code: def batch_normalize(activations):
      mbmean = np.mean(activations, axis=0, keepdims=True)
      return (activations - mbmean) / (
          np.std(activations, axis=0, keepdims=True) + 1
      )
  
file_path: autograd/examples/generative_adversarial_net.py
imports: from __future__ import absolute_import, division
  from __future__ import print_function
  import autograd.numpy
  import autograd.numpy.random
  from autograd import grad
  from autograd.misc import flatten
  from data import load_mnist, save_images
label_desc: Use image node_id 5 for calling a global function with example usage: batch_normalize(activations) and returns: unknown