code: def setUp(self):
      self.m = 100
      self.n = (28, 28, 1)
      self.x = np.random.random((self.m,) + self.n)
      self.y = np.arange(self.m)
      self.batch_size = 30
  
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 TestNumpyDataGenerator obj's underlying member method code with example usage: obj.setUp() without return types