code: def __init__(self, in_features: int, out_features: int) -> None:
      super().__init__(in_features, out_features, bias=True)
  
imports: import math
  from typing import Optional, Tuple
  import torch
  import torch.nn.functional
  from torch.nn import Module, init
  from torch.nn.functional import dropout, linear, softmax
  from torch.nn.init import constant_, xavier_normal_, xavier_uniform_
  from torch.nn.modules.dropout import Dropout
  from torch.nn.modules.normalization import LayerNorm
  from torch.nn.parameter import Parameter
label_desc: Use image node_id 1 to create a new _LinearWithBias object from inherited base classes: Linear with example: obj = _LinearWithBias(in_features, out_features)