absl::StatusOr<FunctionDef> TFRDecomposeContext::ExpandNode(
    const NodeDef& node_def, StringPiece func_name) {
  const OpDef* op_def;
  TF_RETURN_IF_ERROR(OpRegistry::Global()->LookUpOpDef(node_def.op(), &op_def));
  DataTypeVector input_dtys, output_dtys;
  TF_RETURN_IF_ERROR(InputTypesForNode(node_def, *op_def, &input_dtys));
  TF_RETURN_IF_ERROR(OutputTypesForNode(node_def, *op_def, &output_dtys));

  absl::StatusOr<OpKernelRunner> runner = OpKernelRunner::Create(
      node_def->get()->op(), node_def->get()->name(), host_cpu, operands.size(),
      [&](tensorflow::AttrValueMap* attr_value_map) {
        *attr_value_map = node_def->get()->attr();
        return absl::OkStatus();
      },
      fallback_state.device_manager(),

    const FunctionLibraryDefinition& flib_def) {
  for (const std::string& func_name : flib_def.ListFunctionNames()) {
    const FunctionDef* func_def = flib_def.Find(func_name);
    for (const NodeDef& node_def : func_def->node_def()) {
      if (node_def.op() == kPartitionedCall) return true;
    }
  }
  return false;
}

}  // namespace

bool IsSupportedByNonReplicatedBridge(

// ShapedType for the leading values with ShapedType in the results of the
// nodes. Set it to true if the returned NodeDef will be executed by the linked
// TF Eager runtime.
absl::StatusOr<std::unique_ptr<NodeDef>> ConvertTFDialectOpToNodeDef(
    mlir::Operation* inst, llvm::StringRef name,
    bool ignore_unregistered_attrs);

}  // namespace tensorflow

#include "tensorflow/compiler/mlir/tensorflow/translate/mlir_roundtrip_flags.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/graph.pb.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/graph/graph.h"

namespace tensorflow {
namespace tf2xla {
namespace v2 {

// Given an MLIR module, returns a GraphDef.

#include "tensorflow/compiler/mlir/tensorflow/translate/mlir_roundtrip_flags.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/graph.pb.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/graph/graph.h"

namespace tensorflow {

ABSL_DEPRECATED("Use tensorflow::tf2xla::api::ConvertMlirToGraphdef instead.")
// Given an MLIR module, returns a GraphDef.

// dialect back into a TensorFlow valid op name.
absl::StatusOr<llvm::StringRef> GetTensorFlowOpName(llvm::StringRef);

// Converts an MLIR operation to TensorFlow NodeDef with given node name. This
// name should be unique to the graph it is being inserted into.
absl::StatusOr<std::unique_ptr<NodeDef>> GetOperationNodeDef(
    mlir::Operation* inst, llvm::StringRef name);

// Converts MLIR attributes with values to their tensorflow equivalent.

	// TODO: Factor out "stats.Provider" from Kubelet so we don't have a cyclic dependency
	volumeStatsAggPeriod := time.Second * 10
	kb.resourceAnalyzer = stats.NewResourceAnalyzer(kb, volumeStatsAggPeriod, kb.recorder)
	nodeRef := &v1.ObjectReference{
		Kind:      "Node",
		Name:      string(kb.nodeName),
		UID:       types.UID(kb.nodeName),
		Namespace: "",
	}

				OOMScoreAdj:      ptr.To[int32](0),
			},

			Client:      client,
			Proxier:     &FakeProxier{},
			Broadcaster: broadcaster,
			Recorder:    recorder,
			NodeRef: &v1.ObjectReference{
				Kind:      "Node",
				Name:      nodeName,
				UID:       types.UID(nodeName),
				Namespace: "",
			},
		},
	}
}

func (hp *HollowProxy) Run() error {