```python
class SupervisedMonaiProstateDittoLearner(SupervisedMonaiProstateLearner):
    def __init__(self, config_filename, num_epochs_global, num_epochs_personalized, task_name):
        super().__init__(config_filename, num_epochs_global, num_epochs_personalized, task_name)
        self.config_filename = config_filename
        self.num_epochs_global = num_epochs_global
        self.num_epochs_personalized = num_epochs_personalized
        self.task_name = task_name

    def configure_training(self):
        self.helper = SupervisedPTDittoHelper(model=UNet(), optimizer=SGD())

    def train(self):
        try:
            # Initialize training context
            ctx = _prepare_training_ctx(self.config_filename)
            
            # Get global model weights
            global_weights = _get_model_weights(ctx)
            
            # Prepare for fedprox loss if necessary
            # This is a placeholder for any fedprox loss preparation code
            
            # Load Ditto personalized model info
            # This is a placeholder for loading Ditto personalized model information
            
            # Local training of the reference model
            for epoch in range(self.num_epochs_global):
                training_loop(ctx, global_weights, TrainingTopic.GLOBAL_TRAINING)
            
            # Local training of the personalized model
            for epoch in range(self.num_epochs_personalized):
                training_loop(ctx, global_weights, TrainingTopic.PERSONALIZED_TRAINING)
            
            # Return updated weights of the reference model
            updated_weights = _receive_and_update_model(ctx, global_weights)
            
            return updated_weights
        except KeyboardInterrupt:
            stop_training()
        except Exception as e:
            print(f"Training aborted due to an exception: {e}")
```