code: def test_gen_interface(self):
      data_generator = NumpyDataGenerator(
          self.x,
          self.y,
          batch_size=self.batch_size,
          drop_remainder=True,
          shuffle=False,
      )
      x_batch, y_batch = data_generator.get_batch()
  
      # Check return types
      self.assertTrue(isinstance(x_batch, np.ndarray))
      self.assertTrue(isinstance(y_batch, np.ndarray))
  
      # Check shapes
      self.assertEqual(x_batch.shape, (self.batch_size,) + self.n)
      self.assertEqual(y_batch.shape, (self.batch_size,))
  
      # Check underlying properties
      self.assertEqual(data_generator.size, len(self.x))
      self.assertEqual(data_generator.batch_size, 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 2 for calling the TestNumpyDataGenerator obj's underlying member method code with example usage: obj.test_gen_interface() without return types