code: def update(self, other_info, graph, metric_value, model_id):
          
          father_id = other_info
          self.bo.fit([graph.extract_descriptor()], [metric_value])
          self.bo.add_child(father_id, model_id)
docs: Update the controller with evaluation result of a neural architecture.
  
          Parameters
          ----------
          other_info: any object
              In our case it is the father ID in the search tree.
          graph: Graph
              An instance of Graph. The trained neural architecture.
          metric_value: float
              The final evaluated metric value.
          model_id: int