[MNT] resolve comments in abl_model.py

abl/learning/abl_model.py

@@ -45,14 +45,8 @@ class ABLModel:
     """
 
     def __init__(self, base_model: Any) -> None:
-        if not (
-            hasattr(base_model, "fit")
-            and hasattr(base_model, "predict")
-            and hasattr(base_model, "score")
-        ):
-            raise NotImplementedError(
-                "base_model should have fit, predict and score methods."
-            )
+        if not (hasattr(base_model, "fit") and hasattr(base_model, "predict")):
+            raise NotImplementedError("The base_model should implement fit and predict methods.")
 
         self.base_model = base_model
 
@@ -84,27 +78,6 @@ class ABLModel:
 
         return {"label": label, "prob": prob}
 
-    def valid(self, data_samples: ListData) -> float:
-        """
-        Calculate the accuracy for the given data.
-
-        Parameters
-        ----------
-        X : List[List[Any]]
-            The data to calculate the accuracy on.
-        Y : List[Any]
-            The true labels for the given data.
-
-        Returns
-        -------
-        float
-            The accuracy score for the given data.
-        """
-        data_X = data_samples.flatten("X")
-        data_y = data_samples.flatten("gt_idx")
-        score = self.base_model.score(X=data_X, y=data_y)
-        return score
-
     def train(self, data_samples: ListData) -> float:
         """
         Train the model on the given data.
@@ -131,19 +104,20 @@ class ABLModel:
             method = getattr(model, operation)
             method(*args, **kwargs)
         else:
-            try:
-                if not f"{operation}_path" in kwargs.keys():
-                    raise ValueError(f"'{operation}_path' should not be None")
-                if operation == "save":
-                    with open(kwargs["save_path"], "wb") as file:
-                        pickle.dump(model, file, protocol=pickle.HIGHEST_PROTOCOL)
-                elif operation == "load":
-                    with open(kwargs["load_path"], "rb") as file:
-                        self.base_model = pickle.load(file)
-            except:
-                raise NotImplementedError(
-                    f"{type(model).__name__} object doesn't have the {operation} method"
-                )
+            if not f"{operation}_path" in kwargs.keys():
+                raise ValueError(f"'{operation}_path' should not be None")
+            else:
+                try:
+                    if operation == "save":
+                        with open(kwargs["save_path"], "wb") as file:
+                            pickle.dump(model, file, protocol=pickle.HIGHEST_PROTOCOL)
+                    elif operation == "load":
+                        with open(kwargs["load_path"], "rb") as file:
+                            self.base_model = pickle.load(file)
+                except:
+                    raise NotImplementedError(
+                        f"{type(model).__name__} object doesn't have the {operation} method and the default pickle-based {operation} method failed."
+                    )
 
     def save(self, *args, **kwargs) -> None:
         """