code: def test_classify_instance_batch(create_pool_classifiers):
      n_samples = 3
      n_classifiers = 3
      query = np.ones((n_samples, 2))
      pool_classifiers = create_pool_classifiers
      dcs_test = BaseDCS(pool_classifiers)
  
      competences = np.random.rand(n_samples, n_classifiers)
  
      dcs_test.estimate_competence = MagicMock(return_value=competences)
      expected = []
      for ind in range(n_samples):
          expected.append(
              pool_classifiers[np.argmax(competences[ind, :])].predict(
                  query
              )[0]
          )
  
      predictions = []
      for clf in dcs_test.pool_classifiers:
          predictions.append(clf.predict(query)[0])
      predicted_label = dcs_test.classify_with_ds(
          np.tile(predictions, (3, 1))
      )
      assert np.array_equal(predicted_label, expected)
  
imports: from unittest.mock import MagicMock
  import numpy
  import pytest
  from deslib.dcs.base import BaseDCS
label_desc: Use image node_id 14 for calling a global function with example usage: test_classify_instance_batch(create_pool_classifiers) without return types