code: def test_get_probs(heur, num_get_probs):
      dataset = ActiveLearningDataset(
          MyDataset(), make_unlabelled=lambda x: -1
      )
      active_loop = ActiveLearningLoop(
          dataset, get_probs_iter, heur, query_size=5, dummy_param=1
      )
      dataset.label_randomly(10)
      with patch.object(active_loop, "get_probabilities") as mock_probs:
          active_loop.step()
      assert mock_probs.call_count == num_get_probs
  
imports: import os
  import pickle
  import warnings
  from unittest.mock import patch
  import numpy
  import pytest
  from torch.utils.data import Dataset
  from baal.active import ActiveLearningDataset, heuristics
  from baal.active.active_loop import ActiveLearningLoop
label_desc: Use image node_id 8 for calling a global function with example usage: test_get_probs(heur, num_get_probs) without return types