code: def get_norm(norm, out_channels):
      """
      Args:
          norm (str or callable): either one of BN, SyncBN, FrozenBN, GN;
              or a callable that takes a channel number and returns
              the normalization layer as a nn.Module.
      Returns:
          nn.Module or None: the normalization layer
      """
      if isinstance(norm, str):
          if len(norm) == 0:
              return None
          norm = {
              "BN": BatchNorm2d,
              # Fixed in https://github.com/pytorch/pytorch/pull/36382
              "SyncBN": nn.SyncBatchNorm,
              "FrozenBN": FrozenBatchNorm2d,
              "GN": lambda channels: nn.GroupNorm(32, channels),
              # for debugging:
              "nnSyncBN": nn.SyncBatchNorm,
              "naiveSyncBN": NaiveSyncBatchNorm,
          }[norm]
      return norm(out_channels)
  
imports: import logging
  import torch
  import torch.distributed
  from torch import nn
  from torch.autograd.function import Function
  from torch.nn import functional
  from torch.nn import BatchNorm2d
  from ..utils.comm import get_world_size
label_desc: Use image node_id 1 for calling a global function with example usage: get_norm(norm, out_channels) and returns: norm, None