set circle ci (#1804)
Miao Zheng
GitHub
parent
b61347e246
commit
d326471dca
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@ -1,161 +1,34 @@
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version: 2.1
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version: 2.1
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jobs:
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# this allows you to use CircleCI's dynamic configuration feature
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lint:
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setup: true
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docker:
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- image: cimg/python:3.7.4
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steps:
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- checkout
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- run:
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name: Install dependencies
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command: |
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sudo apt-add-repository ppa:brightbox/ruby-ng -y
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sudo apt-get update
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sudo apt-get install -y ruby2.7
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- run:
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name: Install pre-commit hook
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command: |
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pip install pre-commit
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pre-commit install
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- run:
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name: Linting
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command: pre-commit run --all-files
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- run:
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name: Check docstring coverage
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command: |
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pip install interrogate
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interrogate -v --ignore-init-method --ignore-module --ignore-nested-functions --ignore-regex "__repr__" --fail-under 50 mmseg
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build_cpu:
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# the path-filtering orb is required to continue a pipeline based on
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parameters:
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# the path of an updated fileset
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# The python version must match available image tags in
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orbs:
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# https://circleci.com/developer/images/image/cimg/python
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path-filtering: circleci/path-filtering@0.1.2
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python:
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type: string
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default: "3.7.4"
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torch:
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type: string
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torchvision:
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type: string
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docker:
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- image: cimg/python:<< parameters.python >>
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resource_class: large
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steps:
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- checkout
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- run:
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name: Install Libraries
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command: |
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sudo apt-get update
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sudo apt-get install -y ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 libgl1-mesa-glx libjpeg-dev zlib1g-dev libtinfo-dev libncurses5
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- run:
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name: Configure Python & pip
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command: |
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python -m pip install --upgrade pip
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python -m pip install wheel
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- run:
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name: Install PyTorch
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command: |
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python -V
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python -m pip install torch==<< parameters.torch >>+cpu torchvision==<< parameters.torchvision >>+cpu -f https://download.pytorch.org/whl/torch_stable.html
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- run:
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name: Install mmseg dependencies
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command: |
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python -m pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cpu/torch<< parameters.torch >>/index.html
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python -m pip install mmdet
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python -m pip install -r requirements.txt
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- run:
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name: Build and install
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command: |
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python -m pip install -e .
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- run:
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name: Run unittests
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command: |
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python -m pip install timm
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python -m coverage run --branch --source mmseg -m pytest tests/
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python -m coverage xml
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python -m coverage report -m
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build_cu101:
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machine:
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image: ubuntu-1604-cuda-10.1:201909-23
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resource_class: gpu.nvidia.small
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steps:
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- checkout
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- run:
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name: Install Libraries
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command: |
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sudo apt-get update
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sudo apt-get install -y git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 libgl1-mesa-glx
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- run:
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name: Configure Python & pip
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command: |
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pyenv global 3.7.0
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python -m pip install --upgrade pip
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python -m pip install wheel
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- run:
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name: Install PyTorch
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command: |
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python -V
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python -m pip install torch==1.6.0+cu101 torchvision==0.7.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html
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- run:
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name: Install mmseg dependencies
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# python -m pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu101/torch${{matrix.torch_version}}/index.html
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command: |
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python -m pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.6.0/index.html
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python -m pip install mmdet
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python -m pip install -r requirements.txt
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- run:
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name: Build and install
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command: |
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python setup.py check -m -s
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TORCH_CUDA_ARCH_LIST=7.0 python -m pip install -e .
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- run:
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name: Run unittests
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command: |
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python -m pip install timm
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python -m pytest tests/
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workflows:
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workflows:
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unit_tests:
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# the always-run workflow is always triggered, regardless of the pipeline parameters.
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always-run:
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jobs:
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jobs:
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- lint
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# the path-filtering/filter job determines which pipeline
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- build_cpu:
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# parameters to update.
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name: build_cpu_th1.6
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- path-filtering/filter:
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torch: 1.6.0
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name: check-updated-files
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torchvision: 0.7.0
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# 3-column, whitespace-delimited mapping. One mapping per
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requires:
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# line:
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- lint
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# <regex path-to-test> <parameter-to-set> <value-of-pipeline-parameter>
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- build_cpu:
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mapping: |
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name: build_cpu_th1.7
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mmseg/.* lint_only false
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torch: 1.7.0
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requirements/.* lint_only false
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torchvision: 0.8.1
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tests/.* lint_only false
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requires:
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tools/.* lint_only false
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- lint
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configs/.* lint_only false
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- build_cpu:
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.circleci/.* lint_only false
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name: build_cpu_th1.8_py3.9
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base-revision: dev-1.x
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torch: 1.8.0
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# this is the path of the configuration we should trigger once
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torchvision: 0.9.0
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# path filtering and pipeline parameter value updates are
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python: "3.9.0"
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# complete. In this case, we are using the parent dynamic
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requires:
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# configuration itself.
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- lint
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config-path: .circleci/test.yml
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- build_cpu:
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name: build_cpu_th1.9_py3.8
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torch: 1.9.0
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torchvision: 0.10.0
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python: "3.8.0"
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requires:
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- lint
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- build_cpu:
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name: build_cpu_th1.9_py3.9
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torch: 1.9.0
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torchvision: 0.10.0
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python: "3.9.0"
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requires:
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- lint
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- build_cu101:
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requires:
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- build_cpu_th1.6
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- build_cpu_th1.7
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- build_cpu_th1.8_py3.9
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- build_cpu_th1.9_py3.8
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- build_cpu_th1.9_py3.9
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@ -0,0 +1,12 @@
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ARG PYTORCH="1.8.1"
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ARG CUDA="10.2"
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ARG CUDNN="7"
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FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel
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# To fix GPG key error when running apt-get update
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RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
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RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
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RUN apt-get update && apt-get install -y ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 libgl1-mesa-glx
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@ -0,0 +1,192 @@
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version: 2.1
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# the default pipeline parameters, which will be updated according to
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# the results of the path-filtering orb
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parameters:
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lint_only:
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type: boolean
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default: true
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jobs:
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lint:
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docker:
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- image: cimg/python:3.7.4
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steps:
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- checkout
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- run:
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name: Install pre-commit hook
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command: |
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pip install pre-commit
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pre-commit install
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- run:
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name: Linting
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||||||
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command: pre-commit run --all-files
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- run:
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name: Check docstring coverage
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||||||
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command: |
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||||||
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pip install interrogate
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interrogate -v --ignore-init-method --ignore-module --ignore-nested-functions --ignore-magic --ignore-regex "__repr__" --fail-under 75 mmseg
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build_cpu:
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parameters:
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# The python version must match available image tags in
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# https://circleci.com/developer/images/image/cimg/python
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python:
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type: string
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torch:
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type: string
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torchvision:
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type: string
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mmcv:
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type: string
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docker:
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- image: cimg/python:<< parameters.python >>
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resource_class: large
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steps:
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- checkout
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- run:
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name: Install Libraries
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command: |
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sudo apt-get update
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sudo apt-get install -y ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 libgl1-mesa-glx libjpeg-dev zlib1g-dev libtinfo-dev libncurses5
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- run:
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name: Configure Python & pip
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command: |
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python -m pip install --upgrade pip
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python -m pip install wheel
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- run:
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name: Install PyTorch
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command: |
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python -V
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python -m pip install torch==<< parameters.torch >>+cpu torchvision==<< parameters.torchvision >>+cpu -f https://download.pytorch.org/whl/torch_stable.html
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- run:
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name: Install mmseg dependencies
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command: |
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python -m pip install git+ssh://git@github.com/open-mmlab/mmengine.git@main
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python -m pip install << parameters.mmcv >>
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python -m pip install -r requirements.txt
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- run:
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name: Build and install
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command: |
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python -m pip install -e .
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- run:
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name: Run unittests
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command: |
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python -m pip install timm
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python -m coverage run --branch --source mmseg -m pytest tests/
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python -m coverage xml
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python -m coverage report -m
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- run:
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name: Skip timm unittests and generate coverage report
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command: |
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coverage run --branch --source mmseg -m pytest tests/ --ignore tests/test_models/test_backbones/test_timm_backbone.py
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coverage xml
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coverage report -m
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build_cuda:
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parameters:
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torch:
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type: string
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cuda:
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type: enum
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enum: ["10.1", "10.2", "11.1"]
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cudnn:
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type: integer
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default: 7
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mmcv:
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type: string
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machine:
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image: ubuntu-2004-cuda-11.4:202110-01
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# docker_layer_caching: true
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resource_class: gpu.nvidia.small
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steps:
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- checkout
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- run:
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# Cloning repos in VM since Docker doesn't have access to the private key
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name: Clone Repos
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command: |
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git clone -b main --depth 1 ssh://git@github.com/open-mmlab/mmengine.git /home/circleci/mmengine
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- run:
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name: Build Docker image
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command: |
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docker build .circleci/docker -t mmseg:gpu --build-arg PYTORCH=<< parameters.torch >> --build-arg CUDA=<< parameters.cuda >> --build-arg CUDNN=<< parameters.cudnn >>
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docker run --gpus all -t -d -v /home/circleci/project:/mmseg -v /home/circleci/mmengine:/mmengine -w /mmseg --name mmseg mmseg:gpu
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- run:
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name: Install mmseg dependencies
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command: |
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docker exec mmseg pip install -e /mmengine
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docker exec mmseg pip install << parameters.mmcv >>
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docker exec mmseg python -m pip install -r requirements.txt
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- run:
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name: Build and install
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command: |
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docker exec mmseg pip install -e .
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- run:
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name: Run unittests
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command: |
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docker exec mmseg python -m pip install timm
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docker exec mmseg python -m pytest tests/
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workflows:
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pr_stage_lint:
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when: << pipeline.parameters.lint_only >>
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jobs:
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- lint:
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name: lint
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filters:
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branches:
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ignore:
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- dev-1.x
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pr_stage_test:
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when:
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not:
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<< pipeline.parameters.lint_only >>
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jobs:
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- lint:
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name: lint
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filters:
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branches:
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ignore:
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- dev-1.x
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- build_cpu:
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name: minimum_version_cpu
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torch: 1.6.0
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torchvision: 0.7.0
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python: 3.6.9 # The lowest python 3.6.x version available on CircleCI images
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mmcv: https://download.openmmlab.com/mmcv/dev-2.x/cpu/torch1.6.0/mmcv_full-2.0.0rc0-cp36-cp36m-manylinux1_x86_64.whl
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requires:
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- lint
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- build_cpu:
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name: maximum_version_cpu
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torch: 1.9.0
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torchvision: 0.10.0
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python: 3.9.0
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mmcv: https://download.openmmlab.com/mmcv/dev-2.x/cpu/torch1.9.0/mmcv_full-2.0.0rc0-cp39-cp39-manylinux1_x86_64.whl
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requires:
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- minimum_version_cpu
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- hold:
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type: approval
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requires:
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- maximum_version_cpu
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- build_cuda:
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name: mainstream_version_gpu
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torch: 1.8.1
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# Use double quotation mark to explicitly specify its type
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# as string instead of number
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cuda: "10.2"
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mmcv: https://download.openmmlab.com/mmcv/dev-2.x/cu102/torch1.8.0/mmcv_full-2.0.0rc0-cp37-cp37m-manylinux1_x86_64.whl
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requires:
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- hold
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||||||
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merge_stage_test:
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||||||
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when:
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not:
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||||||
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<< pipeline.parameters.lint_only >>
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jobs:
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- build_cuda:
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||||||
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name: minimum_version_gpu
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torch: 1.6.0
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# Use double quotation mark to explicitly specify its type
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||||||
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# as string instead of number
|
||||||
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mmcv: https://download.openmmlab.com/mmcv/dev-2.x/cu101/torch1.6.0/mmcv_full-2.0.0rc0-cp37-cp37m-manylinux1_x86_64.whl
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cuda: "10.1"
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filters:
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||||||
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branches:
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||||||
|
only:
|
||||||
|
- dev-1.x
|
||||||
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Reference in New Issue