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llm-harness-evaluation.yml
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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:
inputs:
model_name:
description: 'Model names, seperated by comma and must be quoted.'
required: true
type: string
precision:
description: 'Precisions, seperated by comma and must be quoted.'
required: true
type: string
task:
description: 'Tasks, seperated by comma and must be quoted.'
required: true
type: string
runs-on:
description: 'Labels to filter the runners, seperated by comma and must be quoted.'
default: "accuracy"
required: false
type: string
# 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
# Set the testing matrix based on the event (schedule, PR, or manual dispatch)
set-matrix:
runs-on: ubuntu-latest
outputs:
model_name: ${{ steps.set-matrix.outputs.model_name }}
precision: ${{ steps.set-matrix.outputs.precision }}
task: ${{ steps.set-matrix.outputs.task }}
runner: ${{ steps.set-matrix.outputs.runner }}
steps:
- name: set-nightly-env
if: ${{github.event_name == 'schedule'}}
env:
NIGHTLY_MATRIX_MODEL_NAME: '["Llama2-7b-guanaco-dolphin-500", "falcon-7b-instruct-with-patch",
"Mistral-7B-v0.1", "mpt-7b-chat", "Baichuan2-7B-Chat-LLaMAfied"]'
NIGHTLY_MATRIX_TASK: '["arc", "truthfulqa", "winogrande"]'
NIGHTLY_MATRIX_PRECISION: '["sym_int4", "fp8"]'
NIGHTLY_LABELS: '["self-hosted", "llm", "accuracy-nightly"]'
run: |
echo "model_name=$NIGHTLY_MATRIX_MODEL_NAME" >> $GITHUB_ENV
echo "precision=$NIGHTLY_MATRIX_PRECISION" >> $GITHUB_ENV
echo "task=$NIGHTLY_MATRIX_TASK" >> $GITHUB_ENV
echo "runner=$NIGHTLY_LABELS" >> $GITHUB_ENV
- name: set-pr-env
if: ${{github.event_name == 'pull_request'}}
env:
PR_MATRIX_MODEL_NAME: '["Llama2-7b-guanaco-dolphin-500"]'
PR_MATRIX_TASK: '["truthfulqa"]'
PR_MATRIX_PRECISION: '["fp8"]'
PR_LABELS: '["self-hosted", "llm", "accuracy2", "accuracy-nightly"]'
run: |
echo "model_name=$PR_MATRIX_MODEL_NAME" >> $GITHUB_ENV
echo "precision=$PR_MATRIX_PRECISION" >> $GITHUB_ENV
echo "task=$PR_MATRIX_TASK" >> $GITHUB_ENV
echo "runner=$PR_LABELS" >> $GITHUB_ENV
- name: set-manual-env
if: ${{github.event_name == 'workflow_dispatch'}}
env:
MANUAL_MATRIX_MODEL_NAME: ${{format('[ {0} ]', inputs.model_name)}}
MANUAL_MATRIX_TASK: ${{format('[ {0} ]', inputs.task)}}
MANUAL_MATRIX_PRECISION: ${{format('[ {0} ]', inputs.precision)}}
MANUAL_LABELS: ${{format('["self-hosted", "llm", {0}]', inputs.runs-on)}}
run: |
echo "model_name=$MANUAL_MATRIX_MODEL_NAME" >> $GITHUB_ENV
echo "precision=$MANUAL_MATRIX_PRECISION" >> $GITHUB_ENV
echo "task=$MANUAL_MATRIX_TASK" >> $GITHUB_ENV
echo "runner=$MANUAL_LABELS" >> $GITHUB_ENV
- name: set-matrix
id: set-matrix
run: |
echo "model_name=$model_name" >> $GITHUB_OUTPUT
echo "precision=$precision" >> $GITHUB_OUTPUT
echo "task=$task" >> $GITHUB_OUTPUT
echo "runner=$runner" >> $GITHUB_OUTPUT
llm-harness-evalution:
timeout-minutes: 1000
needs: [llm-cpp-build, set-matrix]
strategy:
fail-fast: false
matrix:
python-version: ["3.9"]
model_name: ${{ fromJson(needs.set-matrix.outputs.model_name) }}
task: ${{ fromJson(needs.set-matrix.outputs.task) }}
precision: ${{ fromJson(needs.set-matrix.outputs.precision) }}
device: [xpu]
runs-on: ${{ fromJson(needs.set-matrix.outputs.runner) }}
outputs:
output_path: ${{ steps.run_harness.outputs.output_path }}
env:
ANALYTICS_ZOO_ROOT: ${{ github.workspace }}
ORIGIN_DIR: /mnt/disk1/models
HARNESS_HF_HOME: /mnt/disk1/harness_home
steps:
- 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: |
set -e
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_2.1"
- name: Install harness
working-directory: ${{ github.workspace }}/python/llm/dev/benchmark/harness/
shell: bash
run: |
pip install git+https://github.com/EleutherAI/lm-evaluation-harness.git@e81d3cc
- name: Download models and datasets
shell: bash
run: |
echo "MODEL_PATH=${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
fi
wget -r -nH -nc -l inf --no-verbose --cut-dirs=2 ${LLM_FTP_URL}/llm/LeaderBoard_Datasets/ -P $HARNESS_HF_HOME/
wget -r -nH -nc --no-verbose --cut-dirs=1 ${LLM_FTP_URL}/llm/${{ matrix.model_name }} -P ${ORIGIN_DIR}
- name: Upgrade packages
shell: bash
run: |
pip install --upgrade datasets==2.14.6
if [ "${{ matrix.model_name }}" = "Mistral-7B-v0.1" ]; then
pip install --upgrade transformers==4.36
else
pip install --upgrade transformers==4.31
fi
- name: Run harness
shell: bash
working-directory: ${{ github.workspace }}/python/llm/dev/benchmark/harness
env:
USE_XETLA: OFF
# SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS: 1
run: |
export HF_HOME=${HARNESS_HF_HOME}
export HF_DATASETS=$HARNESS_HF_HOME/datasets
export HF_DATASETS_CACHE=$HARNESS_HF_HOME/datasets
source /opt/intel/oneapi/setvars.sh
python run_llb.py \
--model bigdl-llm \
--pretrained ${MODEL_PATH} \
--precision ${{ matrix.precision }} \
--device ${{ matrix.device }} \
--tasks ${{ matrix.task }} \
--batch_size 1 --no_cache --output_path results
- uses: actions/upload-artifact@v3
with:
name: harness_results
path:
${{ github.workspace }}/python/llm/dev/benchmark/harness/results/**
- name: echo single result
shell: bash
working-directory: ${{ github.workspace }}/python/llm/dev/benchmark/harness/results/
run: |
cat ${{ matrix.model_name }}/${{ matrix.device }}/${{ matrix.precision }}/${{ matrix.task }}/result.json
llm-harness-summary:
if: ${{ always() }}
needs: llm-harness-evalution
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python 3.9
uses: actions/setup-python@v4
with:
python-version: 3.9
- name: Install dependencies
shell: bash
run: |
pip install --upgrade pip
pip install jsonlines pytablewriter regex
DATE=$(date +%Y-%m-%d)
OUTPUT_PATH="results_$DATE"
echo "OUTPUT_PATH=$OUTPUT_PATH" >> $GITHUB_ENV
- name: Download all results
uses: actions/download-artifact@v3
with:
name: harness_results
path: ${{ env.OUTPUT_PATH }}
- name: Summarize the results
shell: bash
run: |
echo ${{ env.OUTPUT_PATH }}
ls ${{ env.OUTPUT_PATH }}
python ${{ github.workspace }}/python/llm/dev/benchmark/harness/make_table_results.py ${{ env.OUTPUT_PATH }}