code: def yellow_fin(learning_rate, hparams):
      return yellowfin.YellowFinOptimizer(
          learning_rate=learning_rate,
          momentum=hparams.optimizer_momentum_momentum,
      )
  
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 6 for calling a global function with example usage: yellow_fin(learning_rate, hparams) and returns: yellowfin