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[Fix] Fix ndarray metainfo check in ConcatDataset #2483

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[Fix] Fix ndarray metainfo check in ConcatDataset

[Fix] Fix ndarray metainfo check in ConcatDataset #2483

Workflow file for this run

.github/workflows/pr_stage_test.yml at cdf1fda
name: pr_stage_test
on:
pull_request:
paths-ignore:
- ".github/**.md"
- "docker/**"
- "docs/**"
- "README.md"
- "README_zh-CN.md"
- "CONTRIBUTING.md"
- "CONTRIBUTING_zh-CN.md"
- ".pre-commit-config.yaml"
- ".pre-commit-config-zh-cn.yaml"
- "examples/**"
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
build_cpu:
runs-on: ubuntu-22.04
strategy:
matrix:
python-version: [3.7]
include:
- torch: 1.8.1
torchvision: 0.9.1
steps:
- uses: actions/checkout@v3
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
- name: Upgrade pip
run: python -m pip install pip --upgrade
- name: Upgrade wheel
run: python -m pip install wheel --upgrade
- name: Install PyTorch
run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
- name: Build MMEngine from source
run: pip install -e . -v
- name: Install unit tests dependencies
run: |
pip install -r requirements/tests.txt
pip install openmim
mim install mmcv
- name: Run unittests and generate coverage report
run: |
coverage run --branch --source mmengine -m pytest tests/ --ignore tests/test_dist
coverage xml
coverage report -m
# Upload coverage report for python3.7 && pytorch1.8.1 cpu
- name: Upload coverage to Codecov
uses: codecov/codecov-action@v3
with:
file: ./coverage.xml
flags: unittests
env_vars: OS,PYTHON
name: codecov-umbrella
fail_ci_if_error: false
build_cu102:
runs-on: ubuntu-22.04
container:
image: pytorch/pytorch:1.8.1-cuda10.2-cudnn7-devel
env:
MKL_THREADING_LAYER: GNU
strategy:
matrix:
python-version: [3.7]
steps:
- uses: actions/checkout@v3
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
- name: Upgrade pip
run: pip install pip --upgrade
- name: Fetch GPG keys
run: |
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
- name: Install system dependencies
run: apt-get update && apt-get install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6
- name: Build MMEngine from source
run: pip install -e . -v
- name: Install unit tests dependencies
run: |
pip install -r requirements/tests.txt
pip install openmim
mim install mmcv
- name: Run unittests and generate coverage report
run: |
coverage run --branch --source mmengine -m pytest tests/ --ignore tests/test_dist
coverage xml
coverage report -m
build_cu117:
runs-on: ubuntu-22.04
container:
image: pytorch/pytorch:2.0.0-cuda11.7-cudnn8-devel
strategy:
matrix:
python-version: [3.9]
steps:
- uses: actions/checkout@v3
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
- name: Upgrade pip
run: pip install pip --upgrade
- name: Fetch GPG keys
run: |
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
- name: Install system dependencies
run: apt-get update && apt-get install -y git ffmpeg libturbojpeg
- name: Build MMEngine from source
run: pip install -e . -v
- name: Install unit tests dependencies
run: |
pip install -r requirements/tests.txt
pip install openmim
mim install mmcv
# Distributed related unit test may randomly error in PyTorch 1.13.0
- name: Run unittests and generate coverage report
run: |
coverage run --branch --source mmengine -m pytest tests/ --ignore tests/test_dist/
coverage xml
coverage report -m
build_windows:
runs-on: windows-2022
strategy:
matrix:
python-version: [3.7]
platform: [cpu, cu111]
torch: [1.8.1]
torchvision: [0.9.1]
include:
- python-version: 3.8
platform: cu117
torch: 2.0.0
torchvision: 0.15.1
steps:
- uses: actions/checkout@v3
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
- name: Upgrade pip
# Windows CI could fail If we call `pip install pip --upgrade` directly.
run: python -m pip install pip --upgrade
- name: Install PyTorch
run: pip install torch==${{matrix.torch}}+${{matrix.platform}} torchvision==${{matrix.torchvision}}+${{matrix.platform}} -f https://download.pytorch.org/whl/${{matrix.platform}}/torch_stable.html
- name: Build MMEngine from source
run: pip install -e . -v
- name: Install unit tests dependencies
run: |
pip install -r requirements/tests.txt
pip install openmim
mim install mmcv
- name: Run CPU unittests
run: pytest tests/ --ignore tests/test_dist
if: ${{ matrix.platform == 'cpu' }}
- name: Run GPU unittests
# Skip testing distributed related unit tests since the memory of windows CI is limited
run: pytest tests/ --ignore tests/test_dist --ignore tests/test_optim/test_optimizer/test_optimizer_wrapper.py --ignore tests/test_model/test_wrappers/test_model_wrapper.py --ignore tests/test_hooks/test_sync_buffers_hook.py
if: ${{ matrix.platform == 'cu111' }}