code: def __call__(self, optimizer: base.Optimizer) -> bool:
      best_param = optimizer.provide_recommendation()
      if best_param is None or (
          best_param.loss is None and best_param._losses is None
      ):
          return False
      best_last_losses = best_param.losses
      if self._best_value is None:
          self._best_value = best_last_losses
          return False
      if self._best_value <= best_last_losses:
          self._tolerance_count += 1
      else:
          self._tolerance_count = 0
          self._best_value = best_last_losses
      return self._tolerance_count > self._tolerance_window
  
imports: import json
  import time
  import warnings
  import inspect
  import datetime
  import logging
  from pathlib import Path
  import numpy
  import nevergrad.common.typing
  from nevergrad.common import errors
  from nevergrad.parametrization import parameter
  from nevergrad.parametrization import helpers
  from .None import base
label_desc: Use image node_id 2 for calling the _LossImprovementToleranceCriterion obj's underlying member method code with example usage: obj.__call__(optimizer) and returns: unknown, False, False