code: def test_error(self):
      handle = tf.placeholder(tf.string, shape=[])
      iter_ = tf.data.Iterator.from_string_handle(
          handle,
          tf.compat.v1.data.get_output_types(self.dataset),
          tf.compat.v1.data.get_output_shapes(self.dataset),
      )
      feed_iterator = tf.compat.v1.data.make_initializable_iterator(
          self.dataset
      )
      feed_handle = self.sess.run(feed_iterator.string_handle())
  
      with self.assertRaises(TypeError):
          _ = TensorFlowDataGenerator(
              sess=self.sess,
              iterator="iter_",
              iterator_type="feedable",
              iterator_arg=(feed_iterator, {handle: feed_handle}),
              size=10,
              batch_size=5,
          )
  
      with self.assertRaises(TypeError):
          _ = TensorFlowDataGenerator(
              sess=self.sess,
              iterator=iter_,
              iterator_type="initializable",
              iterator_arg=(feed_iterator, "{handle: feed_handle}"),
              size=10,
              batch_size=5,
          )
  
      with self.assertRaises(TypeError):
          _ = TensorFlowDataGenerator(
              sess=self.sess,
              iterator=iter_,
              iterator_type="reinitializable",
              iterator_arg=(feed_iterator, "{handle: feed_handle}"),
              size=10,
              batch_size=5,
          )
  
      with self.assertRaises(TypeError):
          _ = TensorFlowDataGenerator(
              sess=self.sess,
              iterator=iter_,
              iterator_type="feedable",
              iterator_arg=[feed_iterator, {handle: feed_handle}],
              size=10,
              batch_size=5,
          )
  
      with self.assertRaises(TypeError):
          _ = TensorFlowDataGenerator(
              sess=self.sess,
              iterator=iter_,
              iterator_type="test",
              iterator_arg=(feed_iterator, {handle: feed_handle}),
              size=10,
              batch_size=5,
          )
  
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 6 for calling the TestTensorFlowDataGenerator obj's underlying member method code with example usage: obj.test_error() without return types