100 lines
3.5 KiB
YAML
100 lines
3.5 KiB
YAML
name: LLM Harness Evalution
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# Cancel previous runs in the PR when you push new commits
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concurrency:
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group: ${{ github.workflow }}-llm-nightly-test-${{ github.event.pull_request.number || github.run_id }}
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cancel-in-progress: true
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# Controls when the action will run.
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on:
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# schedule:
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# - cron: "00 13 * * *" # GMT time, 13:00 GMT == 21:00 China
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pull_request:
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branches: [main]
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paths:
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- ".github/workflows/llm-harness-evaluation.yml"
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# Allows you to run this workflow manually from the Actions tab
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workflow_dispatch:
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# A workflow run is made up of one or more jobs that can run sequentially or in parallel
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jobs:
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llm-cpp-build:
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uses: ./.github/workflows/llm-binary-build.yml
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llm-nightly-harness-test:
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needs: llm-cpp-build
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strategy:
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fail-fast: false
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matrix:
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python-version: ["3.9"]
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model_name: [stablelm-3b-4e1t]
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task: ["truthfulqa"]
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precision: ["int4"]
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runs-on: [self-hosted, llm, accuracy, temp-arc01]
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env:
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ANALYTICS_ZOO_ROOT: ${{ github.workspace }}
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steps:
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- name: Set model and dataset directories
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shell: bash
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run: |
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echo "ORIGIN_DIR=/mnt/disk1/models" >> "$GITHUB_ENV"
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echo "HARNESS_HF_HOME=/mnt/disk1/harness_home" >> "$GITHUB_ENV"
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- uses: actions/checkout@v3
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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- name: Install dependencies
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shell: bash
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run: |
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python -m pip install --upgrade pip
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python -m pip install --upgrade setuptools==58.0.4
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python -m pip install --upgrade wheel
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- name: Download llm binary
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uses: ./.github/actions/llm/download-llm-binary
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- name: Run LLM install (all) test
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uses: ./.github/actions/llm/setup-llm-env
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with:
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extra-dependency: "xpu"
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- name: Install harness
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shell: bash
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run: |
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cd python/llm/dev/benchmark/harness/
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git clone https://github.com/EleutherAI/lm-evaluation-harness.git
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cd lm-evaluation-harness
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git checkout e81d3cc
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pip install -e .
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git apply ../bigdl-llm.patch
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cd ..
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- name: Download models and datasets
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shell: bash
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run: |
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echo "MODEL_PATH=${ORIGIN_DIR}/${{ matrix.model_name }}/" >> "$GITHUB_ENV"
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MODEL_PATH=${ORIGIN_DIR}/${{ matrix.model_name }}/
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if [ ! -d $HARNESS_HF_HOME ]; then
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mkdir -p $HARNESS_HF_HOME
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wget -r -nH -l inf --no-verbose --cut-dirs=2 ${LLM_FTP_URL}/llm/LeaderBoard_Datasets/ -P $HARNESS_HF_HOME/
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fi
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if [ ! -d $MODEL_PATH ]; then
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wget -r -nH --no-verbose --cut-dirs=1 ${LLM_FTP_URL}/llm/${{ matrix.model_name }} -P ${ORIGIN_DIR}
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fi
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- name: Set datasets env
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shell: bash
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run: |
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echo "HF_HOME=$HARNESS_HF_HOME" >> "$GITHUB_ENV"
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echo "HF_DATASETS=$HARNESS_HF_HOME/datasets" >> "$GITHUB_ENV"
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echo "HF_DATASETS_CACHE=$HARNESS_HF_HOME/datasets" >> "$GITHUB_ENV"
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- name: Run harness
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shell: bash
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run: |
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export USE_XETLA=OFF
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source /opt/intel/oneapi/setvars.sh
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cd python/llm/dev/benchmark/harness
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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
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