def __init__(self, lambda_reg: float = 1.0, alpha: float = 0.5, verbose=False):
        """
        :param lambda_reg: hyperparameter weighting the penalty term
               in the loss.
        :param alpha: hyperparameter used to update the importance
               by also considering the influence in the previous
               experience.
        :param verbose: when True, the computation of the influence
               shows a progress bar using tqdm.
        """

        # Init super class
        super().__init__()

        # Regularization Parameters
        self._lambda = lambda_reg
        self.alpha = alpha

        # Model parameters
        self.params: Union[Dict, None] = None
        self.importance: Union[Dict, None] = None

        # Progress bar
        self.verbose = verbose

        :param lambda_reg: hyperparameter weighting the penalty term
               in the loss.
        :param alpha: hyperparameter used to update the importance
               by also considering the influence in the previous
               experience.
        :param verbose: when True, the computation of the influence
               shows a progress bar using tqdm.
        
avalanche/training/plugins/mas.py