code: def setUp(self):
      master_seed(seed=42)
  
      def generator(batch_size=5):
          while True:
              yield np.random.rand(
                  batch_size, 5, 5, 1
              ), np.random.randint(0, 10, size=10 * batch_size).reshape(
                  batch_size, -1
              )
  
      self.sess = tf.Session()
      self.dataset = tf.data.Dataset.from_generator(
          generator, (tf.float32, tf.int32)
      )
  
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 1 for calling the TestTensorFlowDataGenerator obj's underlying member method code with example usage: obj.setUp() without return types