code: def drop_path(net, keep_prob, is_training=True):
      """Drops out a whole example hiddenstate with the specified probability."""
      if is_training:
          batch_size = tf.shape(net)[0]
          noise_shape = [batch_size, 1, 1, 1]
          random_tensor = keep_prob
          random_tensor += tf.random_uniform(
              noise_shape, dtype=tf.float32
          )
          binary_tensor = tf.floor(random_tensor)
          net = tf.div(net, keep_prob) * binary_tensor
      return net
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
label_desc: Use image node_id 6 for calling a global function with example usage: drop_path(net, keep_prob, is_training) and returns: net