def __init__(self, clss: Iterable[SupportsInt]):
        """
        :param clss: list of classes of the current layer. This are use
            to identify the columns which are multiplied by the Bias
            correction Layer.
        """
        super().__init__()
        self.alpha = torch.nn.Parameter(torch.ones(1))
        self.beta = torch.nn.Parameter(torch.zeros(1))

        unique_classes = list(sorted(set(int(x) for x in clss)))

        self.register_buffer("clss", torch.tensor(unique_classes, dtype=torch.long))

        :param clss: list of classes of the current layer. This are use
            to identify the columns which are multiplied by the Bias
            correction Layer.
        
avalanche/models/bic_model.py