code: def test_sklearn_wrong_data_type(tmp_path):
      with pytest.raises(
          RuntimeError, match="Expected the data to be numpy"
      ):
          tuner = keras_tuner.SklearnTuner(
              oracle=keras_tuner.oracles.BayesianOptimizationOracle(
                  objective=keras_tuner.Objective("score", "max"),
                  max_trials=10,
              ),
              hypermodel=build_model,
              scoring=metrics.make_scorer(metrics.accuracy_score),
              cv=model_selection.StratifiedKFold(3),
              directory=tmp_path,
          )
  
          tuner.search([1, 2, 3, 4, 5, 6], [1, 1, 1, 2, 2, 2])
  
imports: import numpy
  import pandas
  import pytest
  from sklearn import datasets
  from sklearn import decomposition
  from sklearn import ensemble
  from sklearn import linear_model
  from sklearn import metrics
  from sklearn import model_selection
  from sklearn import neighbors
  from sklearn import pipeline
  import keras_tuner
label_desc: Use image node_id 12 for calling a global function with example usage: test_sklearn_wrong_data_type(tmp_path) without return types