code: def gumbel_sample(shape):
      """Sample from the Gumbel distribution, protect from overflows.
  
      Args:
        shape: Shape of Gumbel samples.
  
      Returns:
        Noise drawn from Gumbel distribution.
      """
      uniform_samples = tf.random_uniform(
          shape, minval=0.00001, maxval=0.99998
      )
      return -tf.log(-tf.log(uniform_samples))
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from functools import partial
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_image_attention
  from tensor2tensor.layers import common_layers
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
  import tensorflow_probability
  from tensorflow.python.training import moving_averages
label_desc: Use image node_id 11 for calling a global function with example usage: gumbel_sample(shape) and returns: unknown