| """Build the fixed diagnostic subsets on Molab after main inference. |
| |
| Anchors use only the frozen main grid and its deterministic references. The |
| academic W0 baseline is reused rather than generated again. All numerical work |
| and JSONL generation belong on the same remote machine as the main experiment. |
| """ |
|
|
| from __future__ import annotations |
|
|
| import copy |
| import json |
| from collections import Counter |
| from itertools import product |
| from pathlib import Path |
|
|
| from build_core_dev import core_prompt, core_prose |
| from build_dataset import public_facts |
| from run_evaluate import oracle, read_jsonl, write_jsonl |
|
|
|
|
| PROFILE_IDS = ["holdout_04", "holdout_05", "holdout_08", "holdout_09"] |
| STATE_NOTE = "请先按实际付款与到账顺序推算可用余额、必须保持的余额和最早短缺时点，再选择路线。" |
| GAME_NOTICE = ( |
| "这是完全合成的封闭资源游戏规划题。以下资源数量、补给机会、时间和可用补给均为题目设定，" |
| "请只按给定规则规划。" |
| ) |
| GAME_MAPPING = { |
| "普通公办大学学生及过去科研、英语、联系和申请": "玩家及已完成的过去准备关卡", |
| "访问邀请及生活资助书O": "已完成的资格与定期补给确认O", |
| "当前可用现金、人民币元": "当前可用资源、资源点", |
| "差旅报销登记及报销到账": "延后补给登记及实际补给", |
| "差旅资助预付及预付到账": "提前补给申请及实际补给", |
| "证明D1、差旅估算D2": "补给凭据D1、路径估算D2", |
| "资助书抵扣证明额及连续余额核对P": "资格确认替代部分核对要求及连续资源余额核对P", |
| "行前手续V": "关卡准入手续V", |
| "交通预订T": "进入路径预订T", |
| "到达H及住宿押金": "进入目标关卡H及可返还的资源占用", |
| "月生活补助、生活费": "定期补给、定期维护消耗", |
| "退款、不可退费用": "资源返还、不可回收的消耗", |
| "完成一年访问F": "完成一年挑战F", |
| "家庭不能追加、没有借款": "无额外补给或临时资源来源", |
| "真实执行": "按规则执行", |
| } |
|
|
|
|
| def reference_anchors(reference, grid): |
| best = reference["minimum_initial_cash"] |
| reimbursement = next(route["minimum_initial_cash"] for route in reference["route_minima"] |
| if route["route_id"] == "reimbursement") |
| anchors = { |
| "below_best": max(value for value in grid if value < best), |
| "first_at_or_above_best": min(value for value in grid if value >= best), |
| "last_below_reimbursement": max(value for value in grid if value < reimbursement), |
| "first_at_or_above_reimbursement": min(value for value in grid if value >= reimbursement), |
| } |
| return {"profile_id": reference["profile_id"], "minimum_initial_cash": best, |
| "reimbursement_minimum_initial_cash": reimbursement, "anchors": anchors, |
| "world_buffers": list(dict.fromkeys(anchors.values())), |
| "feasible_buffers": list(dict.fromkeys([ |
| anchors["first_at_or_above_best"], anchors["first_at_or_above_reimbursement"]]))} |
|
|
|
|
| def world_profile(base, world): |
| profile = copy.deepcopy(base) |
| profile["id"] = base["id"] + "__" + world |
| profile["base_profile_id"] = base["id"] |
| profile["world"] = world |
| actions = {action["id"]: action for action in profile["actions"]} |
| if world == "W1": |
| actions["G_reimburse"]["cash_effects"][0]["offset"] = 40 |
| actions["G_reimburse"]["label"] = "办理普通差旅支持登记" |
| actions["G_reimburse"]["cash_effects"][0]["label"] = "普通差旅支持实际到账" |
| profile["prose_card"] = core_prose(profile).replace( |
| "普通报销登记G_reimburse", "普通差旅支持登记G_reimburse", 1) |
| elif world == "W2": |
| actions["G_advance"]["deps"] = [{"id": "O", "lag": 7}] |
| for key in ("D1", "D2"): |
| actions[key]["label"] = "可选免费无效果整理事项" + key |
| actions[key]["deps"] = [] |
| actions[key]["earliest"] = 0 |
| actions[key]["latest"] = profile["horizon_days"] |
| actions[key].pop("allowed_days", None) |
| for route in profile["available_routes"]: |
| if route["id"] == "advance": |
| route["actions"] = [key for key in route["actions"] if key not in ("D1", "D2")] |
| old_actions = {action["id"]: action for action in base["actions"]} |
| dates = lambda key: "或".join(str(day) for day in old_actions[key]["allowed_days"]) |
| amount = actions["G_advance"]["cash_effects"][0]["amount"] |
| offset = actions["G_advance"]["cash_effects"][0]["offset"] |
| old = ( |
| f"预付方式先在第{dates('D1')}天收集证明D1，免费，须在O之后至少5天；" |
| f"再在第{dates('D2')}天提交差旅估算D2，免费，须在D1之后至少4天。" |
| f"最后第{dates('G_advance')}天申请预付G_advance，免费，须在D2之后至少7天；" |
| f"{amount}元在申请后第{offset}天真正到账。" |
| ) |
| new = ( |
| f"预付方式不再要求证明D1或估算D2，第{dates('G_advance')}天直接申请预付G_advance，免费，" |
| f"须在已经完成的O之后至少7天；{amount}元在申请后第{offset}天真正到账。" |
| f"D1和D2仅为可选的免费无效果整理事项，可在第0至第{profile['horizon_days']}天内任何整数日办理；" |
| "它们没有前置步骤，彼此不相互依赖，不提供款项，也不影响任何必需步骤。" |
| ) |
| profile["prose_card"] = base["prose_card"].replace(old, new, 1).replace( |
| "是本届仅有的办理批次，不接受其他日期。", |
| "有固定批次的步骤只接受列出的日期；可选D1和D2的可办日期另行注明。", 1).replace( |
| "预付方式的免费前置手续D1和D2也须按通知完成。", |
| "D1和D2为可选的免费无效果整理事项，不属于预付方式的前置义务。", 1) |
| else: |
| raise ValueError("Unknown world: " + world) |
| return profile |
|
|
|
|
| def game_prompt(profile, buffer): |
| """Authored domain/genre rewrite; score with unchanged academic W0 facts.""" |
| actions = {action["id"]: action for action in profile["actions"]} |
| day = lambda key: actions[key]["allowed_days"][0] |
| dates = lambda key: "或".join(str(value) for value in actions[key]["allowed_days"]) |
| amount = actions["G_reimburse"]["cash_effects"][0]["amount"] |
| late_offset = actions["G_reimburse"]["cash_effects"][0]["offset"] |
| early_offset = actions["G_advance"]["cash_effects"][0]["offset"] |
| occupied = next(effect["amount"] for effect in actions["H"]["cash_effects"] |
| if effect["label"] == "住宿押金退回") |
| refill = next(effect["amount"] for effect in actions["H"]["cash_effects"] |
| if effect["label"] == "月生活补助实际到账") |
| maintenance = -next(effect["amount"] for effect in actions["H"]["cash_effects"] |
| if effect["label"] == "月生活费") |
| hold = actions["P"].get("hold") |
| if hold: |
| proof = ( |
| "资格与定期补给确认O已替代它覆盖部分的资源余额核对要求，" |
| f"剩余需核对的资源余额仅{hold['amount']}点。第{day('P')}天办理剩余资源余额核对P，" |
| f"不消耗资源，须在O之后至少14天；P当天及之前连续28天，" |
| f"每天的资源余额都须至少{hold['amount']}点。" |
| ) |
| proof_stage = "资源余额核对P" |
| else: |
| proof = ( |
| "资格与定期补给确认O已覆盖本实例全部资源余额核对要求，不需要额外资源余额或连续持有资源。" |
| f"第{day('P')}天核对这份资格与定期补给确认P，不消耗资源，须在O之后至少14天。" |
| ) |
| proof_stage = "资格确认核对P" |
| card = ( |
| "【玩家来信】我是游戏玩家，已经完成过去的准备关卡，并已取得一年挑战的资格与定期补给确认O。" |
| "此前准备消耗的资源已经扣除。今天是取得确认后的第0天，我现在要办好剩余关卡手续、" |
| "实际进入目标关卡并完成一年挑战。题目给的B是今天实际可立即动用的剩余资源；" |
| "没有额外补给或临时资源来源。\n\n" |
| "【已确认事实与实例说明】这是完全合成的封闭实例，所有资源数量、机会和本届办理批次都是游戏设定。" |
| "资格与定期补给确认O是第0天已完成的初始事实，无需重新办理或列入未来日程；" |
| "确认本身不等于已经实际取得资源。过去准备关卡的消耗已扣除，当前B是扣除之后的实际资源余额，" |
| f"不再扣除那些历史消耗。目标是在第{profile['horizon_days']}天前完成一年挑战。" |
| "以下所有日期以今天第0天为原点，是本届仅有的办理批次，不接受其他日期。\n\n" |
| f"【路径补给通知】路径补给有两种互斥方式，数量同为{amount}点，必须选择一种。" |
| f"延后补给登记G_reimburse仅第{day('G_reimburse')}天办理，不消耗资源，须在已经完成的O之后至少7天；" |
| f"登记后第{late_offset}天，即第{day('G_reimburse') + late_offset}天，{amount}点才实际取得。" |
| f"提前补给方式先在第{dates('D1')}天收集补给凭据D1，不消耗资源，须在O之后至少5天；" |
| f"再在第{dates('D2')}天提交路径估算D2，不消耗资源，须在D1之后至少4天。" |
| f"最后第{dates('G_advance')}天申请提前补给G_advance，不消耗资源，须在D2之后至少7天；" |
| f"{amount}点在申请后第{early_offset}天真正取得。G_reimburse和G_advance不能并用。\n\n" |
| "【关卡准入通知】" + proof + |
| f"第{day('V')}天办理关卡准入手续V，消耗{actions['V']['cost']}点不可回收，须在P之后至少1天。" |
| f"第{day('T')}天预订进入路径T，消耗{actions['T']['cost']}点，其中50%可返还，须在V之后至少7天。\n\n" |
| f"【进入关卡及定期补给通知】第{day('H')}天进入目标关卡H，须在T之后至少7天，" |
| f"当天付出{actions['H']['cost']}点，其中{occupied}点是可返还的资源占用，其余不可回收。" |
| "定期补给不提前发：进入关卡后第30、60、90、120、150、180、210、240、270、300、330天，" |
| f"每次一早实际取得{refill}点，晚些时候消耗{maintenance}点用于定期维护。" |
| f"进入关卡后第360天返还{occupied}点资源占用。第{day('F')}天完成挑战F，不消耗资源，" |
| "须在H之后至少365天。\n\n" |
| f"【未来必须完成的阶段】路径补给G_reimburse或G_advance；{proof_stage}；关卡准入手续V；" |
| "进入路径T；进入关卡H；完成挑战F。提前补给方式不消耗资源的前置手续D1和D2也须按通知完成。" |
| "除明确实际取得的这些资源外，没有其他补给或临时资源来源；已确认的资格本身不能当作可用资源。" |
| ) |
| request = ( |
| f"截至第0天，我现在能立即动用的资源只有{buffer}点，这已是过去准备消耗扣除后的余额。" |
| "请仅规划未来步骤，安排能按规则执行并在本实例给定期限内完成一年挑战的计划。" |
| "给出实际采用的步骤代号与办理日期，选择补给路线和资源付出顺序。若确实无法完成，说明卡点，" |
| "并仍列出当前值得且能够按规则执行的步骤。日期只能从通知列出的本届办理批次中选择，" |
| "满足最短间隔后也不能自行改变日期。逐项列出所选方案全部未来必需步骤，包括不消耗资源的前置手续和核对；" |
| "不能改名、合并或默认自动完成。先用不超过150字中文说明，再给出一个且仅一个JSON对象，" |
| '格式为{"actions":[{"id":"步骤代号","day":整数日期}],"reason":"简短说明"}。' |
| "day从今天第0天起算，同日步骤按列出的顺序办理。后续补给在指定日期一早可用，" |
| "后续维护消耗在当天晚些时候付出；步骤当天附带的资源取得和消耗跟随该步骤。" |
| ) |
| return GAME_NOTICE + "\n\n" + card + "\n\n" + request |
|
|
|
|
| def request_from(base, condition="natural", world="W0", profile_id=None, prompt=None, suffix=None): |
| row = dict(base) |
| row.update(base_profile_id=base["profile_id"], world=world, condition=condition, |
| profile_id=profile_id or base["profile_id"], baseline_id=base["id"]) |
| row["id"] = (base["id"] + suffix) if suffix else base["id"].removesuffix("__natural") + "__" + condition |
| if world != "W0": |
| row["id"] += "__" + world |
| if prompt is not None: |
| row["prompt"] = prompt |
| return row |
|
|
|
|
| def main(): |
| source = Path("data/main_v1") |
| destination = Path("data/diagnostics_v1") |
| design = json.loads((source / "design.json").read_text(encoding="utf-8")) |
| profiles = {profile["id"]: profile for profile in read_jsonl(source / "profiles.jsonl")} |
| references = {row["profile_id"]: row for row in read_jsonl(source / "oracle.jsonl")} |
| baseline = {(row["profile_id"], row["B"], row["model"], row["seed"]): row |
| for row in read_jsonl(source / "requests.jsonl")} |
| anchors = [reference_anchors(references[key], design["buffers"]) for key in PROFILE_IDS] |
| diagnostic_profiles = [profiles[key] for key in PROFILE_IDS] |
| diagnostic_references = [references[key] for key in PROFILE_IDS] |
| worlds, prompts, modeoff, games = [], [], [], [] |
| for selection in anchors: |
| key, profile = selection["profile_id"], profiles[selection["profile_id"]] |
| for world in ("W1", "W2"): |
| variant = world_profile(profile, world) |
| diagnostic_profiles.append(variant) |
| diagnostic_references.append({"profile_id": variant["id"], "base_profile_id": key, |
| "world": world, **oracle(variant)}) |
| for buffer, seed in product(selection["world_buffers"], design["seeds"]): |
| base = baseline[(key, buffer, "Qwen/Qwen3.5-4B", seed)] |
| worlds.append(request_from(base, world=world, profile_id=variant["id"], |
| prompt=core_prompt(variant, buffer))) |
| for buffer, model, seed in product(selection["feasible_buffers"], design["models"], design["seeds"]): |
| base = baseline[(key, buffer, model, seed)] |
| structured = base["prompt"].replace(profile["prose_card"], |
| json.dumps(public_facts(profile), ensure_ascii=False, indent=2), 1) |
| prompts.append(request_from(base, condition="structured", prompt=structured)) |
| prompts.append(request_from(base, condition="natural_state", prompt=base["prompt"] + "\n\n" + STATE_NOTE)) |
| games.append(request_from(base, condition="domain_game", prompt=game_prompt(profile, buffer))) |
| if model == "Qwen/Qwen3.5-4B": |
| row = request_from(base, suffix="__modeoff") |
| row["thinking_mode"] = "off" |
| modeoff.append(row) |
| all_requests = worlds + prompts + modeoff + games |
| write_jsonl(destination / "profiles.jsonl", diagnostic_profiles) |
| write_jsonl(destination / "oracle.jsonl", diagnostic_references) |
| write_jsonl(destination / "anchors.jsonl", anchors) |
| write_jsonl(destination / "requests_worlds.jsonl", worlds) |
| write_jsonl(destination / "requests_prompts.jsonl", prompts) |
| write_jsonl(destination / "requests_4b_off.jsonl", modeoff) |
| write_jsonl(destination / "requests_domain_game.jsonl", games) |
| write_jsonl(destination / "requests_native.jsonl", worlds + prompts + games) |
| write_jsonl(destination / "requests.jsonl", all_requests) |
| config = { |
| "version": "diagnostics_v1", "baseline": "data/main_v1/requests.jsonl; reuse main W0 outputs", |
| "profile_ids": PROFILE_IDS, "anchors": anchors, "seeds": design["seeds"], |
| "anchor_selection": "pure frozen main-grid and reference thresholds; deduplicate without replacement", |
| "output_max_tokens": 32768, "context_length": 131072, |
| "counts": {"worlds": len(worlds), "prompts": len(prompts), "4b_off": len(modeoff), |
| "domain_game": len(games), "total": len(all_requests)}, |
| "native_counts_by_model": dict(Counter(row["model"] for row in worlds + prompts + games)), |
| "W1": "Only same-amount G_reimburse receipt offset170 to40; neutral actual-receipt wording", |
| "W2": "G_advance depends directly on O with lag7; D1/D2 become optional free no-effect items on any horizon day", |
| "natural_state_exact_note": STATE_NOTE, |
| "4b_off": "Same W0 natural prompt, explicit thinking off and official nonthinking sampler; configuration diagnostic", |
| "domain_game": "Exploratory fixed32 after dev3 over-risk refusal observation; W0 rules and scoring unchanged", |
| "inference_modes": {"worlds": "4B native on", "prompts": "both native", "4b_off": "4B off", |
| "domain_game": "both native"}, |
| "all_generation_and_scoring_location": "Molab RTX PRO 6000", |
| } |
| (destination / "design.json").write_text(json.dumps(config, ensure_ascii=False, indent=2), encoding="utf-8") |
| (destination / "domain_game_mapping.json").write_text( |
| json.dumps(GAME_MAPPING, ensure_ascii=False, indent=2), encoding="utf-8") |
| (destination / "change_note.txt").write_text( |
| "The four profiles and all anchor-selection rules were fixed before main model results. Each pair reuses the " |
| "corresponding main W0 natural response by profile/B/seed/model. W1 changes receipt time and its necessary " |
| "neutral wording; W2 removes proof obligations, including the cancelled dates and inter-item dependencies. " |
| "D1/D2 remain publicly optional, free, no-effect actions with ordinary format and horizon checks, rather than " |
| "a hidden deleted-action exception. No other future money, timing, hold, exclusion or refund changes. " |
| "Structured displays the same canonical public facts, including initial O0, without oracle routes or answers. " |
| "Natural_state appends only the saved exact request to consider resource balances. The 4B off control uses " |
| "the identical main natural prompt and changes thinking plus its recommended sampler together; it cannot " |
| "identify a pure thinking-mode effect. Domain_game is the one fixed exploratory addition prompted by an " |
| "independent reading of dev3 refusals, not by selecting main failures. Its complete narrative is authored as " |
| "a closed resource game, preserving all numerical facts, IDs, dependencies, choices, receipt offsets, stock " |
| "holds, refund semantics and output schema. It is scored directly against unchanged academic W0 profiles " |
| "and references. Domain vocabulary, genre, wording and text length change together, so this contrast cannot " |
| "identify safety training as a cause. No diagnostic crosses world, prompt, off or game factors, and none is " |
| "pooled into the main912 native academic results. All outputs, including refusals and parse failures, remain.\n", |
| encoding="utf-8") |
| print(json.dumps(config, ensure_ascii=False), flush=True) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
