code: def _simple_exhaustive_active_learning_test(
      self,
      query_strategy,
      query_size=10,
      num_classes=6,
      num_initial=30,
      multi_label=False,
  ):
      dataset = self._get_dataset(num_classes, multi_label=multi_label)
      clf_factory = self._get_factory(
          num_classes, multi_label=multi_label
      )
      active_learner = get_initialized_active_learner(
          clf_factory,
          query_strategy,
          dataset,
          initial_indices=num_initial,
          num_classes=num_classes,
          multi_label=multi_label,
      )
  
      for _ in range(3):
          active_learner.query()
          if multi_label:
              _, y_new = random_matrix_data(
                  "dense",
                  "sparse",
                  num_samples=10,
                  num_labels=num_classes,
              )
          else:
              _, y_new = random_matrix_data(
                  "dense",
                  "dense",
                  num_samples=10,
                  num_labels=num_classes,
              )
          active_learner.update(y_new)
  
      with self.assertRaises(EmptyPoolException):
          active_learner.query()
  
      self.assertEqual(
          query_size * 3 + num_initial,
          active_learner.indices_labeled.shape[0],
      )
  
imports: import unittest
  import pytest
  import numpy
  from unittest.mock import Mock, patch
  from numpy.testing import assert_array_equal
  from sklearn.base import clone
  from sklearn.preprocessing import normalize
  from small_text.query_strategies.exceptions import EmptyPoolException
  from small_text.classifiers import ConfidenceEnhancedLinearSVC, SklearnClassifierFactory
  from small_text.query_strategies import BreakingTies, CategoryVectorInconsistencyAndRanking, ContrastiveActiveLearning, DiscriminativeActiveLearning, EmbeddingKMeans, GreedyCoreset, LeastConfidence, LightweightCoreset, SEALS, SubsamplingQueryStrategy
  from tests.unit.small_text.query_strategies.test_strategies import SamplingStrategiesTests, SklearnClassifierWithRandomEmbeddingsAndProba
  from tests.utils.datasets import random_sklearn_dataset, random_matrix_data
  from tests.utils.object_factory import get_initialized_active_learner
label_desc: Use image node_id 3 for calling the QueryStrategiesExhaustiveIntegrationTest obj's underlying member method code with example usage: obj._simple_exhaustive_active_learning_test(query_strategy, query_size, num_classes, num_initial, multi_label) without return types