code: def test_trial_split_is_new_best_score_should_return_false_with_not_a_new_best_score(
      self,
  ):
      with self.trial.new_validation_split(False) as trial_split:
          trial_split: TrialSplit = trial_split
          trial_split.with_n_epochs(2)
  
          trial_split.next_epoch()
          with trial_split.managed_metric(
              SOME_OTHER_METRIC_NAME_MSE, higher_score_is_better=False
          ) as metric:
              metric: MetricResults = metric
  
              metric.add_train_result(0.45)
              metric.add_valid_result(0.5)
  
          trial_split.next_epoch()
          with trial_split.managed_metric(
              SOME_OTHER_METRIC_NAME_MSE, higher_score_is_better=False
          ) as metric:
              metric: MetricResults = metric
  
              metric.add_train_result(0.6)
              metric.add_valid_result(0.7)
  
              assert not metric.is_new_best_score()
  
imports: import copy
  import datetime
  import json
  from neuraxle.base import TrialStatus
  from neuraxle.hyperparams.space import HyperparameterSamples
  from neuraxle.logging.logging import LOGGING_DATETIME_STR_FORMAT
  from neuraxle.metaopt.context import AutoMLContext
  from neuraxle.metaopt.data.aggregates import MetricResults, Round, Trial, TrialSplit
  from neuraxle.metaopt.data.vanilla import ClientDataclass, MetricResultsDataclass, RoundDataclass, ScopedLocation, TrialDataclass, to_json
  from testing_neuraxle.metaopt.test_automl_dataclasses import SOME_FULL_SCOPED_LOCATION, SOME_ROOT_DATACLASS, SOME_TRIAL_DATACLASS
label_desc: Use image node_id 5 for calling the TestTrials obj's underlying member method code with example usage: obj.test_trial_split_is_new_best_score_should_return_false_with_not_a_new_best_score() without return types