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feat: Add new mmdetection (#19)
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‎newmm/.circleci/config.yml‎

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version: 2.1
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# this allows you to use CircleCI's dynamic configuration feature
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setup: true
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# the path-filtering orb is required to continue a pipeline based on
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# the path of an updated fileset
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orbs:
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path-filtering: circleci/path-filtering@0.1.2
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workflows:
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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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# the path-filtering/filter job determines which pipeline
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# parameters to update.
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- path-filtering/filter:
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name: check-updated-files
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# 3-column, whitespace-delimited mapping. One mapping per
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# line:
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# <regex path-to-test> <parameter-to-set> <value-of-pipeline-parameter>
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mapping: |
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mmdet/.* lint_only false
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requirements/.* lint_only false
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tests/.* lint_only false
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tools/.* lint_only false
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configs/.* lint_only false
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.circleci/.* lint_only false
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base-revision: dev-3.x
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# this is the path of the configuration we should trigger once
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# path filtering and pipeline parameter value updates are
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# complete. In this case, we are using the parent dynamic
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# configuration itself.
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config-path: .circleci/test.yml

‎newmm/.circleci/docker/Dockerfile‎

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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

‎newmm/.circleci/test.yml‎

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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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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-magic --ignore-regex "__repr__" --fail-under 85 mmdet
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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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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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pip install --upgrade pip
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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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- when:
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condition:
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equal: ["3.9.0", << parameters.python >>]
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steps:
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- run: pip install "protobuf <= 3.20.1" && sudo apt-get update && sudo apt-get -y install libprotobuf-dev protobuf-compiler cmake
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- run: pip install dsdl
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- run:
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name: Install mmdet dependencies
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# numpy may be downgraded after building pycocotools, which causes `ImportError: numpy.core.multiarray failed to import`
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# force reinstall pycocotools to ensure pycocotools being built under the currenct numpy
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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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pip install -U openmim
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mim install 'mmcv >= 2.0.0rc4'
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pip install -r requirements/tests.txt -r requirements/optional.txt
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pip install --force-reinstall pycocotools
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pip install albumentations>=0.3.2 --no-binary imgaug,albumentations
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pip install -r requirements/tracking.txt
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pip install git+https://github.com/cocodataset/panopticapi.git
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pip install git+https://github.com/JonathonLuiten/TrackEval.git
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- run:
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name: Build and install
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command: |
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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 coverage run --branch --source mmdet -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_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: ["11.1", "11.7", "11.8"]
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cudnn:
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type: integer
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default: 8
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machine:
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image: linux-cuda-11:default
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# docker_layer_caching: true
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resource_class: gpu.nvidia.small.multi
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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: Install nvidia-container-toolkit and Restart Docker
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command: |
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sudo apt-get update
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sudo apt-get install -y nvidia-container-toolkit
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sudo systemctl restart docker
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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 mmdetection: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:/mmdetection -v /home/circleci/mmengine:/mmengine -w /mmdetection --name mmdetection mmdetection:gpu
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docker exec mmdetection apt-get install -y git
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- run:
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name: Install mmdet dependencies
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command: |
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docker exec mmdetection pip install -e /mmengine
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docker exec mmdetection pip install -U openmim
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docker exec mmdetection mim install 'mmcv >= 2.0.0rc4'
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docker exec mmdetection pip install -r requirements/tests.txt -r requirements/optional.txt
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docker exec mmdetection pip install pycocotools
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docker exec mmdetection pip install albumentations>=0.3.2 --no-binary imgaug,albumentations
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docker exec mmdetection pip install -r requirements/tracking.txt
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docker exec mmdetection pip install git+https://github.com/cocodataset/panopticapi.git
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docker exec mmdetection pip install git+https://github.com/JonathonLuiten/TrackEval.git
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docker exec mmdetection python -c 'import mmcv; print(mmcv.__version__)'
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- run:
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name: Build and install
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command: |
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docker exec mmdetection 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 mmdetection 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-3.x
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pr_stage_test:
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when:
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not: << 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-3.x
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- build_cpu:
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name: minimum_version_cpu
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torch: 1.8.0
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torchvision: 0.9.0
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python: 3.7.16
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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: 2.0.0
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torchvision: 0.15.1
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python: 3.9.0
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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: "11.1"
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requires:
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- hold
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- build_cuda:
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name: maximum_version_gpu
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torch: 2.0.0
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cuda: "11.7"
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cudnn: 8
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requires:
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- hold
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merge_stage_test:
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when:
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not: << pipeline.parameters.lint_only >>
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jobs:
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- build_cuda:
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name: minimum_version_gpu
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torch: 1.8.0
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cuda: "11.1"
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filters:
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branches:
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only:
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- dev-3.x

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