code: def test_dummy_classifier_on_3D_array():
      X = np.array([[["foo"]], [["bar"]], [["baz"]]])
      y = [2, 2, 2]
      y_expected = [2, 2, 2]
      y_proba_expected = [[1], [1], [1]]
      cls = DummyClassifier(strategy="stratified")
      cls.fit(X, y)
      y_pred = cls.predict(X)
      y_pred_proba = cls.predict_proba(X)
      assert_array_equal(y_pred, y_expected)
      assert_array_equal(y_pred_proba, y_proba_expected)
  
imports: import numpy
  import pytest
  import scipy.sparse
  from sklearn.base import clone
  from sklearn.dummy import DummyClassifier, DummyRegressor
  from sklearn.exceptions import NotFittedError
  from sklearn.utils._testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal, ignore_warnings
  from sklearn.utils.fixes import CSC_CONTAINERS
  from sklearn.utils.stats import _weighted_percentile
label_desc: Use image node_id 39 for calling a global function with example usage: test_dummy_classifier_on_3D_array() without return types