code: def __init__(self, device, clss):
      """
      :param device: device used by the main model. 'cpu' or 'cuda'
      :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, device=device))
      self.beta = torch.nn.Parameter(torch.zeros(1, device=device))
  
      self.clss = torch.Tensor(list(clss)).long().to(device)
      self.not_clss = None
  
imports: import torch
label_desc: Use image node_id 1 to create a new BiasLayer object from inherited base classes: torch.nn with example: obj = BiasLayer(device, clss)