}
      }
    }
  }
  return indexes;
}

// Creates a slice of the tensorlist `input_list`, starting from
// [start_index, 0, ...0], with size [size, -1, ...-1].
//
// Requires that `start_index` and `size` are scalar tensors and
// `item_position_shape` is a 1-D tensor with only one element equal to the rank
// of an item in the tensorlist.

	if nilOrEqual((*string)(to.Group), "") && nilOrEqual((*string)(to.Kind), gvk.Service.Kind) {
		// Service
		if to.Port == nil {
			// "Port is required when the referent is a Kubernetes Service."
			return nil, &ConfigError{Reason: InvalidDestination, Message: "port is required in backendRef"}
		}
		if strings.Contains(string(to.Name), ".") {

  "tf.TPUReplicateMetadata"() {_xla_compile_device_type = "TPU", _replication_info = "replicate", device = "/device:TPU:0", topology = "topology"} : () -> ()
  func.return
}


// -----


// Test cluster with bad `num_replicas` attribute.
func.func @bad_num_replicas() {
  // expected-error@+1 {{requires 'num_replicas' int attribute to be at least 1}}

	if restartCPULim || restartCPUReq || restartMemLim {
		// resize policy requires this container to restart
		changes.ContainersToKill[kubeContainerStatus.ID] = containerToKillInfo{
			name:      kubeContainerStatus.Name,
			container: &pod.Spec.Containers[containerIdx],
			message:   fmt.Sprintf("Container %s resize requires restart", container.Name),
		}

	ErrAuthHeaderEmpty: {
		Code:           "InvalidArgument",
		Description:    "Authorization header is invalid -- one and only one ' ' (space) required.",
		HTTPStatusCode: http.StatusBadRequest,
	},
	ErrMissingDateHeader: {
		Code:           "AccessDenied",
		Description:    "AWS authentication requires a valid Date or x-amz-date header",
		HTTPStatusCode: http.StatusBadRequest,
	},
	ErrInvalidQuerySignatureAlgo: {

// is not supported in TensorFlow because TensorFlow requires filters in the
// HWIO data format.
//
// Motivation to prepare for the TFLite legalization before the actual
// legalization is to exploit constant folding opportunities in any newly
// created ops by leveraging constant folding support for the TensorFlow ops.
// This way TFLite can be used as a serialization format only and does not

import org.gradle.internal.reflect.Instantiator
import org.gradle.process.ExecOperations
import org.gradle.test.fixtures.dsl.GradleDsl
import org.gradle.test.fixtures.file.TestFile
import org.gradle.test.precondition.Requires
import org.gradle.test.preconditions.IntegTestPreconditions
import org.gradle.tooling.events.FinishEvent
import org.gradle.tooling.events.OperationCompletionListener
import org.gradle.util.internal.ToBeImplemented

	}

	switch *schema.XListType {
	case "map":
		// ensure all map keys are required or have a default
		isRequired := make(map[string]bool, len(schema.Items.Schema.Required))
		for _, required := range schema.Items.Schema.Required {
			isRequired[required] = true
		}

		for _, k := range schema.XListMapKeys {
			obj, ok := schema.Items.Schema.Properties[k]
			if !ok {

)

tf_cuda_cc_test(
    name = "pjrt_compile_util_test",
    srcs = ["pjrt_compile_util_test.cc"],
    tags = [
        "config-cuda-only",
        "no_oss",  # This test only runs with GPU.
        "requires-gpu-nvidia",
        "xla",
    ],
    deps = [
        ":pjrt_compile_util",
        ":test_util",
        ":xla_gpu_jit",
        "//tensorflow/cc:function_ops",
        "//tensorflow/cc:math_ops",

		return err
	}
	out.CertSANs = *(*[]string)(unsafe.Pointer(&in.CertSANs))
	// WARNING: in.TimeoutForControlPlane requires manual conversion: does not exist in peer-type
	return nil
}

func autoConvert_v1beta4_Arg_To_kubeadm_Arg(in *Arg, out *kubeadm.Arg, s conversion.Scope) error {
	out.Name = in.Name
	out.Value = in.Value