code: def fast_flip(images, is_training):
      """Flips the input images when training."""
  
      def func(inp):
          batch_size = tf.shape(inp)[0]
          flips = tf.to_float(
              tf.random_uniform([batch_size, 1, 1, 1], 0, 2, tf.int32)
          )
          flipped_inp = tf.reverse(inp, [2])
          return flips * flipped_inp + (1 - flips) * images
  
      return tf.cond(is_training, lambda: func(images), lambda: images)
  
file_path: neural-structured-learning/research/gam/gam/models/wide_resnet.py
imports: from .models_base import Model
  import numpy
  import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: fast_flip(images, is_training) and returns: tf, unknown