def METHOD_NAME(self) -> None:
    with skip_if_downloading_fails():
        bundle_generator = BundleGen(
            algo_path=self.work_dir,
            data_stats_filename=self.da_output_yaml,
            data_src_cfg_name=self.data_src_cfg_name,
            templates_path_or_url=get_testing_algo_template_path(),
        )
    bundle_generator.generate(self.work_dir, num_fold=1)
    history = bundle_generator.get_history()
    for algo_dict in history:
        name = algo_dict[AlgoKeys.ID]
        algo = algo_dict[AlgoKeys.ALGO]
        _train_param = train_param.copy()
        if name.startswith("segresnet"):
            _train_param["network#init_filters"] = 8
            _train_param["pretrained_ckpt_name"] = ""
        elif name.startswith("swinunetr"):
            _train_param["network#feature_size"] = 12
        algo.train(_train_param)
    builder = AlgoEnsembleBuilder(history, data_src_cfg_name=self.data_src_cfg_name)
    builder.set_ensemble_method(AlgoEnsembleBestN(n_best=1))
    ensemble = builder.get_ensemble()
    preds = ensemble(pred_param)
    self.assertTupleEqual(preds[0].shape, (2, 24, 24, 24))
    builder.set_ensemble_method(AlgoEnsembleBestByFold(1))
    ensemble = builder.get_ensemble()
    for algo in ensemble.get_algo_ensemble():
        print(algo[AlgoKeys.ID])