string(config.LeastAllocated),
	string(config.MostAllocated),
	string(config.RequestedToCapacityRatio),
)

// ValidateDefaultPreemptionArgs validates that DefaultPreemptionArgs are correct.
func ValidateDefaultPreemptionArgs(path *field.Path, args *config.DefaultPreemptionArgs) error {
	var allErrs field.ErrorList
	percentagePath := path.Child("minCandidateNodesPercentage")

    // CHECK: tfrt_fallback_async.executeop key({{[0-9]+}}) cost({{.*}}) device("/device:CPU:0") "tf.FlatMapDataset"({{.*}}) {Targuments = [], metadata = "", output_shapes = [#corert.shape<>], output_types = [i64]} {f = "__inference_Dataset_flat_map_lambda_19"} : 1

        "//tensorflow/compiler/mlir/tensorflow:attribute_utils",
        "//tensorflow/compiler/tf2xla:xla_op_registry",
        "//tensorflow/core:framework",
        "//tensorflow/core:lib",
        "//tensorflow/core:test",
        "//tensorflow/core/lib/monitoring:cell_reader",
        "//tensorflow/core/platform:resource_loader",
        "//tensorflow/core/tpu:tpu_defs",
        "@com_google_absl//absl/status",

    srcs = ["mlir_pass_instrumentation_test.cc"],
    deps = [
        ":mlir_pass_instrumentation",
        "//tensorflow/compiler/mlir/tf2xla/api/v1:compile_mlir_util_no_tf_dialect_passes",
        "//tensorflow/core:test",
        "@com_google_googletest//:gtest_main",
    ],
)

cc_library(
    name = "legalize_tf_mlir",
    srcs = ["legalize_tf_mlir.cc"],
    hdrs = ["legalize_tf_mlir.h"],
    deps = [

        ear.archiveExtension.get() == Ear.EAR_EXTENSION
    }

    def "correct default deployment descriptor"() {
        when:
        ear.deploymentDescriptor = new DefaultDeploymentDescriptor(null, objectFactory)
        def d = makeDeploymentDescriptor(ear)

        then:
        checkDeploymentDescriptor(d)
    }

    def "correct default deployment descriptor initialized from null"() {
        when:

# Regression test for Issue #62663: we would filter out the toolchain and
# main modules from the build list incorrectly, leading to the workspace
# modules being checked for correct sums. Specifically this would happen when
# the module name sorted after the virtual 'go' version module name because
# it could not get chopped off when we removed the MainModules.Len() modules
# at the beginning of the build list and we would remove the go module instead.

go mod verify

    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,

// pat. If f returns a non-nil error, possiblyConflictingPatterns returns immediately
// with that error.
//
// To be correct, possiblyConflictingPatterns must include all patterns that
// might conflict. But it may also include patterns that cannot conflict.
// For instance, an implementation that returns all registered patterns is correct.
// We use this fact throughout, simplifying the implementation by returning more
// patterns that we might need to.

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",