code: def next_batch(self):
      for x, y in self.train_loader:
          # print(x.size())
          # x = np.reshape(x, (-1, 28, 28, 1))
          yield x, None
  
file_path: AIX360/tests/dipvae/test_DIPVAE.py
imports: import unittest
  from aix360.algorithms.dipvae import DIPVAEExplainer
  import torch
  import torchvision.datasets
  import torchvision.transforms
  import argparse
  import numpy
label_desc: Use image node_id 2 for calling the FakeFMnistDataset obj's underlying member method code with example usage: obj.next_batch() without return types