code: def adafactor(learning_rate, hparams):
      return adafactor_lib.adafactor_optimizer_from_hparams(
          hparams, learning_rate
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  from tensor2tensor.layers import common_layers
  from tensor2tensor.utils import adafactor
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import misc_utils
  from tensor2tensor.utils import mlperf_log
  from tensor2tensor.utils import multistep_optimizer
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import yellowfin
  import tensorflow.compat.v1
  from tensorflow.python.framework import dtypes
label_desc: Use image node_id 9 for calling a global function with example usage: adafactor(learning_rate, hparams) and returns: adafactor_lib