auto func = arg.getParentRegion()->getParentOfType<FuncOp>();

  auto node_def = std::make_unique<NodeDef>();
  if (!name.empty())
    node_def->set_name(std::string(ParseTensorName(name.str()).node()));
  else
    node_def->set_name(
        std::string(op_to_name_.GetUniqueName(func.getName().str())));

  node_def->set_op(FunctionLibraryDefinition::kArgOp);

  auto func = arg.getParentRegion()->getParentOfType<FuncOp>();

  auto node_def = std::make_unique<NodeDef>();
  if (!name.empty())
    node_def->set_name(std::string(ParseTensorName(name.str()).node()));
  else
    node_def->set_name(
        std::string(op_to_name_.GetUniqueName(func.getName().str())));

  node_def->set_op(FunctionLibraryDefinition::kArgOp);

    std::vector<std::string> terminal_nodes;
    terminal_nodes.reserve(specs.outputs.size() + specs.inputs.size());
    for (const auto& output : specs.outputs) {
      terminal_nodes.push_back(std::string(ParseTensorName(output).node()));
    }
    for (const auto& control_output : specs.control_outputs) {
      terminal_nodes.push_back(std::string(control_output));
    }
    for (const auto& input : specs.inputs) {

    TensorId tensor = ParseTensorName(input.first);
    auto remapped_it = remapped_feeds_.find(tensor);
    if (remapped_it != remapped_feeds_.end()) {
      TF_RETURN_IF_ERROR(add_node(remapped_it->second));
    } else {
      TF_RETURN_IF_ERROR(add_node(tensor.node()));
    }
  }

  for (const auto& output : specs_.outputs) {
    TensorId tensor = ParseTensorName(output);

    (*feature_map)["x"].mutable_float_list()->add_value(i);
    input.flat<tstring>()(i) = example.SerializeAsString();
  }

  const tensorflow::string input_op_name(
      tensorflow::ParseTensorName(input_name).first);
  TF_Operation* input_op =
      TF_GraphOperationByName(graph, input_op_name.c_str());
  ASSERT_TRUE(input_op != nullptr);
  Status status;