mmpretrain/.circleci/test.yml

249 lines
7.6 KiB
YAML

# 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 >= 2.0.0rc4'
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 >= 2.0.0rc4'
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: ["11.1", "11.7"]
cudnn:
type: integer
default: 8
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 >= 2.0.0rc4'
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
- main
pr_stage_test:
when:
not:
<< pipeline.parameters.lint_only >>
jobs:
- lint:
name: lint
filters:
branches:
ignore:
- dev
- build_cpu:
name: minimum_version_cpu
torch: 1.8.0
torchvision: 0.9.0
python: 3.7.16
requires:
- lint
- build_cpu_with_3rdparty:
name: maximum_version_cpu
torch: 2.0.0
torchvision: 0.15.1
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: "11.1"
requires:
- hold
- build_cuda:
name: maximum_version_gpu
torch: 2.0.0
cuda: "11.7"
cudnn: 8
requires:
- hold
merge_stage_test:
when:
not:
<< pipeline.parameters.lint_only >>
jobs:
- build_cuda:
name: minimum_version_gpu
torch: 1.8.0
# Use double quotation mark to explicitly specify its type
# as string instead of number
cuda: "11.1"
filters:
branches:
only:
- pretrain