}

func (c *Controller) NewEndpointBuilder(pod *v1.Pod) *EndpointBuilder {
	var locality, sa, namespace, hostname, subdomain, ip, node string
	var podLabels labels.Instance
	if pod != nil {
		locality = c.getPodLocality(pod)
		sa = kube.SecureNamingSAN(pod, c.meshWatcher.Mesh())
		podLabels = pod.Labels
		namespace = pod.Namespace
		subdomain = pod.Spec.Subdomain
		if subdomain != "" {
			hostname = pod.Spec.Hostname

#include "tensorflow/core/lib/monitoring/cell_reader.h"
#include "tensorflow/core/platform/resource_loader.h"
#include "tsl/lib/core/status_test_util.h"
#include "tsl/platform/status.h"

namespace tensorflow {
namespace tf2xla {
namespace v2 {
namespace {

using ::mlir::DialectRegistry;
using ::mlir::MLIRContext;
using ::mlir::ModuleOp;
using ::mlir::OwningOpRef;
using ::mlir::WalkResult;
using ::mlir::func::FuncOp;

#include <string>

#include "mlir/IR/Value.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/utils/attribute_utils.h"
#include "tensorflow/core/util/device_name_utils.h"

namespace mlir {
namespace TF {

namespace {

const char kDeviceAttr[] = "device";
const char kDeviceGpu[] = "GPU";

std::optional<std::string> GetOpDevice(mlir::Operation *op) {

#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "tensorflow/lite/core/model_builder.h"
#include "tensorflow/lite/tools/optimize/reduced_precision_support.h"

namespace mlir {
namespace lite {
namespace {


TEST(SparsifyModelTest, MetadataIsAddedToOutputModel) {
  std::string expected_key = tflite::optimize::kTfLiteReducedPrecisionKey;
  std::string expected_value = "test_data";

		configKey: configKey{
			namespace: "dns",
			name:      "dns-round-robin-2",
		},
	}
	store.addInstances(cpKey, instances)

	assert.Equal(t, store.getByKey(instancesKey{
		hostname:  "example.com",
		namespace: "dns",
	}), expected)
	assert.Equal(t, store.getByKey(instancesKey{
		hostname:  "example.com",
		namespace: otherNs.Namespace,
	}), otherNsExpected)

#include "tensorflow/c/experimental/ops/gen/common/case_format.h"

#include "tensorflow/core/platform/str_util.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace generator {

namespace {

enum CaseFormatType {
  LOWER_CAMEL,
  UPPER_CAMEL,
  LOWER_SNAKE,
  UPPER_SNAKE,
};

string FormatStringCase(const string &str, CaseFormatType to,

#include "tensorflow/c/experimental/ops/gen/cpp/views/arg_view.h"

#include "tensorflow/c/experimental/ops/gen/model/arg_spec.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace generator {
namespace cpp {

ArgView::ArgView(ArgSpec arg) : arg_(arg) {}

string ArgView::VariableName() const { return arg_.name(); }

string ArgView::SetterMethod() const {
  if (IsList()) {

#include "tensorflow/c/experimental/ops/gen/common/case_format.h"

#include "tensorflow/core/platform/test.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace generator {

namespace {

// For each test case, we manually construct the 4 variations in string case and
// test all 16 conversions: from and to each of the 4 string case variations.
struct Variations {

	listConfigMap := func(namespace string, opts metav1.ListOptions) (runtime.Object, error) {
		return kubeClient.CoreV1().ConfigMaps(namespace).List(context.TODO(), opts)
	}
	watchConfigMap := func(namespace string, opts metav1.ListOptions) (watch.Interface, error) {
		return kubeClient.CoreV1().ConfigMaps(namespace).Watch(context.TODO(), opts)
	}
	newConfigMap := func() runtime.Object {

	listSecret := func(namespace string, opts metav1.ListOptions) (runtime.Object, error) {
		return kubeClient.CoreV1().Secrets(namespace).List(context.TODO(), opts)
	}
	watchSecret := func(namespace string, opts metav1.ListOptions) (watch.Interface, error) {
		return kubeClient.CoreV1().Secrets(namespace).Watch(context.TODO(), opts)
	}
	newSecret := func() runtime.Object {