code: def _optimizer(learning_rate):
      return (
          tf.train.GradientDescentOptimizer(learning_rate),
          learning_rate,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import shutil
  from absl import flags
  from absl.testing import parameterized
  import adanet
  from adanet.research.improve_nas.trainer import improve_nas
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling a global function with example usage: _optimizer(learning_rate) and returns: tf,  learning_rate