def METHOD_NAME(
        self, raw_client_model_or_grad_list: List[Tuple[float, OrderedDict]]
):
    if FedMLDifferentialPrivacy.get_instance().is_global_dp_enabled() and FedMLDifferentialPrivacy.get_instance().is_clipping():
        raw_client_model_or_grad_list = FedMLDifferentialPrivacy.get_instance().global_clip(raw_client_model_or_grad_list)
    if FedMLAttacker.get_instance().is_data_reconstruction_attack():
        FedMLAttacker.get_instance().reconstruct_data(
            raw_client_grad_list=raw_client_model_or_grad_list,
            extra_auxiliary_info=self.get_model_params(),
        )
    if FedMLAttacker.get_instance().is_model_attack():
        raw_client_model_or_grad_list = FedMLAttacker.get_instance().attack_model(
            raw_client_grad_list=raw_client_model_or_grad_list,
            extra_auxiliary_info=self.get_model_params(),
        )
    client_idxs = [i for i in range(len(raw_client_model_or_grad_list))]
    if FedMLDefender.get_instance().is_defense_enabled():
        raw_client_model_or_grad_list = FedMLDefender.get_instance().defend_before_aggregation(
            raw_client_grad_list=raw_client_model_or_grad_list,
            extra_auxiliary_info=self.get_model_params(),
        )
        client_idxs = FedMLDefender.get_instance().get_benign_client_idxs(client_idxs=client_idxs)
    return raw_client_model_or_grad_list, client_idxs