Fix ShadowModel MI Attack

Author: Jeratt

gnn_aid/attacks/mi_attacks.py

@@ -232,15 +232,12 @@ def _train_attack_classifier(
             shadow_test_mask: torch.Tensor
     ):
         """Train attack classifier using shadow model outputs."""
-        # Features for shadow train nodes → label 1 (member)
         X_train = self._extract_features(shadow_model, shadow_dataset, shadow_train_mask)
         y_train = np.ones(X_train.shape[0])
 
-        # Features for shadow test nodes → label 0 (non-member)
         X_test = self._extract_features(shadow_model, shadow_dataset, shadow_test_mask)
         y_test = np.zeros(X_test.shape[0])
 
-        # Combine
         X = np.vstack([X_train, X_test])
         y = np.concatenate([y_train, y_test])
 
@@ -252,11 +249,6 @@ def _train_attack_classifier(
 
         self.classifier.fit(X, y)
 
-        # Debug: evaluate on shadow data
-        y_pred = self.classifier.predict(X)
-        acc = accuracy_score(y, y_pred)
-        print(f"  ✓ Shadow attack classifier accuracy: {acc:.4f}")
-
     def attack(
             self,
             model: torch.nn.Module,