testing::ZeroArgInputSignature();
  *saved.mutable_output_signature() = testing::ZeroReturnOutputSignature();
  FunctionDef func = FuncDefWithNumInputsOutputs(0, 0);
  *func.mutable_signature()->mutable_name() = func_name;

  {
    std::unique_ptr<TFConcreteFunction> result;
    Status status =
        internal::LoadTFConcreteFunction(saved, &func, {}, context(), &result);

    auto& attr = iter.second;
    if (attr.has_func()) {
      try_use_original_func_name(attr.mutable_func()->mutable_name());
    } else if (attr.has_list()) {
      for (auto& func_attr : *attr.mutable_list()->mutable_func()) {
        try_use_original_func_name(func_attr.mutable_name());
      }
    }
  }
}

Status Exporter::AddInstructionNode(Operation* inst) {
  std::unique_ptr<NodeDef> node_def;

    auto& attr = iter.second;
    if (attr.has_func()) {
      try_use_original_func_name(attr.mutable_func()->mutable_name());
    } else if (attr.has_list()) {
      for (auto& func_attr : *attr.mutable_list()->mutable_func()) {
        try_use_original_func_name(func_attr.mutable_name());
      }
    }
  }
}

Status Exporter::AddInstructionNode(Operation* inst) {
  std::unique_ptr<NodeDef> node_def;

    %control_11 = tf_executor.island wraps "tf.LoadTPUEmbeddingAdagradParameters"(%outputs_2, %outputs_5) {config = "", num_shards = 1 : i64, shard_id = 0 : i64, table_id = -1 : i64, table_name = "table4"} : (tensor<8xf32>, tensor<8xf32>) -> ()
    tf_executor.fetch
  }
  return
}
// CHECK-LABEL: func @tpu_load_embedding_ops_sink_controls

     %3 = "tf.ReadVariableOp"(%arg3) {device = ""} : (tensor<*x!tf_type.resource<tensor<8xf32>>>) -> tensor<8xf32>
     "tf.LoadTPUEmbeddingAdagradParameters"(%2, %3) {config = "", num_shards = 1 : i64, shard_id = 0 : i64, table_id = -1 : i64, table_name = "table2"} : (tensor<8xf32>, tensor<8xf32>) -> ()

     %3 = "tf.ReadVariableOp"(%arg3) {device = ""} : (tensor<*x!tf_type.resource<tensor<8xf32>>>) -> tensor<8xf32>
     "tf.LoadTPUEmbeddingAdagradParameters"(%2, %3) {config = "", num_shards = 1 : i64, shard_id = 0 : i64, table_id = -1 : i64, table_name = "table2"} : (tensor<8xf32>, tensor<8xf32>) -> ()

    }

    @Managed
    abstract static class MutableName implements Named {
        abstract void setName(String name)
    }

    def "Named cannot have setName"() {
        when:
        extract MutableName

        then:
        def e = thrown Exception
        e.message == """Type ${fullyQualifiedNameOf(MutableName)} is not a valid managed type:

			}); err != nil {
				return err
			}
		}
	}

	return nil
}

// GetTables returns tables
func (m Migrator) GetTables() (tableList []string, err error) {
	err = m.DB.Raw("SELECT TABLE_NAME FROM information_schema.tables where TABLE_SCHEMA=?", m.CurrentDatabase()).
		Scan(&tableList).Error
	return
}

// CreateTable create table in database for values

void GetNodeNameToNodeDefMap(
    GraphDef* graph_def,
    std::unordered_map<string, NodeDef*>* name_to_node_map) {
  for (size_t i = 0; i < graph_def->node_size(); i++) {
    NodeDef* node = graph_def->mutable_node(i);
    (*name_to_node_map)[node->name()] = node;
  }
}

// Strips off the tensor part of the tensor_name to get the node_name.
const string GetNodeNameFromTensorName(string tensor_name) {

  auto dequeue0 =
      QueueDequeue(root.WithOpName(kDequeueOp0), q0, {DataType::DT_FLOAT});

  GraphDef graph_def;
  TF_EXPECT_OK(root.ToGraphDef(&graph_def));
  for (auto& node : *graph_def.mutable_node()) {
    node.set_device("/cpu:0");
  }
  SessionOptions sess_options;
  sess_options.config.mutable_graph_options()->set_build_cost_model(1);
  std::unique_ptr<Session> session(NewSession(sess_options));