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

bool GetFunctionDef(TF_Function* func, tensorflow::FunctionDef* func_def);

bool GetAttrValue(TF_Operation* oper, const char* attr_name,
                  tensorflow::AttrValue* attr_value, TF_Status* s);

// Returns a sorted vector of std::pair<function_name, gradient_func> from
// graph_def.library().gradient()

  return static_cast<TF_Operation*>(static_cast<void*>(node));
}

string OutputName(const TF_Output& output) {
  return StrCat(output.oper->node.name(), ":", output.index);
}

const tensorflow::AttrValue* GetAttrValue(TF_Operation* oper,
                                          const char* attr_name,
                                          TF_Status* status) {
  const tensorflow::AttrValue* attr = oper->node.attrs().Find(attr_name);

  tensorflow::AttrValue attr_value;
  ASSERT_TRUE(GetAttrValue(feed, "dtype", &attr_value, s)) << TF_Message(s);
  EXPECT_EQ(attr_value.type(), tensorflow::DT_INT32);

  // Test not found errors in TF_Operation*() query functions.
  EXPECT_EQ(-1, TF_OperationOutputListLength(feed, "bogus", s));
  EXPECT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(s));

  ASSERT_FALSE(GetAttrValue(feed, "missing", &attr_value, s));

  EXPECT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  if (ret) ret = func_def->ParseFromArray(buffer->data, buffer->length);
  TF_DeleteBuffer(buffer);
  TF_DeleteStatus(s);
  return ret;
}

bool GetAttrValue(TF_Operation* oper, const char* attr_name,
                  tensorflow::AttrValue* attr_value, TF_Status* s) {
  TF_Buffer* buffer = TF_NewBuffer();
  TF_OperationGetAttrValueProto(oper, attr_name, buffer, s);