bool IsPlaceholder(const tensorflow::NodeDef& node_def);

bool IsScalarConst(const tensorflow::NodeDef& node_def, int v);

bool IsAddN(const tensorflow::NodeDef& node_def, int n);

bool IsNeg(const tensorflow::NodeDef& node_def, const string& input);

bool GetGraphDef(TF_Graph* graph, tensorflow::GraphDef* graph_def);

bool GetNodeDef(TF_Operation* oper, tensorflow::NodeDef* node_def);

  node_def.set_name(op->Name());
  node_def.set_op(op->Name());
  for (int i = 0; i < num_inputs; ++i) {
    node_def.add_input("dummy_input");
  }
  OperationFromInterface(op)->Attrs().FillAttrValueMap(node_def.mutable_attr());

  const tensorflow::OpRegistrationData* op_reg_data;
  status->status =
      tensorflow::OpRegistry::Global()->LookUp(node_def.op(), &op_reg_data);

      }
    }
  }
  return found_dtype && found_value;
}

bool IsAddN(const tensorflow::NodeDef& node_def, int n) {
  if (node_def.op() != "AddN" || node_def.name() != "add" ||
      node_def.input_size() != n) {
    return false;
  }
  bool found_t = false;
  bool found_n = false;
  for (const auto& attr : node_def.attr()) {
    if (attr.first == "T") {
      if (attr.second.type() == tensorflow::DT_INT32) {

      "      }"
      "    }"
      "    node_def {"
      "      name: 'read0'"
      "      op: 'ReadVariableOp'"
      "      input: 'var'"
      "      device: '/job:localhost/replica:0/task:0/device:CPU:0'"
      "      attr {"
      "        key: 'dtype'"
      "        value {"
      "          type: DT_FLOAT"
      "        }"
      "      }"
      "    }"
      "    node_def {"
      "      name: 'read1'"

    for (const NodeDef& node_def : fdef.node_def()) {
      for (int i = 0; i < node_def.input_size(); ++i) {
        const string& in = node_def.input(i);
        const auto& v =
            a_edges.insert({in, strings::StrCat(node_def.name(), ":", i)});
        ASSERT_TRUE(v.second) << "Duplicate edge " << in << " -> "
                              << strings::StrCat(node_def.name(), ":", i)

  EXPECT_TRUE(neg == neg2);
  NodeDef node_def2;
  ASSERT_TRUE(GetNodeDef(neg2, &node_def2));
  EXPECT_EQ(node_def.DebugString(), node_def2.DebugString());

  TF_Operation* feed2 = TF_GraphOperationByName(graph, "feed");
  EXPECT_TRUE(feed == feed2);
  ASSERT_TRUE(GetNodeDef(feed, &node_def));
  ASSERT_TRUE(GetNodeDef(feed2, &node_def2));
  EXPECT_EQ(node_def.DebugString(), node_def2.DebugString());

                   "      output_arg {"
                   "        name: 'm'"
                   "        type: DT_FLOAT"
                   "      }"
                   "    }"
                   "    node_def {"
                   "      name: 'matmul'"
                   "      op: 'MatMul'"
                   "      input: 'a'"
                   "      input: 'b'"
                   "      device: '",

#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/function.pb.h"
#include "tensorflow/core/framework/graph_to_functiondef.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/framework/tensor.pb.h"  // NOLINT
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/graph/graph.h"

// Changes an attr value in the node_def Protocol Buffer and sets a status upon
// completion.
TF_CAPI_EXPORT extern void TF_SetAttr(TF_Graph* graph, TF_Operation* op,
                                      const char* attr_name,
                                      TF_Buffer* attr_value_proto,
                                      TF_Status* status);

// Clears the attr in the node_def Protocol Buffer and sets a status upon

      "    signature {"
      "      name: 'FunctionWith__OP_NAME__'"
      "      output_arg {"
      "        name: 'out'"
      "        type: DT_STRING"
      "      }"
      "    }"
      "    node_def {"
      "      name: 'error_op'"
      "      op: '__OP_NAME__'"
      "    }"
      "    ret {"
      "      key: 'out'"
      "      value: 'error_op:out'"
      "    }";