[CI]Update accuracy report test (#1288)
### What this PR does / why we need it? Update accuracy report test 1. Add Record commit hashes and GitHub links for both vllm and vllm-ascend in accuracy reports 2. Add accuracy result verification checks to ensure output correctness 3. Creat PR via forked repository workflow ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? dense-accuracy-test: https://github.com/vllm-project/vllm-ascend/actions/runs/15745619485 create pr via forked repository workflow: https://github.com/zhangxinyuehfad/vllm-ascend/actions/runs/15747013719/job/44385134080 accuracy report pr: https://github.com/vllm-project/vllm-ascend/pull/1292 Currently, the accuracy report used is old and needs to be merged into pr, retest, update new report, then close #1292 . Signed-off-by: hfadzxy <starmoon_zhang@163.com>
This commit is contained in:
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.github/workflows/accuracy_report.yaml
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202
.github/workflows/accuracy_report.yaml
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#
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# This file is a part of the vllm-ascend project.
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#
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name: Accuracy Report
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on:
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workflow_dispatch:
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inputs:
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vllm-ascend-branch:
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description: 'vllm-ascend branch:'
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required: true
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type: choice
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options:
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- main
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- v0.7.3-dev
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models:
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description: 'models:'
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required: true
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type: choice
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options:
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- all
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- Qwen/Qwen2.5-7B-Instruct
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- Qwen/Qwen2.5-VL-7B-Instruct
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- Qwen/Qwen3-8B-Base
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default: 'all'
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jobs:
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download_reports:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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model: ${{ fromJSON(
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(github.event.inputs.models == 'all' &&
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'["Qwen/Qwen2.5-7B-Instruct","Qwen/Qwen2.5-VL-7B-Instruct","Qwen/Qwen3-8B-Base"]') ||
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(github.event.inputs.models == 'Qwen/Qwen2.5-7B-Instruct' &&
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'["Qwen/Qwen2.5-7B-Instruct"]') ||
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(github.event.inputs.models == 'Qwen/Qwen2.5-VL-7B-Instruct' &&
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'["Qwen/Qwen2.5-VL-7B-Instruct"]') ||
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(github.event.inputs.models == 'Qwen/Qwen3-8B-Base' &&
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'["Qwen/Qwen3-8B-Base"]')
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) }}
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version: [0, 1]
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exclude:
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- model: 'Qwen/Qwen2.5-VL-7B-Instruct'
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version: 1
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fail-fast: false
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name: Download ${{ matrix.model }} V${{ matrix.version }}
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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with:
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ref: ${{ github.event.inputs.vllm-ascend-branch }}
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- name: Get base model name
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id: get_basename
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run: |
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model_base_name=$(basename "${{ matrix.model }}")
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echo "model_base_name=$model_base_name" >> $GITHUB_OUTPUT
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shell: bash
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- name: Query artifact run id
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id: get_run_id
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run: |
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ARTIFACT_PATTERN="${{ github.event.inputs.vllm-ascend-branch }}-${{ steps.get_basename.outputs.model_base_name }}-V${{ matrix.version }}-report"
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echo "Querying artifacts with pattern: $ARTIFACT_PATTERN"
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ARTIFACT_JSON=$(gh api --paginate /repos/${{ github.repository }}/actions/artifacts || echo "{}")
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RUN_ID=$(echo "$ARTIFACT_JSON" | \
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jq -s -r --arg pattern "$ARTIFACT_PATTERN" \
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'[.[].artifacts[]] | map(select(.name | test($pattern))) | sort_by(.created_at) | last | .workflow_run.id // empty')
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if [ -z "$RUN_ID" ]; then
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echo "::warning::No artifact found matching pattern $ARTIFACT_PATTERN. Skipping download."
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echo "runid=" >> $GITHUB_OUTPUT
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else
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echo "Found matching artifact with run ID: $RUN_ID"
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echo "runid=$RUN_ID" >> $GITHUB_OUTPUT
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fi
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env:
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GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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- name: Download Artifact
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if: ${{ steps.get_run_id.outputs.runid != '' }}
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uses: actions/download-artifact@v4
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with:
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name: ${{ github.event.inputs.vllm-ascend-branch }}-${{ steps.get_basename.outputs.model_base_name }}-V${{ matrix.version }}-report
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path: ./docs/source/developer_guide/evaluation/accuracy_report_bak
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github-token: ${{ secrets.GITHUB_TOKEN }}
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repository: ${{ github.repository }}
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run-id: ${{ steps.get_run_id.outputs.runid }}
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- name: Upload reports artifact
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if: ${{ steps.get_run_id.outputs.runid != '' }}
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uses: actions/upload-artifact@v4
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with:
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name: report-${{ steps.get_basename.outputs.model_base_name }}-v${{ matrix.version }}
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path: ./docs/source/developer_guide/evaluation/accuracy_report_bak/*.md
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retention-days: 90
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create_pr:
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runs-on: ubuntu-latest
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needs: download_reports
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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with:
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ref: ${{ github.event.inputs.vllm-ascend-branch }}
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- name: Setup workspace
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run: mkdir -p ./accuracy/accuracy_report
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- name: Download only current run reports
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uses: actions/download-artifact@v4
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with:
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path: ./docs/source/developer_guide/evaluation/accuracy_report
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pattern: report-*
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github-token: ${{ secrets.GITHUB_TOKEN }}
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run-id: ${{ github.run_id }}
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- name: Delete old report
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run: |
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find ./docs/source/developer_guide/evaluation/accuracy_report -maxdepth 1 -type f -name '*.md' ! -name 'index.md' -delete
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find ./docs/source/developer_guide/evaluation/accuracy_report -mindepth 2 -type f -name '*.md' -exec mv -f {} ./docs/source/developer_guide/evaluation/accuracy_report \;
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find ./docs/source/developer_guide/evaluation/accuracy_report -mindepth 1 -type d -empty -delete
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- name: Generate step summary
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if: ${{ always() }}
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run: |
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for report in ./docs/source/developer_guide/evaluation/accuracy_report/*.md; do
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filename=$(basename "$report")
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# skip index.md
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if [ "$filename" = "index.md" ]; then
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continue
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fi
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if [ -f "$report" ]; then
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{
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echo -e "\n\n---\n"
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echo "## 📄 Report File: $(basename $report)"
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cat "$report"
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} >> "$GITHUB_STEP_SUMMARY"
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fi
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done
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- name: Update accuracy_report/index.md
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run: |
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REPORT_DIR="./docs/source/developer_guide/evaluation/accuracy_report"
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INDEX_MD="$REPORT_DIR/index.md"
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{
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echo "# Accuracy Report"
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echo ""
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echo "::: {toctree}"
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echo ":caption: Accuracy Report"
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echo ":maxdepth: 1"
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for report in "$REPORT_DIR"/*.md; do
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filename="$(basename "$report" .md)"
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if [ "$filename" != "index" ]; then
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echo "$filename"
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fi
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done
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echo ":::"
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} > "$INDEX_MD"
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- name: Create Pull Request
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uses: peter-evans/create-pull-request@v7
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with:
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token: ${{ secrets.PR_TOKEN }}
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base: ${{ github.event.inputs.vllm-ascend-branch }}
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branch: auto-pr/accuracy-report
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commit-message: "Update accuracy reports for ${{ github.event.inputs.vllm-ascend-branch }}"
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add-paths: ./docs/source/developer_guide/evaluation/accuracy_report/*.md
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title: "[Doc] Update accuracy reports for ${{ github.event.inputs.vllm-ascend-branch }}"
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body: |
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The accuracy results running on NPU Altlas A2 have changed, updating reports for:
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${{
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github.event.inputs.models == 'all'
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&& 'All models (Qwen2.5-7B-Instruct, Qwen2.5-VL-7B-Instruct, Qwen3-8B-Base)'
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|| github.event.inputs.models
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}}
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- [Workflow run][1]
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[1]: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
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146
.github/workflows/accuracy_test.yaml
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146
.github/workflows/accuracy_test.yaml
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@@ -45,8 +45,8 @@ on:
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type: choice
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type: choice
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options:
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options:
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- main
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- main
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- v0.7.3-dev
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- v0.9.1-dev
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- v0.9.1-dev
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- v0.7.3-dev
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models:
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models:
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description: 'model:'
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description: 'model:'
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required: true
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required: true
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@@ -183,7 +183,28 @@ jobs:
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PIP_EXTRA_INDEX_URL: https://mirrors.huaweicloud.com/ascend/repos/pypi
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PIP_EXTRA_INDEX_URL: https://mirrors.huaweicloud.com/ascend/repos/pypi
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run: |
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run: |
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pip install -r requirements-dev.txt
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pip install -r requirements-dev.txt
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pip install -e .
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pip install -v -e .
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- name: Get vLLM commit hash and URL
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working-directory: ./vllm-empty
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run: |
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VLLM_COMMIT=$(git rev-parse HEAD)
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echo "VLLM_COMMIT=$VLLM_COMMIT" >> $GITHUB_ENV
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echo "VLLM_COMMIT_URL=https://github.com/vllm-project/vllm/commit/$VLLM_COMMIT" >> $GITHUB_ENV
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- name: Get vLLM-Ascend commit hash and URL
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working-directory: ./vllm-ascend
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run: |
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VLLM_ASCEND_COMMIT=$(git rev-parse HEAD)
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echo "VLLM_ASCEND_COMMIT=$VLLM_ASCEND_COMMIT" >> $GITHUB_ENV
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echo "VLLM_ASCEND_COMMIT_URL=https://github.com/vllm-project/vllm-ascend/commit/$VLLM_ASCEND_COMMIT" >> $GITHUB_ENV
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- name: Print resolved hashes and URLs
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run: |
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echo "vLLM : ${{ env.VLLM_COMMIT }}"
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echo "vLLM link : ${{ env.VLLM_COMMIT_URL }}"
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echo "vLLM-Ascend: ${{ env.VLLM_ASCEND_COMMIT }}"
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echo "Ascend link: ${{ env.VLLM_ASCEND_COMMIT_URL }}"
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- name: Install lm-eval, ray, and datasets
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- name: Install lm-eval, ray, and datasets
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run: |
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run: |
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@@ -239,7 +260,12 @@ jobs:
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--cann_version "${{ env.GHA_CANN_VERSION }}" \
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--cann_version "${{ env.GHA_CANN_VERSION }}" \
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--torch_npu_version "${{ env.GHA_TORCH_NPU_VERSION }}" \
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--torch_npu_version "${{ env.GHA_TORCH_NPU_VERSION }}" \
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--torch_version "${{ env.GHA_TORCH_VERSION }}" \
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--torch_version "${{ env.GHA_TORCH_VERSION }}" \
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--vllm_version "${{ env.GHA_VLLM_VERSION }}"
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--vllm_version "${{ env.GHA_VLLM_VERSION }}" \
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--vllm_commit "${{ env.VLLM_COMMIT }}" \
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--vllm_ascend_commit "${{ env.VLLM_ASCEND_COMMIT }}" \
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--vllm_commit_url "${{ env.VLLM_COMMIT_URL }}" \
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--vllm_ascend_commit_url "${{ env.VLLM_ASCEND_COMMIT_URL }}" \
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--vllm_use_v1 "$VLLM_USE_V1"
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- name: Generate step summary
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- name: Generate step summary
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if: ${{ always() }}
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if: ${{ always() }}
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@@ -251,12 +277,122 @@ jobs:
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SAFE_VLLM_ASCEND_VERSION="${GHA_VLLM_ASCEND_VERSION//\//-}"
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SAFE_VLLM_ASCEND_VERSION="${GHA_VLLM_ASCEND_VERSION//\//-}"
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echo "SAFE_VLLM_ASCEND_VERSION=$SAFE_VLLM_ASCEND_VERSION" >> "$GITHUB_ENV"
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echo "SAFE_VLLM_ASCEND_VERSION=$SAFE_VLLM_ASCEND_VERSION" >> "$GITHUB_ENV"
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- name: Check report first line for failure
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id: check_report
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run: |
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REPORT_PATH="./benchmarks/accuracy/${{ steps.report.outputs.markdown_name }}.md"
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echo "Scanning $REPORT_PATH for ❌ …"
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if grep -q '❌' "$REPORT_PATH"; then
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echo "contains_fail=true" >> $GITHUB_OUTPUT
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else
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echo "contains_fail=false" >> $GITHUB_OUTPUT
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fi
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- name: Upload Report for V${{ matrix.vllm_use_version }}
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- name: Upload Report for V${{ matrix.vllm_use_version }}
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if: ${{ github.event_name == 'workflow_dispatch' }}
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if: ${{ github.event_name == 'workflow_dispatch' && steps.check_report.outputs.contains_fail == 'false' }}
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uses: actions/upload-artifact@v4
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uses: actions/upload-artifact@v4
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with:
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with:
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name: "${{ env.SAFE_VLLM_ASCEND_VERSION }}-${{ steps.report.outputs.markdown_name }}-report"
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name: "report-${{ env.SAFE_VLLM_ASCEND_VERSION }}-${{ steps.report.outputs.markdown_name }}"
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path: ./benchmarks/accuracy/${{ steps.report.outputs.markdown_name }}.md
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path: ./benchmarks/accuracy/${{ steps.report.outputs.markdown_name }}.md
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if-no-files-found: warn
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if-no-files-found: warn
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retention-days: 90
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retention-days: 90
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overwrite: true
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overwrite: true
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create_pr:
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runs-on: ubuntu-latest
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needs: accuracy_tests
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||||||
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if: ${{ github.event_name == 'workflow_dispatch' }}
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env:
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UPSTREAM_REPO: vllm-project/vllm-ascend
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steps:
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- name: Checkout repository
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||||||
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uses: actions/checkout@v4
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||||||
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with:
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||||||
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repository: vllm-ascend-ci/vllm-ascend
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||||||
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token: ${{ secrets.PAT_TOKEN }}
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ref: main
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- name: Add upstream remote
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run: |
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git remote add upstream https://github.com/${{ env.UPSTREAM_REPO }}.git
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git fetch upstream
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git remote -v
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- name: Set Git user info dynamically
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||||||
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run: |
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git config user.name "${{ github.actor }}"
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||||||
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git config user.email "${{ github.actor }}@users.noreply.github.com"
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||||||
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- name: Create or switch to branch
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||||||
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run: |
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||||||
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TIMESTAMP=$(date +%Y%m%d%H%M%S)
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||||||
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BRANCH_NAME="auto-pr/accuracy-report-${TIMESTAMP}"
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echo "BRANCH_NAME=${BRANCH_NAME}" >> $GITHUB_ENV
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git checkout -B "${BRANCH_NAME}" upstream/${{ github.event.inputs.vllm-ascend-version }}
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||||||
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||||||
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- name: Download only current run reports
|
||||||
|
uses: actions/download-artifact@v4
|
||||||
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with:
|
||||||
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path: ./docs/source/developer_guide/evaluation/accuracy_report
|
||||||
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pattern: report-*
|
||||||
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github-token: ${{ secrets.GITHUB_TOKEN }}
|
||||||
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run-id: ${{ github.run_id }}
|
||||||
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||||||
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- name: Delete old report
|
||||||
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run: |
|
||||||
|
find ./docs/source/developer_guide/evaluation/accuracy_report -maxdepth 1 -type f -name '*.md' ! -name 'index.md' -delete
|
||||||
|
find ./docs/source/developer_guide/evaluation/accuracy_report -mindepth 2 -type f -name '*.md' -exec mv -f {} ./docs/source/developer_guide/evaluation/accuracy_report \;
|
||||||
|
find ./docs/source/developer_guide/evaluation/accuracy_report -mindepth 1 -type d -empty -delete
|
||||||
|
|
||||||
|
- name: Update accuracy_report/index.md
|
||||||
|
run: |
|
||||||
|
REPORT_DIR="./docs/source/developer_guide/evaluation/accuracy_report"
|
||||||
|
INDEX_MD="$REPORT_DIR/index.md"
|
||||||
|
{
|
||||||
|
echo "# Accuracy Report"
|
||||||
|
echo ""
|
||||||
|
echo ":::{toctree}"
|
||||||
|
echo ":caption: Accuracy Report"
|
||||||
|
echo ":maxdepth: 1"
|
||||||
|
|
||||||
|
for report in "$REPORT_DIR"/*.md; do
|
||||||
|
filename="$(basename "$report" .md)"
|
||||||
|
if [ "$filename" != "index" ]; then
|
||||||
|
echo "$filename"
|
||||||
|
fi
|
||||||
|
done
|
||||||
|
echo ":::"
|
||||||
|
} > "$INDEX_MD"
|
||||||
|
|
||||||
|
- name: push accuracy report
|
||||||
|
env:
|
||||||
|
GITHUB_TOKEN: ${{ secrets.PAT_TOKEN }}
|
||||||
|
run: |
|
||||||
|
git add ./docs/source/developer_guide/evaluation/accuracy_report/*.md
|
||||||
|
git commit -s -m "[Doc] Update accuracy reports for ${{ github.event.inputs.vllm-ascend-version }}"
|
||||||
|
git push -f origin "${{ env.BRANCH_NAME }}"
|
||||||
|
|
||||||
|
- name: Create PR in upstream via API
|
||||||
|
uses: actions/github-script@v6
|
||||||
|
with:
|
||||||
|
github-token: ${{ secrets.PAT_TOKEN }}
|
||||||
|
script: |
|
||||||
|
const pr = await github.rest.pulls.create({
|
||||||
|
owner: 'vllm-project',
|
||||||
|
repo: 'vllm-ascend',
|
||||||
|
head: `${{ github.actor }}:${{ env.BRANCH_NAME }}`,
|
||||||
|
base: '${{ github.event.inputs.vllm-ascend-version }}',
|
||||||
|
title: `[Doc] Update accuracy reports for ${{ github.event.inputs.vllm-ascend-version }}`,
|
||||||
|
body: `The accuracy results running on NPU Altlas A2 have changed, updating reports for:
|
||||||
|
${{
|
||||||
|
github.event.inputs.models == 'all'
|
||||||
|
&& 'All models (Qwen2.5-7B-Instruct, Qwen2.5-VL-7B-Instruct, Qwen3-8B-Base)'
|
||||||
|
|| github.event.inputs.models
|
||||||
|
}}
|
||||||
|
|
||||||
|
- [Workflow run][1]
|
||||||
|
|
||||||
|
[1]: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}`
|
||||||
|
});
|
||||||
|
core.info(`Created PR #${pr.data.number}`);
|
||||||
|
|
||||||
@@ -31,24 +31,44 @@ UNIMODAL_TASK = ["ceval-valid", "gsm8k"]
|
|||||||
MULTIMODAL_NAME = ["Qwen/Qwen2.5-VL-7B-Instruct"]
|
MULTIMODAL_NAME = ["Qwen/Qwen2.5-VL-7B-Instruct"]
|
||||||
MULTIMODAL_TASK = ["mmmu_val"]
|
MULTIMODAL_TASK = ["mmmu_val"]
|
||||||
|
|
||||||
batch_size_dict = {"ceval-valid": 1, "mmlu": 1, "gsm8k": "auto", "mmmu_val": 1}
|
BATCH_SIZE = {"ceval-valid": 1, "mmlu": 1, "gsm8k": "auto", "mmmu_val": 1}
|
||||||
|
|
||||||
MODEL_RUN_INFO = {
|
MODEL_RUN_INFO = {
|
||||||
"Qwen/Qwen2.5-7B-Instruct":
|
"Qwen/Qwen2.5-7B-Instruct":
|
||||||
("export MODEL_ARGS='pretrained={model}, max_model_len=4096,dtype=auto,tensor_parallel_size=2,gpu_memory_utilization=0.6'\n"
|
("export MODEL_ARGS='pretrained={model},max_model_len=4096,dtype=auto,tensor_parallel_size=2,gpu_memory_utilization=0.6'\n"
|
||||||
"lm_eval --model vllm --model_args $MODEL_ARGS --tasks {datasets} \ \n"
|
"lm_eval --model vllm --model_args $MODEL_ARGS --tasks {datasets} \ \n"
|
||||||
"--apply_chat_template --fewshot_as_multiturn --num_fewshot 5 --batch_size 1"
|
"--apply_chat_template --fewshot_as_multiturn --num_fewshot 5 --batch_size 1"
|
||||||
),
|
),
|
||||||
"Qwen/Qwen3-8B-Base":
|
"Qwen/Qwen3-8B-Base":
|
||||||
("export MODEL_ARGS='pretrained={model}, max_model_len=4096,dtype=auto,tensor_parallel_size=2,gpu_memory_utilization=0.6'\n"
|
("export MODEL_ARGS='pretrained={model},max_model_len=4096,dtype=auto,tensor_parallel_size=2,gpu_memory_utilization=0.6'\n"
|
||||||
"lm_eval --model vllm --model_args $MODEL_ARGS --tasks {datasets} \ \n"
|
"lm_eval --model vllm --model_args $MODEL_ARGS --tasks {datasets} \ \n"
|
||||||
"--apply_chat_template --fewshot_as_multiturn --num_fewshot 5 --batch_size 1"
|
"--apply_chat_template --fewshot_as_multiturn --num_fewshot 5 --batch_size 1"
|
||||||
),
|
),
|
||||||
"Qwen/Qwen2.5-VL-7B-Instruct":
|
"Qwen/Qwen2.5-VL-7B-Instruct":
|
||||||
("export MODEL_ARGS='pretrained={model}, max_model_len=8192,dtype=auto,tensor_parallel_size=4,max_images=2'\n"
|
("export MODEL_ARGS='pretrained={model},max_model_len=8192,dtype=auto,tensor_parallel_size=4,max_images=2'\n"
|
||||||
"lm_eval --model vllm-vlm --model_args $MODEL_ARGS --tasks {datasets} \ \n"
|
"lm_eval --model vllm-vlm --model_args $MODEL_ARGS --tasks {datasets} \ \n"
|
||||||
"--apply_chat_template --fewshot_as_multiturn --batch_size 1"),
|
"--apply_chat_template --fewshot_as_multiturn --batch_size 1"),
|
||||||
}
|
}
|
||||||
|
FILTER = {
|
||||||
|
"gsm8k": "exact_match,flexible-extract",
|
||||||
|
"ceval-valid": "acc,none",
|
||||||
|
"mmmu_val": "acc,none"
|
||||||
|
}
|
||||||
|
EXPECTED_VALUE = {
|
||||||
|
"Qwen/Qwen2.5-7B-Instruct": {
|
||||||
|
"ceval-valid": 0.80,
|
||||||
|
"gsm8k": 0.72
|
||||||
|
},
|
||||||
|
"Qwen/Qwen3-8B-Base": {
|
||||||
|
"ceval-valid": 0.82,
|
||||||
|
"gsm8k": 0.83
|
||||||
|
},
|
||||||
|
"Qwen/Qwen2.5-VL-7B-Instruct": {
|
||||||
|
"mmmu_val": 0.51
|
||||||
|
}
|
||||||
|
}
|
||||||
|
RTOL = 0.03
|
||||||
|
ACCURACY_FLAG = {}
|
||||||
|
|
||||||
|
|
||||||
def run_accuracy_unimodal(queue, model, dataset):
|
def run_accuracy_unimodal(queue, model, dataset):
|
||||||
@@ -60,7 +80,7 @@ def run_accuracy_unimodal(queue, model, dataset):
|
|||||||
tasks=dataset,
|
tasks=dataset,
|
||||||
apply_chat_template=True,
|
apply_chat_template=True,
|
||||||
fewshot_as_multiturn=True,
|
fewshot_as_multiturn=True,
|
||||||
batch_size=batch_size_dict[dataset],
|
batch_size=BATCH_SIZE[dataset],
|
||||||
num_fewshot=5,
|
num_fewshot=5,
|
||||||
)
|
)
|
||||||
print(f"Success: {model} on {dataset}")
|
print(f"Success: {model} on {dataset}")
|
||||||
@@ -84,7 +104,7 @@ def run_accuracy_multimodal(queue, model, dataset):
|
|||||||
tasks=dataset,
|
tasks=dataset,
|
||||||
apply_chat_template=True,
|
apply_chat_template=True,
|
||||||
fewshot_as_multiturn=True,
|
fewshot_as_multiturn=True,
|
||||||
batch_size=batch_size_dict[dataset],
|
batch_size=BATCH_SIZE[dataset],
|
||||||
)
|
)
|
||||||
print(f"Success: {model} on {dataset}")
|
print(f"Success: {model} on {dataset}")
|
||||||
measured_value = results["results"]
|
measured_value = results["results"]
|
||||||
@@ -102,25 +122,22 @@ def generate_md(model_name, tasks_list, args, datasets):
|
|||||||
run_cmd = MODEL_RUN_INFO[model_name].format(model=model_name,
|
run_cmd = MODEL_RUN_INFO[model_name].format(model=model_name,
|
||||||
datasets=datasets)
|
datasets=datasets)
|
||||||
model = model_name.split("/")[1]
|
model = model_name.split("/")[1]
|
||||||
preamble = f"""# 🎯 {model} Accuracy Test
|
version_info = (
|
||||||
<div>
|
f"**vLLM Version**: vLLM: {args.vllm_version} "
|
||||||
<strong>vLLM version:</strong> vLLM: {args.vllm_version}, vLLM Ascend: {args.vllm_ascend_version} <br>
|
f"([{args.vllm_commit}]({args.vllm_commit_url})), "
|
||||||
</div>
|
f"**vLLM Ascend**: {args.vllm_ascend_version} "
|
||||||
<div>
|
f"([{args.vllm_ascend_commit}]({args.vllm_ascend_commit_url}))")
|
||||||
<strong>Software Environment:</strong> CANN: {args.cann_version}, PyTorch: {args.torch_version}, torch-npu: {args.torch_npu_version} <br>
|
|
||||||
</div>
|
|
||||||
<div>
|
|
||||||
<strong>Hardware Environment</strong>: Atlas A2 Series <br>
|
|
||||||
</div>
|
|
||||||
<div>
|
|
||||||
<strong>Datasets</strong>: {datasets} <br>
|
|
||||||
</div>
|
|
||||||
<div>
|
|
||||||
<strong>Command</strong>:
|
|
||||||
|
|
||||||
```bash
|
preamble = f"""# 🎯 {model}
|
||||||
{run_cmd}
|
{version_info}
|
||||||
```
|
**vLLM Engine**: V{args.vllm_use_v1}
|
||||||
|
**Software Environment**: CANN: {args.cann_version}, PyTorch: {args.torch_version}, torch-npu: {args.torch_npu_version}
|
||||||
|
**Hardware Environment**: Atlas A2 Series
|
||||||
|
**Datasets**: {datasets}
|
||||||
|
**Command**:
|
||||||
|
```bash
|
||||||
|
{run_cmd}
|
||||||
|
```
|
||||||
</div>
|
</div>
|
||||||
<div> </div>
|
<div> </div>
|
||||||
"""
|
"""
|
||||||
@@ -153,11 +170,12 @@ def generate_md(model_name, tasks_list, args, datasets):
|
|||||||
n_shot = "5"
|
n_shot = "5"
|
||||||
else:
|
else:
|
||||||
n_shot = "0"
|
n_shot = "0"
|
||||||
|
flag = ACCURACY_FLAG.get(task_name, "")
|
||||||
row = (f"| {task_name:<37} "
|
row = (f"| {task_name:<37} "
|
||||||
f"| {flt:<6} "
|
f"| {flt:<6} "
|
||||||
f"| {n_shot:6} "
|
f"| {n_shot:6} "
|
||||||
f"| {metric:<6} "
|
f"| {metric:<6} "
|
||||||
f"| ↑ {value:>5.4f} "
|
f"| {flag}{value:>5.4f} "
|
||||||
f"| ± {stderr:>5.4f} |")
|
f"| ± {stderr:>5.4f} |")
|
||||||
if not task_name.startswith("-"):
|
if not task_name.startswith("-"):
|
||||||
rows.append(row)
|
rows.append(row)
|
||||||
@@ -187,6 +205,7 @@ def main(args):
|
|||||||
if args.model in UNIMODAL_MODEL_NAME:
|
if args.model in UNIMODAL_MODEL_NAME:
|
||||||
datasets = ",".join(UNIMODAL_TASK)
|
datasets = ",".join(UNIMODAL_TASK)
|
||||||
for dataset in UNIMODAL_TASK:
|
for dataset in UNIMODAL_TASK:
|
||||||
|
accuracy_expected = EXPECTED_VALUE[args.model][dataset]
|
||||||
p = multiprocessing.Process(target=run_accuracy_unimodal,
|
p = multiprocessing.Process(target=run_accuracy_unimodal,
|
||||||
args=(result_queue, args.model,
|
args=(result_queue, args.model,
|
||||||
dataset))
|
dataset))
|
||||||
@@ -194,10 +213,16 @@ def main(args):
|
|||||||
p.join()
|
p.join()
|
||||||
result = result_queue.get()
|
result = result_queue.get()
|
||||||
print(result)
|
print(result)
|
||||||
|
if accuracy_expected - RTOL < result[dataset][
|
||||||
|
FILTER[dataset]] < accuracy_expected + RTOL:
|
||||||
|
ACCURACY_FLAG[dataset] = "✅"
|
||||||
|
else:
|
||||||
|
ACCURACY_FLAG[dataset] = "❌"
|
||||||
accuracy[args.model].append(result)
|
accuracy[args.model].append(result)
|
||||||
if args.model in MULTIMODAL_NAME:
|
if args.model in MULTIMODAL_NAME:
|
||||||
datasets = ",".join(MULTIMODAL_TASK)
|
datasets = ",".join(MULTIMODAL_TASK)
|
||||||
for dataset in MULTIMODAL_TASK:
|
for dataset in MULTIMODAL_TASK:
|
||||||
|
accuracy_expected = EXPECTED_VALUE[args.model][dataset]
|
||||||
p = multiprocessing.Process(target=run_accuracy_multimodal,
|
p = multiprocessing.Process(target=run_accuracy_multimodal,
|
||||||
args=(result_queue, args.model,
|
args=(result_queue, args.model,
|
||||||
dataset))
|
dataset))
|
||||||
@@ -205,12 +230,18 @@ def main(args):
|
|||||||
p.join()
|
p.join()
|
||||||
result = result_queue.get()
|
result = result_queue.get()
|
||||||
print(result)
|
print(result)
|
||||||
|
if accuracy_expected - RTOL < result[dataset][
|
||||||
|
FILTER[dataset]] < accuracy_expected + RTOL:
|
||||||
|
ACCURACY_FLAG[dataset] = "✅"
|
||||||
|
else:
|
||||||
|
ACCURACY_FLAG[dataset] = "❌"
|
||||||
accuracy[args.model].append(result)
|
accuracy[args.model].append(result)
|
||||||
print(accuracy)
|
print(accuracy)
|
||||||
safe_md(args, accuracy, datasets)
|
safe_md(args, accuracy, datasets)
|
||||||
|
|
||||||
|
|
||||||
if __name__ == "__main__":
|
if __name__ == "__main__":
|
||||||
|
multiprocessing.set_start_method('spawn', force=True)
|
||||||
parser = argparse.ArgumentParser()
|
parser = argparse.ArgumentParser()
|
||||||
parser.add_argument("--output", type=str, required=True)
|
parser.add_argument("--output", type=str, required=True)
|
||||||
parser.add_argument("--model", type=str, required=True)
|
parser.add_argument("--model", type=str, required=True)
|
||||||
@@ -219,8 +250,12 @@ if __name__ == "__main__":
|
|||||||
parser.add_argument("--torch_npu_version", type=str, required=False)
|
parser.add_argument("--torch_npu_version", type=str, required=False)
|
||||||
parser.add_argument("--vllm_version", type=str, required=False)
|
parser.add_argument("--vllm_version", type=str, required=False)
|
||||||
parser.add_argument("--cann_version", type=str, required=False)
|
parser.add_argument("--cann_version", type=str, required=False)
|
||||||
|
parser.add_argument("--vllm_commit", type=lambda s: s[:7], required=False)
|
||||||
|
parser.add_argument("--vllm_commit_url", type=str, required=False)
|
||||||
|
parser.add_argument("--vllm_ascend_commit",
|
||||||
|
type=lambda s: s[:7],
|
||||||
|
required=False)
|
||||||
|
parser.add_argument("--vllm_ascend_commit_url", type=str, required=False)
|
||||||
|
parser.add_argument("--vllm_use_v1", type=str, required=False)
|
||||||
args = parser.parse_args()
|
args = parser.parse_args()
|
||||||
# TODO(yikun):
|
|
||||||
# 1. add a exit 1 if accuracy is not as expected
|
|
||||||
# 2. Add ✅, ❌ to markdown if accuracy is not as expected
|
|
||||||
main(args)
|
main(args)
|
||||||
|
|||||||
Reference in New Issue
Block a user