code: def adafactor_decay_rate_pow(exponent=0.8, offset=0):
      """Second moment decay rate where memory-length grows as step_num^exponent.
  
      For fine-tuning, you may want to gin-configure offset to equal the starting
      step-number for the fine-tuning phase.
  
      Args:
        exponent: a float between 0 and 1
        offset: an integer (the starting step number)
      Returns:
        a scalar
      """
      step_num = tf.cast(
          tf.train.get_or_create_global_step() - offset, tf.float32
      )
      return 1.0 - tf.pow((step_num + 1.0), -exponent)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import re
  import gin
  from mesh_tensorflow import layers
  from mesh_tensorflow import ops_with_redefined_builtins
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling a global function with example usage: adafactor_decay_rate_pow(exponent, offset) and returns: unknown