code: def setUp(self):
      master_seed(seed=42)
      self.batch_size = 5
      x = np.random.rand(self.batch_size, 5, 5, 1)
      y = np.random.randint(0, 10, size=10 * self.batch_size).reshape(
          self.batch_size, -1
      )
  
      self.dataset = (
          tf.data.Dataset.from_tensor_slices((x, y))
          .shuffle(100)
          .batch(self.batch_size)
      )
  
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 TestTensorFlowV2DataGenerator obj's underlying member method code with example usage: obj.setUp() without return types