code: def test_isotonic_regression_auto_increasing():
      # Set y and x for decreasing
      y = np.array([5, 6.1, 6, 7, 10, 9, 10])
      x = np.arange(len(y))
  
      # Create model and fit_transform
      ir = IsotonicRegression(increasing="auto")
      with warnings.catch_warnings(record=True) as w:
          warnings.simplefilter("always")
          y_ = ir.fit_transform(x, y)
          # work-around for pearson divide warnings in scipy <= 0.17.0
          assert all(
              [
                  "invalid value encountered in " in str(warn.message)
                  for warn in w
              ]
          )
  
      # Check that relationship increases
      is_increasing = y_[0] < y_[-1]
      assert is_increasing
  
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 15 for calling a global function with example usage: test_isotonic_regression_auto_increasing() without return types