// This is a brief description of the pass.
    return "Apply graph optimizations such as fusing and constant folding to "
           "prepare lifting.";
  }

  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<TF::TensorFlowDialect, arith::ArithDialect>();
  }

  void runOnOperation() override;

 private:
  Option<OpSet> op_set_{
      *this, "target-opset", llvm::cl::init(OpSet::TF),

struct DecomposeReduceDatasetPass
    : public impl::DecomposeReduceDatasetPassBase<DecomposeReduceDatasetPass> {
  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<tf_device::TensorFlowDeviceDialect>();
  }

  void runOnOperation() override;
};

// Create the AnonymousIterator for `reduce_dataset` with `dataset_types` using
// `builder`.

  StringRef getDescription() const final {
    // This is a brief description of the pass.
    return "Apply converting Tensorflow Xla ops to non-xla ops.";
  }

  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<TF::TensorFlowDialect, arith::ArithDialect>();
  }

  void runOnOperation() override;
};

// Generate an einsum equation from the given DotDimensionNumber.
std::string CreateEinsumEquation(

        DefaultImplicitInputRegistrar registrar = new DefaultImplicitInputRegistrar();
        ImplicitInputsCapturingInstantiator instantiator = findInputCapturingInstantiator(action);
        if (instantiator != null) {
            action = action.withInstantiator(instantiator.capturing(registrar));
        }
        // First step is to find an entry with the explicit inputs in the cache

			log.Debugf("Service %s/%s from registry %s ignored as it is already added", s.Attributes.Namespace, s.Hostname, s.Attributes.ServiceRegistry)
			return
		}
		// We do not merge k8s service with any other services from other registries
		if existing.Attributes.ServiceRegistry == provider.Kubernetes && s.Attributes.ServiceRegistry != provider.Kubernetes {

		}
	}))
	t.Cleanup(app.Close)
	envoyPort, err := strconv.Atoi(strings.Split(envoyServer.URL, ":")[2])
	if err != nil {
		t.Fatal(err)
	}
	registry, err := initializeMonitoring()
	if err != nil {
		t.Fatal(err)
	}
	server := &Server{
		registry: registry,
		prometheus: &PrometheusScrapeConfiguration{
			Port: strings.Split(app.URL, ":")[2],
		},
		envoyStatsPort: envoyPort,

  StringRef getDescription() const final {
    return "Fallback TF-Quantization-unsupported ops to TFLite Flex ops.";
  }

  void getDependentDialects(DialectRegistry &registry) const override {
    registry.insert<TFL::TensorFlowLiteDialect>();
  }

 private:
  // The mode of TF Quantization, might indicate different users/devices.
  Option<std::string> mode_{*this, "mode",

            "Lower threshold of the constant size for unfreezing. Constants "
            "smaller than this value will not be converted to variables."));
  }

  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<TF::TensorFlowDialect,
                    tf_saved_model::TensorFlowSavedModelDialect>();
  }

  // Lower-bound threshold for the size of the constant in bytes. Constants

	"k8s.io/apimachinery/pkg/runtime"
	"k8s.io/apimachinery/pkg/runtime/schema"
	"k8s.io/apimachinery/pkg/util/sets"
	"k8s.io/apimachinery/pkg/util/wait"
	"k8s.io/apiserver/pkg/registry/generic"
	genericregistry "k8s.io/apiserver/pkg/registry/generic/registry"
	"k8s.io/apiserver/pkg/server"
	"k8s.io/apiserver/pkg/server/healthz"
	"k8s.io/apiserver/pkg/server/options/encryptionconfig"

	"k8s.io/client-go/tools/events"
	"k8s.io/client-go/util/retry"
	"k8s.io/kubernetes/pkg/api/legacyscheme"
	api "k8s.io/kubernetes/pkg/apis/core"
	"k8s.io/kubernetes/pkg/registry/core/rangeallocation"
	"k8s.io/kubernetes/pkg/registry/core/service/portallocator"
)

// See ipallocator/controller/repair.go; this is a copy for ports.
type Repair struct {
	interval      time.Duration
	serviceClient corev1client.ServicesGetter