"testdata/strided_slice.mlir",
    ],
    deps = [
        ":error_collector",
        ":error_collector_inst",
        ":types_util",
        "//tensorflow/compiler/mlir/tensorflow",
        "//tensorflow/core:test",
        "//tensorflow/core/platform:errors",
        "//tensorflow/core/platform:resource_loader",
        "//tensorflow/lite/python/metrics:converter_error_data_proto_cc",
        "@com_google_absl//absl/status:statusor",

          sudo chown -R istio-proxy /var/run/secrets

          # Change coredump directory to the correct user. Note this is a volume so we persist between crashes
          sudo chown -R istio-proxy:istio-proxy /var/lib/istio/data

          # place mounted bootstrap files (token is mounted directly to the correct location)
          sudo cp /var/run/secrets/istio/bootstrap/root-cert.pem /var/run/secrets/istio/root-cert.pem

        val generatedTopLevelClassifiers = declarationGenerators
            .asSequence()
            .flatMap {
                // FIXME this function should be called only once during plugin's lifetime, so this usage is not really correct (2)
                it.getTopLevelClassIds()
            }
            .filter { it.packageFqName == packageFqName }
            .map { it.shortClassName }

        return generatedTopLevelClassifiers.toSet()
    }

    DumpMlirOpToFile("tf_to_tfrt_tf_executor_dialect", module);
  }

  mlir::StatusScopedDiagnosticHandler diag_handler(module.getContext());

  // Lower MLIR TF Dialect to MLIR TFRT CoreRT dialect.
  mlir::PassManager pm(module.getContext());
  tensorflow::applyTensorflowAndCLOptions(pm);

  tensorflow::TfrtPipelineOptions pass_options;
  if (!options.default_device.empty()) {

        branch = VersionedSettingsBranch("master"),
        buildScanTags = listOf("Check"),
        subprojects = JsonBasedGradleSubprojectProvider(File("../.teamcity/subprojects.json"))
    )

    @Test
    fun `create correct PerformanceTest build type for Linux`() {
        val performanceTest = PerformanceTest(
            buildModel,
            Stage(
                StageName.PULL_REQUEST_FEEDBACK,

tf_cc_test(
    name = "stream_executor_test",
    srcs = ["stream_executor_test.cc"],
    deps = [
        ":stream_executor",
        ":stream_executor_internal",
        ":stream_executor_test_util",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
        "//tensorflow/core/protobuf:error_codes_proto_impl_cc",
        "@local_tsl//tsl/platform:statusor",
        "@local_xla//xla/stream_executor",

	// Action
	actionIfErrPersistsCheckBugList            = "If this error persists, " + actionCheckBugList
	actionIfErrSureCorrectConfigContactSupport = "If you are sure your configuration is correct, " + actionCheckBugList
	actionCheckBugList                         = "see https://istio.io/latest/about/bugs for possible solutions."

	// LikelyCause
	likelyCauseAPIServer     = "a problem with the Kubernetes API server"

func.func @device_test(
    %arg0: tensor<3x1xf32> {tf_saved_model.index_path = [0]},
    %arg1: tensor<1x3xf32> {tf_saved_model.index_path = [0]})
      -> (tensor<3x3xf32> {tf_saved_model.index_path = []}) {
  // CHECK: {{%.*}} = corert.get_op_handler %arg0 "/device:GPU:0"

    }

    @Test
    fun `maps resolution errors to document errors`() {
        val resolver = tracingCodeResolver()

        val topLevelBlock = parseAsTopLevelBlock(
            """
            addAndConfigure("correct") { }
            addAndConfigure("lambda missing")
            addAndConfigure("incorrect signature", 1) {
                number = 123

 * The special provider is necessary because forward declarations are mere qualified names by themselves.
 * It is a responsibility of the implementor to make the source representation correct.
 * Symbol's properties are not affected by its source representation.
 *