Upload utils.py

utils.py

@@ -57,4 +57,4 @@ def predict(model, device, data, num_users, num_items, user_id, train_edge_label
             recommended_item = meta_dataframe[meta_dataframe['asin'] == asin_of_item]['title'].values
             recommended_items.append(recommended_item)
 
-        return ground_truth_items.to_list(), recommended_items
+        return ground_truth_items.values.tolist(), recommended_items