ci(evaluation): fix script path #26
Workflow file for this run
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| name: Execute algorithm and evaluate metrics | |
| on: | |
| push: | |
| branches: [ "main" ] | |
| paths: | |
| - 'algorithms/*.yaml' | |
| - '.github/workflows/algorithm-evaluation.yml' | |
| pull_request: | |
| branches: [ "main" ] | |
| paths: | |
| - 'algorithms/*.yaml' | |
| - '.github/workflows/algorithm-evaluation.yml' | |
| jobs: | |
| execute: | |
| runs-on: ubuntu-latest | |
| steps: | |
| - name: Find updated algorithm | |
| id: find-algorithm | |
| uses: tj-actions/changed-files@v44 | |
| with: | |
| files: algorithms/**.yaml | |
| - uses: actions/checkout@v4 | |
| - name: Execute algorithm container | |
| if: steps.find-algorithm.outputs.any_changed == 'true' | |
| run: | | |
| # iterate over all datasets in S3 | |
| for recording in $(aws s3api list-objects --bucket ${AWS_BUCKET} --prefix datasets --output text --query 'Contents[].[Key]' | grep '.*edf'); do | |
| # save each recording (dataset slice) to a temp file | |
| aws s3 cp s3://${AWS_BUCKET}/${recording} ./data/tmp.edf | |
| # Run inference on recording for every updated algorithm | |
| for algo in ${{ steps.find-algorithm.outputs.all_changed_files }}; do | |
| IMAGE=$(grep '^image: ' $algo | sed 's/^image: \+//' | tr -d \'\") | |
| ALGO_NAME=$(echo "$IMAGE" | iconv -t ascii//TRANSLIT | sed -r s/[^a-zA-Z0-9]+/-/g | sed -r s/^-+\|-+$//g | tr A-Z a-z) | |
| # Create prediction directory and set permissions for the output file. | |
| mkdir -p ./predictions | |
| touch ./predictions/tmp.tsv | |
| chmod 776 ./predictions/tmp.tsv | |
| echo "Running inference for $ALGO_NAME" | |
| docker run \ | |
| -e INPUT=tmp.edf \ | |
| -e OUTPUT=tmp.tsv \ | |
| -e AWS_BUCKET="${AWS_BUCKET}" \ | |
| -e AWS_REGION="${AWS_DEFAULT_REGION}" \ | |
| -e AWS_ACCESS_KEY="${AWS_ACCESS_KEY}" \ | |
| -e AWS_SECRET_KEY="${AWS_SECRET_KEY}" \ | |
| -v ./predictions:/output:rw \ | |
| -v ./data:/data:ro \ | |
| --network none \ | |
| --name "${ALGO_NAME}" \ | |
| "${IMAGE}" | |
| # Upload predictions to S3 | |
| subpath=${recording#*/} | |
| prediction=${subpath%_eeg.edf}_events.tsv | |
| aws s3 cp \ | |
| ./predictions/tmp.tsv \ | |
| "s3://${AWS_BUCKET}/submissions/${ALGO_NAME}/${prediction}" | |
| # Cleanup | |
| rm ./predictions/tmp.tsv | |
| docker rm "${ALGO_NAME}" | |
| done | |
| # Cleanup | |
| rm ./data/tmp.edf | |
| done | |
| env: | |
| AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY }} | |
| AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_KEY }} | |
| AWS_DEFAULT_REGION: ${{ secrets.AWS_REGION }} | |
| AWS_BUCKET: ${{secrets.AWS_BUCKET }} | |
| evaluate: | |
| runs-on: ubuntu-latest | |
| needs: [execute] | |
| container: | |
| image: ghcr.io/${{ github.repository }}-evaluator:main | |
| credentials: | |
| username: ${{ github.actor }} | |
| password: ${{ secrets.github_token }} | |
| steps: | |
| - name: Evaluate algorithm predictions | |
| run: python /__main__.py |