code: def test_reinit(self):
      iter_ = tf.data.Iterator.from_structure(
          tf.compat.v1.data.get_output_types(self.dataset),
          tf.compat.v1.data.get_output_shapes(self.dataset),
      )
      init_op = iter_.make_initializer(self.dataset)
      data_gen = TensorFlowDataGenerator(
          sess=self.sess,
          iterator=iter_,
          iterator_type="reinitializable",
          iterator_arg=init_op,
          size=10,
          batch_size=5,
      )
      x, y = data_gen.get_batch()
  
      # Check return types
      self.assertTrue(isinstance(x, np.ndarray))
      self.assertTrue(isinstance(y, np.ndarray))
  
      # Check shapes
      self.assertEqual(x.shape, (5, 5, 5, 1))
      self.assertEqual(y.shape, (5, 10))
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import unittest
  import tensorflow
  import numpy
  from keras.preprocessing.image import ImageDataGenerator
  from art.data_generators import KerasDataGenerator, PyTorchDataGenerator, MXDataGenerator, TensorFlowDataGenerator
  from art.data_generators import TensorFlowV2DataGenerator, NumpyDataGenerator
  from tests.utils import master_seed
label_desc: Use image node_id 4 for calling the TestTensorFlowDataGenerator obj's underlying member method code with example usage: obj.test_reinit() without return types