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set circle ci (#1804)

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Miao Zheng 2022-07-21 22:20:09 +08:00 committed by GitHub
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.circleci/config.yml
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version: 2.1
jobs:
lint:
docker:
- image: cimg/python:3.7.4
steps:
- checkout
- run:
name: Install dependencies
command: |
sudo apt-add-repository ppa:brightbox/ruby-ng -y
sudo apt-get update
sudo apt-get install -y ruby2.7
- 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-regex "__repr__" --fail-under 50 mmseg
# this allows you to use CircleCI's dynamic configuration feature
setup: true
build_cpu:
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
- run:
name: Configure Python & pip
command: |
python -m pip install --upgrade pip
python -m pip install wheel
- run:
name: Install PyTorch
command: |
python -V
python -m pip install torch==<< parameters.torch >>+cpu torchvision==<< parameters.torchvision >>+cpu -f https://download.pytorch.org/whl/torch_stable.html
- run:
name: Install mmseg dependencies
command: |
python -m pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cpu/torch<< parameters.torch >>/index.html
python -m pip install mmdet
python -m pip install -r requirements.txt
- run:
name: Build and install
command: |
python -m pip install -e .
- run:
name: Run unittests
command: |
python -m pip install timm
python -m coverage run --branch --source mmseg -m pytest tests/
python -m coverage xml
python -m coverage report -m
build_cu101:
machine:
image: ubuntu-1604-cuda-10.1:201909-23
resource_class: gpu.nvidia.small
steps:
- checkout
- run:
name: Install Libraries
command: |
sudo apt-get update
sudo apt-get install -y git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 libgl1-mesa-glx
- run:
name: Configure Python & pip
command: |
pyenv global 3.7.0
python -m pip install --upgrade pip
python -m pip install wheel
- run:
name: Install PyTorch
command: |
python -V
python -m pip install torch==1.6.0+cu101 torchvision==0.7.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html
- run:
name: Install mmseg dependencies
# python -m pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu101/torch${{matrix.torch_version}}/index.html
command: |
python -m pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.6.0/index.html
python -m pip install mmdet
python -m pip install -r requirements.txt
- run:
name: Build and install
command: |
python setup.py check -m -s
TORCH_CUDA_ARCH_LIST=7.0 python -m pip install -e .
- run:
name: Run unittests
command: |
python -m pip install timm
python -m pytest tests/
# the path-filtering orb is required to continue a pipeline based on
# the path of an updated fileset
orbs:
path-filtering: circleci/path-filtering@0.1.2
workflows:
unit_tests:
# the always-run workflow is always triggered, regardless of the pipeline parameters.
always-run:
jobs:
- lint
- build_cpu:
name: build_cpu_th1.6
torch: 1.6.0
torchvision: 0.7.0
requires:
- lint
- build_cpu:
name: build_cpu_th1.7
torch: 1.7.0
torchvision: 0.8.1
requires:
- lint
- build_cpu:
name: build_cpu_th1.8_py3.9
torch: 1.8.0
torchvision: 0.9.0
python: "3.9.0"
requires:
- lint
- build_cpu:
name: build_cpu_th1.9_py3.8
torch: 1.9.0
torchvision: 0.10.0
python: "3.8.0"
requires:
- lint
- build_cpu:
name: build_cpu_th1.9_py3.9
torch: 1.9.0
torchvision: 0.10.0
python: "3.9.0"
requires:
- lint
- build_cu101:
requires:
- build_cpu_th1.6
- build_cpu_th1.7
- build_cpu_th1.8_py3.9
- build_cpu_th1.9_py3.8
- build_cpu_th1.9_py3.9
# the path-filtering/filter job determines which pipeline
# parameters to update.
- path-filtering/filter:
name: check-updated-files
# 3-column, whitespace-delimited mapping. One mapping per
# line:
# <regex path-to-test> <parameter-to-set> <value-of-pipeline-parameter>
mapping: |
mmseg/.* lint_only false
requirements/.* lint_only false
tests/.* lint_only false
tools/.* lint_only false
configs/.* lint_only false
.circleci/.* lint_only false
base-revision: dev-1.x
# this is the path of the configuration we should trigger once
# path filtering and pipeline parameter value updates are
# complete. In this case, we are using the parent dynamic
# configuration itself.
config-path: .circleci/test.yml

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ARG PYTORCH="1.8.1"
ARG CUDA="10.2"
ARG CUDNN="7"
FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel
# To fix GPG key error when running apt-get update
RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
RUN apt-get update && apt-get install -y ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 libgl1-mesa-glx

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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
- 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 75 mmseg
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
mmcv:
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
- run:
name: Configure Python & pip
command: |
python -m pip install --upgrade pip
python -m pip install wheel
- run:
name: Install PyTorch
command: |
python -V
python -m pip install torch==<< parameters.torch >>+cpu torchvision==<< parameters.torchvision >>+cpu -f https://download.pytorch.org/whl/torch_stable.html
- run:
name: Install mmseg dependencies
command: |
python -m pip install git+ssh://git@github.com/open-mmlab/mmengine.git@main
python -m pip install << parameters.mmcv >>
python -m pip install -r requirements.txt
- run:
name: Build and install
command: |
python -m pip install -e .
- run:
name: Run unittests
command: |
python -m pip install timm
python -m coverage run --branch --source mmseg -m pytest tests/
python -m coverage xml
python -m coverage report -m
- run:
name: Skip timm unittests and generate coverage report
command: |
coverage run --branch --source mmseg -m pytest tests/ --ignore tests/test_models/test_backbones/test_timm_backbone.py
coverage xml
coverage report -m
build_cuda:
parameters:
torch:
type: string
cuda:
type: enum
enum: ["10.1", "10.2", "11.1"]
cudnn:
type: integer
default: 7
mmcv:
type: string
machine:
image: ubuntu-2004-cuda-11.4:202110-01
# docker_layer_caching: true
resource_class: gpu.nvidia.small
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 ssh://git@github.com/open-mmlab/mmengine.git /home/circleci/mmengine
- run:
name: Build Docker image
command: |
docker build .circleci/docker -t mmseg: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:/mmseg -v /home/circleci/mmengine:/mmengine -w /mmseg --name mmseg mmseg:gpu
- run:
name: Install mmseg dependencies
command: |
docker exec mmseg pip install -e /mmengine
docker exec mmseg pip install << parameters.mmcv >>
docker exec mmseg python -m pip install -r requirements.txt
- run:
name: Build and install
command: |
docker exec mmseg pip install -e .
- run:
name: Run unittests
command: |
docker exec mmseg python -m pip install timm
docker exec mmseg python -m pytest tests/
workflows:
pr_stage_lint:
when: << pipeline.parameters.lint_only >>
jobs:
- lint:
name: lint
filters:
branches:
ignore:
- dev-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: 3.6.9 # The lowest python 3.6.x version available on CircleCI images
mmcv: https://download.openmmlab.com/mmcv/dev-2.x/cpu/torch1.6.0/mmcv_full-2.0.0rc0-cp36-cp36m-manylinux1_x86_64.whl
requires:
- lint
- build_cpu:
name: maximum_version_cpu
torch: 1.9.0
torchvision: 0.10.0
python: 3.9.0
mmcv: https://download.openmmlab.com/mmcv/dev-2.x/cpu/torch1.9.0/mmcv_full-2.0.0rc0-cp39-cp39-manylinux1_x86_64.whl
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"
mmcv: https://download.openmmlab.com/mmcv/dev-2.x/cu102/torch1.8.0/mmcv_full-2.0.0rc0-cp37-cp37m-manylinux1_x86_64.whl
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
mmcv: https://download.openmmlab.com/mmcv/dev-2.x/cu101/torch1.6.0/mmcv_full-2.0.0rc0-cp37-cp37m-manylinux1_x86_64.whl
cuda: "10.1"
filters:
branches:
only:
- dev-1.x