[FIX] Fix databse zippath bug

examples/example_market_db/example_db.py

@@ -40,7 +40,10 @@ 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"},
@@ -95,7 +98,7 @@ def test_market():
         semantic_spec["Name"]["Values"] = "learnware_%d" % (idx)
         semantic_spec["Description"]["Values"] = "test_learnware_number_%d" % (idx)
         easy_market.add_learnware(zip_path, semantic_spec)
-    return
+
     print("Total Item:", len(easy_market))
     curr_inds = easy_market._get_ids()
     print("Available ids:", curr_inds)
@@ -165,8 +168,8 @@ def test_stat_search():
 
 
 if __name__ == "__main__":
-    learnware_num = 5
+    learnware_num = 10
     prepare_learnware(learnware_num)
     test_market()
-    # test_stat_search()
+    test_stat_search()
     test_search_semantics()

examples/workflow_by_code/main.py

@@ -1,5 +1,15 @@
-import os
 import fire
+import os
+import joblib
+import numpy as np
+import learnware
+
+from sklearn import svm
+from learnware.market import EasyMarket, BaseUserInfo
+from learnware.market import database_ops
+from learnware.learnware import Learnware
+import learnware.specification as specification
+from learnware.utils import get_module_by_module_path
 
 
 class LearnwareMarketWorkflow:
@@ -53,6 +63,18 @@ class LearnwareMarketWorkflow:
         "Name": {"Values": "", "Type": "Name"},
     }
 
+    def _init_learnware_market(self):
+        """initialize learnware market"""
+        database_ops.clear_learnware_table()
+        learnware.init()
+
+        self.learnware_market = EasyMarket()
+
+    def _generate_learnware_randomly(self):
+        pass
+
+    # def _
+
 
 if __name__ == "__main__":
     fire.Fire(LearnwareMarketWorkflow)

learnware/config.py

@@ -66,7 +66,10 @@ 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",
@@ -79,7 +82,10 @@ 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",
@@ -99,8 +105,14 @@ 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

@@ -29,7 +29,10 @@ 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 +119,13 @@ 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_zip_dir,
+                folder_path=target_folder_dir,
             )
             return id, True
-    
+
     def _convert_dist_to_score(self, dist_list: List[float]) -> List[float]:
         """Convert mmd dist list into min_max score list
 

learnware/specification/rkme.py

@@ -255,7 +255,9 @@ 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:
@@ -343,7 +345,7 @@ 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)