[MNT] black format

examples/dataset_pfs_workflow/pfs/pfs_cross_transfer.py

@@ -85,9 +85,7 @@ def get_split_errs(algo):
                 split = train_xs.shape[0] - proportion_list[tmp]
 
                 model.fit(
-                    train_xs[
-                        split:,
-                    ],
+                    train_xs[split:,],
                     train_ys[split:],
                     eval_set=[(val_xs, val_ys)],
                     early_stopping_rounds=50,

learnware/client/container.py

@@ -127,18 +127,16 @@ class LearnwaresContainer:
             )
             for _learnware, _zippath in zip(learnware_list, learnware_zippaths)
         ]
-        
+
         # We should first register the destroy method
         atexit.register(self.cleanup)
         self.init_env()
-        
+
     def init_env(self):
         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._initialize_model_container, model_list)
 
-        
-
     def cleanup(self):
         for _learnware in self.learnware_list:
             self._destroy_model_container(_learnware.get_model())
@@ -148,17 +146,14 @@ class LearnwaresContainer:
         try:
             model.init_env_and_metadata()
         except Exception as err:
-            logger.warning(f"build env {model.conda_env} failed due to {err}") 
+            logger.warning(f"build env {model.conda_env} failed due to {err}")
 
     @staticmethod
     def _destroy_model_container(model: ModelEnvContainer):
         try:
             model.remove_env()
         except Exception as err:
-            logger.warning(f"remove env {model.conda_env} failed due to {err}") 
-            
+            logger.warning(f"remove env {model.conda_env} failed due to {err}")
 
     def get_learnware_list_with_container(self):
         return self.learnware_list
-
-    

learnware/test/__init__.py

@@ -1 +1 @@
-from .module import get_semantic_specification
+from .module import get_semantic_specification

learnware/test/module.py

@@ -1,5 +1,3 @@
-
-
 def get_semantic_specification():
     semantic_specification = dict()
     semantic_specification["Data"] = {"Type": "Class", "Values": ["Text"]}
@@ -8,4 +6,4 @@ def get_semantic_specification():
     semantic_specification["Scenario"] = {"Type": "Tag", "Values": "Financial"}
     semantic_specification["Name"] = {"Type": "String", "Values": "test"}
     semantic_specification["Description"] = {"Type": "String", "Values": "test"}
-    return semantic_specification
+    return semantic_specification

tests/test_learnware_client/test_learnware.py

@@ -3,7 +3,7 @@ from learnware.test import get_semantic_specification
 
 if __name__ == "__main__":
     semantic_specification = get_semantic_specification()
-    
+
     zip_path = "test.zip"
     client = LearnwareClient()
     client.install_environment(zip_path)

tests/test_learnware_client/test_load.py

@@ -24,7 +24,7 @@ class TestLearnwareLoad(unittest.TestCase):
         self.zip_paths = [os.path.join(root, x) for x in ["1.zip", "2.zip", "3.zip"]]
 
     def test_load_single_learnware_by_zippath(self):
-        for (learnware_id, zip_path) in zip(self.learnware_ids, self.zip_paths):
+        for learnware_id, zip_path in zip(self.learnware_ids, self.zip_paths):
             self.client.download_learnware(learnware_id, zip_path)
 
         learnware_list = [
@@ -39,7 +39,7 @@ class TestLearnwareLoad(unittest.TestCase):
             print(learnware.id, learnware.predict(input_array))
 
     def test_load_multi_learnware_by_zippath(self):
-        for (learnware_id, zip_path) in zip(self.learnware_ids, self.zip_paths):
+        for learnware_id, zip_path in zip(self.learnware_ids, self.zip_paths):
             self.client.download_learnware(learnware_id, zip_path)
 
         learnware_list = self.client.load_learnware(learnware_path=self.zip_paths, runnable_option="conda_env")

tests/test_learnware_client/test_reuse.py

@@ -7,7 +7,6 @@ from learnware.learnware.reuse import AveragingReuser
 from learnware.test.module import get_semantic_specification
 
 if __name__ == "__main__":
-
     semantic_specification = get_semantic_specification()
     zip_paths = [
         "/home/bixd/workspace/learnware/Learnware/tests/test_learnware_client/rf_tic.zip",

tests/test_workflow/test_workflow.py

@@ -70,7 +70,7 @@ class TestAllWorkflow(unittest.TestCase):
 
             env_file = os.path.join(dir_path, "environment.yaml")
             copyfile(os.path.join(curr_root, "learnware_example/environment.yaml"), env_file)
-            
+
             zip_file = dir_path + ".zip"
             # zip -q -r -j zip_file dir_path
             with zipfile.ZipFile(zip_file, "w") as zip_obj: