code: def get_norm(cfg):
      """
      Args:
          cfg (CfgNode): model building configs, details are in the comments of
              the config file.
      Returns:
          nn.Module: the normalization layer.
      """
      if cfg.BN.NORM_TYPE in {"batchnorm", "sync_batchnorm_apex"}:
          return nn.BatchNorm3d
      elif cfg.BN.NORM_TYPE == "sub_batchnorm":
          return partial(SubBatchNorm3d, num_splits=cfg.BN.NUM_SPLITS)
      elif cfg.BN.NORM_TYPE == "sync_batchnorm":
          return partial(
              NaiveSyncBatchNorm3d,
              num_sync_devices=cfg.BN.NUM_SYNC_DEVICES,
              global_sync=cfg.BN.GLOBAL_SYNC,
          )
      else:
          raise NotImplementedError(
              "Norm type {} is not supported".format(cfg.BN.NORM_TYPE)
          )
  
file_path: SlowFast/slowfast/models/batchnorm_helper.py
imports: from functools import partial
  import torch
  import torch.nn
  from pytorchvideo.layers.batch_norm import NaiveSyncBatchNorm1d, NaiveSyncBatchNorm3d
label_desc: Use image node_id 1 for calling a global function with example usage: get_norm(cfg) and returns: nn, partial, partial