mutex_lock l(graph->mu);
  std::vector<const tensorflow::Edge*> control_edges;
  for (const tensorflow::Edge* edge : op->node.in_edges()) {
    if (!edge->IsControlEdge()) continue;
    control_edges.push_back(edge);
  }
  for (const tensorflow::Edge* edge : control_edges) {
    graph->graph.RemoveControlEdge(edge);
  }
}

void TF_SetRequireShapeInferenceFns(TF_Graph* graph, bool require) {

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

  NodeDef node_def_neg;
  ASSERT_TRUE(GetNodeDef(neg, &node_def_neg));
  EXPECT_EQ(string("add"), node_def_neg.input(0));

  // update edge of neg
  TF_UpdateEdge(graph, TF_Output{one, 0}, TF_Input{neg, 0}, s);

  ASSERT_TRUE(GetNodeDef(neg, &node_def_neg));
  EXPECT_EQ(string("one:0"), node_def_neg.input(0));

  // Clean up
  TF_DeleteGraph(graph);

        const auto& v = a_edges.insert({iter->second, arg.name()});
        ASSERT_TRUE(v.second) << "Duplicate edge " << iter->second << " -> "
                              << arg.name() << ". fdef: " << fdef.DebugString();
      } else {
        const auto& v = a_edges.insert({arg.name(), arg.name()});
        ASSERT_TRUE(v.second) << "Duplicate edge " << arg.name() << " -> "
                              << arg.name() << ". fdef: " << fdef.DebugString();