# Ultralytics YOLO 🚀, GPL-3.0 license
# YOLO Continuous Integration (CI) GitHub Actions tests

name: Ultralytics CI

on:
  push:
    branches: [main]
  pull_request:
    branches: [main]
  schedule:
    - cron: '0 0 * * *'  # runs at 00:00 UTC every day

jobs:
  Benchmarks:
    runs-on: ${{ matrix.os }}
    strategy:
      fail-fast: false
      matrix:
        os: [ubuntu-latest]
        python-version: ['3.10']  # requires python<=3.9
        model: [yolov8n]
    steps:
      - uses: actions/checkout@v3
      - uses: actions/setup-python@v4
        with:
          python-version: ${{ matrix.python-version }}
      #- name: Cache pip
      #  uses: actions/cache@v3
      #  with:
      #    path: ~/.cache/pip
      #    key: ${{ runner.os }}-Benchmarks-${{ hashFiles('requirements.txt') }}
      #    restore-keys: ${{ runner.os }}-Benchmarks-
      - name: Install requirements
        run: |
          python -m pip install --upgrade pip wheel
          pip install -e . coremltools openvino-dev tensorflow-cpu paddlepaddle x2paddle --extra-index-url https://download.pytorch.org/whl/cpu
          yolo export format=tflite
      - name: Check environment
        run: |
          echo "RUNNER_OS is ${{ runner.os }}"
          echo "GITHUB_EVENT_NAME is ${{ github.event_name }}"
          echo "GITHUB_WORKFLOW is ${{ github.workflow }}"
          echo "GITHUB_ACTOR is ${{ github.actor }}"
          echo "GITHUB_REPOSITORY is ${{ github.repository }}"
          echo "GITHUB_REPOSITORY_OWNER is ${{ github.repository_owner }}"
          python --version
          pip --version
          pip list
      - name: Benchmark DetectionModel
        shell: python
        run: |
          from ultralytics.yolo.utils.benchmarks import run_benchmarks
          run_benchmarks(model='yolov8n.pt', imgsz=160, half=False, hard_fail=False)
      - name: Benchmark SegmentationModel
        shell: python
        run: |
          from ultralytics.yolo.utils.benchmarks import run_benchmarks
          run_benchmarks(model='yolov8n-seg.pt', imgsz=160, half=False, hard_fail=False)
      - name: Benchmark ClassificationModel
        shell: python
        run: |
          from ultralytics.yolo.utils.benchmarks import run_benchmarks
          run_benchmarks(model='yolov8n-cls.pt', imgsz=160, half=False, hard_fail=False)

  Tests:
    timeout-minutes: 60
    runs-on: ${{ matrix.os }}
    strategy:
      fail-fast: false
      matrix:
        os: [ubuntu-latest]
        python-version: ['3.10']
        model: [yolov8n]
        torch: [latest]
        include:
          - os: ubuntu-latest
            python-version: '3.7'  # '3.6.8' min
            model: yolov8n
          - os: ubuntu-latest
            python-version: '3.8'  # torch 1.7.0 requires python >=3.6, <=3.8
            model: yolov8n
            torch: '1.8.0'  # min torch version CI https://pypi.org/project/torchvision/
    steps:
      - uses: actions/checkout@v3
      - uses: actions/setup-python@v4
        with:
          python-version: ${{ matrix.python-version }}
      - name: Get cache dir
        # https://github.com/actions/cache/blob/master/examples.md#multiple-oss-in-a-workflow
        id: pip-cache
        run: echo "::set-output name=dir::$(pip cache dir)"
      - name: Cache pip
        uses: actions/cache@v3
        with:
          path: ${{ steps.pip-cache.outputs.dir }}
          key: ${{ runner.os }}-${{ matrix.python-version }}-pip-${{ hashFiles('requirements.txt') }}
          restore-keys: ${{ runner.os }}-${{ matrix.python-version }}-pip-
      - name: Install requirements
        run: |
          python -m pip install --upgrade pip wheel
          if [ "${{ matrix.torch }}" == "1.8.0" ]; then
              pip install -e '.[export]' torch==1.8.0 torchvision==0.9.0 pytest --extra-index-url https://download.pytorch.org/whl/cpu
          else
              pip install -e '.[export]' pytest --extra-index-url https://download.pytorch.org/whl/cpu
          fi
        shell: bash  # for Windows compatibility
      - name: Check environment
        run: |
          echo "RUNNER_OS is ${{ runner.os }}"
          echo "GITHUB_EVENT_NAME is ${{ github.event_name }}"
          echo "GITHUB_WORKFLOW is ${{ github.workflow }}"
          echo "GITHUB_ACTOR is ${{ github.actor }}"
          echo "GITHUB_REPOSITORY is ${{ github.repository }}"
          echo "GITHUB_REPOSITORY_OWNER is ${{ github.repository_owner }}"
          python --version
          pip --version
          pip list
      - name: Test pip package
        shell: python
        env:
          APIKEY: ${{ secrets.ULTRALYTICS_HUB_APIKEY }}
        run: |
          import os
          import ultralytics
          from ultralytics import hub, yolo
          key = os.environ['APIKEY']
          print(ultralytics.__version__)
          ultralytics.checks()
          # ultralytics.reset_model(key)  # reset trained model
          # ultralytics.start(key)  # train model
      - name: Test detection
        shell: bash  # for Windows compatibility
        run: |
          yolo task=detect mode=train data=coco8.yaml model=yolov8n.yaml epochs=1 imgsz=32
          yolo task=detect mode=train data=coco8.yaml model=yolov8n.pt epochs=1 imgsz=32
          yolo task=detect mode=val data=coco8.yaml model=runs/detect/train/weights/last.pt imgsz=32
          yolo task=detect mode=predict model=runs/detect/train/weights/last.pt imgsz=32 source=ultralytics/assets/bus.jpg
          yolo mode=export model=runs/detect/train/weights/last.pt imgsz=32 format=torchscript
      - name: Test segmentation
        shell: bash  # for Windows compatibility
        run: |
          yolo task=segment mode=train data=coco8-seg.yaml model=yolov8n-seg.yaml epochs=1 imgsz=32
          yolo task=segment mode=train data=coco8-seg.yaml model=yolov8n-seg.pt epochs=1 imgsz=32
          yolo task=segment mode=val data=coco8-seg.yaml model=runs/segment/train/weights/last.pt imgsz=32
          yolo task=segment mode=predict model=runs/segment/train/weights/last.pt imgsz=32 source=ultralytics/assets/bus.jpg
          yolo mode=export model=runs/segment/train/weights/last.pt imgsz=32 format=torchscript
      - name: Test classification
        shell: bash  # for Windows compatibility
        run: |
          yolo task=classify mode=train data=imagenet10 model=yolov8n-cls.yaml epochs=1 imgsz=32
          yolo task=classify mode=train data=imagenet10 model=yolov8n-cls.pt epochs=1 imgsz=32
          yolo task=classify mode=val data=imagenet10 model=runs/classify/train/weights/last.pt imgsz=32
          yolo task=classify mode=predict model=runs/classify/train/weights/last.pt imgsz=32 source=ultralytics/assets/bus.jpg
          yolo mode=export model=runs/classify/train/weights/last.pt imgsz=32 format=torchscript
      - name: Pytest tests
        shell: bash  # for Windows compatibility
        run: pytest tests