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fix dal-base config #61

fix dal-base config

fix dal-base config #61

Workflow file for this run

# This workflow will install Python dependencies, run tests and lint 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:
- ".dev_scripts/**"
- ".github/**.md"
- "demo/**"
- "docker/**"
- "tools/**"
pull_request:
paths-ignore:
- ".dev_scripts/**"
- ".github/**.md"
- "demo/**"
- "docker/**"
- "tools/**"
- "docs/**"
- "docs_zh-CN/**"
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
build:
env:
FORCE_CUDA: 1
CUDA_ARCH: ${{matrix.cuda_arch}}
runs-on: ubuntu-18.04
container:
image: pytorch/pytorch:1.6.0-cuda10.1-cudnn7-devel
strategy:
matrix:
python-version: [3.6, 3.7]
torch: [1.5.0+cu101, 1.6.0+cu101, 1.7.0+cu101, 1.8.0+cu101]
include:
- torch: 1.5.0+cu101
torch_version: torch1.5
torchvision: 0.6.0+cu101
mmcv_link: "torch1.5.0"
cuda_arch: "7.0"
- torch: 1.6.0+cu101
torch_version: torch1.6
mmcv_link: "torch1.6.0"
torchvision: 0.7.0+cu101
cuda_arch: "7.0"
- torch: 1.7.0+cu101
torch_version: torch1.7
mmcv_link: "torch1.7.0"
torchvision: 0.8.1+cu101
cuda_arch: "7.0"
- torch: 1.8.0+cu101
torch_version: torch1.8
mmcv_link: "torch1.8.0"
torchvision: 0.9.0+cu101
cuda_arch: "7.0"
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Fetch GPG keys
run: |
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
- name: Install system dependencies
run: |
apt-get update && apt-get install -y ffmpeg libsm6 git ninja-build libglib2.0-0 libsm6 libxrender-dev python${{matrix.python-version}}-dev
apt-get clean
rm -rf /var/lib/apt/lists/*
- name: Install PyTorch
run: python -m pip install numpy==1.19.5 torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
- name: Install mmdet3d dependencies
run: |
python -m pip install mmcv-full==1.6.0 -f https://download.openmmlab.com/mmcv/dist/cu101/${{matrix.torch_version}}/index.html
python -m pip install mmdet
python -m pip install mmsegmentation
python -m pip install -r requirements.txt
- name: Build and install
run: |
rm -rf .eggs
python setup.py check -m -s
TORCH_CUDA_ARCH_LIST=${CUDA_ARCH} python setup.py build_ext --inplace
- name: Run unittests and generate coverage report
run: |
coverage run --branch --source mmdet3d -m pytest tests/
coverage xml
coverage report -m
# Only upload coverage report for python3.7 && pytorch1.5
- name: Upload coverage to Codecov
if: ${{matrix.torch == '1.5.0+cu101' && matrix.python-version == '3.7'}}
uses: codecov/[email protected]
with:
file: ./coverage.xml
flags: unittests
env_vars: OS,PYTHON
name: codecov-umbrella
fail_ci_if_error: false
build_windows:
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [windows-2022]
python: [3.8]
platform: [cpu]
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python }}
- name: Upgrade pip
run: python -m pip install pip --upgrade --user
- name: Install PyTorch
# As a complement to Linux CI, we test on PyTorch LTS version
run: pip install torch==1.8.2+${{ matrix.platform }} torchvision==0.9.2+${{ matrix.platform }} -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html
- name: Install mmdet3d dependencies
run: |
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.8/index.html --only-binary mmcv-full
python -m pip install mmdet
python -m pip install mmsegmentation
python -m pip install -r requirements/build.txt -r requirements/runtime.txt -r requirements/tests.txt
- name: Build and install
run: pip install -e .
- name: Run unittests and generate coverage report
run: coverage run --branch --source mmdet3d -m pytest tests/
- name: Generate coverage report
run: |
coverage xml
coverage report -m
- 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