llm-harness-evaluation.yml

name: LLM Harness Evalution

# Cancel previous runs in the PR when you push new commits
concurrency:
  group: ${{ github.workflow }}-llm-nightly-test-${{ github.event.pull_request.number || github.run_id }}
  cancel-in-progress: true

# Controls when the action will run.
on:
  # schedule:
  #   - cron: "00 13 * * *" # GMT time, 13:00 GMT == 21:00 China
  pull_request:
    branches: [main]
    paths:
      - ".github/workflows/llm-harness-evaluation.yml"
  # Allows you to run this workflow manually from the Actions tab
  workflow_dispatch:

# A workflow run is made up of one or more jobs that can run sequentially or in parallel
jobs:
  llm-cpp-build:
    uses: ./.github/workflows/llm-binary-build.yml
  llm-nightly-harness-test:
    needs: llm-cpp-build
    strategy:
      fail-fast: false
      matrix:
        python-version: ["3.9"]
        model_name: [stablelm-3b-4e1t]
        task: ["truthfulqa"]
        precision: ["int4"]
    runs-on: [self-hosted, llm, accuracy, temp-arc01]
    env:
      ANALYTICS_ZOO_ROOT: ${{ github.workspace }}
    steps:
      - name: Set model and dataset directories
        shell: bash
        run: |
          echo "ORIGIN_DIR=/mnt/disk1/models" >> "$GITHUB_ENV"
          echo "HARNESS_HF_HOME=/mnt/disk1/harness_home" >> "$GITHUB_ENV"

      - uses: actions/checkout@v3
      - name: Set up Python ${{ matrix.python-version }}
        uses: actions/setup-python@v4
        with:
          python-version: ${{ matrix.python-version }}
      - name: Install dependencies
        shell: bash
        run: |
          python -m pip install --upgrade pip
          python -m pip install --upgrade setuptools==58.0.4
          python -m pip install --upgrade wheel

      - name: Download llm binary
        uses: ./.github/actions/llm/download-llm-binary

      - name: Run LLM install (all) test
        uses: ./.github/actions/llm/setup-llm-env
        with:
          extra-dependency: "xpu"

      - name: Install harness
        shell: bash
        run: |
          cd python/llm/dev/benchmark/harness/
          git clone https://github.com/EleutherAI/lm-evaluation-harness.git
          cd  lm-evaluation-harness
          git checkout e81d3cc
          pip install -e .
          git apply ../bigdl-llm.patch
          cd ..
      
      
      - name: Download models and datasets
        shell: bash
        run: |
          echo "MODEL_PATH=${ORIGIN_DIR}/${{ matrix.model_name }}/" >> "$GITHUB_ENV"
          MODEL_PATH=${ORIGIN_DIR}/${{ matrix.model_name }}/
          if [ ! -d $HARNESS_HF_HOME ]; then
            mkdir -p $HARNESS_HF_HOME
            wget -r -nH -l inf --no-verbose --cut-dirs=2 ${LLM_FTP_URL}/llm/LeaderBoard_Datasets/ -P $HARNESS_HF_HOME/
          fi
          if [ ! -d $MODEL_PATH ]; then
            wget -r -nH --no-verbose --cut-dirs=1 ${LLM_FTP_URL}/llm/${{ matrix.model_name }} -P ${ORIGIN_DIR}
          fi
          
      - name: Set datasets env
        shell: bash
        run: |
          echo "HF_HOME=$HARNESS_HF_HOME" >> "$GITHUB_ENV"
          echo "HF_DATASETS=$HARNESS_HF_HOME/datasets" >> "$GITHUB_ENV"
          echo "HF_DATASETS_CACHE=$HARNESS_HF_HOME/datasets" >> "$GITHUB_ENV"

      - name: Run harness
        shell: bash
        run: |
          export USE_XETLA=OFF
          source /opt/intel/oneapi/setvars.sh
          cd python/llm/dev/benchmark/harness
          python llb.py --model bigdl-llm --pretrained ${MODEL_PATH} --precision ${{ matrix.precision }} --device xpu --tasks ${{ matrix.task }} --output_dir results/${{ matrix.model_name }} --batch 1