code: def test_nc_sit_type(self):
      mnist_train = MNIST(
          root=expanduser("~") + "/.avalanche/data/mnist/",
          train=True,
          download=True,
      )
      mnist_test = MNIST(
          root=expanduser("~") + "/.avalanche/data/mnist/",
          train=False,
          download=True,
      )
      my_nc_benchmark = nc_benchmark(
          mnist_train, mnist_test, 5, task_labels=False
      )
  
      for batch_info in my_nc_benchmark.train_stream:
          self.assertIsInstance(batch_info, ClassificationExperience)
  
      for batch_info in my_nc_benchmark.test_stream:
          self.assertIsInstance(batch_info, ClassificationExperience)
  
file_path: avalanche/tests/benchmarks/scenarios/deprecated/test_scenarios_typechecks.py
imports: import unittest
  import torch
  from os.path import expanduser
  from torchvision.datasets import MNIST
  from avalanche.benchmarks import tensors_benchmark
  from avalanche.benchmarks.scenarios.deprecated.generators import nc_benchmark, ni_benchmark
  from avalanche.benchmarks.scenarios.deprecated.classification_scenario import ClassificationExperience
label_desc: Use image node_id 2 for calling the ScenariosTypeChecksTests obj's underlying member method code with example usage: obj.test_nc_sit_type() without return types