feat/auc-recovery-plan #1
+14
-4
@@ -105,17 +105,27 @@ def _load_filtered(history_dir, test_csv, test_users):
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def _get_data(cur, ref, rebuild=False):
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"""取过滤后的 (item_dict, user_seq),优先读磁盘缓存。"""
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cache = cur / "bench_filtered_cache.pt"
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"""取过滤后的 (item_dict, user_seq),优先读磁盘缓存。
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用 pickle 而非 torch.save/load:AI Studio overlay 文件系统对 torch 的
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zip/mmap 读取会间歇性报 [Errno 38] Function not implemented。
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"""
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import pickle
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cache = cur / "bench_filtered_cache.pkl"
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test_csv = ref / "test.csv"
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history = ref / "history"
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if cache.exists() and not rebuild:
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print(f"[BENCH] 读取过滤缓存:{cache}")
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d = torch.load(cache, weights_only=False)
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try:
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with open(cache, "rb") as f:
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d = pickle.load(f)
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return d["item_dict"], d["user_seq"]
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except Exception as e:
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print(f"[BENCH][WARN] 缓存读取失败({e}),重新构建")
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test_users = _test_user_ids(test_csv)
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item_dict, user_seq = _load_filtered(history, test_csv, test_users)
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torch.save({"item_dict": item_dict, "user_seq": user_seq}, cache)
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with open(cache, "wb") as f:
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pickle.dump({"item_dict": item_dict, "user_seq": user_seq}, f, protocol=4)
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print(f"[BENCH] 已缓存 -> {cache}")
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return item_dict, user_seq
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