code: def test_get_response_values_regressor(return_response_method_used):
      """Check the behaviour of `_get_response_values` with regressor."""
      X, y = make_regression(n_samples=10, random_state=0)
      regressor = LinearRegression().fit(X, y)
      results = _get_response_values(
          regressor,
          X,
          response_method="predict",
          return_response_method_used=return_response_method_used,
      )
      assert_array_equal(results[0], regressor.predict(X))
      assert results[1] is None
      if return_response_method_used:
          assert results[2] == "predict"
  
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 2 for calling a global function with example usage: test_get_response_values_regressor(return_response_method_used) without return types