def __init__(
        self,
        in_features,
        initial_out_features=2,
        masking=True,
        mask_value=-1000,
        **kwargs,
    ):
        """
        :param in_features: number of input features.
        :param initial_out_features: initial number of classes (can be
            dynamically expanded).
        :param masking: whether unused units should be masked (default=True).
        :param mask_value: the value used for masked units (default=-1000).
        """
        super().__init__(**kwargs)
        self.masking = masking
        self.mask_value = mask_value

        self.classifier = torch.nn.Linear(in_features, initial_out_features)
        au_init = torch.zeros(initial_out_features, dtype=torch.int8)
        self.register_buffer("active_units", au_init)

        :param in_features: number of input features.
        :param initial_out_features: initial number of classes (can be
            dynamically expanded).
        :param masking: whether unused units should be masked (default=True).
        :param mask_value: the value used for masked units (default=-1000).
        
avalanche/models/dynamic_modules.py