name: Nightly Test (NPU)

on:
  schedule:
    - cron: '0 18 * * *'  # Execute at 2:00 a.m. Beijing Time every day
  pull_request:
    branches:
      - main
    paths:
      - ".github/workflows/nightly-test-npu.yml"
  workflow_dispatch:
  workflow_call:
    inputs:
      ref:
        description: 'Git ref (branch, tag, or SHA) to test. If not provided, uses the default branch.'
        required: false
        type: string
        default: ''
      job_filter:
        description: 'Select which job to run (leave empty or "all" to run all jobs)'
        required: false
        type: string
        default: 'all'
      image_a3:
        description: 'The a3 running docker image of the test task.'
        required: false
        type: string
        default: 'swr.cn-southwest-2.myhuaweicloud.com/base_image/ascend-ci/cann:8.5.0-a3-ubuntu22.04-py3.11'
      skip_install_flag:
        description: 'Indicates whether to skip the installation of sglang, defaulting to false.'
        required: false
        type: string
        default: 'false'


concurrency:
  group: nightly-test-npu-${{ inputs.ref || github.ref }}
  cancel-in-progress: ${{ github.event_name != 'workflow_call' }}

jobs:
  set-image-config:
    runs-on: ubuntu-latest
    outputs:
      ref: ${{ steps.set-vars.outputs.ref }}
      job_filter: ${{ steps.set-vars.outputs.job_filter }}
      image_a3: ${{ steps.set-vars.outputs.image_a3 }}
      skip_install_flag: ${{ steps.set-vars.outputs.skip_install_flag }}
    steps:
      # When triggered by PR, no inputs parameters are used. The latest community code is tested by default.
      - name: Set image config
        id: set-vars
        run: |
          if [ -z "${{ inputs.ref }}" ]; then
            echo "ref=" >> $GITHUB_OUTPUT
          else
            echo "ref=${{ inputs.ref }}" >> $GITHUB_OUTPUT
          fi

          if [ -z "${{ inputs.job_filter }}" ]; then
            echo "job_filter=all" >> $GITHUB_OUTPUT
          else
            echo "job_filter=${{ inputs.job_filter }}" >> $GITHUB_OUTPUT
          fi

          if [ -z "${{ inputs.image_a3 }}" ]; then
            echo "image_a3=swr.cn-southwest-2.myhuaweicloud.com/base_image/ascend-ci/cann:8.5.0-a3-ubuntu22.04-py3.11" >> $GITHUB_OUTPUT
          else
            echo "image_a3=${{ inputs.image_a3 }}" >> $GITHUB_OUTPUT
          fi

          if [ -z "${{ inputs.skip_install_flag }}" ]; then
            echo "skip_install_flag=false" >> $GITHUB_OUTPUT
          else
            echo "skip_install_flag=${{ inputs.skip_install_flag }}" >> $GITHUB_OUTPUT
          fi

  nightly-1-npu-a3:
    needs: [set-image-config]
    if: ${{ (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') }}
    runs-on: linux-aarch64-a3-2
    strategy:
      fail-fast: false
      matrix:
        part: [0, 1]
    container:
      image: ${{ needs.set-image-config.outputs.image_a3 }}
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
        with:
          ref: ${{ needs.set-image-config.outputs.ref || github.ref }}

      - name: Install dependencies
        env:
          TORCH_CACHE_URL: "http://cache-service.nginx-pypi-cache.svc.cluster.local/whl/cpu"
          PYPI_CACHE_URL: "http://cache-service.nginx-pypi-cache.svc.cluster.local/pypi/simple"
          GITHUB_PROXY_URL: "https://gh-proxy.test.osinfra.cn/"
        run: |
          # speed up by using infra cache services
          CACHING_URL="cache-service.nginx-pypi-cache.svc.cluster.local"
          sed -Ei "s@(ports|archive).ubuntu.com@${CACHING_URL}:8081@g" /etc/apt/sources.list
          pip config set global.index-url http://${CACHING_URL}/pypi/simple
          pip config set global.trusted-host "${CACHING_URL}"

          if [ ${{ needs.set-image-config.outputs.skip_install_flag }} != "true" ];then
            bash scripts/ci/npu/npu_ci_install_dependency.sh a3
          fi

          # copy required file from our daily cache
          cp ~/.cache/modelscope/hub/datasets/otavia/ShareGPT_Vicuna_unfiltered/ShareGPT_V3_unfiltered_cleaned_split.json /tmp
          # copy gsm8k dataset
          cp ~/.cache/modelscope/hub/datasets/tmp/test.jsonl /tmp

      - name: Print Log Information
        run: |
          bash scripts/ci/npu/npu_log_print.sh

      - name: Run test
        timeout-minutes: 240
        env:
          SGLANG_USE_MODELSCOPE: true
          SGLANG_IS_IN_CI: true
          HF_ENDPOINT: https://hf-mirror.com
          TORCH_EXTENSIONS_DIR: /tmp/torch_extensions
          PYTORCH_NPU_ALLOC_CONF: "expandable_segments:True"
          STREAMS_PER_DEVICE: 32
        run: |
          pip install sglang_router
          hf download lmms-lab/MMMU --repo-type dataset
          pip install sentence_transformers torchaudio==2.8.0
          pip install protobuf==6.31.1 zss pre-commit wandb>=0.16.0 tenacity==8.3.0 loguru openpyxl latex2sympy2 zstandard transformers-stream-generator tqdm-multiprocess pycocoevalcap
          pip install yt-dlp sentencepiece==0.1.99 nltk av ftfy sqlitedict==2.1.0 sacrebleu>=1.5.0 pytablewriter black==24.1.0 isort==5.13.2 peft>=0.2.0 accelerate>=0.29.1
          pip install jsonlines httpx==0.25.0 evaluate>=0.4.0 datasets==2.16.1 numexpr xgrammar==0.1.32 numpy==1.26.4 dotenv
          git clone --branch v0.3.3 --depth 1 https://github.com/EvolvingLMMs-Lab/lmms-eval.git
          cd ./lmms-eval
          nohup pip install . > lmmslog.txt 2>&1 &
          sleep 120
          export PYTHONPATH=$PYTHONPATH:$(pwd)
          cd ../
          cd test
          python3 run_suite.py --hw npu --suite nightly-1-npu-a3 --nightly --continue-on-error --timeout-per-file 3600 --auto-partition-id ${{ matrix.part }} --auto-partition-size 2

  nightly-2-npu-a3:
    needs: [set-image-config]
    if: ${{ (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') }}
    runs-on: linux-aarch64-a3-2
    strategy:
      fail-fast: false
      matrix:
        part: [0]
    container:
      image: ${{ needs.set-image-config.outputs.image_a3 }}
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
        with:
          ref: ${{ needs.set-image-config.outputs.ref || github.ref }}

      - name: Install dependencies
        env:
          TORCH_CACHE_URL: "http://cache-service.nginx-pypi-cache.svc.cluster.local/whl/cpu"
          PYPI_CACHE_URL: "http://cache-service.nginx-pypi-cache.svc.cluster.local/pypi/simple"
          GITHUB_PROXY_URL: "https://gh-proxy.test.osinfra.cn/"
        run: |
          # speed up by using infra cache services
          CACHING_URL="cache-service.nginx-pypi-cache.svc.cluster.local"
          sed -Ei "s@(ports|archive).ubuntu.com@${CACHING_URL}:8081@g" /etc/apt/sources.list
          pip config set global.index-url http://${CACHING_URL}/pypi/simple
          pip config set global.trusted-host "${CACHING_URL}"

          if [ ${{ needs.set-image-config.outputs.skip_install_flag }} != "true" ];then
            bash scripts/ci/npu/npu_ci_install_dependency.sh a3
          fi

          # copy required file from our daily cache
          cp ~/.cache/modelscope/hub/datasets/otavia/ShareGPT_Vicuna_unfiltered/ShareGPT_V3_unfiltered_cleaned_split.json /tmp
          # copy gsm8k dataset
          cp ~/.cache/modelscope/hub/datasets/tmp/test.jsonl /tmp

      - name: Print Log Information
        run: |
          bash scripts/ci/npu/npu_log_print.sh
      - name: Run test
        timeout-minutes: 240
        env:
          SGLANG_USE_MODELSCOPE: true
          SGLANG_IS_IN_CI: true
          HF_ENDPOINT: https://hf-mirror.com
          TORCH_EXTENSIONS_DIR: /tmp/torch_extensions
          PYTORCH_NPU_ALLOC_CONF: "expandable_segments:True"
          STREAMS_PER_DEVICE: 32
        run: |
          pip install sglang_router
          hf download lmms-lab/MMMU --repo-type dataset
          pip install sentence_transformers torchaudio==2.8.0
          pip install protobuf==6.31.1 zss pre-commit wandb>=0.16.0 tenacity==8.3.0 loguru openpyxl latex2sympy2 zstandard transformers-stream-generator tqdm-multiprocess pycocoevalcap
          pip install yt-dlp sentencepiece==0.1.99 nltk av ftfy sqlitedict==2.1.0 sacrebleu>=1.5.0 pytablewriter black==24.1.0 isort==5.13.2 peft>=0.2.0 accelerate>=0.29.1
          pip install jsonlines httpx==0.25.0 evaluate>=0.4.0 datasets==2.16.1 numexpr xgrammar==0.1.32 numpy==1.26.4 dotenv
          git clone --branch v0.3.3 --depth 1 https://github.com/EvolvingLMMs-Lab/lmms-eval.git
          cd ./lmms-eval
          nohup pip install . > lmmslog.txt 2>&1 &
          sleep 120
          export PYTHONPATH=$PYTHONPATH:$(pwd)
          cd ../
          cd test
          python3 run_suite.py --hw npu --suite nightly-2-npu-a3 --nightly --continue-on-error --timeout-per-file 3600 --auto-partition-id ${{ matrix.part }} --auto-partition-size 1

  nightly-4-npu-a3:
    needs: [set-image-config]
    if: ${{ (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') }}
    runs-on: linux-aarch64-a3-4
    strategy:
      fail-fast: false
      matrix:
        part: [0]
    container:
      image: ${{ needs.set-image-config.outputs.image_a3 }}
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
        with:
          ref: ${{ needs.set-image-config.outputs.ref|| github.ref }}

      - name: Install dependencies
        env:
          TORCH_CACHE_URL: "http://cache-service.nginx-pypi-cache.svc.cluster.local/whl/cpu"
          PYPI_CACHE_URL: "http://cache-service.nginx-pypi-cache.svc.cluster.local/pypi/simple"
          GITHUB_PROXY_URL: "https://gh-proxy.test.osinfra.cn/"
        run: |
          # speed up by using infra cache services
          CACHING_URL="cache-service.nginx-pypi-cache.svc.cluster.local"
          sed -Ei "s@(ports|archive).ubuntu.com@${CACHING_URL}:8081@g" /etc/apt/sources.list
          pip config set global.index-url http://${CACHING_URL}/pypi/simple
          pip config set global.trusted-host "${CACHING_URL}"

          if [ ${{ needs.set-image-config.outputs.skip_install_flag }} != "true" ];then
            bash scripts/ci/npu/npu_ci_install_dependency.sh a3
          fi

          # copy required file from our daily cache
          cp ~/.cache/modelscope/hub/datasets/otavia/ShareGPT_Vicuna_unfiltered/ShareGPT_V3_unfiltered_cleaned_split.json /tmp
          # copy gsm8k dataset
          cp ~/.cache/modelscope/hub/datasets/tmp/test.jsonl /tmp

      - name: Print Log Information
        run: |
          bash scripts/ci/npu/npu_log_print.sh

      - name: Run test
        timeout-minutes: 240
        env:
          SGLANG_USE_MODELSCOPE: true
          SGLANG_IS_IN_CI: true
          HF_ENDPOINT: https://hf-mirror.com
          TORCH_EXTENSIONS_DIR: /tmp/torch_extensions
          PYTORCH_NPU_ALLOC_CONF: "expandable_segments:True"
          STREAMS_PER_DEVICE: 32
        run: |
          pip install sglang_router
          hf download lmms-lab/MMMU --repo-type dataset
          pip install sentence_transformers torchaudio==2.8.0
          pip install protobuf==6.31.1 zss pre-commit wandb>=0.16.0 tenacity==8.3.0 loguru openpyxl latex2sympy2 zstandard transformers-stream-generator tqdm-multiprocess pycocoevalcap
          pip install yt-dlp sentencepiece==0.1.99 nltk av ftfy sqlitedict==2.1.0 sacrebleu>=1.5.0 pytablewriter black==24.1.0 isort==5.13.2 peft>=0.2.0 accelerate>=0.29.1
          pip install jsonlines httpx==0.25.0 evaluate>=0.4.0 datasets==2.16.1 numexpr xgrammar==0.1.32 numpy==1.26.4 dotenv
          git clone --branch v0.3.3 --depth 1 https://github.com/EvolvingLMMs-Lab/lmms-eval.git
          cd ./lmms-eval
          nohup pip install . > lmmslog.txt 2>&1 &
          sleep 120
          export PYTHONPATH=$PYTHONPATH:$(pwd)
          cd ../
          cd test
          python3 run_suite.py --hw npu --suite nightly-4-npu-a3 --nightly --continue-on-error --timeout-per-file 3600 --auto-partition-id ${{ matrix.part }} --auto-partition-size 1

  nightly-8-npu-a3:
    needs: [set-image-config]
    if: ${{ (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') }}
    runs-on: linux-aarch64-a3-8
    strategy:
      fail-fast: false
      matrix:
        part: [0]
    container:
      image: ${{ needs.set-image-config.outputs.image_a3 }}
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
        with:
          ref: ${{ needs.set-image-config.outputs.ref || github.ref }}

      - name: Install dependencies
        env:
          TORCH_CACHE_URL: "http://cache-service.nginx-pypi-cache.svc.cluster.local/whl/cpu"
          PYPI_CACHE_URL: "http://cache-service.nginx-pypi-cache.svc.cluster.local/pypi/simple"
          GITHUB_PROXY_URL: "https://gh-proxy.test.osinfra.cn/"
        run: |
          # speed up by using infra cache services
          CACHING_URL="cache-service.nginx-pypi-cache.svc.cluster.local"
          sed -Ei "s@(ports|archive).ubuntu.com@${CACHING_URL}:8081@g" /etc/apt/sources.list
          pip config set global.index-url http://${CACHING_URL}/pypi/simple
          pip config set global.trusted-host "${CACHING_URL}"

          if [ ${{ needs.set-image-config.outputs.skip_install_flag }} != "true" ];then
            bash scripts/ci/npu/npu_ci_install_dependency.sh a3
          fi

          # copy required file from our daily cache
          cp ~/.cache/modelscope/hub/datasets/otavia/ShareGPT_Vicuna_unfiltered/ShareGPT_V3_unfiltered_cleaned_split.json /tmp
          # copy gsm8k dataset
          cp ~/.cache/modelscope/hub/datasets/tmp/test.jsonl /tmp

      - name: Print Log Information
        run: |
          bash scripts/ci/npu/npu_log_print.sh

      - name: Run test
        timeout-minutes: 240
        env:
          SGLANG_USE_MODELSCOPE: true
          SGLANG_IS_IN_CI: true
          HF_ENDPOINT: https://hf-mirror.com
          TORCH_EXTENSIONS_DIR: /tmp/torch_extensions
          PYTORCH_NPU_ALLOC_CONF: "expandable_segments:True"
          STREAMS_PER_DEVICE: 32
        run: |
          pip install sglang_router
          hf download lmms-lab/MMMU --repo-type dataset
          pip install sentence_transformers torchaudio==2.8.0
          pip install protobuf==6.31.1 zss pre-commit wandb>=0.16.0 tenacity==8.3.0 loguru openpyxl latex2sympy2 zstandard transformers-stream-generator tqdm-multiprocess pycocoevalcap
          pip install yt-dlp sentencepiece==0.1.99 nltk av ftfy sqlitedict==2.1.0 sacrebleu>=1.5.0 pytablewriter black==24.1.0 isort==5.13.2 peft>=0.2.0 accelerate>=0.29.1
          pip install jsonlines httpx==0.25.0 evaluate>=0.4.0 datasets==2.16.1 numexpr xgrammar==0.1.32 numpy==1.26.4 dotenv
          git clone --branch v0.3.3 --depth 1 https://github.com/EvolvingLMMs-Lab/lmms-eval.git
          cd ./lmms-eval
          nohup pip install . > lmmslog.txt 2>&1 &
          sleep 120
          export PYTHONPATH=$PYTHONPATH:$(pwd)
          cd ../
          cd test
          python3 run_suite.py --hw npu --suite nightly-8-npu-a3 --nightly --continue-on-error --timeout-per-file 3600 --auto-partition-id ${{ matrix.part }} --auto-partition-size 1

  nightly-16-npu-a3:
    needs: [set-image-config]
    if: ${{ (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') }}
    runs-on: linux-aarch64-a3-16
    strategy:
      fail-fast: false
      matrix:
        part: [0, 1]
    container:
      image: ${{ needs.set-image-config.outputs.image_a3 }}
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
        with:
          ref: ${{ needs.set-image-config.outputs.ref || github.ref }}

      - name: Install dependencies
        env:
          TORCH_CACHE_URL: "http://cache-service.nginx-pypi-cache.svc.cluster.local/whl/cpu"
          PYPI_CACHE_URL: "http://cache-service.nginx-pypi-cache.svc.cluster.local/pypi/simple"
          GITHUB_PROXY_URL: "https://gh-proxy.test.osinfra.cn/"
        run: |
          # speed up by using infra cache services
          CACHING_URL="cache-service.nginx-pypi-cache.svc.cluster.local"
          sed -Ei "s@(ports|archive).ubuntu.com@${CACHING_URL}:8081@g" /etc/apt/sources.list
          pip config set global.index-url http://${CACHING_URL}/pypi/simple
          pip config set global.trusted-host "${CACHING_URL}"

          if [ ${{ needs.set-image-config.outputs.skip_install_flag }} != "true" ];then
            bash scripts/ci/npu/npu_ci_install_dependency.sh a3
          fi

          # copy required file from our daily cache
          cp ~/.cache/modelscope/hub/datasets/otavia/ShareGPT_Vicuna_unfiltered/ShareGPT_V3_unfiltered_cleaned_split.json /tmp
          # copy gsm8k dataset
          cp ~/.cache/modelscope/hub/datasets/tmp/test.jsonl /tmp

      - name: Print Log Information
        run: |
          bash scripts/ci/npu/npu_log_print.sh

      - name: Run test
        timeout-minutes: 240
        env:
          SGLANG_USE_MODELSCOPE: true
          SGLANG_IS_IN_CI: true
          HF_ENDPOINT: https://hf-mirror.com
          TORCH_EXTENSIONS_DIR: /tmp/torch_extensions
          PYTORCH_NPU_ALLOC_CONF: "expandable_segments:True"
          STREAMS_PER_DEVICE: 32
        run: |
          pip install sglang_router
          hf download lmms-lab/MMMU --repo-type dataset
          pip install sentence_transformers torchaudio==2.8.0
          pip install protobuf==6.31.1 zss pre-commit wandb>=0.16.0 tenacity==8.3.0 loguru openpyxl latex2sympy2 zstandard transformers-stream-generator tqdm-multiprocess pycocoevalcap
          pip install yt-dlp sentencepiece==0.1.99 nltk av ftfy sqlitedict==2.1.0 sacrebleu>=1.5.0 pytablewriter black==24.1.0 isort==5.13.2 peft>=0.2.0 accelerate>=0.29.1
          pip install jsonlines httpx==0.25.0 evaluate>=0.4.0 datasets==2.16.1 numexpr xgrammar==0.1.32 numpy==1.26.4 dotenv
          git clone --branch v0.3.3 --depth 1 https://github.com/EvolvingLMMs-Lab/lmms-eval.git
          cd ./lmms-eval
          nohup pip install . > lmmslog.txt 2>&1 &
          sleep 120
          export PYTHONPATH=$PYTHONPATH:$(pwd)
          cd ../
          cd test
          python3 run_suite.py --hw npu --suite nightly-16-npu-a3 --nightly --continue-on-error --timeout-per-file 3600 --auto-partition-id ${{ matrix.part }} --auto-partition-size 2

  check-all-jobs:
    if: github.repository == 'sgl-project/sglang' && always()
    needs:
      - nightly-1-npu-a3
      - nightly-2-npu-a3
      - nightly-4-npu-a3
      - nightly-8-npu-a3
      - nightly-16-npu-a3
    runs-on: ubuntu-latest
    container:
      image: docker.m.daocloud.io/ubuntu:22.04
    steps:
      - name: Check if any job failed
        run: |
          if [[ "${{ contains(needs.*.result, 'failure') }}" == "true" ]]; then
            echo "One or more nightly test jobs failed"
            exit 1
          fi
          if [[ "${{ contains(needs.*.result, 'cancelled') }}" == "true" ]]; then
            echo "One or more nightly test jobs were cancelled"
            exit 1
          fi
          echo "All nightly test jobs passed"