ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  EXPECT_EQ(TF_GraphNumFunctions(func_graph_), 1);
  EXPECT_EQ(TF_GraphGetFunctions(func_graph_, funcs, 1, s_), 1);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  TF_GraphRemoveFunction(func_graph_, func_name_, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  EXPECT_EQ(TF_GraphNumFunctions(func_graph_), 0);

  gdef.set_function_name(func->record->fdef().signature().name());
  gdef.set_gradient_func(grad->record->fdef().signature().name());
  status->status = g->graph.AddGradientDef(std::move(gdef));
}

int TF_GraphNumFunctions(TF_Graph* g) {
  tensorflow::mutex_lock l(g->mu);
  return g->graph.flib_def().num_functions();
}

int TF_GraphGetFunctions(TF_Graph* g, TF_Function** funcs, int max_func,

  GetFunctionDef(func, &fdef);
  return fdef.signature().name();
}

TEST_F(CApiFunctionTest, GetFunctionsFromGraph) {
  TF_Function* funcs[2];

  // Get functions from empty graph
  EXPECT_EQ(TF_GraphNumFunctions(host_graph_), 0);
  TF_GraphGetFunctions(host_graph_, nullptr, 0, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  // Define a function and add it to host_graph_
  TF_Function* func0;

// Returns the number of TF_Functions registered in `g`.
TF_CAPI_EXPORT extern int TF_GraphNumFunctions(TF_Graph* g);

// Fills in `funcs` with the TF_Function* registered in `g`.
// `funcs` must point to an array of TF_Function* of length at least
// `max_func`. In usual usage, max_func should be set to the result of
// TF_GraphNumFunctions(g). In this case, all the functions registered in