code: def testTransformerWithoutProblem(self):
      hparams = transformer.transformer_test()
  
      embedded_inputs = np.random.random_sample(
          (BATCH_SIZE, INPUT_LENGTH, 1, hparams.hidden_size)
      )
      embedded_targets = np.random.random_sample(
          (BATCH_SIZE, TARGET_LENGTH, 1, hparams.hidden_size)
      )
  
      transformed_features = {
          "inputs": tf.constant(embedded_inputs, dtype=tf.float32),
          "targets": tf.constant(embedded_targets, dtype=tf.float32),
      }
  
      model = transformer.Transformer(hparams)
      body_out, _ = model(transformed_features)
  
      self.assertAllEqual(
          body_out.get_shape().as_list(),
          [BATCH_SIZE, TARGET_LENGTH, 1, hparams.hidden_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 11 for calling the TransformerTest obj's underlying member method code with example usage: obj.testTransformerWithoutProblem() without return types