def reset_trial(self, trial, new_config, new_experiment_tag):
        """Tries to invoke `Trainable.reset_config()` to reset trial.

        Args:
            trial (Trial): Trial to be reset.
            new_config (dict): New configuration for Trial
                trainable.
            new_experiment_tag (str): New experiment name
                for trial.

        Returns:
            True if `reset_config` is successful else False.
        """
        trial.experiment_tag = new_experiment_tag
        trial.config = new_config
        trainable = trial.runner
        with warn_if_slow("reset_config"):
            reset_val = ray.get(trainable.reset_config.remote(new_config))
        return reset_val
Tries to invoke `Trainable.reset_config()` to reset trial.

        Args:
            trial (Trial): Trial to be reset.
            new_config (dict): New configuration for Trial
                trainable.
            new_experiment_tag (str): New experiment name
                for trial.

        Returns:
            True if `reset_config` is successful else False.