code: def norm(norm_type, nc):
      """Return a normalization layer"""
      norm_type = norm_type.lower()
      if norm_type == "batch":
          layer = nn.BatchNorm2d(nc, affine=True)
      elif norm_type == "instance":
          layer = nn.InstanceNorm2d(nc, affine=False)
      elif norm_type == "none":
  
          def norm_layer(x):
              return Identity()
  
      else:
          raise NotImplementedError(
              f"normalization layer [{norm_type}] is not found"
          )
      return layer
  
imports: from collections import OrderedDict
  import math
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 7 for calling a global function with example usage: norm(norm_type, nc) and returns: layer, Identity