class_docstr: Creates window boundaries for fixed-length windows that include the current row.
  
  Examples
  --------
  >>> df = pd.DataFrame({'B': [0, 1, 2, np.nan, 4]})
  >>> df
       B
  0  0.0
  1  1.0
  2  2.0
  3  NaN
  4  4.0
  
  >>> indexer = pd.api.indexers.FixedForwardWindowIndexer(window_size=2)
  >>> df.rolling(window=indexer, min_periods=1).sum()
       B
  0  1.0
  1  3.0
  2  2.0
  3  4.0
  4  4.0
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code: def get_window_bounds(
      self,
      num_values: int = 0,
      min_periods: int | None = None,
      center: bool | None = None,
      closed: str | None = None,
      step: int | None = None,
  ) -> tuple[np.ndarray, np.ndarray]:
      if center:
          raise ValueError(
              "Forward-looking windows can't have center=True"
          )
      if closed is not None:
          raise ValueError(
              "Forward-looking windows don't support setting the closed argument"
          )
      if step is None:
          step = 1
  
      start = np.arange(0, num_values, step, dtype="int64")
      end = start + self.window_size
      if self.window_size:
          end = np.clip(end, 0, num_values)
  
      return start, end
  
imports: from __future__ import annotations
  from datetime import timedelta
  import numpy
  from pandas._libs.tslibs import BaseOffset
  from pandas._libs.window.indexers import calculate_variable_window_bounds
  from pandas.util._decorators import Appender
  from pandas.core.dtypes.common import ensure_platform_int
  from pandas.core.indexes.datetimes import DatetimeIndex
  from pandas.tseries.offsets import Nano
label_desc: Use image node_id 1 for calling the FixedForwardWindowIndexer obj's underlying member method code with example usage: obj.get_window_bounds(num_values, min_periods, center, closed, step) and returns: start,  end