code: def test_get_response_values_classifier_inconsistent_y_pred_for_binary_proba(
      response_method,
  ):
      """Check that `_get_response_values` will raise an error when `y_pred` has a
      single class with `predict_proba`."""
      X, y_two_class = make_classification(
          n_samples=10, n_classes=2, random_state=0
      )
      y_single_class = np.zeros_like(y_two_class)
      classifier = DecisionTreeClassifier().fit(X, y_single_class)
  
      err_msg = (
          r"Got predict_proba of shape \(10, 1\), but need classifier with "
          r"two classes"
      )
      with pytest.raises(ValueError, match=err_msg):
          _get_response_values(
              classifier, X, response_method=response_method
          )
  
imports: import numpy
  import pytest
  from sklearn.datasets import load_iris, make_classification, make_multilabel_classification, make_regression
  from sklearn.ensemble import IsolationForest
  from sklearn.linear_model import LinearRegression, LogisticRegression
  from sklearn.multioutput import ClassifierChain
  from sklearn.preprocessing import scale
  from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from sklearn.utils._mocking import _MockEstimatorOnOffPrediction
  from sklearn.utils._response import _get_response_values, _get_response_values_binary
  from sklearn.utils._testing import assert_allclose, assert_array_equal
label_desc: Use image node_id 5 for calling a global function with example usage: test_get_response_values_classifier_inconsistent_y_pred_for_binary_proba(response_method) without return types