class_docstr: Helper class to implement skip multiplication.
  Args:
      layer (nn.Module): layer for skip multiplication. With input x, _SkipConnectMul
          implements layer(x)*x.
class_docstr_tok: ["Helper","class","to","implement","skip","multiplication",".","Args",":","layer","(","nn.Module",")",":","layer","for","skip","multiplication",".","With","input","x",",","_SkipConnectMul","implements","layer","(","x",")","*","x","."]
code: def __init__(
      self,
      layer: nn.Module,
  ):
      super().__init__()
      self.layer = layer
      self.mul_func = nn.quantized.FloatFunctional()
  
imports: from copy import deepcopy
  from typing import Tuple
  import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new _SkipConnectMul object from inherited base classes: nn with example: obj = _SkipConnectMul(layer)