feat(cv): 断点续跑 - 主循环跳过已完成的 outer fold

启动时若 fold_dir 已有 test_metrics/best_params/epoch_mean,直接读回结果跳过训练。
仅对主循环生效(precomputed_best_params is None),不影响 repeat 阶段。
应对服务器偶发崩溃,崩溃重启后重跑同一 output-dir 可接续未完成的 fold。

lnp_ml/modeling/nested_cv_optuna.py

@@ -632,6 +632,21 @@ def _run_single_outer_fold(
     fold_dir.mkdir(parents=True, exist_ok=True)
 
     full_dataset = LNPDataset(df)
+    # === 断点续跑:已完成的 fold 直接跳过(读回磁盘结果)===
+    _tm = fold_dir / "test_metrics.json"
+    _bp = fold_dir / "best_params.json"
+    _em = fold_dir / "epoch_mean.json"
+    if precomputed_best_params is None and _tm.exists() and _bp.exists() and _em.exists():
+        logger.success(f"[SKIP] Outer fold {outer_fold} already done, loading cached results.")
+        with open(_tm) as _f: _tmd = json.load(_f)
+        with open(_bp) as _f: _bpd = json.load(_f)
+        with open(_em) as _f: _emd = json.load(_f)
+        return {
+            "fold": outer_fold,
+            "best_params": _bpd,
+            "epoch_mean": int(_emd.get("epoch_mean", _emd) if isinstance(_emd, dict) else _emd),
+            "test_metrics": _tmd,
+        }
 
     logger.info(f"\n{'='*60}")
     logger.info(f"OUTER FOLD {outer_fold}")