code: def test_isotonic_regression_output_predict():
      """Check that `predict` does return the expected output type.
  
      We need to check that `transform` will output a DataFrame and a NumPy array
      when we set `transform_output` to `pandas`.
  
      Non-regression test for:
      https://github.com/scikit-learn/scikit-learn/issues/25499
      """
      pd = pytest.importorskip("pandas")
      X, y = make_regression(
          n_samples=10, n_features=1, random_state=42
      )
      regressor = IsotonicRegression()
      with sklearn.config_context(transform_output="pandas"):
          regressor.fit(X, y)
          X_trans = regressor.transform(X)
          y_pred = regressor.predict(X)
  
      assert isinstance(X_trans, pd.DataFrame)
      assert isinstance(y_pred, np.ndarray)
  
imports: import copy
  import pickle
  import warnings
  import numpy
  import pytest
  from scipy.special import expit
  import sklearn
  from sklearn.datasets import make_regression
  from sklearn.isotonic import IsotonicRegression, _make_unique, check_increasing, isotonic_regression
  from sklearn.utils import shuffle
  from sklearn.utils._testing import assert_allclose, assert_array_almost_equal, assert_array_equal
  from sklearn.utils.validation import check_array
label_desc: Use image node_id 40 for calling a global function with example usage: test_isotonic_regression_output_predict() without return types