fix(ceus): 降低长视频内存峰值，快照开跑即写，build 核对 CEUS 运行与交付包

- 内存：prepare_segmentation 改为流式解码，只留分屏和配准的抽样帧，绿框逐帧在两半上找；
  分割那一半由 SegmentationInput.target_frames() 到用时再解码，segment_video 边读边写 jpg；
  MedSAM2 init_state 的读帧换成直接在存放设备上建张量（不改 MedSAM2 源码，结果逐位相同）；
  传播结果写进预分配数组。帧数最多的一段视频常驻内存峰值 11.2 GiB → 2.3 GiB，分辨率最大的
  一段原代码被 OOM 杀掉、现为 4.2 GiB；两段的掩码和全部产物与改前逐字节相同，33 段视频的
  第 1–2 步结果与改前一致，29 例配准与 review.csv 一致。
- 快照：ceus_quant 开跑时写 snapshot/（git、ceus.yaml、review.csv、uv.lock、segment.json），
  配置和核对表从快照副本读；收尾由新函数 runs.finish_snapshot 只新建 finished.json。
  build 与 ceus_align_review 同样改用 finish_snapshot 记结束时间。
- build：summary.json 加 video_sha256；装 CEUS 结果时核对快照里的 delivery_dir、逐例核对
  视频 SHA-256 和推注时间，不同就整次停下；新字段做类型检查，不进 tic.json。

来源：主会话任务（问题 1–3 及补充的 delivery_dir 比对）。

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

tests/test_ceus_quant.py

@@ -13,7 +13,7 @@ import csv
 import hashlib
 import importlib.util
 import json
-from collections.abc import Callable, Mapping, Sequence
+from collections.abc import Callable, Iterable, Mapping
 from datetime import datetime
 from pathlib import Path
 from types import ModuleType
@@ -88,11 +88,12 @@ class _CountingSegment:
 
     def __call__(
         self,
-        frames: Sequence[npt.NDArray[np.uint8]],
+        frames: Iterable[npt.NDArray[np.uint8]],
         prompt_masks: Mapping[int, npt.NDArray[np.bool_]],
         cfg: object,
     ) -> npt.NDArray[np.bool_]:
         self.calls += 1
+        frames = list(frames)
         height, width = frames[0].shape[:2]
         masks = np.zeros((len(frames), height, width), dtype=bool)
         x1, y1, x2, y2 = LESION
@@ -170,7 +171,11 @@ def test_run_writes_outputs_and_failed_case(
     assert (snapshot / "align_review.csv").read_bytes() == (tmp_path / "review.csv").read_bytes()
     segment_record = json.loads((snapshot / "segment.json").read_text(encoding="utf-8"))
     assert segment_record["medsam2_commit"] == "c" * 40
-    assert segment_record["cuda_peak_memory_bytes"] is None  # device 是 cpu
+    assert segment_record["checkpoint_sha256"] == hashlib.sha256(b"fake weights").hexdigest()
+    finished = json.loads((snapshot / "finished.json").read_text(encoding="utf-8"))
+    assert finished["cuda_peak_memory_bytes"] is None  # device 是 cpu
+    assert finished["segment_cache_hits"] == 0
+    assert "finished_at" in finished
     assert (snapshot / "snapshot.json").is_file()
 
     out = capsys.readouterr().out
@@ -178,6 +183,37 @@ def test_run_writes_outputs_and_failed_case(
     assert "U001" not in out and "U002" not in out
 
 
+def test_snapshot_written_before_cases_run(
+    tmp_path: Path,
+    monkeypatch: pytest.MonkeyPatch,
+    setup: tuple[ModuleType, _CountingSegment, dict[str, Any], Callable[[str], None]],
+) -> None:
+    """跑病例时快照已在 .partial 里；运行中途改了 ceus.yaml 和 review.csv，快照仍是开跑时那份。"""
+    module, segment, document, next_run_id = setup
+    config = _write_config(tmp_path, document, "ceus.yaml")
+    review = Path(document["paths"]["align_review"])
+    original_config, original_review = config.read_bytes(), review.read_bytes()
+    snapshot = tmp_path / "runs" / "run-a.partial" / "snapshot"
+    seen: list[bool] = []
+
+    def editing_segment(*args: Any) -> npt.NDArray[np.bool_]:
+        seen.append(all((snapshot / name).is_file() for name in ("snapshot.json", "segment.json")))
+        config.write_text("# 运行中途改了\n", encoding="utf-8")
+        review.write_text("改了\n", encoding="utf-8")
+        return segment(*args)
+
+    monkeypatch.setattr(module, "segment_video", editing_segment)
+    next_run_id("run-a")
+    module.main(["--config", str(config)])
+
+    assert seen == [True]
+    done = tmp_path / "runs" / "run-a" / "snapshot"
+    assert (done / "ceus.yaml").read_bytes() == original_config
+    assert (done / "align_review.csv").read_bytes() == original_review
+    snapshot_json = json.loads((done / "snapshot.json").read_text(encoding="utf-8"))
+    assert "finished_at" not in snapshot_json and "started_at" in snapshot_json
+
+
 def test_build_reads_real_run_layout(
     tmp_path: Path,
     setup: tuple[ModuleType, _CountingSegment, dict[str, Any], Callable[[str], None]],