WpyQwq
643e22ecb9
- 引入 MemoryRouterXL 与 v5/v6 流式多线程训练/编码管线 - 修复 prepare_memory_router_dataset 候选池重建缺陷（mega 家族 3568x 加速，输出逐字节相同） - 修复 v5 被破坏的拒答与多跳标签（train 未知样本 319 -> 16319，multi_hop 平均正例 1.00 -> 2.00） - 同存储预算下 V2-128 v6 逐轴 22/22 通过：Top-1 41.12% -> 94.62%，未知拒答 0.00% -> 100.00% - 记录三条被实测推翻的显然优化（logits_to_keep=1 反而慢 55%、XL 容量未带来收益） - 记忆手术跨架构可移植性 14/14，读写关闭时与原生模型逐位相同
35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
"""Check how LoCoMo's adversarial questions carry evidence, before trusting the mapping."""
|
|
import json
|
|
import sys
|
|
from collections import Counter
|
|
from pathlib import Path
|
|
|
|
path = Path(sys.argv[1] if len(sys.argv) > 1 else r"H:\Memory\V2_dpskw\data\net_locomo\locomo10.json")
|
|
data = json.loads(path.read_text(encoding="utf-8"))
|
|
|
|
with_evidence = Counter()
|
|
without_evidence = Counter()
|
|
keys_seen = Counter()
|
|
examples = []
|
|
for item in data:
|
|
for qa in item["qa"]:
|
|
cat = qa.get("category")
|
|
keys_seen.update(qa.keys())
|
|
ev = qa.get("evidence") or []
|
|
if ev:
|
|
with_evidence[cat] += 1
|
|
else:
|
|
without_evidence[cat] += 1
|
|
if cat == 5 and len(examples) < 4:
|
|
examples.append(qa)
|
|
|
|
print("qa field names:", dict(keys_seen))
|
|
print()
|
|
print(f"{'category':>9}{'with evidence':>15}{'without':>10}")
|
|
for cat in sorted(set(with_evidence) | set(without_evidence)):
|
|
print(f"{cat:>9}{with_evidence[cat]:>15}{without_evidence[cat]:>10}")
|
|
print()
|
|
print("=== adversarial examples ===")
|
|
for qa in examples:
|
|
print(json.dumps(qa, ensure_ascii=False, indent=1)[:600])
|