feat: continuous concurrent gate orchestrator (algo #6)
- validate_skills_concurrent: 多题型全部臂共享题槽并发编排,发射序 = 题型 round-robin × 阶梯序(base 先 cand 后),终态统一组装 outcome, verdict None(全 INFRA)保留 RuntimeError 语义 - gate_evidence 列 block_idx → ladder_rank(阶梯序号,0-based);旧块路径 _build_evidence_rows 仅键名同步(值仍为块号)保持落库兼容 - 新增 3 项编排测试:乱序到达前缀有序性/双题型隔离/全 INFRA raise Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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@@ -103,7 +103,7 @@ _GATE_EVIDENCE_COLS: dict[str, str] = {
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# question_id 列承载 unit_id（single=question_id，pair=pair_id）；
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# 逐题明细在 predictions 表溯源，按 pair_id join 真实 question 表会 join 不上。
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"question_id": "TEXT",
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"block_idx": "INTEGER",
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"ladder_rank": "INTEGER",
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"baseline_correct": "INTEGER",
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"candidate_correct": "INTEGER",
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"e_value": "REAL",
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@@ -341,8 +341,9 @@ def write_gate_evidence(
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run_id: 训练 run ID。
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epoch: 该 gate 所属的轮次（1-based）。
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step: epoch 内 step 序号（0-based）。
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rows: 每 **单元** 一行，含 question_id/task_type/block_idx/baseline_correct/
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candidate_correct/e_value（该单元所在块判定后的累计 e 值）/
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rows: 每 **单元** 一行，含 question_id/task_type/ladder_rank（阶梯序号，
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0-based）/baseline_correct/
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candidate_correct/e_value（该单元判定后的累计 e 值）/
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stop_reason（仅最后一单元携带最终 stop_reason，其余空串）。
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question_id 字段承载 **unit_id**（single=question_id，pair=pair_id）——
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逐题明细在 predictions 表溯源，按 pair_id join 真实 question 表会 join 不上。
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+151
-1
@@ -435,7 +435,9 @@ def _build_evidence_rows(
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{
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"question_id": u.unit_id,
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"task_type": task_type,
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"block_idx": block_idx,
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# 落库列已更名 ladder_rank(阶梯序号);旧块路径此处值仍为块号,
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# 仅键名对齐 gate_evidence 表结构以保持落库兼容。
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"ladder_rank": block_idx,
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"baseline_correct": b_units[u.unit_id],
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"candidate_correct": c_units[u.unit_id],
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"e_value": None,
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@@ -1172,3 +1174,151 @@ def _register_arm_arrival(
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)
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else:
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slot.cand_per_q = per_q
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def _validate_gate_specs(specs: list[GateSpec]) -> None:
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"""校验各题型 gate 规格,不合法直接报错(不兜底)。
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参数:
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specs: 各题型 gate 规格。
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异常:
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ValueError: 阶梯为空,或 gate_run_prefix 缺 "_gate_"(防泄露过滤依赖
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该标记识别 gate run)。
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"""
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for spec in specs:
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if "_gate_" not in spec.gate_run_prefix:
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raise ValueError(f"gate_run_prefix 必须含 '_gate_': {spec.gate_run_prefix!r}")
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if not spec.units:
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raise ValueError(f"task_type={spec.task_type} 阶梯为空,无法验证")
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def _cleanup_candidate_dirs(cand_dirs: dict[str, Path]) -> None:
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"""尽力清理全部候选临时目录,单个失败只记 warning 不中断其余清理。
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参数:
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cand_dirs: task_type -> 候选临时目录路径。
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返回:
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无。
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"""
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for d in cand_dirs.values():
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try:
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shutil.rmtree(d)
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except OSError as e:
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logger.warning("候选临时目录清理失败 {}: {}", d, e)
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def _build_launch_order(runs: list[_GateRun]) -> list[tuple[_GateRun, int, str]]:
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"""构建 (run, rank, arm) 发射队列:题型 round-robin × 题型内阶梯序。
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交错顺序 = rank 0 各题型 → rank 1 各题型 → ...;同一 (题型, rank) 内
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base 先 cand 后。round-robin 让各题型的阶梯头部同批起跑,配合前缀消费
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使统计推进不因某题型阶梯过长而饿死其他题型。
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参数:
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runs: 各题型 gate 运行时状态(slots 已按阶梯序初始化)。
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返回:
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(run, rank, arm) 三元组列表,即任务创建顺序。
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"""
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order: list[tuple[_GateRun, int, str]] = []
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max_rank = max((len(r.slots) for r in runs), default=0)
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for rank in range(max_rank):
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for r in runs:
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if rank < len(r.slots):
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for arm in ("base", "cand"):
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order.append((r, rank, arm))
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return order
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async def validate_skills_concurrent(
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workspace_dir: Path,
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base_skills_version: str,
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specs: list[GateSpec],
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gate_params: GateParams,
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gate_guard_err: float,
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baseline_cache: BaselineCache,
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prompts_version: str,
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run_inference: RunInferenceFn,
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log: HarnessLog,
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concurrency: int,
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) -> dict[str, ValidationOutcome]:
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"""连续并发 gate:多题型全部臂共享题槽并发,统计按阶梯序前缀有序推进。
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发射顺序 = 题型 round-robin × 题型内阶梯序(base 先 cand 后);题型过线即
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冻结,其排队任务启动时自查冻结标志撤销,in-flight 结果不计入(τ 之后样本,
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合法丢弃)。全部题型判定后统一组装 ValidationOutcome。
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参数:
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workspace_dir: workspace 根目录(候选物化用)。
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base_skills_version: 基线 skills 版本名。
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specs: 各题型 gate 规格(units 已阶梯序 + 截断 n_max)。
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gate_params: e-process 判据阈值组。
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gate_guard_err: INFRA 错误率护栏阈值。
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baseline_cache: 基线侧单元级对错缓存。
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prompts_version: 当前 prompts 版本(缓存键成分)。
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run_inference: 注入推理函数(调用方须绑定共享 HarnessLog)。
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log: HarnessLog 共享实例(推理后读预测,与 run_inference 同库)。
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concurrency: 题槽宽度(峰值在飞题数上限)。
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返回:
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{task_type: ValidationOutcome}。
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异常:
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RuntimeError: INFRA 护栏超阈值,或某题型全部单元被 INFRA 排除。
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ValueError: spec 校验失败(空阶梯 / run_prefix 缺 "_gate_")。
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"""
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_validate_gate_specs(specs)
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base_skills_dir = workspace_dir / "skills" / base_skills_version
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runs = [_GateRun.from_spec(s) for s in specs]
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cand_dirs = {
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r.spec.task_type: materialize_candidate_skill(
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workspace_dir, base_skills_version, r.spec.target_file, r.spec.candidate_content
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)
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for r in runs
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}
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slots_gate = _QuestionSlots(concurrency)
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try:
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coros = [
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_run_unit_arm(
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r,
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rank,
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arm,
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slots_gate,
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run_inference,
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log,
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baseline_cache,
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prompts_version,
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base_skills_dir,
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cand_dirs[r.spec.task_type],
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gate_params,
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gate_guard_err,
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)
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for r, rank, arm in _build_launch_order(runs)
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]
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# gather 任一任务 raise(INFRA 护栏)即向上传播中止整轮,与现行"护栏
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# 中止训练"语义一致;finally 仍清理候选目录。
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await asyncio.gather(*coros)
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finally:
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_cleanup_candidate_dirs(cand_dirs)
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outcomes: dict[str, ValidationOutcome] = {}
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for r in runs:
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if r.verdict is None:
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raise RuntimeError(
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f"gate[{r.spec.task_type}] 全部 unit 被判为 INFRA 排除,无法验证(检查推理基础设施)"
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)
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outcomes[r.spec.task_type] = _finalize_outcome(
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verdict=r.verdict,
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w=r.w,
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l=r.l,
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n_used=r.n_used,
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n_plan=len(r.slots),
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base_obs=r.base_obs,
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cand_obs=r.cand_obs,
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candidate_per_q=r.candidate_per_q,
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evidence_rows=r.evidence_rows,
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task_type=r.spec.task_type,
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)
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return outcomes
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