code: def testBasicExampleReading(self):
      dataset = self.problem.dataset(
          tf_estimator.ModeKeys.TRAIN,
          data_dir=self.data_dir,
          shuffle_files=False,
      )
      examples = dataset.make_one_shot_iterator().get_next()
      with tf.train.MonitoredSession() as sess:
          # Check that there are multiple examples that have the right fields of the
          # right type (lists of int/float).
          for _ in range(10):
              ex_val = sess.run(examples)
              inputs, targets, floats = (
                  ex_val["inputs"],
                  ex_val["targets"],
                  ex_val["floats"],
              )
              self.assertEqual(np.int64, inputs.dtype)
              self.assertEqual(np.int64, targets.dtype)
              self.assertEqual(np.float32, floats.dtype)
              for field in [inputs, targets, floats]:
                  self.assertGreater(len(field), 0)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import tempfile
  import numpy
  from six.moves import range
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import data_reader
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 3 for calling the DataReaderTest obj's underlying member method code with example usage: obj.testBasicExampleReading() without return types