code: def test_window_splitter_in_sample_fh_greater_than_window_length(CV):
      """Test WindowSplitter."""
      y = np.arange(10)
      fh = ForecastingHorizon([-5, -3])
      window_length = 3
      cv = CV(fh, window_length)
      train_windows, test_windows, cutoffs, n_splits = _check_cv(cv, y)
      np.testing.assert_array_equal(test_windows[0], np.array([0, 2]))
      np.testing.assert_array_equal(
          train_windows[0], np.array([3, 4, 5])
      )
  
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 10 for calling a global function with example usage: test_window_splitter_in_sample_fh_greater_than_window_length(CV) without return types