code: def test_isotonic_non_regression_inf_slope():
      # Non-regression test to ensure that inf values are not returned
      # see: https://github.com/scikit-learn/scikit-learn/issues/10903
      X = np.array([0.0, 4.1e-320, 4.4e-314, 1.0])
      y = np.array([0.42, 0.42, 0.44, 0.44])
      ireg = IsotonicRegression().fit(X, y)
      y_pred = ireg.predict(np.array([0, 2.1e-319, 5.4e-316, 1e-10]))
      assert np.all(np.isfinite(y_pred))
  
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 34 for calling a global function with example usage: test_isotonic_non_regression_inf_slope() without return types