def METHOD_NAME(self, global_weights):
    # load local model from last round's record if model exist,
    # otherwise initialize from global model weights for the first round.
    if os.path.exists(self.model_file_path):
        model_data = torch.load(self.model_file_path)
        self.model.load_state_dict(model_data["model"])
        self.epoch_of_start_time = model_data["epoch"]
    else:
        self.model.load_state_dict(global_weights)
        self.epoch_of_start_time = 0
    if os.path.exists(self.best_model_file_path):
        model_data = torch.load(self.best_model_file_path)
        self.best_metric = model_data["best_metric"]