code: def normalize_list(
      whole_batch,
      data_batch,
      axes=None,
      mean=None,
      stddev=None,
      ddof=0,
      eps=0,
  ):
      if whole_batch:
          return batch_norm(data_batch, axes, mean, stddev, ddof, eps)
      else:
          if type(mean) is not list:
              mean = [mean] * len(data_batch)
          if type(stddev) is not list:
              stddev = [stddev] * len(data_batch)
          return [
              normalize(
                  data_batch[i].astype(np.float),
                  axes,
                  mean[i],
                  stddev[i],
                  ddof,
                  eps,
              )
              for i in range(len(data_batch))
          ]
  
imports: from nvidia.dali.pipeline import Pipeline
  from nvidia.dali import backend
  import nvidia.dali.ops
  import numpy
  from test_utils import dali_type
  from nvidia.dali import fn, pipeline_def, types
  from nose2.tools import params
label_desc: Use image node_id 9 for calling a global function with example usage: normalize_list(whole_batch, data_batch, axes, mean, stddev, ddof, eps) and returns: batch_norm, unknown