code: def test_nc_sit_slicing(self):
      mnist_train = MNIST(
          root=default_dataset_location("mnist"),
          train=True,
          download=True,
      )
      mnist_test = MNIST(
          root=default_dataset_location("mnist"),
          train=False,
          download=True,
      )
      my_nc_benchmark = nc_benchmark(
          mnist_train,
          mnist_test,
          5,
          task_labels=False,
          shuffle=True,
          seed=1234,
      )
  
      experience: NCExperience
      for batch_id, experience in enumerate(
          my_nc_benchmark.train_stream
      ):
          self.assertEqual(batch_id, experience.current_experience)
          self.assertIsInstance(experience, NCExperience)
  
      for batch_id, experience in enumerate(
          my_nc_benchmark.test_stream
      ):
          self.assertEqual(batch_id, experience.current_experience)
          self.assertIsInstance(experience, NCExperience)
  
      iterable_slice = [3, 4, 1]
      sliced_stream = my_nc_benchmark.train_stream[iterable_slice]
      self.assertIsInstance(sliced_stream, ClassificationStream)
      self.assertEqual(len(iterable_slice), len(sliced_stream))
      self.assertEqual("train", sliced_stream.name)
  
      for batch_id, experience in enumerate(sliced_stream):
          self.assertEqual(
              iterable_slice[batch_id], experience.current_experience
          )
          self.assertIsInstance(experience, NCExperience)
  
      sliced_stream = my_nc_benchmark.test_stream[iterable_slice]
      self.assertIsInstance(sliced_stream, ClassificationStream)
      self.assertEqual(len(iterable_slice), len(sliced_stream))
      self.assertEqual("test", sliced_stream.name)
  
      for batch_id, experience in enumerate(sliced_stream):
          self.assertEqual(
              iterable_slice[batch_id], experience.current_experience
          )
          self.assertIsInstance(experience, NCExperience)
  
imports: import random
  import unittest
  from PIL.Image import Image
  from torch import Tensor
  from torchvision.datasets import MNIST
  from torchvision.transforms import ToTensor
  from avalanche.benchmarks import nc_benchmark, ClassificationStream
  from avalanche.benchmarks.datasets import default_dataset_location
  from avalanche.benchmarks.scenarios.deprecated.new_classes import NCExperience
  from avalanche.benchmarks.scenarios.deprecated.new_classes.nc_utils import make_nc_transformation_subset
  from avalanche.benchmarks.utils import _taskaware_classification_subset, _make_taskaware_classification_dataset
  from tests.unit_tests_utils import DummyImageDataset
label_desc: Use image node_id 10 for calling the SITTests obj's underlying member method code with example usage: obj.test_nc_sit_slicing() without return types