class_docstr: Optimizer interface.
  
  Every optimizer inherits from this base interface.
  
  Parameters
  ----------
  lr
  
  Attributes
  ----------
  learning_rate : float
      Returns the current learning rate value.
docstr: Updates a weight vector before a prediction is made.
  
  Parameters:
      w (dict): A dictionary of weight parameters. The weights are modified in-place.
  
  Returns:
      The updated weights.
docstr_tok: ["Updates","a","weight","vector","before","a","prediction","is","made",".","Parameters",":","w","(","dict",")",":","A","dictionary","of","weight","parameters",".","The","weights","are","modified","in-place",".","Returns",":","The","updated","weights","."]
code: def look_ahead(self, w: dict) -> dict:
      """Updates a weight vector before a prediction is made.
  
      Parameters:
          w (dict): A dictionary of weight parameters. The weights are modified in-place.
  
      Returns:
          The updated weights.
  
      """
      return w
  
imports: from __future__ import annotations
  import abc
  import typing
  import numpy
  from river import base, optim, utils
label_desc: Use image node_id 4 for calling the Optimizer obj's underlying member method code with example usage: obj.look_ahead(w) and returns: w