class_docstr: Base class for sliding and expanding window splitter.
docstr: Abstract method for sliding/expanding windows.
docstr_tok: ["Abstract","method","for","sliding\/expanding","windows","."]
code: def _split_windows(
      self,
      window_length: ACCEPTED_WINDOW_LENGTH_TYPES,
      y: pd.Index,
      fh: ForecastingHorizon,
  ) -> SPLIT_GENERATOR_TYPE:
      """Abstract method for sliding/expanding windows."""
      raise NotImplementedError("abstract method")
  
imports: from typing import Optional
  import numpy
  import pandas
  from sktime.datatypes._utilities import get_index_for_series
  from sktime.forecasting.base import ForecastingHorizon
  from sktime.split.base import BaseSplitter
  from sktime.split.base._common import ACCEPTED_Y_TYPES, FORECASTING_HORIZON_TYPES, SPLIT_ARRAY_TYPE, SPLIT_GENERATOR_TYPE, _check_fh, _check_inputs_for_compatibility, _get_end
  from sktime.utils.validation import ACCEPTED_WINDOW_LENGTH_TYPES, NON_FLOAT_WINDOW_LENGTH_TYPES, array_is_int, check_window_length, is_int, is_timedelta_or_date_offset
  from sktime.utils.validation.forecasting import check_step_length
label_desc: Use image node_id 5 for calling the BaseWindowSplitter obj's underlying member method code with example usage: obj._split_windows(window_length, y, fh) without return types