code: def test_drop_remainder_false(self):
      data_generator = NumpyDataGenerator(
          self.x,
          self.y,
          batch_size=self.batch_size,
          drop_remainder=False,
          shuffle=False,
      )
      self.assertEquals(data_generator.batches_per_epoch, 4)
      for i in range(3):
          data_generator.get_batch()
      x_batch, _ = data_generator.get_batch()
      self.assertEquals(len(x_batch), self.m % 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 6 for calling the TestNumpyDataGenerator obj's underlying member method code with example usage: obj.test_drop_remainder_false() without return types