linux_cuda_plugin_ci.yml

name: CUDA Plugin Linux CI

on:
  push:
    branches: [main, 'rel-*']
  pull_request:
    branches: [main, 'rel-*']
  workflow_dispatch:

concurrency:
  group: ${{ github.workflow }}-${{ github.event_name == 'pull_request' && github.ref || github.sha }}
  cancel-in-progress: true

permissions:
  contents: read
  packages: write
  attestations: write
  id-token: write

jobs:
  build-linux-cuda-plugin-x64-release:
    name: Build Linux CUDA Plugin EP x64 Release
    uses: ./.github/workflows/reusable_linux_build.yml
    with:
      pool_name: "onnxruntime-github-Ubuntu2204-AMD-CPU" # Build pool
      build_config: Release
      architecture: x64
      dockerfile_path: tools/ci_build/github/linux/docker/Dockerfile.manylinux2_28_cuda
      docker_build_args: '--build-arg BASEIMAGE=onnxruntimebuildcache.azurecr.io/internal/azureml/onnxruntime/build/cuda13_x64_almalinux8_gcc14:20251107.1'
      docker_image_repo: onnxruntimecuda13manylinuxbuild
      extra_build_flags: >-
        --use_binskim_compliant_compile_flags
        --build_wheel
        --parallel
        --nvcc_threads 4
        --flash_nvcc_threads 4
        --cuda_version=13.0
        --cuda_home=/usr/local/cuda-13.0
        --cudnn_home=/usr/local/cuda-13.0
        --enable_cuda_profiling
        --cmake_extra_defines CMAKE_CUDA_ARCHITECTURES=86
        --cmake_extra_defines onnxruntime_BUILD_UNIT_TESTS=ON
        --cmake_extra_defines onnxruntime_QUICK_BUILD=ON
        --cmake_extra_defines onnxruntime_BUILD_CUDA_EP_AS_PLUGIN=ON
      python_path_prefix: 'PATH=/opt/python/cp312-cp312/bin:$PATH'
      run_tests: false
      upload_build_output: true
      execution_providers: 'cuda'
      job_identifier: build-linux-cuda-plugin-x64-release
    secrets:
      GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}

  test-linux-cuda-plugin-x64-release:
    name: Test Linux CUDA Plugin EP x64 Release
    needs: build-linux-cuda-plugin-x64-release
    runs-on:
      - self-hosted
      - "1ES.Pool=onnxruntime-github-linux-a10"
      - "1ES.ImageOverride=onnxruntime-ubuntu2204-CUDA-A10-Test"
      - "JobId=test-linux-cuda-plugin-x64-release-${{ github.run_id }}-${{ github.run_number }}-${{ github.run_attempt }}"
    permissions:
      contents: read
      packages: read
    steps:
      - name: Checkout code
        uses: actions/checkout@v6

      - uses: microsoft/onnxruntime-github-actions/build-docker-image@8bad63a3c05d448311dfa8e5f531171c97471aa1 # v0.0.12
        id: build_docker_image_step
        with:
          dockerfile: ${{ github.workspace }}/tools/ci_build/github/linux/docker/Dockerfile.manylinux2_28_cuda
          image-name: ghcr.io/microsoft/onnxruntime/onnxruntimecuda13manylinuxbuild
          build-args: '--build-arg BASEIMAGE=onnxruntimebuildcache.azurecr.io/internal/azureml/onnxruntime/build/cuda13_x64_almalinux8_gcc14:20251107.1'
          push: true
          azure-container-registry-name: onnxruntimebuildcache
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

      # --- Download Build Artifact to Runner Temp Directory ---
      - name: Download Build Artifact
        uses: actions/download-artifact@v7
        with:
          name: build-output-x64-Release
          path: ${{ runner.temp }}/Release

      # --- Restore Permissions in the Temp Directory ---
      - name: Restore Executable Permissions
        if: success()
        working-directory: ${{ runner.temp }}/Release
        run: |
          if [ -f perms.txt ]; then
            echo "Restoring executable permissions in ${{ runner.temp }}/Release ..."
            while IFS= read -r file; do
              if [ -f "$file" ]; then
                chmod +x "$file"
              else
                echo "Warning: File '$file' listed in perms.txt not found."
              fi
            done < perms.txt
            echo "Permissions restored."
          else
            echo "Warning: perms.txt not found in artifact."
          fi

      # Verify the GPU is accessible inside Docker before running the full test suite.
      # If the NVIDIA Container Toolkit fails to expose /dev/nvidia* devices,
      # tests will fail with "CUDA failure 100" and waste 10+ minutes.
      - name: Verify GPU access in Docker
        run: |
          docker run --rm --gpus all \
            "${{ steps.build_docker_image_step.outputs.full-image-name }}" \
            nvidia-smi

      - name: Run CUDA Plugin EP C++ Tests
        run: |
          docker run --rm --gpus all \
            -v ${{ github.workspace }}:/onnxruntime_src \
            -v ${{ runner.temp }}/Release:/build/Release \
            -e NVIDIA_VISIBLE_DEVICES=all \
            -e ORT_UNIT_TEST_MAIN_DYNAMIC_PLUGIN_EP_CONFIG_JSON='{"ep_library_registration_name":"CUDAExecutionProvider","ep_library_path":"libonnxruntime_providers_cuda.so","selected_ep_name":"CUDAExecutionProvider","tests_to_skip":["BeamSearchTest.*","ContribOpAttentionTest.AttentionPastState_dynamic","ContribOpAttentionTest.Attention_Mask1D_Fp32_B2_S64","ContribOpAttentionTest.Attention_Mask2D_Fp32_B2_S32","ConvTest.Conv2D_MatMul_*","CudaPluginArenaTest.DeviceAllocator_ArenaReusesMemory","CudaPluginArenaTest.DeviceAllocator_CudaMemoryIsValid","CudaPluginArenaTest.DeviceAllocator_IsArena","CudaPluginArenaTest.DeviceAllocator_MultipleAllocations","DeformConvTest.Group1OffsetGroup2","GRUTest.*","GreedySearchTest.*","InferenceSessionTests.Test2LayerNestedSubgraph","InferenceSessionTests.Test3LayerNestedSubgraph","InferenceSessionTests.TestArenaShrinkageAfterRun","LSTMTest.*","LogSoftmaxOperator.*","LongformerAttentionTest.*","LoraAdapterTest.VerifyDeviceCopy","PackedAttentionTest.*","PlannerTest.MultiStream","PlannerTest.MultiStream1StreamWaitFor2Streams","PlannerTest.MultiStream2NodesSameStreamConsumedBy1NodeInDifferentStream","PlannerTest.MultiStreamCudaEPNodeCPUOutput","PlannerTest.MultiStreamMultiOutput","RNNTest.*","ReductionOpTest.ArgMax2D_select_last","ReductionOpTest.ArgMin_do_not_keepdims_2_select_last","SamplingTest.*","Scan.MixedExecutionProvidersUnknownDimInSubgraphOutput","Scan8.*","SessionStateTest.TestLayeringPartitioning","SessionStateTest.TestResourceAwarePartitioning_LargeLimit","SessionStateTest.TestResourceAwarePartitioning_NoLimit","SkipGroupNormTest.*","TopKOperator.NthElementBFloat16_NegativeVals"]}' \
            ${{ steps.build_docker_image_step.outputs.full-image-name }} \
            bash -c "
              set -ex
              export LD_LIBRARY_PATH=/build/Release/Release:/usr/local/cuda-13.0/lib64:\${LD_LIBRARY_PATH:-}
              cd /build/Release/Release
              ./onnxruntime_test_all
              ./onnxruntime_provider_test
            "

      - name: Run CUDA Plugin EP Python Tests
        run: |
          docker run --rm --gpus all \
            -v ${{ github.workspace }}:/onnxruntime_src \
            -v ${{ runner.temp }}/Release:/build/Release \
            -e NVIDIA_VISIBLE_DEVICES=all \
            -e ORT_TEST_CUDA_PLUGIN_EP=1 \
            ${{ steps.build_docker_image_step.outputs.full-image-name }} \
            bash -c "
              set -ex
              export PATH=/opt/python/cp312-cp312/bin:\$PATH
              export LD_LIBRARY_PATH=/build/Release/Release:/usr/local/cuda-13.0/lib64:\${LD_LIBRARY_PATH:-}
              python -m pip install /build/Release/Release/dist/onnxruntime*.whl
              python -m pip install numpy onnx
              python -m pip install torch --index-url https://download.pytorch.org/whl/cpu
              cd /onnxruntime_src/onnxruntime/test/python/transformers
              python test_cuda_plugin_ep.py
            "