code: def test_pool(self):
      self.dataset._dataset.label = unittest.mock.MagicMock()
      labels_initial = self.dataset.n_labelled
  
      # Test that we can label without value for research
      self.dataset.can_label = False
      self.dataset.label(0, value=np.arange(1, 10))
      self.dataset._dataset.label.assert_not_called()
      labels_next_1 = self.dataset.n_labelled
      assert labels_next_1 == labels_initial + 1
  
      # Test that a warning is raised if we dont supply a label.
      self.dataset.can_label = True
      with pytest.raises(
          ValueError,
          match="The dataset is able to label data, but no label was provided.",
      ) as w:
          self.dataset.label(np.arange(0, 9))
      self.dataset._dataset.label.assert_not_called()
      assert self.dataset.n_labelled == labels_next_1
  
      with pytest.raises(ValueError, match="same length"):
          self.dataset.label(np.arange(0, 9), value=np.arange(0, 10))
  
      # cleanup
      del self.dataset._dataset.label
      self.dataset.can_label = False
  
      pool = self.dataset.pool
      assert np.equal(
          [i for i in pool],
          [(i, -1) for i in np.arange(labels_next_1, 100)],
      ).all()
      assert np.equal(
          [i for i in self.dataset],
          [(i, i) for i in np.arange(labels_next_1)],
      ).all()
  
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 3 for calling the ActiveDatasetTest obj's underlying member method code with example usage: obj.test_pool() without return types