(self)
Called by main to set models
        After this call, model related attributes should be setup (e.g. self.l2_loss)
        The followings MUST be setup
            - self.model (torch.nn.Module)
            - self.optimizer (src.Optimizer),
                init. w/ self.optimizer = src.Optimizer(self.model.parameters(),**self.config['hparas'])
        Loading pre-trained model should also be performed here 
        No return value
Called by main to set models
        After this call, model related attributes should be setup (e.g. self.l2_loss)
        The followings MUST be setup
            - self.model (torch.nn.Module)
            - self.optimizer (src.Optimizer),
                init. w/ self.optimizer = src.Optimizer(self.model.parameters(),**self.config['hparas'])
        Loading pre-trained model should also be performed here 
        No return value
Called by main to set models After this call model related attributes should be setup ( e . g . self . l2_loss ) The followings MUST be setup - self . model ( torch . nn . Module ) - self . optimizer ( src . Optimizer ) init . w / self . optimizer = src . Optimizer ( self . model . parameters () ** self . config [ hparas ] ) Loading pre - trained model should also be performed here No return value
def set_model(self):
        '''
        Called by main to set models
        After this call, model related attributes should be setup (e.g. self.l2_loss)
        The followings MUST be setup
            - self.model (torch.nn.Module)
            - self.optimizer (src.Optimizer),
                init. w/ self.optimizer = src.Optimizer(self.model.parameters(),**self.config['hparas'])
        Loading pre-trained model should also be performed here 
        No return value
        '''
        raise NotImplementedError
def set_model ( self ) : raise NotImplementedError