class_docstr: Base class for all forecasters in skforecast. All forecasters should specify
  all the parameters that can be set at the class level in their ``__init__``.     
docstr: Set new value to the attribute `lags`.
  Attributes `max_lag` and `window_size` are also updated.
  
  Parameters
  ----------
  lags : int, list, numpy ndarray, range
      Lags used as predictors. Index starts at 1, so lag 1 is equal to t-1.
  
      - `int`: include lags from 1 to `lags` (included).
      - `list`, `1d numpy ndarray` or `range`: include only lags present in 
      `lags`, all elements must be int.
  
  Returns
  -------
  None
code: def set_lags(self, lags: int) -> None:
      """
      Set new value to the attribute `lags`.
      Attributes `max_lag` and `window_size` are also updated.
  
      Parameters
      ----------
      lags : int, list, numpy ndarray, range
          Lags used as predictors. Index starts at 1, so lag 1 is equal to t-1.
  
          - `int`: include lags from 1 to `lags` (included).
          - `list`, `1d numpy ndarray` or `range`: include only lags present in
          `lags`, all elements must be int.
  
      Returns
      -------
      None
  
      """
  
      pass
  
file_path: skforecast/skforecast/ForecasterBase/ForecasterBase.py
imports: from abc import ABC, abstractmethod
  from typing import Union, Dict, List, Tuple, Any, Optional
  import logging
  import pandas
label_desc: Use image node_id 5 for calling the ForecasterBase obj's underlying member method code with example usage: obj.set_lags(lags) without return types