code: def test_len(self):
      assert len(self.dataset) == 0
      assert self.dataset.n_unlabelled == 100
      assert len(self.dataset.pool) == 100
      self.dataset.label(0)
      assert len(self.dataset) == self.dataset.n_labelled == 1
      assert self.dataset.n_unlabelled == 99
      assert len(self.dataset.pool) == 99
      self.dataset.label(list(range(99)))
      assert len(self.dataset) == 100
      assert self.dataset.n_unlabelled == 0
      assert len(self.dataset.pool) == 0
  
      dummy_dataset = ActiveLearningDataset(
          MyDataset(),
          labelled=self.dataset.labelled,
          make_unlabelled=lambda x: (x[0], -1),
      )
      assert len(dummy_dataset) == len(self.dataset)
      assert len(dummy_dataset.pool) == len(self.dataset.pool)
  
      dummy_lbl = self.dataset.labelled.astype(np.float32)
      dummy_dataset = ActiveLearningDataset(
          MyDataset(),
          labelled=dummy_lbl,
          make_unlabelled=lambda x: (x[0], -1),
      )
      assert len(dummy_dataset) == len(self.dataset)
      assert len(dummy_dataset.pool) == len(self.dataset.pool)
  
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 2 for calling the ActiveDatasetTest obj's underlying member method code with example usage: obj.test_len() without return types