip install pre-commit
            pre-commit install
      - run:
          name: Linting
          command: pre-commit run --all-files
  build_without_torch:
    parameters:
      # The python version must match available image tags in
      # https://circleci.com/developer/images/image/cimg/python
      python:
        type: string
        default: "3.7.4"
    docker:
      - image: cimg/python:<< parameters.python >>
    resource_class: large
    steps:
      - checkout
      - run:
          name: Install Libraries
          command: |
            sudo apt-get update
            sudo apt-get install -y ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 libgl1-mesa-glx libjpeg-dev zlib1g-dev libtinfo-dev libncurses5 ffmpeg libturbojpeg
      - run:
          name: Upgrade pip
          command: |
            pip install pip --upgrade
            pip --version
      - run:
          name: Install MMEngine from main branch
          command: pip install git+https://github.com/open-mmlab/mmengine.git@main
      - run:
          name: Build MMCV from source
          command: pip install -e . -v
          environment:
            MMCV_WITH_OPS: 0
      - run:
          name: Install unit tests dependencies
          command: pip install -r requirements/test.txt
      - run:
          name: Run unit tests
          command: pytest tests/test_image tests/test_transforms tests/test_video tests/test_arraymisc.py tests/test_visualization.py tests/test_utils/test_env.py --ignore=tests/test_image/test_io.py
  build_without_ops:
    parameters:
      # The python version must match available image tags in
      # https://circleci.com/developer/images/image/cimg/python
      python:
        type: string
        default: "3.7.4"
      torch:
        type: string
      torchvision:
        type: string
    docker:
      - image: cimg/python:<< parameters.python >>
    resource_class: large
    steps:
      - checkout
      - run:
          name: Install Libraries
          command: |
            sudo apt-get update
            sudo apt-get install -y ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 libgl1-mesa-glx libjpeg-dev zlib1g-dev libtinfo-dev libncurses5 ffmpeg libturbojpeg
      - run:
          name: Configure Python & pip
          command: |
            pip install --upgrade pip
            pip install wheel
      - run:
          name: Install PyTorch
          command: pip install torch==<< parameters.torch >>+cpu torchvision==<< parameters.torchvision >>+cpu -f https://download.pytorch.org/whl/torch_stable.html
      - run:
          name: Install MMEngine from main branch
          command: pip install git+https://github.com/open-mmlab/mmengine.git@main
      - run:
          name: Create sdist and untar
          command: |
            sed -i "s/os.getenv('MMCV_WITH_OPS', '1')/os.getenv('MMCV_WITH_OPS', '0')/g" setup.py
            python setup.py sdist
            tar zxvf dist/mmcv* -C /tmp
            rm -r mmcv
      - run:
          name: Build and install from sdist
          command: |
            pushd /tmp/mmcv*
            pip install -e . -v
            popd
      - run:
          name: Install unit tests dependencies
          command: pip install -r requirements/test.txt
      - run:
          name: Run unit tests
          command: pytest tests --ignore=tests/test_ops
  build_cpu:
    parameters:
      # The python version must match available image tags in
      # https://circleci.com/developer/images/image/cimg/python
      python:
        type: string
      torch:
        type: string
      torchvision:
        type: string
    docker:
      - image: cimg/python:<< parameters.python >>
    resource_class: large
    steps:
      - checkout
      - run:
          name: Install Libraries
          command: |
            sudo apt-get update
            sudo apt-get install -y ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 libgl1-mesa-glx libjpeg-dev zlib1g-dev libtinfo-dev libncurses5 ffmpeg libturbojpeg
      - run:
          name: Configure Python & pip
          command: |
            pip install --upgrade pip
            pip install wheel
      - run:
          name: Install PyTorch
          command: pip install torch==<< parameters.torch >>+cpu torchvision==<< parameters.torchvision >>+cpu -f https://download.pytorch.org/whl/torch_stable.html
      - run:
          name: Install MMEngine from main branch
          command: pip install git+https://github.com/open-mmlab/mmengine.git@main
      - run:
          name: Install ninja to speed the compilation
          command: pip install ninja
      - run:
          name: Create sdist and untar
          command: |
            python setup.py sdist
            tar zxvf dist/mmcv* -C /tmp
            rm -r mmcv
      - run:
          name: Build and install from sdist
          command: |
            pushd /tmp/mmcv*
            pip install -e . -v
            popd
      - run:
          name: Install unit tests dependencies
          command: pip install -r requirements/test.txt
      - run:
          name: Run unit tests
          command: |
            coverage run --branch --source mmcv -m pytest tests/
            coverage xml
            coverage report -m
  build_cuda:
    parameters:
      torch:
        type: string
      cuda:
        type: enum
        enum: ["10.1", "10.2", "11.1", "11.7"]
      cudnn:
        type: integer
        default: 7
    machine:
      image: ubuntu-2004-cuda-11.4:202110-01
      docker_layer_caching: true
    resource_class: gpu.nvidia.small
    steps:
      - checkout
      - run:
          name: Build Docker image
          command: |
            docker build .circleci/docker -t mmcv:gpu --build-arg PYTORCH=<< parameters.torch >> --build-arg CUDA=<< parameters.cuda >> --build-arg CUDNN=<< parameters.cudnn >>
            docker run --gpus all -t -d -v /home/circleci/project:/mmcv -w /mmcv --name mmcv mmcv:gpu
      - run:
          name: Install MMEngine from main branch
          command: docker exec mmcv pip install git+https://github.com/open-mmlab/mmengine.git@main
      - run:
          name: Install ninja to speed the compilation
          command: docker exec mmcv pip install ninja
      - run:
          name: Build MMCV from source
          command: docker exec mmcv pip install -e . -v
      - run:
          name: Install unit tests dependencies
          command: docker exec mmcv pip install -r requirements/test.txt
      - run:
          name: Run unit tests
          command: docker exec mmcv python -m pytest tests/

workflows:
  pr_stage_lint:
    when: << pipeline.parameters.lint_only >>
    jobs:
      - lint:
          name: lint
          filters:
            branches:
              ignore:
                - main
  pr_stage_test:
    when:
      not:
        << pipeline.parameters.lint_only >>
    jobs:
      - lint:
          name: lint
          filters:
            branches:
              ignore:
                - main
      - build_without_torch:
          name: build_without_torch
          requires:
            - lint
      - build_without_ops:
          name: build_without_ops
          torch: 1.8.1
          torchvision: 0.9.1
          requires:
            - build_without_torch
      - build_cpu:
          name: minimum_version_cpu
          torch: 1.8.1
          torchvision: 0.9.1
          python: 3.7.4
          requires:
            - build_without_ops
      - build_cpu:
          name: maximum_version_cpu
          torch: 2.0.0
          torchvision: 0.15.1
          python: 3.9.0
          requires:
            - minimum_version_cpu
      - hold_cuda_test:
          type: approval
      - build_cuda:
          name: minimum_version_gpu
          torch: 1.8.1
          # Use double quotation mark to explicitly specify its type
          # as string instead of number
          cuda: "10.2"
          requires:
            - hold_cuda_test
      - build_cuda:
          name: maximum_version_gpu
          torch: 2.0.0
          # Use double quotation mark to explicitly specify its type
          # as string instead of number
          cuda: "11.7"
          cudnn: 8
          requires:
            - hold_cuda_test
  merge_stage_test:
    when:
      not:
        << pipeline.parameters.lint_only >>
    jobs:
      - build_cuda:
          name: minimum_version_gpu
          torch: 1.8.1
          # Use double quotation mark to explicitly specify its type
          # as string instead of number
          cuda: "10.2"
          filters:
            branches:
              only:
                - main
      - build_cuda:
          name: maximum_version_gpu
          torch: 2.0.0
          # Use double quotation mark to explicitly specify its type
          # as string instead of number
          cuda: "11.7"
          cudnn: 8
          filters:
            branches:
              only:
                - main