class_docstr: The module wraps normalization, dropout, residual connection into one equation:
  sublayerwrapper(sublayer)(x) = x + dropout(sublayer(norm(x)))
code: def __init__(self, size, dropout):
      super(SubLayerWrapper, self).__init__()
      self.norm = LayerNorm(size)
      self.dropout = nn.Dropout(dropout)
  
imports: import torch
  import torch.nn
  from torch.nn import LayerNorm
  import copy
label_desc: Use image node_id 1 to create a new SubLayerWrapper object from inherited base classes: nn with example: obj = SubLayerWrapper(size, dropout)