# Use the latest 2.1 version of CircleCI pipeline process engine. # See: https://circleci.com/docs/2.0/configuration-reference 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 # Define a job to be invoked later in a workflow. # See: https://circleci.com/docs/2.0/configuration-reference/#jobs jobs: lint: docker: - image: cimg/python:3.7.4 # Add steps to the job # See: https://circleci.com/docs/2.0/configuration-reference/#steps 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 - run: name: Check docstring coverage command: | pip install interrogate interrogate -v --ignore-init-method --ignore-module --ignore-nested-functions --ignore-magic --ignore-regex "__repr__" --fail-under 60 mmpretrain build_cpu_with_3rdparty: 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 libjpeg8-dev zlib1g-dev - run: name: Configure Python & pip command: | pip install --upgrade pip pip install wheel - run: name: Install PyTorch command: | python -V pip install torch==<< parameters.torch >>+cpu torchvision==<< parameters.torchvision >>+cpu -f https://download.pytorch.org/whl/torch_stable.html - run: name: Install mmpretrain dependencies command: | pip install git+https://github.com/open-mmlab/mmengine.git@main pip install -U openmim mim install 'mmcv >= 2.0.0rc1' pip install timm pip install transformers pip install -r requirements.txt python -c 'import mmcv; print(mmcv.__version__)' - run: name: Build and install command: | pip install -e . - run: name: Run unittests command: | coverage run --branch --source mmpretrain -m pytest tests/ coverage xml coverage report -m 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 libjpeg8-dev zlib1g-dev - run: name: Configure Python & pip command: | pip install --upgrade pip pip install wheel - run: name: Install PyTorch command: | python -V pip install torch==<< parameters.torch >>+cpu torchvision==<< parameters.torchvision >>+cpu -f https://download.pytorch.org/whl/torch_stable.html - run: name: Install mmpretrain dependencies command: | pip install git+https://github.com/open-mmlab/mmengine.git@main pip install -U openmim mim install 'mmcv >= 2.0.0rc1' pip install -r requirements.txt python -c 'import mmcv; print(mmcv.__version__)' - run: name: Build and install command: | pip install -e . - run: name: Run unittests command: | coverage run --branch --source mmpretrain -m pytest tests/ coverage xml coverage report -m build_cuda: machine: image: ubuntu-2004-cuda-11.4:202110-01 resource_class: gpu.nvidia.small parameters: torch: type: string cuda: type: enum enum: ["10.1", "10.2", "11.1"] cudnn: type: integer default: 7 steps: - checkout - run: # Cloning repos in VM since Docker doesn't have access to the private key name: Clone Repos command: | git clone -b main --depth 1 https://github.com/open-mmlab/mmengine.git /home/circleci/mmengine - run: name: Build Docker image command: | docker build .circleci/docker -t mmpretrain: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:/mmpretrain -v /home/circleci/mmengine:/mmengine -w /mmpretrain --name mmpretrain mmpretrain:gpu - run: name: Install mmpretrain dependencies command: | docker exec mmpretrain pip install -e /mmengine docker exec mmpretrain pip install -U openmim docker exec mmpretrain mim install 'mmcv >= 2.0.0rc1' docker exec mmpretrain pip install -r requirements.txt docker exec mmpretrain python -c 'import mmcv; print(mmcv.__version__)' - run: name: Build and install command: | docker exec mmpretrain pip install -e . - run: name: Run unittests command: | docker exec mmpretrain python -m pytest tests/ # Invoke jobs via workflows # See: https://circleci.com/docs/2.0/configuration-reference/#workflows workflows: pr_stage_lint: when: << pipeline.parameters.lint_only >> jobs: - lint: name: lint filters: branches: ignore: - dev-1.x - 1.x pr_stage_test: when: not: << pipeline.parameters.lint_only >> jobs: - lint: name: lint filters: branches: ignore: - dev-1.x - build_cpu: name: minimum_version_cpu torch: 1.6.0 torchvision: 0.7.0 python: 3.7.16 requires: - lint - build_cpu_with_3rdparty: name: maximum_version_cpu torch: 1.13.0 torchvision: 0.14.0 python: 3.10.0 requires: - minimum_version_cpu - hold: type: approval requires: - maximum_version_cpu - build_cuda: name: mainstream_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 merge_stage_test: when: not: << pipeline.parameters.lint_only >> jobs: - build_cuda: name: minimum_version_gpu torch: 1.6.0 # Use double quotation mark to explicitly specify its type # as string instead of number cuda: "10.1" filters: branches: only: - dev-1.x