TF_ATTRIBUTE_NOINLINE Status BuildHostGraphForIfNode(
    const string& xla_cluster_attr_name,
    const string& outside_compilation_attr_name, const string& xla_cluster_name,
    const string& if_node_name, const string& host_transfer_key,
    const string& host_graph_func_name, FunctionLibraryDefinition* fld,
    const string& then_branch_host_func_name,
    const string& else_branch_host_func_name) {
  Graph host_graph(fld);

	const operation = "version"
	defer recordOperation(operation, time.Now())

	out, err := in.service.Version(ctx, apiVersion)
	recordError(operation, err)
	return out, err
}

func (in instrumentedRuntimeService) Status(ctx context.Context, verbose bool) (*runtimeapi.StatusResponse, error) {
	const operation = "status"
	defer recordOperation(operation, time.Now())

  template <typename T>
  const T& get() const {
    assert(type_ == EnumValueOf<T>::value);
    return UnionAccess<T>::unsafe_reference(*this);
  }

  /// Retrieves underlying value from a TaggedValue with type INT64.
  const Int64& i64() const { return get<impl::Int64>(); }

  /// Retrieves underlying value from a TaggedValue with type FLOAT32.
  const Float32& f32() const { return get<impl::Float32>(); }

}

template <class Tkey, class Tvalue>
bool EqualProtoMap(const ::tensorflow::protobuf::Map<Tkey, Tvalue>& a,
                   const ::tensorflow::protobuf::Map<Tkey, Tvalue>& b,
                   const std::function<string(const Tkey&)>& key_to_string,
                   const std::function<string(const Tvalue&)>& value_to_string,
                   const std::function<bool(const Tkey&, const Tvalue&,

      // LINT.IfChange
      "quantize_qat_model",
      [](const absl::string_view src_saved_model_path,
         const absl::string_view dst_saved_model_path,
         const QuantizationOptions& quantization_options,
         const std::vector<std::string>& signature_keys,
         const absl::flat_hash_map<std::string, SignatureDef>&
             signature_def_map,
         const PyFunctionLibrary& py_function_library) -> absl::Status {

      continue;
    }
    const auto entry = AttrTypeName(attr.type());
    const auto attr_type_name = entry.first;
    const bool use_const = entry.second;
    const string camel_case_name = ToCamelCase(api_def_attr.rename_to());
    const string suffix =
        (camel_case_name == op_name || camel_case_name == "Attrs") ? "_" : "";
    const string attr_func_def =

  // compatible, update d1 with a more specific one.
  // TODO(sanjoy): Cache DeviceNameUtils::ParsedName inside device_info_cache.
  const auto is_multiple_devices =
      [&](const jit::DeviceId& d0, std::optional<jit::DeviceId>* d1) -> bool {
    const absl::string_view name0 = device_info_cache.GetNameFor(d0);
    const absl::string_view name1 = device_info_cache.GetNameFor(d1->value());

    DeviceNameUtils::ParsedName parsed0, parsed1;

    const std::vector<::tensorflow::proto_splitter::ChunkInfo>& chunks_info,
    const RepeatedPtrField<::tensorflow::proto_splitter::FieldIndex>&
        field_tags);

// Hashes the contents of `graph_def`.
absl::StatusOr<uint64_t> HashGraphDef(
    tensorflow::GraphDef* graph_def,
    const ::tensorflow::proto_splitter::ChunkedMessage& chunked_message,
    riegeli::RecordReader<riegeli::FdReader<>>& reader,

)

// Image manager event reason list
const (
	InvalidDiskCapacity = "InvalidDiskCapacity"
	FreeDiskSpaceFailed = "FreeDiskSpaceFailed"
)

// Probe event reason list
const (
	ContainerUnhealthy    = "Unhealthy"
	ContainerProbeWarning = "ProbeWarning"
)

// Pod worker event reason list
const (
	FailedSync = "FailedSync"
)

// Config event reason list
const (
	FailedValidation = "FailedValidation"
)

    const std::vector<std::string>& target_nodes,
    std::vector<Tensor>* outputs) {
  tensorflow::RunMetadata run_metadata;
  return Run(tensorflow::RunOptions(), inputs, output_names, target_nodes,
             outputs, &run_metadata);
}

Status FakeSession::Run(
    const tensorflow::RunOptions& run_options,
    const std::vector<std::pair<std::string, Tensor>>& inputs,