代码/code/bench.py

@@ -105,17 +105,27 @@ def _load_filtered(history_dir, test_csv, test_users):
 
 
 def _get_data(cur, ref, rebuild=False):
-    """取过滤后的 (item_dict, user_seq)，优先读磁盘缓存。"""
+    """取过滤后的 (item_dict, user_seq)，优先读磁盘缓存。
-    cache = cur / "bench_filtered_cache.pt"
+
+    用 pickle 而非 torch.save/load：AI Studio overlay 文件系统对 torch 的
+    zip/mmap 读取会间歇性报 [Errno 38] Function not implemented。
+    """
+    import pickle
+    cache = cur / "bench_filtered_cache.pkl"
     test_csv = ref / "test.csv"
     history = ref / "history"
     if cache.exists() and not rebuild:
         print(f"[BENCH] 读取过滤缓存：{cache}")
-        d = torch.load(cache, weights_only=False)
+        try:
-        return d["item_dict"], d["user_seq"]
+            with open(cache, "rb") as f:
+                d = pickle.load(f)
+            return d["item_dict"], d["user_seq"]
+        except Exception as e:
+            print(f"[BENCH][WARN] 缓存读取失败（{e}），重新构建")
     test_users = _test_user_ids(test_csv)
     item_dict, user_seq = _load_filtered(history, test_csv, test_users)
-    torch.save({"item_dict": item_dict, "user_seq": user_seq}, cache)
+    with open(cache, "wb") as f:
+        pickle.dump({"item_dict": item_dict, "user_seq": user_seq}, f, protocol=4)
     print(f"[BENCH] 已缓存 -> {cache}")
     return item_dict, user_seq