using tensorflow::tracing::TracingOperation;
using tensorflow::tracing::TracingTensorHandle;

namespace {

void RegisterDialects(mlir::MLIRContext& ctx) {
  mlir::DialectRegistry registry;
  mlir::RegisterAllTensorFlowDialects(registry);
  ctx.appendDialectRegistry(registry);
  ctx.loadAllAvailableDialects();
}

Status ConvertDataTypeToTensor(tensorflow::DataType dtype, Builder builder,
                               Type* type) {

	// Check that system has "Volume level setting" set.
	expected := "The registry state of NtfsDisable8dot3NameCreation is 2, the default (Volume level setting)"
	if !strings.Contains(string(out), expected) {
		// Windows 10 version of fsutil has different output message.
		expectedWindow10 := "The registry state is: 2 (Per volume setting - the default)"
		if !strings.Contains(string(out), expectedWindow10) {

type LNumber float64
func (LNumber) assertFunction() *LFunction
type LFunction struct {
	GFunction LGFunction
}
type LGFunction func(*LState)
type LState struct {
	reg *registry
}
type registry struct {
	alloc *allocator
}
type allocator struct {
	_ [int(preloadLimit)]int
}

// Test that we don't crash when type-checking composite literals
// containing errors in the type.
var issue27346

			apiVersion: %s
			certificatesDir: /etc/kubernetes/pki
			clusterName: LeCluster
			controllerManager: {}
			etcd:
			  local:
			    dataDir: /var/lib/etcd
			imageRepository: registry.k8s.io
			kind: ClusterConfiguration
			kubernetesVersion: 1.2.3
			networking:
			  dnsDomain: cluster.local
			  serviceSubnet: 10.96.0.0/12
			scheduler: {}
		`, kubeadmapiv1.SchemeGroupVersion.String())),

};

class PrepareCompositeFunctionsPass
    : public impl::PrepareCompositeFunctionsPassBase<
          PrepareCompositeFunctionsPass> {
  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<TFL::TensorFlowLiteDialect>();
  }

 public:
  MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(PrepareCompositeFunctionsPass)

  explicit PrepareCompositeFunctionsPass() {}

// training quantization simpler.
class PrepareQuantizePass
    : public PassWrapper<PrepareQuantizePass, OperationPass<func::FuncOp>> {
  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<TF::TensorFlowDialect, ::mlir::quant::QuantizationDialect,
                    ::mlir::quantfork::QuantizationForkDialect>();
  }

 public:

    private static final Object[] NO_ARG = new Object[0];

    public CallInterceptingMetaClass(
        MetaClassRegistry registry,
        Class<?> javaClass,
        MetaClass adaptee,
        InstrumentedGroovyCallsTracker callsTracker,
        CallInterceptorResolver interceptorResolver
    ) {
        super(registry, javaClass);
        this.adaptee = adaptee;
        this.callsTracker = callsTracker;

}

func (conn *Connection) XdsConnection() *xds.Connection {
	return &conn.Connection
}

func (conn *Connection) Proxy() *model.Proxy {
	return conn.proxy
}

// Event represents a config or registry event that results in a push.
type Event struct {
	// pushRequest PushRequest to use for the push.
	pushRequest *model.PushRequest

		RecordTime: store.clock.Now(),
	}
	b.ResetTimer()
	for i := 0; i < b.N; i++ {
		store.updateCache(add)
	}
}

func TestHistogramCacheReadWait(t *testing.T) {
	registry := k8smetrics.NewKubeRegistry()
	if err := registry.Register(metrics.WatchCacheReadWait); err != nil {
		t.Errorf("unexpected error: %v", err)
	}
	ctx := context.Background()
	testedMetrics := "apiserver_watch_cache_read_wait_seconds"

			Labels:         labels,
			TLSMode:        tlsMode,
			ServiceAccount: sa,
			// Workload entry config name is used as workload name, which will appear in metric label.
			// After VM auto registry is introduced, workload group annotation should be used for workload name.
			WorkloadName: configKey.name,
			Namespace:    configKey.namespace,
		},
		Service:     service,
		ServicePort: convertPort(servicePort),