code: def get_normalization(config, conditional=False):
      """Obtain normalization modules from the config file."""
      norm = config.model.normalization
      if conditional:
          if norm == "InstanceNorm++":
              return functools.partial(
                  ConditionalInstanceNorm2dPlus,
                  num_classes=config.model.num_classes,
              )
          else:
              raise NotImplementedError(f"{norm} not implemented yet.")
      else:
          if norm == "InstanceNorm":
              return nn.InstanceNorm2d
          elif norm == "InstanceNorm++":
              return InstanceNorm2dPlus
          elif norm == "VarianceNorm":
              return VarianceNorm2d
          elif norm == "GroupNorm":
              return nn.GroupNorm
          else:
              raise ValueError("Unknown normalization: %s" % norm)
  
imports: import functools
  import torch
  import torch.nn
label_desc: Use image node_id 1 for calling a global function with example usage: get_normalization(config, conditional) and returns: functools, nn, InstanceNorm2dPlus, VarianceNorm2d, nn