ax/early_stopping/strategies/percentile.py [65:95]:
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        self.trial_indices_to_ignore = trial_indices_to_ignore

    def should_stop_trials_early(
        self,
        trial_indices: Set[int],
        experiment: Experiment,
        **kwargs: Dict[str, Any],
    ) -> Dict[int, Optional[str]]:
        """Stop a trial if its performance is in the bottom `percentile_threshold`
        of the trials at the same step.

        Args:
            trial_indices: Indices of candidate trials to consider for early stopping.
            experiment: Experiment that contains the trials and other contextual data.

        Returns:
            A dictionary mapping trial indices that should be early stopped to
            (optional) messages with the associated reason. An empty dictionary
            means no suggested updates to any trial's status.
        """
        data = self._check_validity_and_get_data(experiment=experiment)
        if data is None:
            # don't stop any trials if we don't get data back
            return {}

        optimization_config = not_none(experiment.optimization_config)
        objective_name = optimization_config.objective.metric.name

        map_key = next(iter(data.map_keys))
        minimize = optimization_config.objective.minimize
        df = data.map_df
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ax/early_stopping/strategies/threshold.py [45:75]:
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        self.trial_indices_to_ignore = trial_indices_to_ignore

    def should_stop_trials_early(
        self,
        trial_indices: Set[int],
        experiment: Experiment,
        **kwargs: Dict[str, Any],
    ) -> Dict[int, Optional[str]]:
        """Stop a trial if its performance doesn't reach a pre-specified threshold
        by `min_progression`.

        Args:
            trial_indices: Indices of candidate trials to consider for early stopping.
            experiment: Experiment that contains the trials and other contextual data.

        Returns:
            A dictionary mapping trial indices that should be early stopped to
            (optional) messages with the associated reason. An empty dictionary
            means no suggested updates to any trial's status.
        """
        data = self._check_validity_and_get_data(experiment=experiment)
        if data is None:
            # don't stop any trials if we don't get data back
            return {}

        optimization_config = not_none(experiment.optimization_config)
        objective_name = optimization_config.objective.metric.name

        map_key = next(iter(data.map_keys))
        minimize = optimization_config.objective.minimize
        df = data.map_df
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