Natural Memory NM2.1: 记忆路由器分叉、数据集缺陷修复与全轴评测证据

- 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

natural_memory_app.py

@@ -0,0 +1,54 @@
+"""Unified entry point for Natural Memory v2 local production workflows.
+
+Examples:
+  python -m V2_dpskw.natural_memory_app chat --model-path ...
+  python -m V2_dpskw.natural_memory_app serve --port 8765
+  python -m V2_dpskw.natural_memory_app build-dataset
+  python -m V2_dpskw.natural_memory_app train-policy --steps 240
+  python -m V2_dpskw.natural_memory_app stress --rounds 40
+  python -m V2_dpskw.natural_memory_app make-mega-validation
+  python -m V2_dpskw.natural_memory_app benchmark-kv --limit 32
+"""
+
+from __future__ import annotations
+
+import argparse
+import sys
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument(
+        "command",
+        choices=(
+            "chat",
+            "serve",
+            "build-dataset",
+            "train-policy",
+            "stress",
+            "make-mega-validation",
+            "benchmark-kv",
+        ),
+        help="workflow to run; remaining arguments are passed to that workflow",
+    )
+    args, remaining = parser.parse_known_args()
+    sys.argv = [sys.argv[0], *remaining]
+    if args.command == "chat":
+        from .stream_chat_qwen_memory import main as run
+    elif args.command == "serve":
+        from .natural_memory_service import main as run
+    elif args.command == "build-dataset":
+        from .build_production_memory_dataset import main as run
+    elif args.command == "train-policy":
+        from .train_production_memory_policy import main as run
+    elif args.command == "stress":
+        from .stress_test_natural_memory import main as run
+    elif args.command == "make-mega-validation":
+        from .make_mega_memory_validation import main as run
+    else:
+        from .benchmark_memory_vs_full_kv import main as run
+    run()
+
+
+if __name__ == "__main__":
+    main()