code: def test_sit_single_dataset_fixed_order(self):
      order = [2, 3, 5, 7, 8, 9, 0, 1, 4, 6]
      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,
          fixed_class_order=order,
      )
  
      all_classes = []
      for batch_id in range(5):
          all_classes.extend(
              my_nc_benchmark.classes_in_experience["train"][batch_id]
          )
  
      self.assertEqual(order, all_classes)
  
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 2 for calling the SITTests obj's underlying member method code with example usage: obj.test_sit_single_dataset_fixed_order() without return types