class_docstr: The module wraps normalization, dropout, residual connection into one equation:
  sublayerwrapper(sublayer)(x) = x + dropout(sublayer(norm(x)))
code: def forward(self, x, sublayer):
      return x + self.dropout(sublayer(self.norm(x)))
  
imports: import torch
  import torch.nn
  from torch.nn import LayerNorm
  import copy
label_desc: Use image node_id 2 for calling the SubLayerWrapper obj's underlying member method code with example usage: obj.forward(x, sublayer) and returns: unknown