code: def test_pytorch_specific(self):
      import torch
  
      iter_ = iter(self.data_gen.iterator)
      x, y = next(iter_)
  
      # Check return types
      self.assertTrue(isinstance(x, torch.Tensor))
      self.assertTrue(isinstance(y, torch.Tensor))
  
      # Check shapes
      self.assertEqual(x.shape, (5, 1, 5, 5))
      self.assertEqual(y.shape, (5,))
  
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 3 for calling the TestPyTorchGenerator obj's underlying member method code with example usage: obj.test_pytorch_specific() without return types