class_docstr: Fashion-MNIST [#]_ is a large-scale image dataset of various fashion items (T-shirt/top, Trouser,
  Pullover, Dress. Coat, Sandal, Shirt, Sneaker, Bag, Ankle boot. The images are grayscale and 28x28
  in size with each image belong to one the above mentioned 10 categories. The training set contains
  60000 examples and the test set contains 10000 examples.
  
  References:
      .. [#] `Xiao, Han, Kashif Rasul, and Roland Vollgraf. Fashion-mnist: a
         novel image dataset for benchmarking machine learning algorithms.
         <https://arxiv.org/abs/1708.07747>`_
code: def next_test_batch(self):
      for x, y in self.test_loader:
          x = np.reshape(x, (-1, 28, 28, 1))
          yield x, y
  
file_path: AIX360/aix360/datasets/fashion_mnist_dataset.py
imports: import numpy
  import torch
  import os
  import torchvision.datasets
  import torchvision.transforms
label_desc: Use image node_id 3 for calling the FMnistDataset obj's underlying member method code with example usage: obj.next_test_batch() without return types