[CI] Add Circle CI for mmcls 1.x. (#970)

* [CI] Add Circle CI for mmcls 1.x

* Fix circle-ci config

* Use `torch.cat` instead of `torch.hstack` to compat with PyTorch 1.6

* Compat the behavior of LongTensor in PyTorch 1.6

* Avoid random behavior in the unit test of Lighting

* Fix cuda ci

* Remove github workflow temporarily.
pull/977/head^2
Ma Zerun 2022-08-22 15:02:08 +08:00 committed by GitHub
parent e4252d6848
commit 20f9ace5c5
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11 changed files with 243 additions and 485 deletions

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# See: https://circleci.com/docs/2.0/configuration-reference
version: 2.1
# 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 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 40 mmcls
build:
parameters:
# The python version must match available image tags in
# https://circleci.com/developer/images/image/cimg/python
python:
type: string
default: "3.6.15"
torch:
type: string
torchvision:
type: string
env:
type: string
default: ""
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: |
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 mmcls 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 -r requirements.txt
- run:
name: Build and install
command: |
python -m pip install -e .
- run:
name: Run unittests
command: |
<< parameters.env >> python -m pytest tests/ --ignore tests/test_models/test_backbones/test_timm_backbone.py
# This allows you to use CircleCI's dynamic configuration feature
setup: true
build_with_cuda:
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 libjpeg8-dev zlib1g-dev
- 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 mmcls dependencies
command: |
python -m pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.6.0/index.html
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 pytest tests/ --ignore tests/test_models/test_backbones/test_timm_backbone.py
# 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
build_with_timm:
parameters:
# The python version must match available image tags in
# https://circleci.com/developer/images/image/cimg/python
python:
type: string
default: "3.7.12"
torch:
type: string
default: "1.10.0"
torchvision:
type: string
default: "0.11.1"
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: |
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 mmcls 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 -r requirements.txt
- run:
name: Install TIMM
command: |
pip install timm
- run:
name: Build and install
command: |
python -m pip install -e .
- run:
name: Run unittests
command: |
python -m coverage run --branch --source mmcls -m pytest tests/
python -m coverage xml
python -m coverage report -m
# Invoke jobs via workflows
# See: https://circleci.com/docs/2.0/configuration-reference/#workflows
workflows:
unit_tests:
jobs:
- lint
- build_with_timm:
name: build_with_timm
requires:
- lint
- build:
name: build_py36_torch1.5
torch: 1.5.0
torchvision: 0.6.0
# To fix memory leak in torch1.5+cpu, refers to pytorch#32037
env: LRU_CACHE_CAPACITY=1
requires:
- lint
- build:
name: build_py36_torch1.6
torch: 1.6.0
torchvision: 0.7.0
requires:
- lint
- build:
name: build_py36_torch1.7
torch: 1.7.0
torchvision: 0.8.1
requires:
- lint
- build:
name: build_py36_torch1.8
torch: 1.8.0
torchvision: 0.9.0
requires:
- lint
- build:
name: build_py39_torch1.8
torch: 1.8.0
torchvision: 0.9.0
python: "3.9.0"
requires:
- lint
- build:
name: build_py39_torch1.9
torch: 1.9.0
torchvision: 0.10.0
python: "3.9.0"
requires:
- lint
- build:
name: build_py39_torch1.10
torch: 1.10.0
torchvision: 0.11.1
python: "3.9.0"
requires:
- lint
- build_with_cuda:
name: build_py36_torch1.6_cu101
requires:
- build_with_timm
- build_py36_torch1.5
- build_py36_torch1.6
- build_py36_torch1.7
- build_py36_torch1.8
- build_py39_torch1.8
- build_py39_torch1.9
- build_py39_torch1.10
# the always-run workflow is always triggered, regardless of the pipeline parameters.
always-run:
jobs:
# 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: |
mmcls/.* lint_only false
requirements/.* lint_only false
tests/.* 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

196
.circleci/test.yml 100644
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# 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-regex "__repr__" --fail-under 60 mmcls
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 libjpeg8-dev zlib1g-dev
- 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 mmcls 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 timm
python -m pip install -r requirements.txt
python -c 'import mmcv; print(mmcv.__version__)'
- run:
name: Build and install
command: |
python -m pip install -e .
- run:
name: Run unittests
command: |
python -m coverage run --branch --source mmcls -m pytest tests/
python -m coverage xml
python -m 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
mmcv:
type: string
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 mmcls: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:/mmcls -v /home/circleci/mmengine:/mmengine -w /mmcls --name mmcls mmcls:gpu
- run:
name: Install mmcls dependencies
command: |
docker exec mmcls pip install -e /mmengine
docker exec mmcls pip install << parameters.mmcv >>
docker exec mmcls pip install -r requirements.txt
docker exec mmcls python -c 'import mmcv; print(mmcv.__version__)'
- run:
name: Build and install
command: |
docker exec mmcls pip install -e .
- run:
name: Run unittests
command: |
docker exec mmcls python -m pytest tests/ --ignore tests/test_models/test_backbones/test_timm_backbone.py
# 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
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 # TODO: Update the version after mmcv provides more pre-compiled packages.
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

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@ -1,198 +0,0 @@
# This workflow will install Python dependencies, run tests with a variety of Python versions
# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
name: build
on:
push:
paths-ignore:
- 'README.md'
- 'README_zh-CN.md'
- 'model-index.yml'
- 'configs/**'
- 'docs/**'
- 'demo/**'
- '.dev_scripts/**'
pull_request:
paths-ignore:
- 'README.md'
- 'README_zh-CN.md'
- 'model-index.yml'
- 'configs/**'
- 'docs/**'
- 'demo/**'
- '.dev_scripts/**'
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
build_without_timm:
runs-on: ubuntu-latest
env:
UBUNTU_VERSION: ubuntu1804
strategy:
matrix:
python-version: [3.6]
torch: [1.5.0, 1.8.0, 1.9.0]
include:
- torch: 1.5.0
torchvision: 0.6.0
torch_major: 1.5.0
- torch: 1.8.0
torchvision: 0.9.0
torch_major: 1.8.0
- torch: 1.9.0
torchvision: 0.10.0
torch_major: 1.9.0
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Install PyTorch
run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
- name: Install MMCV
run: |
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cpu/torch${{matrix.torch_major}}/index.html
python -c 'import mmcv; print(mmcv.__version__)'
- name: Install mmcls dependencies
run: |
pip install -r requirements.txt
- name: Build and install
run: |
rm -rf .eggs
pip install -e . -U
- name: Run unittests
run: |
pytest tests/ --ignore tests/test_models/test_backbones/test_timm_backbone.py
build:
runs-on: ubuntu-latest
env:
UBUNTU_VERSION: ubuntu1804
strategy:
matrix:
python-version: [3.7]
torch: [1.5.0, 1.6.0, 1.7.0, 1.8.0, 1.9.0]
include:
- torch: 1.5.0
torchvision: 0.6.0
torch_major: 1.5.0
- torch: 1.6.0
torchvision: 0.7.0
torch_major: 1.6.0
- torch: 1.7.0
torchvision: 0.8.1
torch_major: 1.7.0
- torch: 1.8.0
torchvision: 0.9.0
torch_major: 1.8.0
- torch: 1.8.0
torchvision: 0.9.0
torch_major: 1.8.0
python-version: 3.8
- torch: 1.8.0
torchvision: 0.9.0
torch_major: 1.8.0
python-version: 3.9
- torch: 1.9.0
torchvision: 0.10.0
torch_major: 1.9.0
- torch: 1.10.0
torchvision: 0.11.1
torch_major: 1.10.0
- torch: 1.10.0
torchvision: 0.11.1
torch_major: 1.10.0
python-version: 3.8
- torch: 1.10.0
torchvision: 0.11.1
torch_major: 1.10.0
python-version: 3.9
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Install PyTorch
run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
- name: Install MMCV
run: |
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cpu/torch${{matrix.torch_major}}/index.html
python -c 'import mmcv; print(mmcv.__version__)'
- name: Install mmcls dependencies
run: |
pip install -r requirements.txt
- name: Install timm
run: |
pip install timm
- name: Build and install
run: |
rm -rf .eggs
pip install -e . -U
- name: Run unittests and generate coverage report
run: |
coverage run --branch --source mmcls -m pytest tests/
coverage xml
coverage report -m --omit="mmcls/utils/*","mmcls/apis/*"
- name: Upload coverage to Codecov
uses: codecov/codecov-action@v2
with:
file: ./coverage.xml
flags: unittests
env_vars: OS,PYTHON
name: codecov-umbrella
fail_ci_if_error: false
build-windows:
runs-on: windows-2022
strategy:
matrix:
python-version: [3.8]
torch: [1.8.1]
include:
- torch: 1.8.1
torchvision: 0.9.1
torch_major: 1.8.0
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Install PyTorch
run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
- name: Install MMCV & OpenCV
run: |
pip install opencv-python
pip install mmcv-full==1.4.2 -f https://download.openmmlab.com/mmcv/dist/cpu/torch${{matrix.torch_major}}/index.html
python -c 'import mmcv; print(mmcv.__version__)'
- name: Install mmcls dependencies
run: |
pip install -r requirements.txt
- name: Install timm
run: |
pip install timm
- name: Build and install
run: |
pip install -e . -U
- name: Run unittests and generate coverage report
run: |
coverage run --branch --source mmcls -m pytest tests/
coverage xml
coverage report -m --omit="mmcls/utils/*","mmcls/apis/*"
- name: Upload coverage to Codecov
uses: codecov/codecov-action@v2
with:
file: ./coverage.xml
flags: unittests
env_vars: OS,PYTHON
name: codecov-umbrella
fail_ci_if_error: false

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@ -1,22 +0,0 @@
name: deploy
on: push
jobs:
build-n-publish:
runs-on: ubuntu-latest
if: startsWith(github.event.ref, 'refs/tags')
steps:
- uses: actions/checkout@v2
- name: Set up Python 3.7
uses: actions/setup-python@v2
with:
python-version: 3.7
- name: Build MMClassification
run: |
pip install wheel
python setup.py sdist bdist_wheel
- name: Publish distribution to PyPI
run: |
pip install twine
twine upload dist/* -u __token__ -p ${{ secrets.pypi_password }}

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@ -1,25 +0,0 @@
# This workflow will run lint
name: lint
on: [push, pull_request]
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
lint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Set up Python 3.7
uses: actions/setup-python@v2
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

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@ -411,7 +411,7 @@ def _average_precision(pred: torch.Tensor,
pred_pos_nums[pred_pos_nums < eps] = eps
tps[torch.logical_not(pos_inds)] = 0
precision = tps / pred_pos_nums
precision = tps / pred_pos_nums.float()
ap = torch.sum(precision, 0) / max(total_pos, eps)
return ap

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@ -38,8 +38,8 @@ def _precision_recall_f1_support(pred_positive, gt_positive, average):
pred_sum = pred_positive.sum(0)
gt_sum = gt_positive.sum(0)
precision = tp_sum / torch.clamp(pred_sum, min=1.) * 100
recall = tp_sum / torch.clamp(gt_sum, min=1.) * 100
precision = tp_sum / torch.clamp(pred_sum, min=1).float() * 100
recall = tp_sum / torch.clamp(gt_sum, min=1).float() * 100
f1_score = 2 * precision * recall / torch.clamp(
precision + recall, min=torch.finfo(torch.float32).eps)
if average in ['macro', 'micro']:

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@ -85,7 +85,7 @@ class ClsHead(BaseHead):
# Batch augmentation may convert labels to one-hot format scores.
target = torch.stack([i.gt_label.score for i in data_samples])
else:
target = torch.hstack([i.gt_label.label for i in data_samples])
target = torch.cat([i.gt_label.label for i in data_samples])
# compute loss
losses = dict()

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@ -99,7 +99,7 @@ class ConformerHead(ClsHead):
# Batch augmentation may convert labels to one-hot format scores.
target = torch.stack([i.gt_label.score for i in data_samples])
else:
target = torch.hstack([i.gt_label.label for i in data_samples])
target = torch.cat([i.gt_label.label for i in data_samples])
# compute loss
losses = dict()

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@ -641,9 +641,10 @@ class TestLighting(TestCase):
# test call
cfg = copy.deepcopy(self.DEFAULT_ARGS)
lightening_module = TRANSFORMS.build(cfg)
results = lightening_module(results)
self.assertEqual(results['img'].dtype, ori_img.dtype)
assert not np.equal(results['img'], ori_img).all()
with patch('numpy.random', np.random.RandomState(0)):
results = lightening_module(results)
self.assertEqual(results['img'].dtype, ori_img.dtype)
assert not np.equal(results['img'], ori_img).all()
# test call with alphastd == 0
results = dict(img=copy.deepcopy(ori_img))