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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def update(self, other_info, graph, metric_value, model_id):
 """ 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 """

        father_id = other_info
        self.bo.fit([graph.extract_descriptor()], [metric_value])
        self.bo.add_child(father_id, model_id)