code: def test_isotonic_mismatched_dtype(y_dtype):
      # regression test for #15004
      # check that data are converted when X and y dtype differ
      reg = IsotonicRegression()
      y = np.array([2, 1, 4, 3, 5], dtype=y_dtype)
      X = np.arange(len(y), dtype=np.float32)
      reg.fit(X, y)
      assert reg.predict(X).dtype == X.dtype
  
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 30 for calling a global function with example usage: test_isotonic_mismatched_dtype(y_dtype) without return types