code: def testTransformer(self, get_model_fn=None, p=None):
      if get_model_fn:
          model, features = get_model_fn(param_overrides=p)
      else:
          model, features = get_model(transformer.transformer_small())
      logits, _ = model(features)
      with self.test_session() as session:
          session.run(tf.global_variables_initializer())
          res = session.run(logits)
      self.assertEqual(
          res.shape, (BATCH_SIZE, TARGET_LENGTH, 1, 1, VOCAB_SIZE)
      )
  
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 1 for calling the TransformerTest obj's underlying member method code with example usage: obj.testTransformer(get_model_fn, p) without return types