[MNT] Fix typo finetune

examples/example_market_db/example_init.py

@@ -15,5 +15,5 @@ class SVM(BaseModel):
     def predict(self, X: np.ndarray) -> np.ndarray:
         return self.model.predict(X)
 
-    def fintune(self, X: np.ndarray, y: np.ndarray):
+    def finetune(self, X: np.ndarray, y: np.ndarray):
         pass

examples/workflow_by_code/example_init.py

@@ -15,5 +15,5 @@ class SVM(BaseModel):
     def predict(self, X: np.ndarray) -> np.ndarray:
         return self.model.predict(X)
 
-    def fintune(self, X: np.ndarray, y: np.ndarray):
+    def finetune(self, X: np.ndarray, y: np.ndarray):
         pass

examples/workflow_by_code/main.py

@@ -135,8 +135,6 @@ class LearnwareMarketWorkflow:
         os.makedirs(unzip_dir, exist_ok=True)
         os.system(f"unzip -o -q {zip_path} -d {unzip_dir}")
 
-        user_spec = specification.rkme.RKMEStatSpecification()
-        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)
 
@@ -151,6 +149,7 @@ class LearnwareMarketWorkflow:
         self._init_learnware_market()
         self.prepare_learnware_randomly(learnware_num)
 
+        print(self.zip_path_list)
         easy_market = EasyMarket()
         print("Total Item:", len(easy_market))
 

learnware/model/base.py

@@ -1,4 +1,5 @@
 import numpy as np
+from abc import abstractmethod
 
 
 class BaseModel:
@@ -11,5 +12,5 @@ class BaseModel:
     def predict(self, X: np.ndarray) -> np.ndarray:
         pass
 
-    def fintune(self, X: np.ndarray, y: np.ndarray):
+    def finetune(self, X: np.ndarray, y: np.ndarray):
         pass