cuda-windows.yml

# Test ExecuTorch CUDA Windows Artifacts
# This workflow exports models targeting CUDA Windows using optimum-executorch on Linux.
# Then it runs those exported artifacts on a Windows CI machine.

name: Test CUDA Windows Export and E2E

on:
  push:
    branches:
      - main
      - release/*
    tags:
      - ciflow/cuda/*
  pull_request:
    paths:
      - .github/workflows/cuda-windows.yml
      - backends/cuda/**
      - backends/aoti/**
  workflow_dispatch:

concurrency:
  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}
  cancel-in-progress: false

permissions:
  contents: read

jobs:
  changed-files:
    name: Get changed files
    uses: ./.github/workflows/_get-changed-files.yml
    with:
      include-push-diff: true

  run-decision:
    name: CI run decision
    uses: ./.github/workflows/_ci-run-decision.yml

  export-model-cuda-windows-artifact:
    name: export-model-cuda-windows-artifact
    # Skip this job if the pull request is from a fork (HuggingFace secrets are not available).
    # Path-filtered on push: mirrors the workflow-level pull_request `paths:`
    # filter so push commits that don't touch CUDA-relevant paths skip
    # this job on non-sampled commits. See _ci-run-decision.yml for
    # the sampling policy.
    needs: [changed-files, run-decision]
    if: |
      (github.event.pull_request.head.repo.full_name == github.repository || github.event_name != 'pull_request') &&
      (
        contains(needs.changed-files.outputs.changed-files, 'backends/cuda') ||
        contains(needs.changed-files.outputs.changed-files, 'backends/aoti') ||
        contains(needs.changed-files.outputs.changed-files, '.github/workflows/cuda-windows.yml') ||
        needs.run-decision.outputs.is-full-run == 'true'
      )
    uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
    permissions:
      id-token: write
      contents: read
    secrets: inherit
    strategy:
      fail-fast: false
      matrix:
        include:
          - model_repo: "mistralai"
            model_name: "Voxtral-Mini-3B-2507"
            quant: "non-quantized"
          - model_repo: "mistralai"
            model_name: "Voxtral-Mini-3B-2507"
            quant: "quantized-int4-weight-only"
          - model_repo: "nvidia"
            model_name: "parakeet-tdt"
            quant: "non-quantized"
          - model_repo: "nvidia"
            model_name: "parakeet-tdt"
            quant: "quantized-int4-weight-only"
          # TODO: sortformer produces 0 segments on Windows after D97788666.
          # Temporarily disabled until root cause is debugged.
          # - model_repo: "nvidia"
          #   model_name: "diar_streaming_sortformer_4spk-v2"
          #   quant: "non-quantized"
          - model_repo: "mistralai"
            model_name: "Voxtral-Mini-4B-Realtime-2602"
            quant: "quantized-int4-tile-packed"
          - model_repo: "facebook"
            model_name: "dinov2-small-imagenet1k-1-layer"
            quant: "non-quantized"
    with:
      timeout: 90
      secrets-env: EXECUTORCH_HF_TOKEN
      runner: linux.g5.4xlarge.nvidia.gpu
      gpu-arch-type: cuda
      gpu-arch-version: "13.0"
      docker-image: ci-image:executorch-ubuntu-22.04-cuda-windows
      submodules: recursive
      upload-artifact: ${{ matrix.model_repo }}-${{ matrix.model_name }}-cuda-windows-${{ matrix.quant }}
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      script: |
        set -eux

        echo "::group::Fix libstdc++ GLIBCXX version"
        # The executorch pybindings require GLIBCXX_3.4.30 which conda's libstdc++ doesn't have.
        # Replace conda's libstdc++ with the system version to fix ImportError.
        # Verify system version has GLIBCXX_3.4.30
        strings /usr/lib/x86_64-linux-gnu/libstdc++.so.6 | grep GLIBCXX_3.4.30
        # Backup and replace conda's version
        mv /opt/conda/lib/libstdc++.so.6 /opt/conda/lib/libstdc++.so.6.bak || true
        ln -sf /usr/lib/x86_64-linux-gnu/libstdc++.so.6 /opt/conda/lib/libstdc++.so.6
        echo "::endgroup::"

        echo "::group::Verify pre-installed dependencies"
        x86_64-w64-mingw32-g++ --version
        nvcc --version
        echo "WINDOWS_CUDA_HOME=${WINDOWS_CUDA_HOME}"
        ls -la "${WINDOWS_CUDA_HOME}"
        echo "::endgroup::"

        echo "::group::Setup ExecuTorch"
        # Disable MKL to avoid duplicate target error when conda has multiple MKL installations
        export USE_MKL=OFF
        PYTHON_EXECUTABLE=python ./install_executorch.sh
        echo "::endgroup::"

        # Setup Huggingface only for models that need it (not dinov2)
        if [ "${{ matrix.model_name }}" != "dinov2-small-imagenet1k-1-layer" ]; then
          echo "::group::Setup Huggingface"
          pip install -U "huggingface_hub[cli]>=1.2.1,<2.0" accelerate "optimum~=2.0.0" "transformers==5.0.0rc1"
          HF_AUTH_TOKEN="$(printf '%s' "$SECRET_EXECUTORCH_HF_TOKEN" | tr -d '\r\n')"
          hf auth login --token "$HF_AUTH_TOKEN"
          OPTIMUM_ET_VERSION=$(cat .ci/docker/ci_commit_pins/optimum-executorch.txt)
          pip install --no-deps git+https://github.com/huggingface/optimum-executorch.git@${OPTIMUM_ET_VERSION}
          echo "::endgroup::"
        fi

        VR_MODE=""
        if [ "${{ matrix.model_name }}" = "Voxtral-Mini-4B-Realtime-2602" ]; then
          VR_MODE="vr-offline"
        fi
        source .ci/scripts/export_model_artifact.sh cuda-windows "${{ matrix.model_repo }}/${{ matrix.model_name }}" "${{ matrix.quant }}" "${RUNNER_ARTIFACT_DIR}" "${VR_MODE}"

  test-model-cuda-windows-e2e:
    name: test-model-cuda-windows-e2e
    # Same path filter as the export job above. Also explicitly gated
    # on the export job succeeding — when needs: jobs are *skipped*
    # (e.g. fork PR), GitHub still evaluates this if:, so without the
    # explicit success-check this job would run and then fail trying
    # to download an artifact that was never produced.
    needs: [changed-files, export-model-cuda-windows-artifact, run-decision]
    if: |
      needs.export-model-cuda-windows-artifact.result == 'success' &&
      (
        contains(needs.changed-files.outputs.changed-files, 'backends/cuda') ||
        contains(needs.changed-files.outputs.changed-files, 'backends/aoti') ||
        contains(needs.changed-files.outputs.changed-files, '.github/workflows/cuda-windows.yml') ||
        needs.run-decision.outputs.is-full-run == 'true'
      )
    uses: pytorch/test-infra/.github/workflows/windows_job.yml@main
    strategy:
      fail-fast: false
      matrix:
        include:
          - model_repo: "mistralai"
            model_name: "Voxtral-Mini-3B-2507"
            quant: "non-quantized"
          - model_repo: "mistralai"
            model_name: "Voxtral-Mini-3B-2507"
            quant: "quantized-int4-weight-only"
          - model_repo: "nvidia"
            model_name: "parakeet-tdt"
            quant: "non-quantized"
          - model_repo: "nvidia"
            model_name: "parakeet-tdt"
            quant: "quantized-int4-weight-only"
          # TODO: sortformer produces 0 segments on Windows after D97788666.
          # Temporarily disabled until root cause is debugged.
          # - model_repo: "nvidia"
          #   model_name: "diar_streaming_sortformer_4spk-v2"
          #   quant: "non-quantized"
          - model_repo: "mistralai"
            model_name: "Voxtral-Mini-4B-Realtime-2602"
            quant: "quantized-int4-tile-packed"
          - model_repo: "facebook"
            model_name: "dinov2-small-imagenet1k-1-layer"
            quant: "non-quantized"
    with:
      timeout: 240
      runner: windows.g5.4xlarge.nvidia.gpu
      gpu-arch-type: cuda
      gpu-arch-version: "13.0"
      download-artifact: ${{ matrix.model_repo }}-${{ matrix.model_name }}-cuda-windows-${{ matrix.quant }}
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      script: |
        git config --global http.sslBackend openssl
        git submodule update --init --recursive
        conda init powershell
        powershell -Command "& {
          Set-PSDebug -Trace 1
          \$ErrorActionPreference = 'Stop'
          \$PSNativeCommandUseErrorActionPreference = \$true

          \$env:CUDA_HOME = 'C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.0'
          \$env:CUDA_PATH = \$env:CUDA_HOME
          \$env:PATH = \"\$env:CUDA_HOME\bin;\$env:PATH\"
          nvcc --version

          .ci/scripts/setup-windows.ps1
          \$artifactDir = \$env:RUNNER_ARTIFACT_DIR
          if ([string]::IsNullOrWhiteSpace(\$artifactDir)) {
            throw 'RUNNER_ARTIFACT_DIR is empty. Ensure download-artifact is configured for windows_job.yml.'
          }

          .ci/scripts/test_model_e2e_windows.ps1 -Device cuda-windows -HfModel '${{ matrix.model_repo }}/${{ matrix.model_name }}' -QuantName '${{ matrix.quant }}' -ModelDir \$artifactDir -ExpectedCudaVersion '13.0'
        }"