[MNT] black -l

examples/example_market_db/example_db.py

@@ -40,10 +40,7 @@ semantic_specs = [
 
 user_senmantic = {
     "Data": {"Values": ["Tabular"], "Type": "Class"},
-    "Task": {
-        "Values": ["Classification"],
-        "Type": "Class",
-    },
+    "Task": {"Values": ["Classification"], "Type": "Class",},
     "Device": {"Values": ["GPU"], "Type": "Tag"},
     "Scenario": {"Values": ["Business"], "Type": "Tag"},
     "Description": {"Values": "", "Type": "Description"},

examples/workflow_by_code/main.py

@@ -16,10 +16,7 @@ curr_root = os.path.dirname(os.path.abspath(__file__))
 semantic_specs = [
     {
         "Data": {"Values": ["Tabular"], "Type": "Class"},
-        "Task": {
-            "Values": ["Classification"],
-            "Type": "Class",
-        },
+        "Task": {"Values": ["Classification"], "Type": "Class",},
         "Device": {"Values": ["GPU"], "Type": "Tag"},
         "Scenario": {"Values": ["Nature"], "Type": "Tag"},
         "Description": {"Values": "", "Type": "Description"},
@@ -27,10 +24,7 @@ semantic_specs = [
     },
     {
         "Data": {"Values": ["Tabular"], "Type": "Class"},
-        "Task": {
-            "Values": ["Classification"],
-            "Type": "Class",
-        },
+        "Task": {"Values": ["Classification"], "Type": "Class",},
         "Device": {"Values": ["GPU"], "Type": "Tag"},
         "Scenario": {"Values": ["Business", "Nature"], "Type": "Tag"},
         "Description": {"Values": "", "Type": "Description"},
@@ -38,10 +32,7 @@ semantic_specs = [
     },
     {
         "Data": {"Values": ["Tabular"], "Type": "Class"},
-        "Task": {
-            "Values": ["Classification"],
-            "Type": "Class",
-        },
+        "Task": {"Values": ["Classification"], "Type": "Class",},
         "Device": {"Values": ["GPU"], "Type": "Tag"},
         "Scenario": {"Values": ["Business"], "Type": "Tag"},
         "Description": {"Values": "", "Type": "Description"},
@@ -51,10 +42,7 @@ semantic_specs = [
 
 user_senmantic = {
     "Data": {"Values": ["Tabular"], "Type": "Class"},
-    "Task": {
-        "Values": ["Classification"],
-        "Type": "Class",
-    },
+    "Task": {"Values": ["Classification"], "Type": "Class",},
     "Device": {"Values": ["GPU"], "Type": "Tag"},
     "Scenario": {"Values": ["Business"], "Type": "Tag"},
     "Description": {"Values": "", "Type": "Description"},

learnware/config.py

@@ -66,10 +66,7 @@ os.makedirs(LEARNWARE_FOLDER_POOL_PATH, exist_ok=True)
 os.makedirs(DATABASE_PATH, exist_ok=True)
 
 semantic_config = {
-    "Data": {
-        "Values": ["Tabular", "Image", "Video", "Text", "Audio"],
-        "Type": "Class",
-    },  # Choose only one class
+    "Data": {"Values": ["Tabular", "Image", "Video", "Text", "Audio"], "Type": "Class",},  # Choose only one class
     "Task": {
         "Values": [
             "Classification",
@@ -82,10 +79,7 @@ semantic_config = {
         ],
         "Type": "Class",  # Choose only one class
     },
-    "Device": {
-        "Values": ["CPU", "GPU"],
-        "Type": "Tag",
-    },  # Choose one or more tags
+    "Device": {"Values": ["CPU", "GPU"], "Type": "Tag",},  # Choose one or more tags
     "Scenario": {
         "Values": [
             "Business",
@@ -105,14 +99,8 @@ semantic_config = {
         ],
         "Type": "Tag",  # Choose one or more tags
     },
-    "Description": {
-        "Values": None,
-        "Type": "Description",
-    },
-    "Name": {
-        "Values": None,
-        "Type": "Name",
-    },
+    "Description": {"Values": None, "Type": "Description",},
+    "Name": {"Values": None, "Type": "Name",},
 }
 
 _DEFAULT_CONFIG = {
@@ -123,10 +111,7 @@ _DEFAULT_CONFIG = {
     "learnware_pool_path": LEARNWARE_POOL_PATH,
     "learnware_zip_pool_path": LEARNWARE_ZIP_POOL_PATH,
     "learnware_folder_pool_path": LEARNWARE_FOLDER_POOL_PATH,
-    "learnware_folder_config": {
-        "yaml_file": "learnware.yaml",
-        "module_file": "__init__.py",
-    },
+    "learnware_folder_config": {"yaml_file": "learnware.yaml", "module_file": "__init__.py",},
     "database_path": DATABASE_PATH,
 }
 

learnware/learnware/__init__.py

@@ -29,10 +29,7 @@ def get_learnware_from_dirpath(id: str, semantic_spec: dict, learnware_dirpath:
         The contructed learnware object, return None if build failed
     """
     learnware_config = {
-        "model": {
-            "class_name": "Model",
-            "kwargs": {},
-        },
+        "model": {"class_name": "Model", "kwargs": {},},
         "stat_specifications": [
             {
                 "module_path": "learnware.specification",

learnware/market/easy.py

@@ -119,10 +119,7 @@ class EasyMarket(BaseMarket):
             self.learnware_folder_list[id] = target_folder_dir
             self.count += 1
             add_learnware_to_db(
-                id,
-                semantic_spec=semantic_spec,
-                zip_path=target_zip_dir,
-                folder_path=target_folder_dir,
+                id, semantic_spec=semantic_spec, zip_path=target_zip_dir, folder_path=target_folder_dir,
             )
             return id, True
 

learnware/specification/rkme.py

@@ -255,9 +255,7 @@ class RKMEStatSpecification(BaseStatSpecification):
         rkme_to_save["beta"] = rkme_to_save["beta"].tolist()
         rkme_to_save["device"] = "gpu" if rkme_to_save["cuda_idx"] != -1 else "cpu"
         json.dump(
-            rkme_to_save,
-            codecs.open(save_path, "w", encoding="utf-8"),
-            separators=(",", ":"),
+            rkme_to_save, codecs.open(save_path, "w", encoding="utf-8"), separators=(",", ":"),
         )
 
     def load(self, filepath: str) -> bool:
@@ -345,7 +343,7 @@ def torch_rbf_kernel(x1, x2, gamma) -> torch.Tensor:
     """
     x1 = x1.double()
     x2 = x2.double()
-    X12norm = torch.sum(x1**2, 1, keepdim=True) - 2 * x1 @ x2.T + torch.sum(x2**2, 1, keepdim=True).T
+    X12norm = torch.sum(x1 ** 2, 1, keepdim=True) - 2 * x1 @ x2.T + torch.sum(x2 ** 2, 1, keepdim=True).T
     return torch.exp(-X12norm * gamma)