class_docstr: Adds LayerNorm after computing attention
class_docstr_tok: ["Adds","LayerNorm","after","computing","attention"]
code: def forward(self, inputs: List[torch.Tensor], **kwargs):
      if self.wrap_inputs:
          x = self.sublayer(inputs=inputs, **kwargs)
      else:
          x = self.sublayer(*inputs, **kwargs)
      return self.norm(x)
  
imports: from enum import Enum
  from typing import List, Optional, Tuple, Union
  import torch
  import torch.nn
  from xformers import _is_triton_available
  from collections import namedtuple
label_desc: Use image node_id 2 for calling the PostNorm obj's underlying member method code with example usage: obj.forward(inputs) and returns: self