code: def test_labelled_map():
      ds = ActiveLearningDataset(MyDataset())
      assert ds.current_al_step == 0
      ds.label_randomly(10)
      assert ds.current_al_step == 1
      ds.label_randomly(10)
      assert (
          ds.labelled_map.max() == 2
          and np.equal(ds.labelled, ds.labelled_map > 0).all()
      )
  
      st = ds.state_dict()
      ds2 = ActiveLearningDataset(MyDataset(), labelled=st["labelled"])
      assert ds2.current_al_step == ds.current_al_step
  
imports: import pickle
  import unittest
  import unittest.mock
  import warnings
  import datasets
  import numpy
  import pytest
  import torch.utils.data
  from torchvision.transforms import Lambda
  from baal.active import ActiveLearningDataset
label_desc: Use image node_id 5 for calling a global function with example usage: test_labelled_map() without return types