code: def featurewise_zero_center(X, mean=None):
      """featurewise_zero_center.
  
      Zero center every sample with specified mean. If not specified, the mean
      is evaluated over all samples.
  
      Arguments:
          X: `array`. The batch of samples to center.
          mean: `float`. The mean to use for zero centering. If not specified, it
              will be evaluated on provided data.
  
      Returns:
          A numpy array with same shape as input. Or a tuple (array, mean) if no
          mean value was specified.
  
      """
      if mean is None:
          mean = np.mean(X, axis=0)
          return X - mean, mean
      else:
          return X - mean
  
imports: from __future__ import division, print_function, absolute_import
  import os
  import random
  import numpy
  from PIL import Image
  import pickle
  import csv
  import warnings
  import tensorflow.compat.v1
  from io import BytesIO
label_desc: Use image node_id 22 for calling a global function with example usage: featurewise_zero_center(X, mean) and returns: unknown,  mean, unknown