class_docstr: Decide to continue or not given the results so far.
  
  The optimization procedure will be stopped if the callback returns True.
class_docstr_tok: ["Decide","to","continue","or","not","given","the","results","so","far",".","The","optimization","procedure","will","be","stopped","if","the","callback","returns","True","."]
docstr: Compute the decision to stop or not.
  
  Classes inheriting from `EarlyStop` should use this method to
  implement their decision logic.
  
  Parameters
  ----------
  result : `OptimizeResult`, scipy object
      The optimization as a OptimizeResult object.
  
  Returns
  -------
  decision : boolean or None
      Return True/False if the criterion can make a decision or `None` if
      there is not enough data yet to make a decision.
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code: def _criterion(self, result):
      """Compute the decision to stop or not.
  
      Classes inheriting from `EarlyStop` should use this method to
      implement their decision logic.
  
      Parameters
      ----------
      result : `OptimizeResult`, scipy object
          The optimization as a OptimizeResult object.
  
      Returns
      -------
      decision : boolean or None
          Return True/False if the criterion can make a decision or `None` if
          there is not enough data yet to make a decision.
      """
      raise NotImplementedError(
          "The _criterion method should be implemented"
          " by subclasses of EarlyStopper."
      )
  
imports: from time import time
  import numpy
  from guild._skopt.utils import dump
label_desc: Use image node_id 2 for calling the EarlyStopper obj's underlying member method code with example usage: obj._criterion(result) without return types