code: def test_strategy_drift_window_length(fh, window_length):
      """Test whether window_length is properly working."""
      if window_length != 1:
          if window_length is None:
              window_length = len(y_train)
  
          values = np.random.normal(size=window_length)
          y = pd.Series(values)
          f = NaiveForecaster(
              strategy="drift", window_length=window_length
          )
          f.fit(y)
          y_pred = f.predict(fh)
  
          slope = (values[-1] - values[0]) / (window_length - 1)
  
          # get well formatted fh values
          fh = check_fh(fh)
          expected = values[-1] + slope * fh
  
          np.testing.assert_array_equal(y_pred, expected)
  
imports: import numpy
  import pandas
  import pytest
  from sktime.datatypes._utilities import get_cutoff
  from sktime.forecasting.base import ForecastingHorizon
  from sktime.forecasting.naive import NaiveForecaster
  from sktime.forecasting.tests._config import TEST_OOS_FHS, TEST_SPS, TEST_WINDOW_LENGTHS_INT
  from sktime.utils._testing.forecasting import _assert_correct_pred_time_index
  from sktime.utils.validation.forecasting import check_fh
label_desc: Use image node_id 8 for calling a global function with example usage: test_strategy_drift_window_length(fh, window_length) without return types