[Fix] fix container bugs

learnware/client/container.py

@@ -62,7 +62,7 @@ class ModelEnvContainer(BaseModel):
                 pickle.dump({"method": method, "kargs": kargs}, input_fp)
 
             system_execute(
-                ["conda", "run", "-n", f"{self.conda_env}", "--no-capture-output", "python3", f"{self.model_script}", f"--model-path", f"{model_path}", f"--input-path", f"{input_path}", f"--output-path", "{output_path}"]
+                ["conda", "run", "-n", f"{self.conda_env}", "--no-capture-output", "python3", f"{self.model_script}", f"--model-path", f"{model_path}", f"--input-path", f"{input_path}", f"--output-path", f"{output_path}"]
             )
 
             with open(output_path, "rb") as output_fp:
@@ -124,7 +124,6 @@ class LearnwaresContainer:
         model_list = [_learnware.get_model() for _learnware in self.learnware_list]
         with ProcessPoolExecutor(max_workers=max(os.cpu_count() // 2, 1)) as executor:
             executor.map(self._destroy_model_container, model_list)
-        return self
     
     def get_learnware_list_with_container(self):
         return self.learnware_list

learnware/client/utils.py

@@ -8,9 +8,9 @@ from .package_utils import filter_nonexist_conda_packages_file, filter_nonexist_
 
 logger = get_module_logger(module_name="client_utils")
 
-def system_execute(args):
+def system_execute(args, timeout=None):
     try:
-        com_process = subprocess.run(args, stdout=subprocess.DEVNULL, stderr=subprocess.PIPE, check=True)
+        com_process = subprocess.run(args, stdout=subprocess.DEVNULL, stderr=subprocess.PIPE, check=True, timeout=timeout)
     except subprocess.CalledProcessError as err:
         print(com_process.stderr)
         raise err

tests/test_learnware_client/test_reuse.py

@@ -3,7 +3,7 @@ import numpy as np
 
 from learnware.learnware import get_learnware_from_dirpath, Learnware
 from learnware.market import EasyMarket
-from learnware.client.container import ModelEnvContainer
+from learnware.client.container import ModelEnvContainer, LearnwaresContainer
 from learnware.learnware.reuse import AveragingReuser
 
 if __name__ == "__main__":
@@ -24,27 +24,22 @@ if __name__ == "__main__":
         '/home/bixd/workspace/learnware/Learnware/tests/test_learnware_client/svc_tic',
     ]
     
+    
     learnware_list = []
     for id, (zip_path, dir_path) in enumerate(zip(zip_paths, dir_paths)):
         with zipfile.ZipFile(zip_path, "r") as z_file:
             z_file.extractall(dir_path)
             
         learnware = get_learnware_from_dirpath(f'test_id{id}', semantic_specification, dir_path)
-
-        model = ModelEnvContainer(learnware.get_model(), zip_path)
-        model.init_env_and_metadata()
-        
-        env_leanware = Learnware(id=learnware.id, model=model, specification=learnware.get_specification())
-            
-        learnware_list.append(env_leanware)
-        
-        print('check:', EasyMarket.check_learnware(env_leanware))
-    
-    reuser = AveragingReuser(learnware_list, mode='vote')
-    input_array = np.random.randint(0, 3, size=(20, 9))
-    print(reuser.predict(input_array).argmax(axis=1))
+        learnware_list.append(learnware)
     
-    for id, ind_learner in enumerate(learnware_list):
-        print(f"learner_{id}", reuser.predict(input_array).argmax(axis=1))
+    with LearnwaresContainer(learnware_list, zip_paths) as env_container:
+        
+        learnware_list = env_container.get_learnware_list_with_container()
+        reuser = AveragingReuser(learnware_list, mode='vote')
+        input_array = np.random.randint(0, 3, size=(20, 9))
+        print(reuser.predict(input_array).argmax(axis=1))
+        for id, ind_learner in enumerate(learnware_list):
+            print(f"learner_{id}", reuser.predict(input_array).argmax(axis=1))
     
     

tests/test_learnware_client/test_reuse2.py

@@ -1,46 +0,0 @@
-import zipfile
-import numpy as np
-
-from learnware.learnware import get_learnware_from_dirpath, Learnware
-from learnware.market import EasyMarket
-from learnware.client.container import ModelEnvContainer, LearnwaresContainer
-from learnware.learnware.reuse import AveragingReuser
-
-if __name__ == "__main__":
-    semantic_specification = dict()
-    semantic_specification["Data"] = {"Type": "Class", "Values": ["Text"]}
-    semantic_specification["Task"] = {"Type": "Class", "Values": ["Ranking"]}
-    semantic_specification["Library"] = {"Type": "Class", "Values": ["Scikit-learn"]}
-    semantic_specification["Scenario"] = {"Type": "Tag", "Values": "Financial"}
-    semantic_specification["Name"] = {"Type": "String", "Values": "test"}
-    semantic_specification["Description"] = {"Type": "String", "Values": "test"}
-    
-    zip_paths = [
-        '/home/bixd/workspace/learnware/Learnware/tests/test_learnware_client/rf_tic.zip',
-        '/home/bixd/workspace/learnware/Learnware/tests/test_learnware_client/svc_tic.zip',
-    ]
-    dir_paths = [
-        '/home/bixd/workspace/learnware/Learnware/tests/test_learnware_client/rf_tic',
-        '/home/bixd/workspace/learnware/Learnware/tests/test_learnware_client/svc_tic',
-    ]
-    
-    
-    learnware_list = []
-    for id, (zip_path, dir_path) in enumerate(zip(zip_paths, dir_paths)):
-        with zipfile.ZipFile(zip_path, "r") as z_file:
-            z_file.extractall(dir_path)
-            
-        learnware = get_learnware_from_dirpath(f'test_id{id}', semantic_specification, dir_path)
-        learnware_list.append(learnware)
-    
-    with LearnwaresContainer(learnware_list, zip_paths) as env_container:
-        learnware_list = env_container.get_learnware_list_with_container()
-    
-        reuser = AveragingReuser(learnware_list, mode='vote')
-        input_array = np.random.randint(0, 3, size=(20, 9))
-        print(reuser.predict(input_array).argmax(axis=1))
-    
-        for id, ind_learner in enumerate(learnware_list):
-            print(f"learner_{id}", reuser.predict(input_array).argmax(axis=1))
-    
-