[MNT] Change the logic of search by semantic

examples/example_market_db/example_db.py

@@ -44,7 +44,7 @@ user_senmantic = {
     "Device": {"Values": ["GPU"], "Type": "Tag"},
     "Scenario": {"Values": ["Business"], "Type": "Tag"},
     "Description": {"Values": "", "Type": "Description"},
-    "Name": {"Values": "", "Type": "Name"},
+    "Name": {"Values": "learnware_4", "Type": "Name"},
 }
 
 
@@ -126,7 +126,7 @@ def test_search_semantics():
     user_spec.load(os.path.join(unzip_dir, "svm.json"))
     user_info = BaseUserInfo(id="user_0", semantic_spec=user_senmantic)
     _, single_learnware_list, _ = easy_market.search_learnware(user_info)
-    
+
     print("User info:", user_info.get_semantic_spec())
     print(f"search result of user{idx}:")
     for learnware in single_learnware_list:

learnware/config.py

@@ -57,10 +57,7 @@ os.makedirs(LEARNWARE_ZIP_POOL_PATH, exist_ok=True)
 os.makedirs(LEARNWARE_FOLDER_POOL_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",
@@ -73,10 +70,7 @@ 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",
@@ -96,14 +90,8 @@ 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 = {

learnware/learnware/__init__.py

@@ -28,10 +28,7 @@ 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

@@ -117,10 +117,7 @@ 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_folder_dir,
-                folder_path=target_folder_dir,
+                id, semantic_spec=semantic_spec, zip_path=target_folder_dir, folder_path=target_folder_dir,
             )
             return id, True
 
@@ -319,9 +316,9 @@ class EasyMarket(BaseMarket):
         self, learnware_list: List[Learnware], user_info: BaseUserInfo
     ) -> List[Learnware]:
         user_semantic_spec = user_info.get_semantic_spec()
-        user_input_description = user_semantic_spec["Description"]["Values"]
+        user_input_description = user_semantic_spec["Name"]["Values"]
         if not user_input_description:
-            return []
+            return learnware_list
         match_learnwares = []
         for learnware in learnware_list:
             learnware_semantic_spec = learnware.get_specification().get_semantic_spec()
@@ -338,10 +335,21 @@ class EasyMarket(BaseMarket):
                 return False
             for key in semantic_spec1.keys():
                 if semantic_spec1[key]["Type"] == "Class":
-                    if semantic_spec1[key]["Values"] != semantic_spec2[key]["Values"]:
+                    if (
+                        len(semantic_spec2[key]["Values"]) > 0
+                        and semantic_spec1[key]["Values"] != semantic_spec2[key]["Values"]
+                    ):
                         return False
                 elif semantic_spec1[key]["Type"] == "Tag":
-                    if not (set(semantic_spec1[key]["Values"]) & set(semantic_spec2[key]["Values"])):
+                    if len(semantic_spec2[key]["Values"]) > 0 and not (
+                        set(semantic_spec1[key]["Values"]) & set(semantic_spec2[key]["Values"])
+                    ):
+                        return False
+                elif semantic_spec1[key]["Type"] == "Name":
+                    if (
+                        len(semantic_spec2[key]["Values"]) > 0
+                        and semantic_spec2[key]["Values"] not in semantic_spec1[key]["Values"]
+                    ):
                         return False
             return True
 
@@ -373,9 +381,8 @@ class EasyMarket(BaseMarket):
             the third is the list of Learnware (mixture), the size is search_num
         """
         learnware_list = [self.learnware_list[key] for key in self.learnware_list]
-        learnware_list_tags = self._search_by_semantic_tags(learnware_list, user_info)
-        learnware_list_description = self._search_by_semantic_description(learnware_list, user_info)
-        learnware_list = list(set(learnware_list_tags + learnware_list_description))
+        learnware_list = self._search_by_semantic_tags(learnware_list, user_info)
+        # learnware_list = list(set(learnware_list_tags + learnware_list_description))
 
         if "RKMEStatSpecification" not in user_info.stat_info:
             return None, learnware_list, None

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)