code: def test_make_unique_dtype():
      x_list = [2, 2, 2, 3, 5]
      for dtype in (np.float32, np.float64):
          x = np.array(x_list, dtype=dtype)
          y = x.copy()
          w = np.ones_like(x)
          x, y, w = _make_unique(x, y, w)
          assert_array_equal(x, [2, 3, 5])
  
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 31 for calling a global function with example usage: test_make_unique_dtype() without return types