[ENH] add reuse method in learnware client

learnware/client/container.py

@@ -129,19 +129,11 @@ class LearnwaresContainer:
 
     @staticmethod
     def _initialize_model_container(model: ModelEnvContainer):
-        try:
-            model.init_env_and_metadata()
-        except Exception as e:
-            logger.warning(f"fail to initialize model container, due to {e}")
-            pass
+        model.init_env_and_metadata()
 
     @staticmethod
     def _destroy_model_container(model: ModelEnvContainer):
-        try:
-            model.remove_env()
-        except Exception as e:
-            logger.warning(f"fail to destroy model container, due to {e}")
-            pass
+        model.remove_env()
 
     def __enter__(self):
         model_list = [_learnware.get_model() for _learnware in self.learnware_list]

learnware/client/learnware_client.py

@@ -1,4 +1,5 @@
 import os
+import numpy as np
 import yaml
 import json
 import zipfile
@@ -7,13 +8,16 @@ import requests
 import tempfile
 from enum import Enum
 from tqdm import tqdm
+from typing import List
 
 from ..config import C
 from .. import learnware
 from . import package_utils
+from .container import LearnwaresContainer
 from ..market.easy import EasyMarket
 from ..logger import get_module_logger
 from ..specification import Specification
+from ..learnware import BaseReuser, Learnware
 
 CHUNK_SIZE = 1024 * 1024
 logger = get_module_logger(module_name="LearnwareClient")
@@ -427,3 +431,12 @@ 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):
+        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

learnware/learnware/base.py

@@ -77,7 +77,7 @@ class Learnware:
 class BaseReuser:
     """Providing the interfaces to reuse the learnwares which is searched by learnware"""
 
-    def __init__(self, learnware_list: List[Learnware]):
+    def __init__(self, learnware_list: List[Learnware] = None):
         """The initializaiton method for base reuser
 
         Parameters
@@ -87,6 +87,11 @@ class BaseReuser:
         """
         self.learnware_list = learnware_list
 
+    def reset(self, **kwargs):
+        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
 

learnware/learnware/reuse.py

@@ -21,7 +21,7 @@ logger = get_module_logger("Reuser")
 class JobSelectorReuser(BaseReuser):
     """Baseline Multiple Learnware Reuser using Job Selector Method"""
 
-    def __init__(self, learnware_list: List[Learnware], herding_num: int = 1000, use_herding: bool = True):
+    def __init__(self, learnware_list: List[Learnware] = None, herding_num: int = 1000, use_herding: bool = True):
         """The initialization method for job selector reuser
 
         Parameters
@@ -265,7 +265,7 @@ class JobSelectorReuser(BaseReuser):
 class AveragingReuser(BaseReuser):
     """Baseline Multiple Learnware Reuser using Ensemble Method"""
 
-    def __init__(self, learnware_list: List[Learnware], mode: str):
+    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], mode: str):
+    def __init__(self, learnware_list: List[Learnware] = None, mode: str = 'classification'):
         """The initialization method for ensemble pruning reuser
 
         Parameters