void, FuncT, tensorflow::NodeDef&>>>
void MutateNodeDefs(tensorflow::GraphDef& graph_def, FuncT&& func) {
  for (tensorflow::NodeDef& node_def : *graph_def.mutable_node()) {
    func(node_def);
  }

  for (tensorflow::FunctionDef& function_def :
       *graph_def.mutable_library()->mutable_function()) {
    for (tensorflow::NodeDef& node_def : *function_def.mutable_node_def()) {

                absl::StrCat(node_def.name(), "@", func_name));
          }
        }
      }
    }
  }

  // Upgrade nodes in the GraphDef.
  for (auto& node_def : *gdef.mutable_node()) {
    const OpDef* op_def = nullptr;
    TF_RETURN_IF_ERROR(flib_def->LookUpOpDef(node_def.op(), &op_def));
    // TODO(b/197144710): improve the shared_name attr, each op may use the
    // shared_name differently.

void GetNodeNameToNodeDefMap(
    GraphDef* graph_def,
    std::unordered_map<string, NodeDef*>* name_to_node_map) {
  for (size_t i = 0; i < graph_def->node_size(); i++) {
    NodeDef* node = graph_def->mutable_node(i);
    (*name_to_node_map)[node->name()] = node;
  }
}

// Strips off the tensor part of the tensor_name to get the node_name.
const string GetNodeNameFromTensorName(string tensor_name) {

  auto dequeue0 =
      QueueDequeue(root.WithOpName(kDequeueOp0), q0, {DataType::DT_FLOAT});

  GraphDef graph_def;
  TF_EXPECT_OK(root.ToGraphDef(&graph_def));
  for (auto& node : *graph_def.mutable_node()) {
    node.set_device("/cpu:0");
  }
  SessionOptions sess_options;
  sess_options.config.mutable_graph_options()->set_build_cost_model(1);
  std::unique_ptr<Session> session(NewSession(sess_options));

// ordered.
void SortControlInputs(GraphDef* gdef) {
  int64_t num_nodes = gdef->node_size();
  for (int64_t i = 0; i < num_nodes; ++i) {
    NodeDef* node = gdef->mutable_node(i);
    // Stable sort control inputs and leave the order of data inputs unchanged.
    std::stable_sort(node->mutable_input()->begin(),
                     node->mutable_input()->end(),

// - Replacing LegacyFedInput nodes with Placeholder nodes if
//   convert_legacy_fed_inputs option is enabled.
Status PreprocessGraphDef(const GraphImportConfig* specs, GraphDef* graph_def) {
  for (auto& node_def : *graph_def->mutable_node()) {
    // TODO(hinsu): Completely deprecate support for LegacyFedInput ops. One
    // solution could be have a tool to let users upgrade old serialized graphs.
    if (specs && specs->convert_legacy_fed_inputs &&

      testing::ZeroArgInputSignature();
  *saved.mutable_output_signature() = testing::ZeroReturnOutputSignature();
  FunctionDef func = FuncDefWithNumInputsOutputs(0, 0);
  *func.mutable_signature()->mutable_name() = func_name;

  {
    std::unique_ptr<TFConcreteFunction> result;
    Status status =
        internal::LoadTFConcreteFunction(saved, &func, {}, context(), &result);

    auto& attr = iter.second;
    if (attr.has_func()) {
      try_use_original_func_name(attr.mutable_func()->mutable_name());
    } else if (attr.has_list()) {
      for (auto& func_attr : *attr.mutable_list()->mutable_func()) {
        try_use_original_func_name(func_attr.mutable_name());
      }
    }
  }
}

Status Exporter::AddInstructionNode(Operation* inst) {
  std::unique_ptr<NodeDef> node_def;

    auto& attr = iter.second;
    if (attr.has_func()) {
      try_use_original_func_name(attr.mutable_func()->mutable_name());
    } else if (attr.has_list()) {
      for (auto& func_attr : *attr.mutable_list()->mutable_func()) {
        try_use_original_func_name(func_attr.mutable_name());
      }
    }
  }
}

Status Exporter::AddInstructionNode(Operation* inst) {
  std::unique_ptr<NodeDef> node_def;

      result.Append(std::move(pad));
    }
    AppendBufferData(result);
    std::string result_str = std::string(std::move(result));
    auto mutable_model = tflite::GetMutableModel(result_str.data());
    bool ret = UpdateBufferOffsets(mutable_model);
    if (!ret) {
      return std::nullopt;
    }
    return result_str;
  }
  return std::string(result);
}