code: def get_early_stop_trials(self, trials):
      result = []
  
      for trial in trials:
          study = Study.objects.get(name=trial.study_name)
          study_configuration_json = json.loads(
              study.study_configuration
          )
          study_goal = study_configuration_json["goal"]
  
          metrics = TrialMetric.objects.filter(
              trial_id=trial.id
          ).order_by("-training_step")
          metrics = [metric for metric in metrics]
  
          if len(metrics) >= 2:
              if study_goal == "MAXIMIZE":
                  if (
                      metrics[0].objective_value
                      < metrics[1].objective_value
                  ):
                      result.append(trial)
              elif study_goal == "MINIMIZE":
                  if (
                      metrics[0].objective_value
                      > metrics[1].objective_value
                  ):
                      result.append(trial)
  
      return result
  
imports: import json
  from suggestion.models import Study
  from suggestion.models import TrialMetric
  from suggestion.early_stop_algorithm.abstract_early_stop import AbstractEarlyStopAlgorithm
label_desc: Use image node_id 1 for calling the EarlyStopDescendingAlgorithm obj's underlying member method code with example usage: obj.get_early_stop_trials(trials) and returns: result