94 lines
3.4 KiB
YAML
94 lines
3.4 KiB
YAML
# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
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name: CI CPU testing
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on: # https://help.github.com/en/actions/reference/events-that-trigger-workflows
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push:
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branches: [ master ]
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pull_request:
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# The branches below must be a subset of the branches above
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branches: [ master ]
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schedule:
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- cron: '0 0 * * *' # Runs at 00:00 UTC every day
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jobs:
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cpu-tests:
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runs-on: ${{ matrix.os }}
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strategy:
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fail-fast: false
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matrix:
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os: [ ubuntu-latest, macos-latest, windows-latest ]
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python-version: [ 3.9 ]
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model: [ 'yolov5n' ] # models to test
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# Timeout: https://stackoverflow.com/a/59076067/4521646
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timeout-minutes: 60
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v2
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with:
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python-version: ${{ matrix.python-version }}
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# Note: This uses an internal pip API and may not always work
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# https://github.com/actions/cache/blob/master/examples.md#multiple-oss-in-a-workflow
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- name: Get pip cache
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id: pip-cache
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run: |
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python -c "from pip._internal.locations import USER_CACHE_DIR; print('::set-output name=dir::' + USER_CACHE_DIR)"
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- name: Cache pip
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uses: actions/cache@v2.1.7
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with:
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path: ${{ steps.pip-cache.outputs.dir }}
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key: ${{ runner.os }}-${{ matrix.python-version }}-pip-${{ hashFiles('requirements.txt') }}
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restore-keys: |
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${{ runner.os }}-${{ matrix.python-version }}-pip-
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# Known Keras 2.7.0 issue: https://github.com/ultralytics/yolov5/pull/5486
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install -qr requirements.txt -f https://download.pytorch.org/whl/cpu/torch_stable.html
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pip install -q onnx tensorflow-cpu keras==2.6.0 # wandb # extras
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python --version
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pip --version
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pip list
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shell: bash
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# - name: W&B login
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# run: wandb login 345011b3fb26dc8337fd9b20e53857c1d403f2aa
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# - name: Download data
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# run: |
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# curl -L -o tmp.zip https://github.com/ultralytics/yolov5/releases/download/v1.0/coco128.zip
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# unzip -q tmp.zip -d ../datasets
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- name: Tests workflow
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run: |
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# export PYTHONPATH="$PWD" # to run '$ python *.py' files in subdirectories
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d=cpu # device
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weights=runs/train/exp/weights/best.pt
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# Train
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python train.py --img 64 --batch 32 --weights ${{ matrix.model }}.pt --cfg ${{ matrix.model }}.yaml --epochs 1 --device $d
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# Val
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python val.py --img 64 --batch 32 --weights ${{ matrix.model }}.pt --device $d
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python val.py --img 64 --batch 32 --weights $weights --device $d
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# Detect
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python detect.py --weights ${{ matrix.model }}.pt --device $d
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python detect.py --weights $weights --device $d
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python hubconf.py # hub
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# Export
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python models/yolo.py --cfg ${{ matrix.model }}.yaml # build PyTorch model
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python models/tf.py --weights ${{ matrix.model }}.pt # build TensorFlow model
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python export.py --weights ${{ matrix.model }}.pt --img 64 --include torchscript onnx # export
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# Python
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python - <<EOF
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import torch
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# model = torch.hub.load('ultralytics/yolov5', 'custom', path=$weights)
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EOF
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shell: bash
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