From bf43b582cccedd247f37cf1f596cdcc3112922b5 Mon Sep 17 00:00:00 2001 From: bxdd Date: Thu, 12 Oct 2023 16:36:03 +0800 Subject: [PATCH] [MNT] black format --- learnware/client/learnware_client.py | 12 +++++++++--- learnware/learnware/base.py | 2 +- learnware/learnware/reuse.py | 4 ++-- 3 files changed, 12 insertions(+), 6 deletions(-) diff --git a/learnware/client/learnware_client.py b/learnware/client/learnware_client.py index 645d1ff..2982cdf 100644 --- a/learnware/client/learnware_client.py +++ b/learnware/client/learnware_client.py @@ -432,11 +432,17 @@ class LearnwareClient: logger.info("test ok") pass - def reuse_learnware(self, input_array: np.ndarray, learnware_list: List[Learnware], learnware_zippaths: List[str], reuser: BaseReuser): + def reuse_learnware( + self, + input_array: np.ndarray, + learnware_list: List[Learnware], + learnware_zippaths: List[str], + reuser: BaseReuser, + ): logger.info(f"reuse learnare list {learnware_list} with reuser {reuser}") with LearnwaresContainer(learnware_list, learnware_zippaths) as env_container: learnware_list = env_container.get_learnware_list_with_container() reuser.reset(learnware_list=learnware_list) result = reuser.predict(input_array) - - return result \ No newline at end of file + + return result diff --git a/learnware/learnware/base.py b/learnware/learnware/base.py index 4662369..7f309fd 100644 --- a/learnware/learnware/base.py +++ b/learnware/learnware/base.py @@ -91,7 +91,7 @@ class BaseReuser: for _k, _v in kwargs.items(): if hasattr(_k): setattr(_k, _v) - + def predict(self, user_data: np.ndarray) -> np.ndarray: """Give the final prediction for user data with reused learnware diff --git a/learnware/learnware/reuse.py b/learnware/learnware/reuse.py index 0091e6b..565ba89 100644 --- a/learnware/learnware/reuse.py +++ b/learnware/learnware/reuse.py @@ -265,7 +265,7 @@ class JobSelectorReuser(BaseReuser): class AveragingReuser(BaseReuser): """Baseline Multiple Learnware Reuser using Ensemble Method""" - def __init__(self, learnware_list: List[Learnware] = None, mode: str = 'mean'): + def __init__(self, learnware_list: List[Learnware] = None, mode: str = "mean"): """The initialization method for averaging ensemble reuser Parameters @@ -330,7 +330,7 @@ class EnsemblePruningReuser(BaseReuser): References: [1] Yu-Chang Wu, Yi-Xiao He, Chao Qian, and Zhi-Hua Zhou. Multi-objective Evolutionary Ensemble Pruning Guided by Margin Distribution. In: Proceedings of the 17th International Conference on Parallel Problem Solving from Nature (PPSN'22), Dortmund, Germany, 2022. """ - def __init__(self, learnware_list: List[Learnware] = None, mode: str = 'classification'): + def __init__(self, learnware_list: List[Learnware] = None, mode: str = "classification"): """The initialization method for ensemble pruning reuser Parameters