def METHOD_NAME(self, round_idx, client_indexes, mode="simulate"):
    self.runtime_history = {}
    for i in range(self.worker_num):
        self.runtime_history[i] = {}
        for j in range(self.args.client_num_in_total):
            self.runtime_history[i][j] = []
    fit_params, fit_funcs, fit_errors = t_sample_fit(
        self.worker_num, self.args.client_num_in_total, self.runtime_history, 
        self.train_data_local_num_dict, uniform_client=True, uniform_gpu=False)
    METHOD_NAME = np.array_split(client_indexes, self.worker_num)
    return METHOD_NAME