code: def test_classify_instance_all_batch(create_pool_classifiers):
      competences = np.array([[0.6, 0.2, 0.6], [0.5, 0.8, 0.5]])
      expected = [0, 1]
      n_samples = 2
      query = np.ones((n_samples, 2))
      pool_classifiers = create_pool_classifiers
      dcs_test = BaseDCS(pool_classifiers, selection_method="all")
      dcs_test.estimate_competence = MagicMock(
          return_value=np.array(competences)
      )
  
      predictions = []
      for clf in dcs_test.pool_classifiers:
          predictions.append(clf.predict(query)[0])
      predicted_label = dcs_test.classify_with_ds(
          np.tile(predictions, (n_samples, 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 16 for calling a global function with example usage: test_classify_instance_all_batch(create_pool_classifiers) without return types