tensorflow-to-larod-artpec8.yml

name: Build tensorflow-to-larod-artpec8 application
on:
  workflow_dispatch:
  push:
    paths:
      - 'tensorflow-to-larod-artpec8/**'
      - '!tensorflow-to-larod-artpec8/README.md'
      - '.github/workflows/tensorflow-to-larod-artpec8.yml'
jobs:
  build:
    runs-on: ubuntu-latest
    strategy:
      matrix:
        include:
          - arch: aarch64
            chip: artpec8
            axis-os: 11.5.64
    env:
      EXREPO: acap-native-examples
      EXNAME: tensorflow-to-larod-artpec8
    steps:
      - uses: actions/checkout@v4
      - uses: docker/setup-buildx-action@v2

      - name: Build ${{ env.example }} application
        env:
          example: ${{ env.EXNAME }}
          imagetag: ${{ env.EXREPO }}_${{ env.EXNAME }}:1.0
        run: |
          docker image rm -f $imagetag
          cd $EXNAME
          docker build --no-cache --tag $imagetag . --build-arg TRAIN_EPOCHS=1 --build-arg TUNE_EPOCHS=1

      - name: Check if model file exists and its size
        env:
          imagetag: ${{ env.EXREPO }}_${{ env.EXNAME }}:1.0
          buildpath: /env/training/models
          modeldir: model
          modelname: converted_model.tflite
        run: |
          found_error=no
          [ -d $modeldir ] && rm -rf $modeldir
          mkdir -p ./$modeldir
          docker cp $(docker create $imagetag):$buildpath/$modelname ./$modeldir
          if [ -f $modeldir/$modelname ]; then
            echo "Model file exists"
            # Check the file size
            filesize=$(stat --printf="%s" $modeldir/$modelname)
            minsize=$((1*1024*1024)) # 1MB
            maxsize=$((10*1024*1024*1024)) # 10GB
            if [ $filesize -ge $minsize ] && [ $filesize -le $maxsize ]; then
                echo "Model file size ($filesize bytes) is within the expected range"
            else
                echo "Model file size ($filesize bytes) is out of the expected range"
                found_error=yes
            fi
          else
            echo "Model file does not exist, build directory contains"
            ls -la $modeldir
            found_error=yes
          fi

          # Cleanup
          [ -d $modeldir ] && rm -rf $modeldir
          docker image rm -f $imagetag

          [ "$found_error" = no ] || {
            echo "Error found during tests"
            exit 1
          }