code: def __call__(self, trial_id, result):
      if self._metric_threshold is not None:
          if (
              self._mode == "max"
              and result[self._metric] >= self._metric_threshold
          ):
              return True
          if (
              self._mode == "min"
              and result[self._metric] <= self._metric_threshold
          ):
              return True
      if result["training_iteration"] >= self._epochs:
          return True
      return False
  
imports: import ray
  from ray import tune
  import os
  from bigdl.orca.automl.search.base import SearchEngine, TrialOutput, GoodError
  from bigdl.orca.automl.search.parameters import DEFAULT_LOGGER_NAME, DEFAULT_METRIC_NAME
  from bigdl.orca.automl.search.ray_tune.utils import convert_bayes_configs
  from bigdl.orca.automl.search.utils import get_ckpt_hdfs, put_ckpt_hdfs
  from ray.tune import Stopper
  from bigdl.orca.automl.model.abstract import ModelBuilder
  from bigdl.orca.data import ray_xshards
  from ray.tune.progress_reporter import TrialProgressCallback
  from bigdl.dllib.utils.log4Error import *
label_desc: Use image node_id 2 for calling the TrialStopper obj's underlying member method code with example usage: obj.__call__(trial_id, result) and returns: False, True, True, True