code: def testVarNames(self):
      with tf.Graph().as_default():
          model, features = get_model(
              mode=tf_estimator.ModeKeys.PREDICT,
              model_cls=transformer.TransformerScorer,
          )
          _ = model.infer(features)
          scorer_vars = [v.name for v in tf.global_variables()]
  
      with tf.Graph().as_default():
          model, features = get_model(
              mode=tf_estimator.ModeKeys.EVAL,
              model_cls=transformer.TransformerScorer,
          )
          _ = model(features)
          scorer_eval_vars = [v.name for v in tf.global_variables()]
  
      with tf.Graph().as_default():
          model, features = get_model(
              mode=tf_estimator.ModeKeys.EVAL,
              model_cls=transformer.Transformer,
          )
          _ = model(features)
          transformer_vars = [v.name for v in tf.global_variables()]
  
      self.assertEqual(sorted(scorer_vars), sorted(transformer_vars))
      self.assertEqual(
          sorted(scorer_eval_vars), sorted(transformer_vars)
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  from tensor2tensor.data_generators import librispeech
  from tensor2tensor.data_generators import problem_hparams
  from tensor2tensor.models import transformer
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 2 for calling the TransformerScorerTest obj's underlying member method code with example usage: obj.testVarNames() without return types