class_docstr: Base class for evaluating optimization convergence.
  
  Stopping criteria are implemented as a objects rather than a function, so that they
  can keep track of past function values between optimization steps.
  
  :meta private:
code: def __call__(self, fvals: Tensor) -> bool:
      return self.evaluate(fvals)
  
file_path: botorch/botorch/optim/stopping.py
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  import torch
  from torch import Tensor
label_desc: Use image node_id 2 for calling the StoppingCriterion obj's underlying member method code with example usage: obj.__call__(fvals) and returns: self