Parameters
        ----------
        data: dict()
            it has three keys: trial_job_id, event, hyper_params
            trial_job_id: the id generated by training service
            event: the job's state
            hyper_params: the hyperparameters (a string) generated and returned by tuner

def handle_trial_end(self, data):
        """
        Parameters
        ----------
        data: dict()
            it has three keys: trial_job_id, event, hyper_params
            trial_job_id: the id generated by training service
            event: the job's state
            hyper_params: the hyperparameters (a string) generated and returned by tuner
        """
        hyper_params = json_tricks.loads(data['hyper_params'])
        bracket_id, i, _ = hyper_params['parameter_id'].split('_')
        hyper_configs = self.brackets[int(bracket_id)].inform_trial_end(int(i))
        if hyper_configs is not None:
            _logger.debug('bracket %s next round %s, hyper_configs: %s', bracket_id, i, hyper_configs)
            self.generated_hyper_configs = self.generated_hyper_configs + hyper_configs
            for _ in range(self.credit):
                if not self.generated_hyper_configs:
                    break
                params = self.generated_hyper_configs.pop()
                ret = {
                    'parameter_id': params[0],
                    'parameter_source': 'algorithm',
                    'parameters': params[1]
                }
                send(CommandType.NewTrialJob, json_tricks.dumps(ret))
                self.credit -= 1