code: def test_nc_benchmark_classes_in_exp_range(self):
      train_set = DummyImageDataset(n_classes=100)
      test_set = DummyImageDataset(n_classes=100)
  
      benchmark_instance = nc_benchmark(
          train_dataset=train_set,
          test_dataset=test_set,
          n_experiences=5,
          task_labels=False,
          seed=1234,
          shuffle=False,
      )
  
      cie_data = benchmark_instance.classes_in_exp_range(0, None)
      self.assertEqual(100, len(cie_data))
      self.assertSetEqual(set(range(0, 100)), set(cie_data))
  
      cie_data = benchmark_instance.classes_in_exp_range(1, 4)
      self.assertEqual(60, len(cie_data))
      self.assertSetEqual(set(range(20, 80)), set(cie_data))
  
      # Test additional desired behavior: classes are ordered by experience
      random_class_order = list(range(100))
      random.shuffle(random_class_order)
      benchmark_instance = nc_benchmark(
          train_dataset=train_set,
          test_dataset=test_set,
          n_experiences=5,
          task_labels=False,
          seed=1234,
          fixed_class_order=random_class_order,
          shuffle=False,
      )
  
      cie_data = benchmark_instance.classes_in_exp_range(0, None)
      self.assertEqual(100, len(cie_data))
  
      for i in range(5):
          expected = set(random_class_order[i * 20 : (i + 1) * 20])
          self.assertSetEqual(
              expected, set(cie_data[i * 20 : (i + 1) * 20])
          )
  
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 13 for calling the SITTests obj's underlying member method code with example usage: obj.test_nc_benchmark_classes_in_exp_range() without return types