code: def test_isotonic_regression_pickle():
      y = np.array([3, 7, 5, 9, 8, 7, 10])
      x = np.arange(len(y))
  
      # Create model and fit
      ir = IsotonicRegression(increasing="auto", out_of_bounds="clip")
      ir.fit(x, y)
  
      ir_ser = pickle.dumps(ir, pickle.HIGHEST_PROTOCOL)
      ir2 = pickle.loads(ir_ser)
      np.testing.assert_array_equal(ir.predict(x), ir2.predict(x))
  
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 23 for calling a global function with example usage: test_isotonic_regression_pickle() without return types