code: def l2_batch_normalize(x, epsilon=1e-12, scope=None):
      """
      Helper function to normalize a batch of vectors.
      :param x: the input placeholder
      :param epsilon: stabilizes division
      :return: the batch of l2 normalized vector
      """
      with tf.name_scope(scope, "l2_batch_normalize") as name_scope:
          x_shape = tf.shape(x)
          x = tf.contrib.layers.flatten(x)
          x /= epsilon + reduce_max(tf.abs(x), 1, keepdims=True)
          square_sum = reduce_sum(tf.square(x), 1, keepdims=True)
          x_inv_norm = tf.rsqrt(np.sqrt(epsilon) + square_sum)
          x_norm = tf.multiply(x, x_inv_norm)
          return tf.reshape(x_norm, x_shape, name_scope)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import logging
  import math
  import os
  import time
  import warnings
  import numpy
  import six
  from six.moves import xrange
  import tensorflow
  from cleverhans.compat import device_lib
  from cleverhans.compat import reduce_sum, reduce_mean
  from cleverhans.compat import reduce_max
  from cleverhans.compat import softmax_cross_entropy_with_logits
  from cleverhans.utils import batch_indices, _ArgsWrapper, create_logger
label_desc: Use image node_id 8 for calling a global function with example usage: l2_batch_normalize(x, epsilon, scope) and returns: tf