cancel-in-progress: ${{ github.ref != 'master' }}

jobs:
  #build-and-test-linux-x86-cpu:
  #  uses: ./.github/workflows/build-reusable.yml
  #  with:
  #    runner: 'linux-x86-n2-16'
  #    tfci: 'py313,linux_x86,rbe'

  #build-and-test-linux-x86-cuda:
  #  uses: ./.github/workflows/build-reusable.yml
  #  with:
  #    runner: 'linux-x86-n4-32'
  #    tfci: 'py313,linux_x86_cuda'

  #build-and-test-arm64:

    "linux" : 478
  }, {
    "testProject" : "mediumNative",
    "linux" : 272
  }, {
    "testProject" : "multiNative",
    "linux" : 1650
  }, {
    "testProject" : "smallCppApp",
    "linux" : 328
  }, {
    "testProject" : "smallCppMulti",
    "linux" : 345
  }, {
    "testProject" : "smallNative",
    "linux" : 315
  } ]
}, {

#     rbe_linux_cuda_nvcc:            RBE options to build with GPU support using nvcc.
#
# Embedded Linux options (experimental and only tested with TFLite build yet)
#     elinux:          General Embedded Linux options shared by all flavors.
#     elinux_aarch64:  Embedded Linux options for aarch64 (ARM64) CPU support.
#     elinux_armhf:    Embedded Linux options for armhf (ARMv7) CPU support.
#
# Release build options (for all operating systems)

    env:
      PIP_NO_CACHE_DIR: 1
    defaults:
      run:
        shell: bash
    container: ${{ (contains(inputs.runner, 'linux-x86') && 'us-docker.pkg.dev/ml-oss-artifacts-published/ml-public-container/ml-build:latest') ||
                   (contains(inputs.runner, 'linux-arm64') && 'us-docker.pkg.dev/ml-oss-artifacts-published/ml-public-container/ml-build-arm64:latest') ||

    flakyTestStrategy: FlakyTestStrategy,
) : OsAwareBaseGradleBuildType(os = Os.LINUX, stage = stage, init = {
        val suffix = if (flakyTestStrategy == FlakyTestStrategy.ONLY)"_FlakyTestQuarantine" else ""
        id("${model.projectId}_SmokeTest_$id$suffix")
        name = "Smoke Tests with 3rd Party Plugins ($task) - ${testJava.version.toCapitalized()} Linux$suffix"

**Linux CPU**                 | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-cc.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-cc.html)           | [PyPI](https://pypi.org/project/tf-nightly/)

 */
class Gradleception(
    model: CIBuildModel,
    stage: Stage,
    buildJvm: Jvm,
    jvmDescription: String,
    bundleGroovyMajor: Int? = null,
) : OsAwareBaseGradleBuildType(os = Os.LINUX, stage = stage, init = {
        val idParts = mutableListOf<String>()
        val labels = mutableListOf<String>()
        val descriptionParts = mutableListOf<String>()
        if (bundleGroovyMajor != null) {

    outputs:
      matrix: ${{ steps.setup-matrix.outputs.matrix }}
      sys-prop-args: ${{ steps.determine-sys-prop-args.outputs.sys-prop-args }}

  sanity-check:
    name: "Sanity Check on Linux"
    permissions:
      contents: read
    runs-on: ubuntu-latest
    needs: build
    steps:
      - name: git clone
        uses: actions/checkout@v6
      - name: setup java

          distribution: 'temurin'

      - name: Install Graphviz (MacOS)
        if: runner.os == 'macOS'
        run: brew install graphviz

      - name: Install Graphviz (Ubuntu)
        if: runner.os == 'Linux'
        run: sudo apt-get install graphviz

      - name: Install Graphviz (Windows)
        if: runner.os == 'Windows'
        run: choco install graphviz

      - name: Checkout maven

# TF_LoadLibrary/tf.load_op_library) register their ops and kernels with this
# shared object directly.
#
# For example, from Python tf.load_op_library loads a custom op library (via
# dlopen() on Linux), the library finds libtensorflow_framework.so (no
# filesystem search takes place, since libtensorflow_framework.so has already
# been loaded by pywrap_tensorflow) and registers its ops and kernels via