code: def get_normalization_layer(normalization_type: NormalizationType):
      class Skip(nn.Module):
          def __init__(self, *_, **__) -> None:
              super().__init__()
  
          def forward(self, x: torch.Tensor, **_):
              return x
  
      return {
          NormalizationType.LayerNorm: nn.LayerNorm,
          NormalizationType.Skip: Skip,
      }[normalization_type]
  
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 1 for calling a global function with example usage: get_normalization_layer(normalization_type) and returns: dict, x