code: def random_laplace(
      shape, loc=0.0, scale=1.0, dtype=tf.float32, seed=None
  ):
      """
      Helper function to sample from the Laplace distribution, which is not
      included in core TensorFlow.
  
      :shape: shape of the sampled tensor.
      :loc: (optional) mean of the laplace distribution, defaults to 0.0.
      :scale: (optional) scale parameter of the laplace diustribution, defaults to 1.0.
      :dtype: (optional) data type of the sempled tensor, defaults to tf.float32.
      :seed: (optional) custom seed to be used for sampling.
      """
      z1 = random_exponential(
          shape, 1.0 / scale, dtype=dtype, seed=seed
      )
      z2 = random_exponential(
          shape, 1.0 / scale, dtype=dtype, seed=seed
      )
      return z1 - z2 + loc
  
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 13 for calling a global function with example usage: random_laplace(shape, loc, scale, dtype, seed) and returns: unknown