code: def _check_cutoffs_against_train_windows(cutoffs, windows, y):
      # Cutoffs should always be the last values of the train windows.
      assert array_is_int(cutoffs)
      actual = np.array([window[-1] for window in windows[1:]])
      np.testing.assert_array_equal(actual, cutoffs[1:])
  
      # We treat the first window separately, since it may be empty when setting
      # `start_with_window=False`.
      if len(windows[0]) > 0:
          np.testing.assert_array_equal(windows[0][-1], cutoffs[0])
  
file_path: sktime/sktime/split/tests/test_split.py
imports: import numpy
  import pytest
  from sktime.forecasting.base import ForecastingHorizon
  from sktime.split import ExpandingWindowSplitter, SlidingWindowSplitter
  from sktime.utils.datetime import _coerce_duration_to_int
  from sktime.utils.validation import array_is_datetime64, array_is_int, array_is_timedelta_or_date_offset, is_int
  from sktime.utils.validation.forecasting import check_fh
label_desc: Use image node_id 6 for calling a global function with example usage: _check_cutoffs_against_train_windows(cutoffs, windows, y) without return types