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"/root/data/hf-releases/drc-data-0664d82e/raw/stage2_town10_v1", + "/root/data/releases/model-d38b274e/stage2_town10_universal_latent32x64_v1/checkpoints", + "/root/data/runs/stage7b_per_vehicle_vs_shared_continuation_l40s_v3a/source_preflight/executions/round_01/audi_etron" + ], + "scoped_open_events": 266, + "unique_scoped_paths": 245 + }, + "status": "endpoint_execution_complete", + "texture": { + "all_finite": true, + "observations": 144, + "sha256": "40de9daaa9a67212972058d3a10326a86d0cd627103897dcecad6db2f2798350" + }, + "treatment": "source", + "validity_gates": { + "clean_prediction_rows_match_frozen_reference": true, + "excluded_runtime_path_open_count_exact_zero": true, + "inherited_v2_nonhistorical_endpoint_gates_pass": true, + "sample_count_order_and_predictions_finite": true, + "source_attacked_recall_matches_historical_within_1e_9": true, + "source_clean_metrics_match_historical_within_1e_9": true, + "source_texture_matches_frozen_reference": true + }, + "vehicle": "audi.etron" +} diff --git a/stage7/stage7b_v3_source_gate_l40s_v3a/formal_output/source_preflight/executions/round_01/audi_etron/process_stderr.txt b/stage7/stage7b_v3_source_gate_l40s_v3a/formal_output/source_preflight/executions/round_01/audi_etron/process_stderr.txt new file mode 100644 index 0000000000000000000000000000000000000000..52105f11c84ed8c4bc5603858ba48de6d08e8351 --- /dev/null +++ b/stage7/stage7b_v3_source_gate_l40s_v3a/formal_output/source_preflight/executions/round_01/audi_etron/process_stderr.txt @@ -0,0 +1,160 @@ +2026-08-04 20:15:09,176 - INFO - enable console log +2026-08-04 20:15:09,176 - INFO - enable file log,the log file is in the log +2026-08-04 20:15:09,467 - INFO - Try to loading data from /root/data/hf-releases/drc-data-0664d82e/raw/stage2_town10_v1. +2026-08-04 20:15:09,524 - INFO - Detector: YoloV5 is selected,trying to load the detector. +2026-08-04 20:15:10,839 - INFO - Try to loading weight named yolov5x6.pt +Fusing layers... +YOLOv5x6 summary: 574 layers, 140730220 parameters, 0 gradients, 209.6 GFLOPs +2026-08-04 20:15:13,053 - INFO - Detector frozen for input-gradient optimization: modules=1, parameters=140730220 +2026-08-04 20:15:14,592 - INFO - Geometry loaded from mask=asset/audi_etron_carla_attack/audi_etron_carla_attack_mask.png, position=True, normal=True +2026-08-04 20:15:14,592 - INFO - Universal camouflage initialized: style=forest, latent=8x32x64, texture=2048x2048, stochastic_train=True, highres_residual=False, spatial_geometry_decoder=True, canonical_surface_decoder=False +2026-08-04 20:15:15,295 - INFO - Loaded evaluation generator checkpoint from /root/data/releases/model-d38b274e/stage2_town10_universal_latent32x64_v1/checkpoints/epoch_0006.pt + +Evaluating train seed=42: 0%| | 0/144 [00:00= 0.005 and at least 3/4 vehicles >= 0.003", + "specialization_gate": "median >= 0.005 and at least 3/4 vehicles >= 0.003", + "oracle_recovery_gate": "Audi/Tesla/Ford only: median recovery >= 0.50 and all three >= 0.25", + "historical_anchor_gate_that_failed": "Both clean and attacked source AP50:95/AP50/recall had to match frozen Stage 7a metrics at absolute tolerance 1e-9 before any treatment training." + }, + "formal_v2a_observation_boundary": { + "git_commit": "369d609", + "status": "source_anchor_indeterminate_no_treatment_training_started", + "completed_source_vehicles": 4, + "optimization_updates": 0, + "all_clean_metric_anchors_exact": true, + "all_source_texture_hashes_exact": true, + "all_recall_anchors_exact": true, + "all_attacked_ap_anchors_within_1e_9": false, + "attacked_ap50_95_absolute_differences": { + "audi.etron": 0.000017106984858905605, + "tesla.model3": 0.000011670512584521786, + "ford.mustang": 0.000003857935103712684, + "jeep.wrangler_rubicon": 0.000021260494761699 + } + }, + "source_only_repeatability_diagnostic": { + "preregistered_before_repeat_outcomes": true, + "additional_repeats": 2, + "runs_per_vehicle_including_formal_v2a": 3, + "optimization_updates": 0, + "all_diagnostic_validity_gates_pass": true, + "all_clean_prediction_rows_exact_across_runs": true, + "all_texture_hashes_exact_across_runs": true, + "all_attacked_prediction_rows_exact_across_runs": false, + "unique_attacked_prediction_hashes_per_vehicle": 3, + "recall_span_per_vehicle": 0.0, + "attacked_ap50_95_span": { + "audi.etron": 0.00004485015502994627, + "tesla.model3": 0.00003673229325190652, + "ford.mustang": 0.000015598613848477605, + "jeep.wrangler_rubicon": 0.000003037786354759958 + }, + "attacked_ap50_span": { + "audi.etron": 0.00008220588312257693, + "tesla.model3": 0.00015103375446323675, + "ford.mustang": 0.00003063472497166764, + "jeep.wrangler_rubicon": 0.00001765210316709287 + }, + "diagnostic_status": "within_environment_rendered_attacked_pipeline_nonrepeatability_observed", + "causal_limit": "The evidence localizes non-bitwise repeatability to the rendered attacked endpoint pipeline relative to exact clean predictions and texture tensors, but does not identify a unique CUDA/rasterizer/conversion/detector kernel.", + "training_authorized": false, + "threshold_or_protocol_change_authorized": false + }, + "public_evidence": { + "repository": "bailuyucha/differentiable-render-camouflage-data", + "revision": "f2ff75d8b9f493eac2122fc486185219da3061a2", + "path": "stage7/stage7b_v2_source_anchor_repeatability_diagnostic_v1", + "url": "https://huggingface.co/datasets/bailuyucha/differentiable-render-camouflage-data/tree/f2ff75d8b9f493eac2122fc486185219da3061a2/stage7/stage7b_v2_source_anchor_repeatability_diagnostic_v1", + "payload_files": 95, + "sha256sums_sha256": "20a8f20eac8d07fb8c03eeb6116e1eb7c6c5e11e1a3da042c5d290e9610c6bb5", + "exact_revision_redownload_verified": true + }, + "candidate_minimal_amendment_for_review_not_yet_authorized": { + "historical_stage7a_role": "Keep historical attacked metrics as a disclosed diagnostic, not a bitwise validity gate. Retain exact source checkpoint, protocol/code/environment/data identities, exact source texture hashes, exact clean prediction rows/metrics, finite predictions, frozen detector, and excluded-path gates.", + "fresh_v3_source_gate": "Before treatment, evaluate each source endpoint exactly three times in the fresh formal runtime. Require clean rows/metrics and texture hashes to be exact across repetitions. Require the within-vehicle attacked AP50:95 max-minus-min spread to be <= 0.0003, defined mechanically as 10% of the already-frozen 0.003 minimum per-vehicle treatment threshold. Treat attacked AP50 and historical differences as diagnostics.", + "formal_comparator": "Use a within-run source estimator rather than the historical Stage 7a scalar. Candidate estimator: median attacked AP50:95 across the three fixed repetitions.", + "final_checkpoint_evaluation": "Evaluate source, specialist, and shared checkpoints with the same fixed count of three endpoint executions per vehicle and use their medians. Pre-freeze a balanced comparator order so evaluation position is not confounded with treatment.", + "independence_language": "Endpoint repetitions quantify numerical execution sensitivity only; they are not latent seeds, training runs, or iid replicates and support no confidence interval.", + "unchanged_scientific_inputs": "All training arms, schedules, losses, thresholds, oracle definitions, and claim boundaries remain unchanged.", + "freshness": "Run from exact source state in a new v3 output; never resume v2a." + }, + "questions": [ + "Is it methodologically legitimate, before any treatment outcome, to replace the impossible historical attacked bitwise gate using only this preregistered source-only numerical-repeatability evidence?", + "Should historical attacked AP become diagnostic-only, or should it retain a non-bitwise bound? If a bound is required, give a mechanically justified formula that is not chosen from treatment outcomes.", + "Is three fixed endpoint executions and a median an adequate minimum for source/specialist/shared, or is another deterministic summary/order required?", + "Is the proposed source spread gate <=0.0003 defensible because it is exactly 10% of the pre-existing 0.003 treatment threshold, or should the fraction differ?", + "What balanced evaluation order should be frozen across source, specialist, and shared to limit temporal/GPU-state position confounding?", + "Must we first attempt deterministic CUDA/cuDNN/nvdiffrast settings, even though that changes the frozen numerical environment and may not make rasterization deterministic? Distinguish required from optional future diagnosis.", + "Which exact gates must still pass before treatment training begins, and which gates should apply only after final checkpoint evaluation?", + "Confirm that a valid v3 result would remain a fixed-cohort training-fit continuation audit and cannot repair v2a, prove gradient conflict, generalization, SOTA, or physical robustness." + ], + "required_response_format": { + "A_verdict": "Choose one: minimal nuisance amendment is defensible; repeatable renderer/inference must be achieved first; Stage 7b should be abandoned. Explain in one paragraph.", + "B_issue_table": "issue | severity | why | pre-treatment mandatory | exact minimal revision", + "C_gate_specification": "Provide exact source pre-treatment gates, endpoint repetition count/order/summary, any numerical bound formula, and indeterminate logic.", + "D_claim_boundary": "State exactly what positive, negative, and validity-failure outcomes may and may not claim.", + "E_go_no_go_checklist": "A mechanical checklist ending in GO, conditional GO, or NO-GO." + } +} diff --git a/stage7/stage7b_v3_source_gate_l40s_v3a/frozen/WEB_PRO_STAGE7B_SOURCE_GATE_REVIEW_20260804.md b/stage7/stage7b_v3_source_gate_l40s_v3a/frozen/WEB_PRO_STAGE7B_SOURCE_GATE_REVIEW_20260804.md new file mode 100644 index 0000000000000000000000000000000000000000..d0eaf96298bd2d0eb17d11b1f902dca8dba94b38 --- /dev/null +++ b/stage7/stage7b_v3_source_gate_l40s_v3a/frozen/WEB_PRO_STAGE7B_SOURCE_GATE_REVIEW_20260804.md @@ -0,0 +1,276 @@ +# Web Pro Stage 7b source-gate review — 2026-08-04 + +Provenance: the user pasted a Web GPT response into the project conversation on +2026-08-04, before any Stage 7b v3 endpoint execution or treatment update. This +file is a structure-preserving transcription of that response: all verdicts, +numeric rules, execution orders, validity logic, and claim boundaries are +retained; repetitive checklist wording is consolidated. It is not represented +as a byte-for-byte export from the Web UI. + +## A. Verdict + +**minimal nuisance amendment is defensible。** v2a 的失败发生在所有 treatment arm 尚未开始、`optimization_updates=0` 的 source-only 阶段；随后预注册的重复性诊断又表明，source texture、clean prediction rows、clean metrics 和 recall 可精确复现，而 attacked prediction rows 与 attacked AP 只能做到小幅但非 bitwise 的重复。这足以在不接触任何 treatment outcome 的前提下，把不可执行的 historical attacked-AP `1e-9` gate 改成一个预先冻结的数值稳定性 gate。该修改不能修复 v2a，必须新建 v3 协议和输出。候选方案还需要两处关键收紧：historical attacked AP50:95 不应完全降为 diagnostic-only，而应保留非 bitwise 的 gross-drift bound；`0.0003` 应作为两端 AP 对比的总 nuisance budget，单个 endpoint 的 spread 上限应为 `0.00015`。 + +## B. Issue table + +| issue | severity | why | pre-treatment mandatory | exact minimal revision | +| --- | --- | --- | --- | --- | +| 继续保留 historical attacked AP 的 `1e-9` gate | **fatal** | source-only 三次执行已经产生三个不同 attacked prediction hashes；继续要求 bitwise AP 等价会使任何诚实执行都无法进入 treatment。 | **是** | 删除 attacked AP50:95/AP50 的 `1e-9` 等价要求；clean 和可重复的 recall gate 不变。 | +| 将 historical attacked AP 完全降为 diagnostic-only | **major** | 当前三次 source 内部一致并不能排除整个 attacked renderer/inference 路径发生了稳定但系统性的偏移。clean 与 texture 精确也不能单独验证 attacked 路径。 | **是** | historical attacked AP50:95 保留宽松 compatibility gate：当前 source median 与历史值绝对差不得超过 `0.0003`。 | +| 对每个 endpoint 使用 spread `<=0.0003` | **major** | primary 和 specialization contrast 都是两个独立执行 endpoint 之差；若两端各允许 `0.0003`，最坏 observed range envelope 可达 `0.0006`，即 frozen `0.003` 门槛的 20%。 | **是** | 每个 endpoint 的 AP50:95 spread 改为 `<=0.00015`；两端合计最多 `0.00030`，即门槛的 10%。 | +| pre-treatment source 和正式 source comparator 角色未完全区分 | **major** | 只使用训练前 source median，无法控制训练完成后的 runtime/GPU-state 漂移；只使用训练后 source，又缺少训练授权前 gate。 | **是** | 训练前做三次 source gate；最终评价阶段再对 source、specialist、shared 各做三次。正式 contrast 使用最终评价阶段的 contemporaneous source median。 | +| source/specialist/shared 的执行顺序未精确冻结 | **major** | 顺序固定但不平衡会把 checkpoint 身份与第一个、第二个或第三个执行位置混杂。 | **是** | 按车型冻结三块 cyclic Latin order；每个 checkpoint 在三个位置各出现一次，并在四车型间使用正向/反向循环平衡 directed adjacency。 | +| 三次执行的 summary 与 outlier 处理未机械定义 | **major** | outcome 后改用 mean、删除一次执行或增加第四次，都会形成结果依赖的分析选择。 | **是** | 每个 endpoint 恰好三次；summary 固定为排序后的第二个值；不得删除、替换或追加执行。 | +| 是否必须先修改 CUDA/cuDNN/nvdiffrast deterministic settings | **minor** | 修改这些设置会改变已经冻结的数值环境，并且不保证 rasterization bitwise deterministic；当前 source-only evidence 显示的是小幅、可界定的 nuisance，而不是无法控制的漂移。 | **否** | v3 保持原数值环境和 flags；完整记录环境。deterministic-kernel 调查只能作为未来独立 source-only diagnosis。 | +| 最终 checkpoint 也可能具有 endpoint nonrepeatability | **major** | 只在 source 上做 spread gate，不能保证 specialist/shared 的 AP median 具有同等数值稳定性。 | **否，训练前冻结规则必须完成；实际检查在最终评价后** | 对 source、每个 specialist 和 shared 的每车 AP50:95 三次执行均应用 `<=0.00015` spread gate。 | +| 缺少 pre-vs-post source drift gate | **major** | 即使 pre-source 和 post-source 各自内部稳定，二者仍可能发生时间相关的整体位移。 | **否，规则须训练前冻结** | 每车要求 `abs(post_source_median - pre_source_median) <= 0.0003`。 | +| 附件未给出每车 clean-row reference 的字面 SHA | **major for executable freeze** | packet 只给出了 sealed payload 的顶层校验信息，不能从本附件写出四车 clean prediction-row 的实际 hash。 | **是** | 从已封存且已发布的 source-only diagnostic manifest 复制这些 hash 到 v3；不得在 treatment 后生成或替换 reference。 | +| v2a、diagnostic 与 v3 execution 的边界 | **fatal if mixed** | 使用 v2a 或 diagnostic 的三次 source 结果作为 v3 正式重复，会把旧输出与新 runtime 混合，并构成对 v2a 的事实性修补。 | **是** | v2a 永久 indeterminate；diagnostic 只用于制定规则；v3 的 pre-source 和 final-source 均在全新 v3 output 中重新执行。 | + +附件中的最大 source AP50:95 三次 span 为 Audi 的 `0.000044850155...`，小于建议的 `0.00015`；最大 historical difference 为 Jeep 的 `0.000021260495...`，小于建议的 `0.0003`。因此这些规则并不是为了勉强包住现有诊断值；其上限分别约为当前最大 observed span 的 3.34 倍和最大 historical difference 的 14.1 倍。attacked AP50 的最大 span 为 `0.000151033754...`，因此 AP50 不应被偷偷纳入 `0.00015` primary gate，而应继续作为 diagnostic。 + +## C. Gate specification + +### C1. 数值界限的冻结公式 + +设 frozen minimum per-vehicle treatment threshold 为： + +\[ +T_{\min}=0.003. +\] + +预先分配给 endpoint execution nuisance 的**总对比预算**为该门槛的 10%： + +\[ +B_{\text{contrast}}=0.10T_{\min}=0.0003. +\] + +由于 primary contrast 和 specialization contrast 都是两个独立执行 endpoint 的差： + +\[ +\Delta_v=M_{v,\text{source}}-M_{v,\text{specialist}}, +\] + +\[ +\Gamma_v=M_{v,\text{shared}}-M_{v,\text{specialist}}, +\] + +将总预算平均分配到两个 endpoint： + +\[ +B_{\text{endpoint}}=\frac{B_{\text{contrast}}}{2}=0.00015. +\] + +因此，对任意车型 \(v\)、任意 checkpoint +\(c\in\{\text{source},\text{specialist},\text{shared}\}\)，令三次 attacked +AP50:95 为 \(a_{v,c,1},a_{v,c,2},a_{v,c,3}\)。冻结定义： + +\[ +M_{v,c}=\operatorname{median}(a_{v,c,1},a_{v,c,2},a_{v,c,3}), +\] + +其中 median 必须实现为排序后的第二个数值；以及 + +\[ +W_{v,c}=\max_r a_{v,c,r}-\min_r a_{v,c,r}. +\] + +有效性要求： + +\[ +W_{v,c}\le 0.00015. +\] + +这里的 10% 和 5% 是**本次协议的 nuisance-budget 设计规则，不是文献常数，也不是统计置信界限**。三次执行不用于估计方差或置信区间。 + +### C2. historical attacked AP 的精确角色 + +historical Stage 7a attacked AP50:95 应保留为： + +> **bounded source-pipeline compatibility gate，不是 formal treatment comparator，也不是 bitwise anchor。** + +对每车 historical Stage 7a source attacked AP50:95 \(H_v\)，训练前 source median 必须满足： + +\[ +|M^{pre}_{v,\text{source}}-H_v|\le0.0003. +\] + +最终评价阶段重新执行的 source median 也必须满足： + +\[ +|M^{final}_{v,\text{source}}-H_v|\le0.0003. +\] + +此外要求： + +\[ +|M^{final}_{v,\text{source}}-M^{pre}_{v,\text{source}}|\le0.0003. +\] + +选择 `0.0003` 而不是经验 span 的倍数，是因为它机械地来自 treatment 前已经存在的 `0.003` threshold，不依赖 specialist 或 shared outcome。 + +historical attacked AP50：强制报告并计算 current-vs-historical difference，但**不作为 validity gate**。historical attacked recall 保留 exact/tolerance-`1e-9` gate；要求三次 source recall 相同，并与 frozen historical recall 相符。 + +### C3. 训练前 source gate + +v3 在任何 optimizer update 前必须完成四车各三次、共 **12 次** source endpoint execution。v2a 和 diagnostic 的旧执行不得计入这 12 次。 + +固定 source-preflight execution order： + +```text +round 1: Audi → Tesla → Ford → Jeep +round 2: Audi → Tesla → Ford → Jeep +round 3: Audi → Tesla → Ford → Jeep +``` + +每次 execution 必须：从 exact frozen source checkpoint 重新加载；使用固定 vehicle manifest、144 个 sample IDs 和固定顺序；使用 latent seed 42；不加载 optimizer、不产生任何 optimization update；使用相同 detector、renderer、scene stats、threshold 和 numerical environment；在独立进程或等价的完整无状态重新加载中执行。 + +每车必须全部满足：source checkpoint identity；code/data/environment identity；excluded runtime paths 为零；source texture 三次及 reference SHA exact；clean rows 三次及 reference SHA exact；clean AP50、AP50:95、recall 在 `1e-9` 内匹配；attacked sample identity/finite；attacked recall exact；attacked AP50:95 spread `<=0.00015`；source median 与 historical AP50:95 差 `<=0.0003`。attacked AP50 只报告，attacked prediction-row hash 可以不同。 + +12 次完成后，必须在 treatment 前写出并冻结 `source_preflight.json`、`source_preflight.sha256`、每车三份 raw endpoint artifacts、它们的 SHA-256 manifest、pre-source medians/spreads、historical compatibility decisions 和 `optimization_updates=0` assertion。只有四车全部通过才允许训练。 + +任一 gate 失败时： + +```text +status = stage7b_v3_source_gate_indeterminate_no_treatment_training_authorized +training_authorized = false +optimization_updates must remain 0 +``` + +不得通过增加第四次 execution、删除一个值、改用 mean、按车型豁免或扩大 tolerance 来修复。 + +### C4. 最终 endpoint 执行次数、顺序和 summary + +训练完成且训练/checkpoint gates 通过后，每车评价 source 三次、该车 specialist 三次、shared 三次，共 `4 × 3 × 3 = 36` 个 endpoint executions。每个 execution 都重新加载对应 checkpoint，并使用相同 manifest、sample order、seed 42、renderer、detector 和 scene stats。 + +Audi 和 Ford 使用 forward cyclic order： + +```text +block 1: source → specialist → shared +block 2: specialist → shared → source +block 3: shared → source → specialist +``` + +Tesla 和 Jeep 使用 reverse cyclic order： + +```text +block 1: source → shared → specialist +block 2: shared → specialist → source +block 3: specialist → source → shared +``` + +正式 estimator： + +\[ +S_v=M^{final}_{v,\text{source}},\qquad +P_v=M^{final}_{v,\text{specialist}},\qquad +C_v=M^{final}_{v,\text{shared}}. +\] + +\[ +\Delta_v=S_v-P_v,\qquad \Gamma_v=C_v-P_v. +\] + +pre-treatment source median 只用于 treatment authorization、historical compatibility 和 pre-vs-final runtime drift gate，不进入正式 treatment numerator。Stage 7a direct-output oracle、Audi/Tesla/Ford recovery denominator、capacity threshold、specialization threshold 和 oracle-recovery threshold 全部保持原样。 + +### C5. 最终评价后的 validity gates + +对 source、specialist、shared 的每个 vehicle-checkpoint endpoint 要求 `W_{v,c} <= 0.00015`。还必须满足：final source 与 historical source AP50:95 差不超过 `0.0003`；final source 与 pre-treatment source median 差不超过 `0.0003`；每个 checkpoint 的 seed-42 generated texture hash 在三次评价间 exact；source texture 还匹配 frozen source；clean rows 在全部 comparator executions 间 exact 并匹配 reference；sample identity exact；predictions/metric inputs finite；三次都保留且不新增 treatment AP50/recall threshold。 + +训练 validity gates 继续使用 frozen v2 design，包括四个 specialist 各 432 updates、shared 1,728 total/每车 432、paired tapes、inherited model/Adam/RNG、optimizer/generation steps、detector freeze、checkpoint round-trip、finite state、no selection、no excluded access。 + +### C6. 完整 indeterminate logic + +以下任一情况发生，v3 整体 scientific result 均为 indeterminate：pre-source 任一失败；source freeze 前开始 treatment；任一预定 endpoint 缺失；任一 endpoint spread 超限；final source historical/pre drift 超限；clean rows、texture、sample、finite 或 excluded gate 失败；任一 training/checkpoint/compute gate 失败；顺序错误；使用额外/删除 execution、替换 summary 或 outcome 后放宽 tolerance；复用 v2a/diagnostic artifact。 + +```text +status = stage7b_v3_indeterminate +capacity_decision = unavailable +specialization_decision = unavailable +oracle_recovery_decision = unavailable +``` + +### C7. 可直接写入协议的核心字段 + +```json +{ + "source_gate_amendment": { + "amendment_type": "pre_treatment_numerical_nuisance_only", + "formal_v2a_status": "permanently_indeterminate_not_repaired_or_reused", + "fresh_v3_output_required": true, + "historical_attacked_bitwise_gate_removed": true, + "frozen_minimum_per_vehicle_treatment_threshold": 0.003, + "total_contrast_numerical_nuisance_fraction": 0.1, + "total_contrast_numerical_nuisance_budget": 0.0003, + "endpoint_attacked_ap50_95_spread_limit": 0.00015, + "endpoint_spread_limit_formula": "0.5 * 0.10 * 0.003", + "historical_source_attacked_ap50_95_compatibility_limit": 0.0003, + "pre_to_final_source_median_drift_limit": 0.0003, + "attacked_ap50_role": "diagnostic_only", + "attacked_prediction_row_hash_equality_required": false, + "source_attacked_recall_historical_tolerance": 1e-9, + "clean_metric_historical_tolerance": 1e-9, + "endpoint_repetitions_are_iid": false, + "confidence_intervals_from_endpoint_repetitions_permitted": false + }, + "pre_treatment_source_gate": { + "executions_per_vehicle": 3, + "vehicles_required": 4, + "total_executions": 12, + "summary": "median_second_order_statistic", + "spread": "maximum_minus_minimum", + "formal_comparator_role": "authorization_and_runtime_drift_reference_only", + "old_v2a_or_diagnostic_executions_may_be_reused": false, + "source_checkpoint_reloaded_for_every_execution": true, + "independent_process_or_complete_stateless_reload_required": true, + "additional_or_replacement_endpoint_execution_permitted": false + }, + "final_endpoint_evaluation": { + "checkpoints": ["source", "specialist", "shared"], + "executions_per_checkpoint_per_vehicle": 3, + "vehicles": 4, + "total_endpoint_executions": 36, + "summary": "median_second_order_statistic", + "formal_source_comparator": "final_phase_median_of_three_source_executions", + "primary_contrast": "final_source_median_minus_specialist_median", + "specialization_contrast": "shared_median_minus_specialist_median", + "endpoint_attacked_ap50_95_spread_limit": 0.00015, + "source_historical_compatibility_limit": 0.0003, + "source_pre_to_final_median_drift_limit": 0.0003, + "additional_or_replacement_endpoint_execution_permitted": false + }, + "historical_attacked_metric_roles": { + "ap50_95": "bounded_source_pipeline_compatibility_gate_not_formal_comparator", + "ap50": "diagnostic_only", + "recall": "exact_source_identity_gate" + }, + "source_gate_indeterminate_rule": { + "pre_treatment_failure_status": "stage7b_v3_source_gate_indeterminate_no_treatment_training_authorized", + "post_treatment_failure_status": "stage7b_v3_indeterminate", + "partial_vehicle_decision_permitted": false, + "partial_checkpoint_decision_permitted": false, + "outlier_removal_permitted": false, + "fallback_to_mean_permitted": false, + "adaptive_extra_repetitions_permitted": false, + "outcome_conditioned_tolerance_change_permitted": false + } +} +``` + +附件没有列出四车 clean-row reference 的实际 SHA-256，因此 placeholder 不能留在 executable protocol 中；必须从 sealed diagnostic manifest 复制真实值后再冻结，不能从 treatment 后的第一次 clean run 反向定义 reference。 + +## D. Claim boundary + +Positive outcome 只允许声称当前 frozen environment 下 endpoint 满足协议数值稳定性、exact inherited-state continuation 在四辆固定训练车上的 same-vehicle training-fit 结果，以及在相应 gate 通过时 specialist 相对 frozen balanced shared control 的策略优势和 Audi/Tesla/Ford 的 oracle-gap recovery。不能声称 bitwise historical identity、唯一 gradient-conflict cause、universal/unseen generalization、SOTA/fair baseline、physical robustness，三次 endpoint 也不是独立实验重复。 + +Negative outcome 只允许绑定 exact checkpoint、inherited Adam/RNG、固定 LR/loss/budget/four-vehicle cohort 和 bounded endpoint numerical sensitivity；不能外推到 representation impossibility、fresh Adam、其他 LR/预算/初始化或物理泛化。 + +Validity failure 时只能报告失败 gate 和 raw diagnostics，capacity、specialization、oracle recovery 均 unavailable；不能使用部分车型、增加 repetitions、删除 execution 或放宽 threshold 追认结果。无论 v3 成败，v2a 均永久 `indeterminate`。 + +## E. GO/NO-GO checklist and final decision + +执行前必须隔离 v2a/diagnostic/v3；冻结新的 audit/protocol/runner/test SHA；保持原 scientific inputs、thresholds、optimizer、tapes、四车 specialist 和 shared exposure；写入真实 clean-row/source-texture SHA；保持 CUDA/cuDNN/nvdiffrast flags；执行全新 12 个 source endpoints 并封存；全部通过后才训练；最终严格执行 36 个 balanced endpoints 和所有 spread/drift/identity gates；任何失败机械设为 indeterminate，禁止额外 execution 或替换 summary。 + +**最终判定：CONDITIONAL GO。** + +只有在新的 v3 中完成上述 source gate replacement、写入真实 reference hashes、冻结三次执行与 balanced order，并且四车 pre-treatment source gate 全部通过后，才授权开始 Stage 7b treatment training。在此之前为 **NO-GO**；无需先改变 deterministic CUDA/cuDNN/nvdiffrast settings，也不应放弃 Stage 7b。 diff --git a/stage7/stage7b_v3_source_gate_l40s_v3a/frozen/run_stage7b_per_vehicle_vs_shared_continuation_v3.py b/stage7/stage7b_v3_source_gate_l40s_v3a/frozen/run_stage7b_per_vehicle_vs_shared_continuation_v3.py new file mode 100644 index 0000000000000000000000000000000000000000..e87ac5fb1eb10384bba4cad62f826d14b9723f69 --- /dev/null +++ b/stage7/stage7b_v3_source_gate_l40s_v3a/frozen/run_stage7b_per_vehicle_vs_shared_continuation_v3.py @@ -0,0 +1,1201 @@ +#!/usr/bin/env python3 +"""Run the Stage 7b v3 numerical-nuisance amendment. + +V3 leaves every Stage 7b v2 treatment input frozen. It replaces only the +unexecutable bitwise attacked-source anchor with preregistered repeated +endpoint gates. The source gate and treatment are deliberately separate CLI +phases: a successful source gate writes a sealed authorization artifact and +returns without performing an optimizer update. +""" + +from __future__ import annotations + +import argparse +import copy +from datetime import datetime, timezone +from decimal import Decimal +import json +import math +from pathlib import Path +import subprocess +import sys +import traceback +from typing import Any, Iterable, Mapping + + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from tools import run_stage7b_per_vehicle_vs_shared_continuation as stage7b_v2 + + +AUDIT_ID = "stage7b_per_vehicle_vs_shared_continuation_control_v3" +PROTOCOL_PATH = ( + PROJECT_ROOT + / "experiments/protocols/stage7b_per_vehicle_vs_shared_continuation_control_v3.json" +) +EXECUTION_READY_STATUS = "preregistered_before_v3_outcomes_after_external_review" +SOURCE_GATE_PASS_STATUS = "stage7b_v3_source_gate_passed_treatment_authorized" +SOURCE_GATE_FAIL_STATUS = ( + "stage7b_v3_source_gate_indeterminate_no_treatment_training_authorized" +) +FINAL_INDETERMINATE_STATUS = "stage7b_v3_indeterminate" +FINAL_VALID_STATUS = "stage7b_v3_valid_decisions_recorded" +ENDPOINT_SPREAD_LIMIT = 0.00015 +SOURCE_COMPATIBILITY_LIMIT = 0.0003 +CLEAN_METRIC_TOLERANCE = 1e-9 +SOURCE_RECALL_TOLERANCE = 1e-9 +EXECUTIONS_PER_ENDPOINT = 3 +ALLOWED_VEHICLES = stage7b_v2.ALLOWED_VEHICLES +SOURCE_EXECUTION_ORDER = ALLOWED_VEHICLES +FINAL_ORDER = { + "audi.etron": ( + ("source", "specialist", "shared"), + ("specialist", "shared", "source"), + ("shared", "source", "specialist"), + ), + "tesla.model3": ( + ("source", "shared", "specialist"), + ("shared", "specialist", "source"), + ("specialist", "source", "shared"), + ), + "ford.mustang": ( + ("source", "specialist", "shared"), + ("specialist", "shared", "source"), + ("shared", "source", "specialist"), + ), + "jeep.wrangler_rubicon": ( + ("source", "shared", "specialist"), + ("shared", "specialist", "source"), + ("specialist", "source", "shared"), + ), +} + + +def parse_args(argv=None): + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--phase", + choices=("preflight", "source-gate", "treatment", "_endpoint"), + required=True, + ) + parser.add_argument("--protocol", type=Path, default=PROTOCOL_PATH) + parser.add_argument("--dataset-root", type=Path) + parser.add_argument("--source-checkpoint", type=Path) + parser.add_argument("--output", type=Path, required=True) + parser.add_argument("--device", default="cuda:0") + parser.add_argument("--runtime-config", type=Path) + parser.add_argument("--vehicle", choices=ALLOWED_VEHICLES) + parser.add_argument("--treatment", choices=("source", "specialist", "shared")) + return parser.parse_args(argv) + + +def _utc_now() -> str: + return datetime.now(timezone.utc).isoformat() + + +def _load_json(path: Path) -> dict[str, Any]: + return stage7b_v2._load_json(path) + + +def _write_json(path: Path, payload: Mapping[str, Any]) -> None: + stage7b_v2._write_json(path, payload) + + +def _sha256_file(path: Path) -> str: + return stage7b_v2._sha256_file(path) + + +def _contains_placeholder(value: Any) -> bool: + if isinstance(value, str): + return "REQUIRED_" in value + if isinstance(value, Mapping): + return any(_contains_placeholder(item) for item in value.values()) + if isinstance(value, (list, tuple)): + return any(_contains_placeholder(item) for item in value) + return False + + +def _resolve(path: Path | str, launch_directory: Path) -> Path: + value = Path(path) + return ( + value.resolve() if value.is_absolute() else (launch_directory / value).resolve() + ) + + +def _require_file(specification: Mapping[str, Any], label: str) -> Path: + path = PROJECT_ROOT / str(specification["path"]) + observed = _sha256_file(path) + if observed != specification["sha256"]: + raise ValueError( + f"{label} SHA-256 changed: expected {specification['sha256']}, " + f"observed {observed}" + ) + return path + + +def _base_protocol(protocol: Mapping[str, Any]) -> tuple[Path, dict[str, Any]]: + path = _require_file( + protocol["base_scientific_protocol"], "Stage 7b v2 base protocol" + ) + base = _load_json(path) + stage7b_v2.validate_protocol_static(base) + return path, base + + +def validate_protocol_static(protocol: Mapping[str, Any]) -> None: + if int(protocol.get("schema_version", 0)) != 3: + raise ValueError("Stage 7b v3 protocol schema must equal 3") + if protocol.get("audit_id") != AUDIT_ID: + raise ValueError("Stage 7b v3 audit identity changed") + if protocol.get("status") != EXECUTION_READY_STATUS: + raise ValueError("Stage 7b v3 protocol is not execution-ready") + if _contains_placeholder(protocol): + raise ValueError("Stage 7b v3 contains an unresolved REQUIRED_ placeholder") + + _base_protocol(protocol) + review = protocol["external_review_gate"] + if review.get("status") != "completed_before_v3_outcomes": + raise ValueError("Stage 7b v3 external review timing changed") + for key in ("request_packet", "response", "disposition"): + _require_file(review[key], f"Stage 7b v3 external review {key}") + + amendment = protocol["source_gate_amendment"] + expected = { + "formal_v2a_status": "permanently_indeterminate_not_repaired_or_reused", + "fresh_v3_output_required": True, + "frozen_minimum_per_vehicle_treatment_threshold": 0.003, + "total_contrast_numerical_nuisance_fraction": 0.1, + "total_contrast_numerical_nuisance_budget": SOURCE_COMPATIBILITY_LIMIT, + "endpoint_attacked_ap50_95_spread_limit": ENDPOINT_SPREAD_LIMIT, + "historical_source_attacked_ap50_95_compatibility_limit": SOURCE_COMPATIBILITY_LIMIT, + "pre_to_final_source_median_drift_limit": SOURCE_COMPATIBILITY_LIMIT, + "attacked_ap50_role": "diagnostic_only", + "attacked_prediction_row_hash_equality_required": False, + "source_attacked_recall_historical_tolerance": SOURCE_RECALL_TOLERANCE, + "clean_metric_historical_tolerance": CLEAN_METRIC_TOLERANCE, + "endpoint_repetitions_are_iid": False, + "confidence_intervals_from_endpoint_repetitions_permitted": False, + } + for key, value in expected.items(): + if amendment.get(key) != value: + raise ValueError(f"Stage 7b v3 amendment field changed: {key}") + if amendment.get("endpoint_spread_limit_formula") != "0.5 * 0.10 * 0.003": + raise ValueError("Stage 7b v3 endpoint nuisance formula changed") + + pre = protocol["pre_treatment_source_gate"] + if ( + int(pre.get("executions_per_vehicle", -1)) != 3 + or int(pre.get("vehicles_required", -1)) != 4 + or int(pre.get("total_executions", -1)) != 12 + or tuple(pre.get("execution_order_each_round", ())) != SOURCE_EXECUTION_ORDER + or pre.get("summary") != "median_second_order_statistic" + or pre.get("additional_or_replacement_endpoint_execution_permitted") + is not False + or pre.get("old_v2a_or_diagnostic_executions_may_be_reused") is not False + or pre.get("independent_process_required") is not True + ): + raise ValueError("Stage 7b v3 pre-treatment source design changed") + + final = protocol["final_endpoint_evaluation"] + if ( + tuple(final.get("checkpoints", ())) != ("source", "specialist", "shared") + or int(final.get("executions_per_checkpoint_per_vehicle", -1)) != 3 + or int(final.get("vehicles", -1)) != 4 + or int(final.get("total_endpoint_executions", -1)) != 36 + or final.get("summary") != "median_second_order_statistic" + or float(final.get("endpoint_attacked_ap50_95_spread_limit", -1.0)) + != ENDPOINT_SPREAD_LIMIT + or float(final.get("source_historical_compatibility_limit", -1.0)) + != SOURCE_COMPATIBILITY_LIMIT + or float(final.get("source_pre_to_final_median_drift_limit", -1.0)) + != SOURCE_COMPATIBILITY_LIMIT + or final.get("additional_or_replacement_endpoint_execution_permitted") + is not False + ): + raise ValueError("Stage 7b v3 final endpoint design changed") + observed_order = { + vehicle: tuple(tuple(block) for block in blocks) + for vehicle, blocks in final["evaluation_order_by_vehicle"].items() + } + if observed_order != FINAL_ORDER: + raise ValueError("Stage 7b v3 balanced final endpoint order changed") + + references = protocol["source_gate_reference_artifacts"] + diagnostic_path = _require_file( + references["sealed_diagnostic_decision"], "sealed source-only diagnostic" + ) + diagnostic = _load_json(diagnostic_path) + if diagnostic.get("optimization_updates") != 0: + raise ValueError("Sealed diagnostic contains an optimizer update") + if diagnostic.get("training_authorized") is not False: + raise ValueError("Sealed diagnostic unexpectedly authorized training") + for vehicle in ALLOWED_VEHICLES: + record = diagnostic["repeatability"]["per_vehicle"][vehicle] + if len(set(record["clean_prediction_hashes"])) != 1: + raise ValueError(f"Diagnostic clean rows are not exact for {vehicle}") + if ( + references["clean_prediction_row_sha256_by_vehicle"][vehicle] + != record["clean_prediction_hashes"][0] + ): + raise ValueError(f"Frozen clean-row reference changed for {vehicle}") + if len(set(record["texture_hashes"])) != 1: + raise ValueError(f"Diagnostic source texture is not exact for {vehicle}") + if ( + references["source_texture_sha256_by_vehicle"][vehicle] + != record["texture_hashes"][0] + ): + raise ValueError(f"Frozen source-texture reference changed for {vehicle}") + + implementation = protocol["implementation_freeze"] + for key in ("runner", "tests"): + _require_file(implementation[key], f"Stage 7b v3 {key}") + + +def _second_order_statistic(values: Iterable[float]) -> float: + materialized = [float(value) for value in values] + if len(materialized) != 3 or not all( + math.isfinite(value) for value in materialized + ): + raise ValueError("A Stage 7b v3 endpoint requires exactly three finite values") + return sorted(materialized)[1] + + +def _span(values: Iterable[float]) -> float: + materialized = [float(value) for value in values] + if len(materialized) != 3 or not all( + math.isfinite(value) for value in materialized + ): + raise ValueError("A Stage 7b v3 endpoint spread requires three finite values") + return float(Decimal(str(max(materialized))) - Decimal(str(min(materialized)))) + + +def _at_most(value: float, limit: float) -> bool: + return Decimal(str(value)) <= Decimal(str(limit)) + + +def _absolute_difference(left: float, right: float) -> float: + return float(abs(Decimal(str(left)) - Decimal(str(right)))) + + +def _arm_by_vehicle(base: Mapping[str, Any]) -> dict[str, Mapping[str, Any]]: + return {str(arm["vehicle"]): arm for arm in base["arms"]} + + +def _rewrite_runtime_bundle( + bundle: Mapping[str, Any], protocol_path: Path, output_root: Path +) -> dict[str, Any]: + rewritten = copy.deepcopy(dict(bundle)) + protocol_sha256 = _sha256_file(protocol_path) + for treatment, records in rewritten["vehicle"].items(): + for vehicle, runtime in records.items(): + runtime["evaluation"]["audit_protocol_path"] = str(protocol_path) + runtime["evaluation"]["audit_protocol_sha256"] = protocol_sha256 + runtime["stage7b_audit"].update( + { + "audit_id": AUDIT_ID, + "base_v2_audit_id": stage7b_v2.AUDIT_ID, + "v3_endpoint_repetitions": 3, + "treatment": treatment, + "vehicle": vehicle, + } + ) + rewritten["shared_training"]["evaluation"]["audit_protocol_path"] = str( + protocol_path + ) + rewritten["shared_training"]["evaluation"][ + "audit_protocol_sha256" + ] = protocol_sha256 + rewritten["shared_training"]["stage7b_audit"].update( + {"audit_id": AUDIT_ID, "base_v2_audit_id": stage7b_v2.AUDIT_ID} + ) + return rewritten + + +def _persist_runtime_bundle( + output_root: Path, bundle: Mapping[str, Any] +) -> dict[str, Any]: + root = output_root / "runtime_configs" + records: dict[str, Any] = {"vehicle": {}} + for treatment, vehicle_records in bundle["vehicle"].items(): + records["vehicle"][treatment] = {} + for vehicle, runtime in vehicle_records.items(): + slug = vehicle.replace(".", "_") + path = root / treatment / f"{slug}.json" + _write_json(path, runtime) + records["vehicle"][treatment][vehicle] = { + "path": str(path.relative_to(output_root)), + "sha256": _sha256_file(path), + } + shared_path = root / "shared_training.json" + _write_json(shared_path, bundle["shared_training"]) + records["shared_training"] = { + "path": str(shared_path.relative_to(output_root)), + "sha256": _sha256_file(shared_path), + } + _write_json(root / "manifest.json", records) + records["manifest_sha256"] = _sha256_file(root / "manifest.json") + return records + + +def _load_runtime_bundle( + output_root: Path, base: Mapping[str, Any] +) -> tuple[dict[str, Any], dict[str, Any]]: + manifest_path = output_root / "runtime_configs/manifest.json" + manifest = _load_json(manifest_path) + bundle: dict[str, Any] = {"vehicle": {}} + for treatment, records in manifest["vehicle"].items(): + bundle["vehicle"][treatment] = {} + for vehicle, specification in records.items(): + path = output_root / specification["path"] + if _sha256_file(path) != specification["sha256"]: + raise ValueError( + f"Frozen runtime config changed: {treatment}/{vehicle}" + ) + bundle["vehicle"][treatment][vehicle] = _load_json(path) + shared_spec = manifest["shared_training"] + shared_path = output_root / shared_spec["path"] + if _sha256_file(shared_path) != shared_spec["sha256"]: + raise ValueError("Frozen shared runtime config changed") + bundle["shared_training"] = _load_json(shared_path) + tapes, shared_interleave = stage7b_v2._load_and_validate_schedules(base) + bundle["tapes"] = tapes + bundle["shared_interleave"] = shared_interleave + return bundle, manifest + + +def _endpoint_result_path(execution_root: Path) -> Path: + return execution_root / "endpoint_result.json" + + +def _endpoint_common_gates( + protocol: Mapping[str, Any], + base: Mapping[str, Any], + raw: Mapping[str, Any], + access: Mapping[str, Any], +) -> dict[str, bool]: + vehicle = str(raw["vehicle"]) + treatment = str(raw["treatment"]) + raw_gates = dict(raw["validity_gates"]) + if treatment == "source": + raw_gates.pop("source_attacked_anchor_passed", None) + clean_reference = protocol["source_gate_reference_artifacts"][ + "clean_prediction_row_sha256_by_vehicle" + ][vehicle] + gates = { + "inherited_v2_nonhistorical_endpoint_gates_pass": all(raw_gates.values()), + "clean_prediction_rows_match_frozen_reference": raw["prediction_rows"][ + "clean_sha256" + ] + == clean_reference, + "sample_count_order_and_predictions_finite": bool( + raw["validity_gates"]["evaluation_sample_count_exact"] + and raw["validity_gates"]["sample_order_exact"] + and raw["validity_gates"]["full_prediction_rows_finite"] + ), + "excluded_runtime_path_open_count_exact_zero": int( + access.get("excluded_runtime_path_open_count", -1) + ) + == 0, + } + if treatment == "source": + arm = _arm_by_vehicle(base)[vehicle] + observed_recall = float(raw["metrics"]["attacked"]["recall"]) + historical_recall = float(arm["source_metrics"]["attacked"]["recall"]) + gates.update( + { + "source_texture_matches_frozen_reference": raw["texture"]["sha256"] + == protocol["source_gate_reference_artifacts"][ + "source_texture_sha256_by_vehicle" + ][vehicle], + "source_clean_metrics_match_historical_within_1e_9": bool( + raw["source_clean_anchor"]["passed"] + ), + "source_attacked_recall_matches_historical_within_1e_9": abs( + observed_recall - historical_recall + ) + <= SOURCE_RECALL_TOLERANCE, + } + ) + return gates + + +def _run_endpoint_internal( + protocol_path: Path, + runtime_config_path: Path, + execution_root: Path, + vehicle: str, + treatment: str, + device: str, +) -> int: + if execution_root.exists(): + raise FileExistsError(f"Endpoint output must be new: {execution_root}") + protocol = _load_json(protocol_path) + validate_protocol_static(protocol) + _, base = _base_protocol(protocol) + arm = _arm_by_vehicle(base)[vehicle] + runtime = _load_json(runtime_config_path) + if runtime["stage7b_audit"]["audit_id"] != AUDIT_ID: + raise ValueError("Endpoint runtime v3 audit identity changed") + if runtime["stage7b_audit"]["treatment"] != treatment: + raise ValueError("Endpoint runtime treatment identity changed") + runtime = copy.deepcopy(runtime) + runtime["evaluation"]["results_folder_name"] = str( + execution_root / "renderer_evaluation" + ) + dataset_root = Path(runtime["dataset"]["load"]["load_path"]) + checkpoint_path = Path(runtime["evaluation"]["checkpoint_path"]) + access_audit = stage7b_v2.FileAccessAudit( + (PROJECT_ROOT, dataset_root, checkpoint_path.parent, execution_root) + ) + sys.addaudithook(access_audit) + runtime_environment = stage7b_v2._runtime_identity_record(base) + raw = stage7b_v2.run_evaluation( + base, + arm, + runtime, + treatment=treatment, + output_root=execution_root, + device_text=device, + ) + evaluation_summary = _load_json(Path(raw["summary_path"])) + evaluated_checkpoint_sha256 = evaluation_summary["protocol"]["checkpoint_sha256"] + access = access_audit.record() + gates = _endpoint_common_gates(protocol, base, raw, access) + result = { + "audit_id": AUDIT_ID, + "status": "endpoint_execution_complete", + "recorded_at_utc": _utc_now(), + "vehicle": vehicle, + "treatment": treatment, + "optimization_updates_performed_by_endpoint": 0, + "metrics": raw["metrics"], + "prediction_rows": raw["prediction_rows"], + "texture": raw["texture"], + "evaluated_checkpoint_sha256": evaluated_checkpoint_sha256, + "runtime_environment": runtime_environment, + "raw_evaluator_result": raw, + "runtime_file_access": access, + "validity_gates": gates, + "all_per_execution_validity_gates_pass": all(gates.values()), + } + _write_json(_endpoint_result_path(execution_root), result) + print(json.dumps(result, ensure_ascii=True, sort_keys=True)) + return 0 + + +def _invoke_endpoint( + *, + protocol_path: Path, + runtime_config_path: Path, + execution_root: Path, + vehicle: str, + treatment: str, + device: str, +) -> dict[str, Any]: + command = [ + sys.executable, + str(Path(__file__).resolve()), + "--phase", + "_endpoint", + "--protocol", + str(protocol_path), + "--runtime-config", + str(runtime_config_path), + "--output", + str(execution_root), + "--vehicle", + vehicle, + "--treatment", + treatment, + "--device", + device, + ] + completed = subprocess.run( + command, cwd=PROJECT_ROOT, capture_output=True, text=True + ) + execution_root.mkdir(parents=True, exist_ok=True) + (execution_root / "process_stdout.txt").write_text( + completed.stdout, encoding="utf-8" + ) + (execution_root / "process_stderr.txt").write_text( + completed.stderr, encoding="utf-8" + ) + if completed.returncode != 0: + raise RuntimeError( + f"Endpoint process failed for {vehicle}/{treatment}: " + f"return code {completed.returncode}; stderr={completed.stderr[-2000:]}" + ) + return _load_json(_endpoint_result_path(execution_root)) + + +def _summarize_endpoint( + protocol: Mapping[str, Any], + base: Mapping[str, Any], + vehicle: str, + treatment: str, + records: list[Mapping[str, Any]], + *, + pre_source_median: float | None = None, + expected_checkpoint_sha256: str | None = None, +) -> dict[str, Any]: + arm = _arm_by_vehicle(base)[vehicle] + ap_values = [ + float(record["metrics"]["attacked"]["mean_ap_50_95"]) for record in records + ] + ap50_values = [float(record["metrics"]["attacked"]["ap50"]) for record in records] + recall_values = [ + float(record["metrics"]["attacked"]["recall"]) for record in records + ] + median = _second_order_statistic(ap_values) + spread = _span(ap_values) + clean_hashes = [record["prediction_rows"]["clean_sha256"] for record in records] + attacked_hashes = [ + record["prediction_rows"]["attacked_sha256"] for record in records + ] + sample_hashes = [ + record["prediction_rows"]["sample_order_sha256"] for record in records + ] + texture_hashes = [record["texture"]["sha256"] for record in records] + checkpoint_hashes = [record["evaluated_checkpoint_sha256"] for record in records] + clean_reference = protocol["source_gate_reference_artifacts"][ + "clean_prediction_row_sha256_by_vehicle" + ][vehicle] + gates = { + "exactly_three_executions": len(records) == EXECUTIONS_PER_ENDPOINT, + "all_per_execution_gates_pass": len(records) == EXECUTIONS_PER_ENDPOINT + and all(record["all_per_execution_validity_gates_pass"] for record in records), + "attacked_ap50_95_spread_at_most_0_00015": _at_most( + spread, ENDPOINT_SPREAD_LIMIT + ), + "generated_texture_hash_exact_across_executions": len(set(texture_hashes)) == 1, + "evaluated_checkpoint_hash_exact_across_executions": len(set(checkpoint_hashes)) + == 1, + "clean_prediction_rows_exact_and_match_reference": len(set(clean_hashes)) == 1 + and clean_hashes[0] == clean_reference, + "sample_order_exact_across_executions": len(set(sample_hashes)) == 1, + "all_endpoint_values_finite": all( + math.isfinite(value) for value in (*ap_values, *ap50_values, *recall_values) + ), + } + historical_ap = float(arm["source_metrics"]["attacked"]["mean_ap_50_95"]) + if treatment == "source": + if expected_checkpoint_sha256 is None: + expected_checkpoint_sha256 = base["frozen_inputs"]["source_checkpoint"][ + "sha256" + ] + historical_recall = float(arm["source_metrics"]["attacked"]["recall"]) + gates.update( + { + "source_texture_matches_frozen_reference": texture_hashes[0] + == protocol["source_gate_reference_artifacts"][ + "source_texture_sha256_by_vehicle" + ][vehicle], + "source_checkpoint_matches_frozen_reference": checkpoint_hashes[0] + == expected_checkpoint_sha256, + "source_recall_exact_across_executions": len(set(recall_values)) == 1, + "source_recall_matches_historical_within_1e_9": all( + abs(value - historical_recall) <= SOURCE_RECALL_TOLERANCE + for value in recall_values + ), + "source_median_matches_historical_within_0_0003": _at_most( + _absolute_difference(median, historical_ap), + SOURCE_COMPATIBILITY_LIMIT, + ), + } + ) + if pre_source_median is not None: + gates["final_source_median_matches_pre_source_within_0_0003"] = _at_most( + _absolute_difference(median, pre_source_median), + SOURCE_COMPATIBILITY_LIMIT, + ) + elif expected_checkpoint_sha256 is not None: + gates["evaluated_checkpoint_matches_training_artifact"] = ( + checkpoint_hashes[0] == expected_checkpoint_sha256 + ) + return { + "vehicle": vehicle, + "treatment": treatment, + "executions": len(records), + "attacked_ap50_95": { + "values": ap_values, + "median_second_order_statistic": median, + "spread_max_minus_min": spread, + "historical_source_value": historical_ap if treatment == "source" else None, + "historical_absolute_difference": ( + _absolute_difference(median, historical_ap) + if treatment == "source" + else None + ), + }, + "attacked_ap50_diagnostic": { + "values": ap50_values, + "median_second_order_statistic": _second_order_statistic(ap50_values), + "spread_max_minus_min": _span(ap50_values), + }, + "attacked_recall": { + "values": recall_values, + "median_second_order_statistic": _second_order_statistic(recall_values), + "spread_max_minus_min": _span(recall_values), + }, + "clean_prediction_hashes": clean_hashes, + "attacked_prediction_hashes": attacked_hashes, + "sample_order_hashes": sample_hashes, + "texture_hashes": texture_hashes, + "evaluated_checkpoint_hashes": checkpoint_hashes, + "validity_gates": gates, + "all_validity_gates_pass": all(gates.values()), + } + + +def _hash_tree(root: Path) -> dict[str, str]: + return { + str(path.relative_to(root)): _sha256_file(path) + for path in sorted(root.rglob("*")) + if path.is_file() + } + + +def _tree_matches_manifest(root: Path, manifest_path: Path) -> bool: + expected = _load_json(manifest_path) + return expected == _hash_tree(root) + + +def _write_sha_file(path: Path, target: Path) -> None: + path.write_text(f"{_sha256_file(target)} {target.name}\n", encoding="utf-8") + + +def _preflight( + protocol_path: Path, + dataset_root: Path, + source_checkpoint: Path, + output_root: Path, + device: str, +) -> tuple[dict[str, Any], dict[str, Any], dict[str, Any], dict[str, Any]]: + protocol = _load_json(protocol_path) + validate_protocol_static(protocol) + base_path, base = _base_protocol(protocol) + base_record, bundle = stage7b_v2.preflight( + base_path, dataset_root, source_checkpoint, output_root, device + ) + bundle = _rewrite_runtime_bundle(bundle, protocol_path, output_root) + record = { + "audit_id": AUDIT_ID, + "status": "v3_preflight_passed_before_detector_or_sample_tensor_load", + "recorded_at_utc": _utc_now(), + "protocol_path": str(protocol_path), + "protocol_sha256": _sha256_file(protocol_path), + "base_v2_protocol_path": str(base_path), + "base_v2_protocol_sha256": _sha256_file(base_path), + "base_v2_preflight": base_record, + "optimization_updates": 0, + "gates": { + "v3_protocol_and_external_review_hashes_exact": True, + "v2_scientific_protocol_unchanged_and_valid": True, + "base_v2_preflight_all_gates_pass": all(base_record["gates"].values()), + "fresh_v3_output_absent": not output_root.exists(), + }, + } + if not all(record["gates"].values()): + raise RuntimeError("Stage 7b v3 preflight produced a failed gate") + return protocol, base, record, bundle + + +def run_source_gate( + protocol_path: Path, + dataset_root: Path, + source_checkpoint: Path, + output_root: Path, + device: str, +) -> int: + protocol, base, preflight, bundle = _preflight( + protocol_path, dataset_root, source_checkpoint, output_root, device + ) + output_root.mkdir(parents=True, exist_ok=False) + _write_json(output_root / "preflight.json", preflight) + runtime_manifest = _persist_runtime_bundle(output_root, bundle) + source_root = output_root / "source_preflight" + records = {vehicle: [] for vehicle in ALLOWED_VEHICLES} + execution_order: list[dict[str, Any]] = [] + try: + for round_index in range(1, EXECUTIONS_PER_ENDPOINT + 1): + for vehicle in SOURCE_EXECUTION_ORDER: + slug = vehicle.replace(".", "_") + execution_root = ( + source_root / "executions" / f"round_{round_index:02d}" / slug + ) + runtime_spec = runtime_manifest["vehicle"]["source"][vehicle] + result = _invoke_endpoint( + protocol_path=protocol_path, + runtime_config_path=output_root / runtime_spec["path"], + execution_root=execution_root, + vehicle=vehicle, + treatment="source", + device=device, + ) + records[vehicle].append(result) + execution_order.append( + { + "ordinal": len(execution_order) + 1, + "round": round_index, + "vehicle": vehicle, + "treatment": "source", + "endpoint_result_sha256": _sha256_file( + _endpoint_result_path(execution_root) + ), + } + ) + _write_json( + source_root / "partial_source_preflight.json", + { + "audit_id": AUDIT_ID, + "optimization_updates": 0, + "completed_execution_order": execution_order, + }, + ) + summaries = { + vehicle: _summarize_endpoint( + protocol, base, vehicle, "source", records[vehicle] + ) + for vehicle in ALLOWED_VEHICLES + } + all_valid = all(item["all_validity_gates_pass"] for item in summaries.values()) + endpoint_manifest = _hash_tree(source_root / "executions") + endpoint_manifest_path = source_root / "endpoint_artifacts_sha256.json" + _write_json(endpoint_manifest_path, endpoint_manifest) + result = { + "audit_id": AUDIT_ID, + "status": SOURCE_GATE_PASS_STATUS if all_valid else SOURCE_GATE_FAIL_STATUS, + "recorded_at_utc": _utc_now(), + "optimization_updates": 0, + "training_authorized": all_valid, + "old_v2a_or_diagnostic_executions_reused": False, + "executions_expected": 12, + "executions_observed": len(execution_order), + "execution_order": execution_order, + "per_vehicle": summaries, + "runtime_config_manifest_sha256": runtime_manifest["manifest_sha256"], + "endpoint_artifact_manifest_sha256": _sha256_file(endpoint_manifest_path), + "all_source_gate_validity_gates_pass": all_valid, + "claim_boundary": protocol["claim_boundary"], + } + result_path = source_root / "source_preflight.json" + _write_json(result_path, result) + _write_sha_file(source_root / "source_preflight.sha256", result_path) + seal = { + "audit_id": AUDIT_ID, + "status": result["status"], + "training_authorized": all_valid, + "optimization_updates": 0, + "protocol_sha256": _sha256_file(protocol_path), + "runner_sha256": _sha256_file(Path(__file__).resolve()), + "source_preflight_sha256": _sha256_file(result_path), + "endpoint_artifact_manifest_sha256": _sha256_file(endpoint_manifest_path), + "runtime_config_manifest_sha256": runtime_manifest["manifest_sha256"], + } + seal_path = output_root / "source_gate_seal.json" + _write_json(seal_path, seal) + _write_sha_file(output_root / "source_gate_seal.sha256", seal_path) + _write_json(output_root / "decision.json", result) + print(json.dumps(result, ensure_ascii=True, indent=2, sort_keys=True)) + return 0 if all_valid else 2 + except BaseException as exc: + failure = { + "audit_id": AUDIT_ID, + "status": SOURCE_GATE_FAIL_STATUS, + "recorded_at_utc": _utc_now(), + "optimization_updates": 0, + "training_authorized": False, + "completed_endpoint_executions": len(execution_order), + "error_type": type(exc).__name__, + "error": str(exc), + "traceback": traceback.format_exc(), + } + _write_json(output_root / "decision.json", failure) + _write_json(output_root / "failure.json", failure) + print(json.dumps(failure, ensure_ascii=True, indent=2, sort_keys=True)) + return 2 + + +def _verify_source_gate_seal( + protocol_path: Path, output_root: Path +) -> tuple[dict[str, Any], dict[str, Any]]: + seal_path = output_root / "source_gate_seal.json" + result_path = output_root / "source_preflight/source_preflight.json" + endpoint_manifest = output_root / "source_preflight/endpoint_artifacts_sha256.json" + runtime_manifest = output_root / "runtime_configs/manifest.json" + seal = _load_json(seal_path) + result = _load_json(result_path) + gates = { + "source_gate_pass_status_exact": seal.get("status") == SOURCE_GATE_PASS_STATUS + and result.get("status") == SOURCE_GATE_PASS_STATUS, + "training_authorized_exact": seal.get("training_authorized") is True + and result.get("training_authorized") is True, + "optimization_updates_zero": int(seal.get("optimization_updates", -1)) == 0 + and int(result.get("optimization_updates", -1)) == 0, + "protocol_hash_exact": seal.get("protocol_sha256") + == _sha256_file(protocol_path), + "runner_hash_exact": seal.get("runner_sha256") + == _sha256_file(Path(__file__).resolve()), + "source_preflight_hash_exact": seal.get("source_preflight_sha256") + == _sha256_file(result_path), + "endpoint_manifest_hash_exact": seal.get("endpoint_artifact_manifest_sha256") + == _sha256_file(endpoint_manifest), + "endpoint_tree_matches_frozen_manifest": _tree_matches_manifest( + output_root / "source_preflight/executions", endpoint_manifest + ), + "runtime_manifest_hash_exact": seal.get("runtime_config_manifest_sha256") + == _sha256_file(runtime_manifest), + "exactly_twelve_source_executions": int(result.get("executions_observed", -1)) + == 12, + "all_four_source_gates_pass": bool( + result.get("all_source_gate_validity_gates_pass") + ), + } + if not all(gates.values()): + failed = [key for key, passed in gates.items() if not passed] + raise RuntimeError(f"Stage 7b v3 source-gate seal failed: {failed}") + return seal, result + + +def _final_decision( + protocol: Mapping[str, Any], + base: Mapping[str, Any], + pre_source: Mapping[str, Any], + endpoint_summaries: Mapping[str, Mapping[str, Mapping[str, Any]]], + specialist_training: Mapping[str, Mapping[str, Any]], + shared_training: Mapping[str, Any], + all_file_access_valid: bool, +) -> dict[str, Any]: + source_results: dict[str, Any] = {} + specialist_results: dict[str, Any] = {} + shared_results: dict[str, Any] = {} + for vehicle in ALLOWED_VEHICLES: + summaries = endpoint_summaries[vehicle] + clean_sha = protocol["source_gate_reference_artifacts"][ + "clean_prediction_row_sha256_by_vehicle" + ][vehicle] + sample_sha = summaries["source"]["sample_order_hashes"][0] + for treatment, target in ( + ("source", source_results), + ("specialist", specialist_results), + ("shared", shared_results), + ): + summary = summaries[treatment] + target[vehicle] = { + "all_validity_gates_pass": summary["all_validity_gates_pass"], + "metrics": { + "attacked": { + "mean_ap_50_95": summary["attacked_ap50_95"][ + "median_second_order_statistic" + ] + } + }, + "prediction_rows": { + "clean_sha256": clean_sha, + "sample_order_sha256": sample_sha, + }, + } + inherited = stage7b_v2.decide( + base, + source_results, + specialist_training, + specialist_results, + shared_training, + shared_results, + {"excluded_runtime_path_open_count": 0 if all_file_access_valid else 1}, + ) + all_endpoint_valid = all( + summary["all_validity_gates_pass"] + for summaries in endpoint_summaries.values() + for summary in summaries.values() + ) + all_valid = bool( + inherited["validity"]["all_combined_validity_gates_pass"] + and all_endpoint_valid + and all_file_access_valid + ) + inherited["audit_id"] = AUDIT_ID + inherited["status"] = ( + FINAL_VALID_STATUS if all_valid else FINAL_INDETERMINATE_STATUS + ) + inherited["validity"][ + "all_v3_endpoint_spread_and_identity_gates_pass" + ] = all_endpoint_valid + inherited["validity"][ + "all_parent_and_child_file_access_gates_pass" + ] = all_file_access_valid + inherited["validity"]["all_combined_validity_gates_pass"] = all_valid + inherited["endpoint_estimator"] = { + "executions_per_checkpoint_vehicle": 3, + "summary": "median_second_order_statistic", + "primary_contrast": "final_source_median_minus_specialist_median", + "specialization_contrast": "shared_median_minus_specialist_median", + "pre_source_role": "authorization_and_runtime_drift_reference_only", + "endpoint_repetitions_are_iid": False, + } + inherited["pre_treatment_source_gate"] = pre_source + inherited["final_endpoint_summaries"] = endpoint_summaries + inherited["claim_boundary"] = protocol["claim_boundary"] + return inherited + + +def run_treatment( + protocol_path: Path, + source_checkpoint_path: Path, + output_root: Path, + device: str, +) -> int: + protocol = _load_json(protocol_path) + validate_protocol_static(protocol) + _, base = _base_protocol(protocol) + _, pre_source = _verify_source_gate_seal(protocol_path, output_root) + forbidden_existing = [ + output_root / "treatment_started.json", + output_root / "specialists", + output_root / "shared", + output_root / "final_evaluation", + ] + if any(path.exists() for path in forbidden_existing): + raise RuntimeError("V3 treatment output is not fresh; resume is prohibited") + _write_json( + output_root / "treatment_started.json", + { + "audit_id": AUDIT_ID, + "status": "treatment_started_after_sealed_source_gate", + "recorded_at_utc": _utc_now(), + "source_gate_seal_sha256": _sha256_file( + output_root / "source_gate_seal.json" + ), + "optimization_updates_before_record": 0, + }, + ) + bundle, _ = _load_runtime_bundle(output_root, base) + access_audit = stage7b_v2.FileAccessAudit( + (PROJECT_ROOT, source_checkpoint_path.parent, output_root) + ) + sys.addaudithook(access_audit) + specialist_training: dict[str, dict[str, Any]] = {} + shared_training: dict[str, Any] = {} + endpoint_records: dict[str, dict[str, list[Mapping[str, Any]]]] = { + vehicle: {treatment: [] for treatment in ("source", "specialist", "shared")} + for vehicle in ALLOWED_VEHICLES + } + execution_order: list[dict[str, Any]] = [] + try: + from utils.checkpoint import load_checkpoint + + source_checkpoint = load_checkpoint( + source_checkpoint_path, map_location="cpu", restore_rng=False + ) + source_inventory = _load_json( + PROJECT_ROOT / base["frozen_inputs"]["source_checkpoint_inventory"]["path"] + ) + for arm in base["arms"]: + vehicle = str(arm["vehicle"]) + specialist_training[vehicle] = stage7b_v2.run_training_arm( + base, + bundle["vehicle"]["specialist"][vehicle], + bundle["vehicle"]["specialist"], + source_checkpoint, + source_inventory, + bundle["tapes"], + bundle["shared_interleave"], + treatment="specialist", + vehicle=vehicle, + output_root=output_root, + device_text=device, + ) + _write_json( + output_root / "partial_specialist_training_results.json", + specialist_training, + ) + if not specialist_training[vehicle]["all_validity_gates_pass"]: + raise RuntimeError(f"Invalid specialist training arm: {vehicle}") + shared_training = stage7b_v2.run_training_arm( + base, + bundle["shared_training"], + bundle["vehicle"]["specialist"], + source_checkpoint, + source_inventory, + bundle["tapes"], + bundle["shared_interleave"], + treatment="shared", + vehicle=None, + output_root=output_root, + device_text=device, + ) + _write_json(output_root / "shared_training_result.json", shared_training) + if not shared_training["all_validity_gates_pass"]: + raise RuntimeError("Invalid shared training arm") + + final_root = output_root / "final_evaluation" + for vehicle in ALLOWED_VEHICLES: + slug = vehicle.replace(".", "_") + for block_index, block in enumerate(FINAL_ORDER[vehicle], start=1): + for position, treatment in enumerate(block, start=1): + runtime_spec = _load_json( + output_root / "runtime_configs/manifest.json" + )["vehicle"][treatment][vehicle] + execution_root = ( + final_root + / "executions" + / slug + / f"block_{block_index:02d}_position_{position:02d}_{treatment}" + ) + result = _invoke_endpoint( + protocol_path=protocol_path, + runtime_config_path=output_root / runtime_spec["path"], + execution_root=execution_root, + vehicle=vehicle, + treatment=treatment, + device=device, + ) + endpoint_records[vehicle][treatment].append(result) + execution_order.append( + { + "ordinal": len(execution_order) + 1, + "vehicle": vehicle, + "block": block_index, + "position": position, + "treatment": treatment, + } + ) + _write_json( + final_root / "partial_final_evaluation.json", + {"completed_execution_order": execution_order}, + ) + endpoint_summaries = { + vehicle: { + treatment: _summarize_endpoint( + protocol, + base, + vehicle, + treatment, + endpoint_records[vehicle][treatment], + pre_source_median=( + float( + pre_source["per_vehicle"][vehicle]["attacked_ap50_95"][ + "median_second_order_statistic" + ] + ) + if treatment == "source" + else None + ), + expected_checkpoint_sha256=( + base["frozen_inputs"]["source_checkpoint"]["sha256"] + if treatment == "source" + else ( + specialist_training[vehicle]["checkpoint"]["sha256"] + if treatment == "specialist" + else shared_training["checkpoint"]["sha256"] + ) + ), + ) + for treatment in ("source", "specialist", "shared") + } + for vehicle in ALLOWED_VEHICLES + } + access = access_audit.record() + child_access_valid = all( + int(record["runtime_file_access"]["excluded_runtime_path_open_count"]) == 0 + for vehicle_records in endpoint_records.values() + for records in vehicle_records.values() + for record in records + ) + all_file_access_valid = ( + int(access["excluded_runtime_path_open_count"]) == 0 and child_access_valid + ) + decision = _final_decision( + protocol, + base, + pre_source, + endpoint_summaries, + specialist_training, + shared_training, + all_file_access_valid, + ) + decision["final_evaluation_order"] = execution_order + decision["runtime_file_access"] = access + _write_json(final_root / "endpoint_summaries.json", endpoint_summaries) + _write_json(final_root / "execution_order.json", {"order": execution_order}) + _write_json(output_root / "runtime_file_access.json", access) + _write_json(output_root / "decision.json", decision) + print(json.dumps(decision, ensure_ascii=True, indent=2, sort_keys=True)) + return 0 if decision["status"] == FINAL_VALID_STATUS else 2 + except BaseException as exc: + access = access_audit.record() + failure = { + "audit_id": AUDIT_ID, + "status": FINAL_INDETERMINATE_STATUS, + "recorded_at_utc": _utc_now(), + "capacity_decision": "unavailable", + "specialization_decision": "unavailable", + "oracle_recovery_decision": "unavailable", + "completed_specialist_training_vehicles": list(specialist_training), + "shared_training_completed": bool(shared_training), + "completed_final_endpoint_executions": len(execution_order), + "error_type": type(exc).__name__, + "error": str(exc), + "traceback": traceback.format_exc(), + "runtime_file_access": access, + "claim_boundary": protocol["claim_boundary"], + } + _write_json(output_root / "runtime_file_access.json", access) + _write_json(output_root / "failure.json", failure) + _write_json(output_root / "decision.json", failure) + print(json.dumps(failure, ensure_ascii=True, indent=2, sort_keys=True)) + return 2 + + +def main(argv=None) -> int: + args = parse_args(argv) + launch = Path.cwd() + protocol_path = _resolve(args.protocol, launch) + output_root = _resolve(args.output, launch) + if args.phase == "_endpoint": + if ( + args.runtime_config is None + or args.vehicle is None + or args.treatment is None + ): + raise ValueError( + "Internal endpoint phase requires runtime, vehicle, and treatment" + ) + return _run_endpoint_internal( + protocol_path, + _resolve(args.runtime_config, launch), + output_root, + args.vehicle, + args.treatment, + args.device, + ) + if args.source_checkpoint is None: + raise ValueError(f"Phase {args.phase} requires --source-checkpoint") + source_checkpoint = _resolve(args.source_checkpoint, launch) + if args.phase in {"preflight", "source-gate"} and args.dataset_root is None: + raise ValueError(f"Phase {args.phase} requires --dataset-root") + if args.phase == "preflight": + _, _, record, _ = _preflight( + protocol_path, + _resolve(args.dataset_root, launch), + source_checkpoint, + output_root, + args.device, + ) + print(json.dumps(record, ensure_ascii=True, indent=2, sort_keys=True)) + return 0 + if args.phase == "source-gate": + return run_source_gate( + protocol_path, + _resolve(args.dataset_root, launch), + source_checkpoint, + output_root, + args.device, + ) + return run_treatment(protocol_path, source_checkpoint, output_root, args.device) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/stage7/stage7b_v3_source_gate_l40s_v3a/frozen/stage7b_per_vehicle_vs_shared_continuation_control_v3.json b/stage7/stage7b_v3_source_gate_l40s_v3a/frozen/stage7b_per_vehicle_vs_shared_continuation_control_v3.json new file mode 100644 index 0000000000000000000000000000000000000000..a63e26cd039617f0df172bdd0eeecffadf23b3a2 --- /dev/null +++ b/stage7/stage7b_v3_source_gate_l40s_v3a/frozen/stage7b_per_vehicle_vs_shared_continuation_control_v3.json @@ -0,0 +1,196 @@ +{ + "schema_version": 3, + "audit_id": "stage7b_per_vehicle_vs_shared_continuation_control_v3", + "status": "preregistered_before_v3_outcomes_after_external_review", + "recorded_date": "2026-08-04", + "purpose": "Apply a pre-treatment numerical-nuisance amendment to the frozen Stage 7b v2 per-vehicle-versus-shared continuation audit without changing any treatment input, threshold, or claim boundary.", + "base_scientific_protocol": { + "path": "experiments/protocols/stage7b_per_vehicle_vs_shared_continuation_control_v2.json", + "sha256": "3720fb0b19bfc240a195f3ae4e3bf4e54d098e42070bf18ee5e31b3e0da6e3e7", + "inheritance": "All treatment arms, scientific inputs, schedules, compute, decision thresholds, exclusions, oracle artifacts, and non-numerical validity gates are inherited byte-for-byte." + }, + "source_gate_amendment": { + "amendment_type": "pre_treatment_numerical_nuisance_only", + "formal_v2a_status": "permanently_indeterminate_not_repaired_or_reused", + "source_only_diagnostic_role": "pre_amendment_evidence_only_not_a_v3_formal_repetition", + "fresh_v3_output_required": true, + "historical_attacked_bitwise_gate_removed": true, + "frozen_minimum_per_vehicle_treatment_threshold": 0.003, + "total_contrast_numerical_nuisance_fraction": 0.1, + "total_contrast_numerical_nuisance_budget": 0.0003, + "total_contrast_numerical_nuisance_budget_formula": "0.10 * 0.003", + "endpoint_attacked_ap50_95_spread_limit": 0.00015, + "endpoint_spread_limit_formula": "0.5 * 0.10 * 0.003", + "historical_source_attacked_ap50_95_compatibility_limit": 0.0003, + "historical_compatibility_limit_formula": "0.10 * 0.003", + "pre_to_final_source_median_drift_limit": 0.0003, + "attacked_ap50_role": "diagnostic_only", + "attacked_prediction_row_hash_equality_required": false, + "source_attacked_recall_historical_tolerance": 1e-09, + "clean_metric_historical_tolerance": 1e-09, + "endpoint_repetitions_are_iid": false, + "confidence_intervals_from_endpoint_repetitions_permitted": false, + "deterministic_kernel_or_environment_change_permitted": false + }, + "pre_treatment_source_gate": { + "executions_per_vehicle": 3, + "vehicles_required": 4, + "total_executions": 12, + "execution_order_each_round": [ + "audi.etron", + "tesla.model3", + "ford.mustang", + "jeep.wrangler_rubicon" + ], + "summary": "median_second_order_statistic", + "spread": "maximum_minus_minimum", + "formal_comparator_role": "authorization_and_runtime_drift_reference_only", + "old_v2a_or_diagnostic_executions_may_be_reused": false, + "source_checkpoint_reloaded_for_every_execution": true, + "independent_process_required": true, + "optimizer_loaded_or_updated": false, + "source_texture_hash_exact": true, + "clean_prediction_rows_exact_across_repetitions_and_reference": true, + "clean_metrics_exact_within_tolerance": true, + "attacked_prediction_rows_may_differ": true, + "attacked_predictions_finite": true, + "attacked_sample_ids_order_and_count_exact": true, + "attacked_recall_exact_within_tolerance": true, + "attacked_ap50_95_spread_must_pass": true, + "historical_attacked_ap50_95_compatibility_must_pass": true, + "all_four_vehicles_required": true, + "freeze_artifacts_before_any_optimizer_update": true, + "additional_or_replacement_endpoint_execution_permitted": false + }, + "final_endpoint_evaluation": { + "checkpoints": [ + "source", + "specialist", + "shared" + ], + "executions_per_checkpoint_per_vehicle": 3, + "vehicles": 4, + "total_endpoint_executions": 36, + "independent_process_required": true, + "summary": "median_second_order_statistic", + "formal_source_comparator": "final_phase_median_of_three_source_executions", + "primary_contrast": "final_source_median_minus_specialist_median", + "specialization_contrast": "shared_median_minus_specialist_median", + "pre_source_role": "authorization_historical_compatibility_and_pre_to_final_drift_only", + "endpoint_attacked_ap50_95_spread_limit": 0.00015, + "all_checkpoint_vehicle_endpoint_spread_gates_required": true, + "source_historical_compatibility_limit": 0.0003, + "source_pre_to_final_median_drift_limit": 0.0003, + "additional_or_replacement_endpoint_execution_permitted": false, + "evaluation_order_by_vehicle": { + "audi.etron": [ + ["source", "specialist", "shared"], + ["specialist", "shared", "source"], + ["shared", "source", "specialist"] + ], + "tesla.model3": [ + ["source", "shared", "specialist"], + ["shared", "specialist", "source"], + ["specialist", "source", "shared"] + ], + "ford.mustang": [ + ["source", "specialist", "shared"], + ["specialist", "shared", "source"], + ["shared", "source", "specialist"] + ], + "jeep.wrangler_rubicon": [ + ["source", "shared", "specialist"], + ["shared", "specialist", "source"], + ["specialist", "source", "shared"] + ] + } + }, + "historical_attacked_metric_roles": { + "ap50_95": "bounded_source_pipeline_compatibility_gate_not_formal_comparator", + "ap50": "diagnostic_only", + "recall": "exact_source_identity_gate" + }, + "source_gate_reference_artifacts": { + "public_diagnostic_repository": "bailuyucha/differentiable-render-camouflage-data", + "public_diagnostic_revision": "f2ff75d8b9f493eac2122fc486185219da3061a2", + "public_diagnostic_path": "stage7/stage7b_v2_source_anchor_repeatability_diagnostic_v1", + "public_diagnostic_sha256s_sha256": "20a8f20eac8d07fb8c03eeb6116e1eb7c6c5e11e1a3da042c5d290e9610c6bb5", + "sealed_diagnostic_decision": { + "path": "experiments/provenance/stage7_20260804/stage7b_v2_source_anchor_repeatability_diagnostic_v1/completed_decision.json", + "sha256": "c8cf030abdb9c86163faf205febb352a3c009591b90614fe83106ad85828dbff" + }, + "clean_prediction_row_sha256_by_vehicle": { + "audi.etron": "1336b3793af306dc5ee316b3b67b79c1ed4cb5233b998c7e9079d409e98343c6", + "tesla.model3": "e574afb985edbbfe2a31f9056156fc8a14cca08584618492c4fc2a4d280f94ab", + "ford.mustang": "98d931682a54c100fef50526e7bf530ac078e8f31880b3a1a2b24e4079100785", + "jeep.wrangler_rubicon": "4bb55c97140c64420b241d70d93805cf3e00338fa5f597f3699b9cb99bf2144e" + }, + "source_texture_sha256_by_vehicle": { + "audi.etron": "40de9daaa9a67212972058d3a10326a86d0cd627103897dcecad6db2f2798350", + "tesla.model3": "048998c2520d5cafb3163462dee26ab5ad50457458ab45d9d873896f23041dda", + "ford.mustang": "18f21d911f991a73c2dbb6a51fee4873edb4c2c066334241d5704679015c2bbb", + "jeep.wrangler_rubicon": "a13676614e77d8c09f894f62e1bf35856fef4887e74f572b0db8ec429e145f50" + } + }, + "external_review_gate": { + "status": "completed_before_v3_outcomes", + "reviewer": "Web GPT Pro protocol red-team review supplied by the user", + "review_scope": "Whether the source-only attacked-AP nonrepeatability supports a minimal pre-treatment numerical nuisance amendment and the exact v3 gates required before treatment.", + "request_packet": { + "path": "docs/paper/STAGE7B_SOURCE_GATE_EXTERNAL_REVIEW_PACKET_V3.json", + "sha256": "6be908970092345affad171ca13844fcf155655e38715307a568de16911df05a" + }, + "response": { + "path": "docs/research/WEB_PRO_STAGE7B_SOURCE_GATE_REVIEW_20260804.md", + "sha256": "9ed09319fd36ec734cea6a6cd5c0963f37f8a120fc544cf82eea9214f40761ff" + }, + "disposition": { + "path": "docs/research/STAGE7B_SOURCE_GATE_EXTERNAL_REVIEW_DISPOSITION_V3.md", + "sha256": "5f6f93aef705c780208c9d5e476a4b670f4a0431d95515b8d0eac98eb0f7d366" + }, + "treatment_outcomes_observed_before_review": 0, + "optimization_updates_before_review": 0, + "verdict": "conditional_go_after_v3_source_gate_implementation_and_pass" + }, + "implementation_freeze": { + "runner": { + "path": "tools/run_stage7b_per_vehicle_vs_shared_continuation_v3.py", + "sha256": "d4ea5bc8da2babff14f5e5d748ee1a2205e4b95bbcc2942cb82b93aadd9490b1" + }, + "tests": { + "path": "tests/test_stage7b_per_vehicle_vs_shared_continuation_v3.py", + "sha256": "2949fb7bfa3bbfa4d5dd02d887967c6fd4039c0ad6d987329c4842e9db13ffc8" + } + }, + "source_gate_indeterminate_rule": { + "pre_treatment_failure_status": "stage7b_v3_source_gate_indeterminate_no_treatment_training_authorized", + "post_treatment_failure_status": "stage7b_v3_indeterminate", + "capacity_decision_on_failure": "unavailable", + "specialization_decision_on_failure": "unavailable", + "oracle_recovery_decision_on_failure": "unavailable", + "partial_vehicle_decision_permitted": false, + "partial_checkpoint_decision_permitted": false, + "outlier_removal_permitted": false, + "fallback_to_mean_permitted": false, + "adaptive_extra_repetitions_permitted": false, + "outcome_conditioned_tolerance_change_permitted": false, + "resume_after_failed_or_interrupted_v3_permitted": false + }, + "treatment_design_nonchanges": { + "generator_renderer_detector_loss_regularizers_learning_rate": "inherited_exactly_from_base_v2_protocol", + "model_adam_rng_z_base_and_generation_step_initialization": "inherited_exactly_from_base_v2_protocol", + "specialist_updates_per_vehicle": 432, + "shared_updates_total": 1728, + "shared_updates_per_vehicle": 432, + "formal_training_updates_total": 3456, + "formal_rendered_training_views_total": 6912, + "paired_stochastic_tapes_and_shared_interleave": "inherited_exactly_from_base_v2_protocol", + "capacity_specialization_and_oracle_recovery_thresholds": "inherited_exactly_from_base_v2_protocol", + "fresh_adam_arm_required": false, + "additional_latent_seed_permitted": false, + "architecture_or_renderer_search_permitted": false, + "checkpoint_selection_permitted": false, + "nissan_selection_permitted": false + }, + "claim_boundary": "A valid Stage 7b v3 result is only a fixed-cohort same-training-data continuation audit under the exact inherited source checkpoint, Adam/RNG state, frozen learning rate, losses, schedules, numerical environment, and seed-42 endpoint. Three endpoint executions bound protocol-defined numerical sensitivity; they are not iid training runs or population replicates and support no confidence interval or p-value. A positive specialist-versus-shared contrast identifies only a continuation-strategy effect under the frozen exposure-matched control, not cross-vehicle gradient conflict as a unique mechanism. Direct output is an unmatched training-fit oracle, not a fair baseline. No result supports unseen-vehicle or detector generalization, naturalness, renderer fidelity, weather robustness, physical robustness, SOTA, or representation impossibility. V2a remains permanently indeterminate regardless of v3 outcome." +} diff --git a/stage7/stage7b_v3_source_gate_l40s_v3a/frozen/test_stage7b_per_vehicle_vs_shared_continuation_v3.py b/stage7/stage7b_v3_source_gate_l40s_v3a/frozen/test_stage7b_per_vehicle_vs_shared_continuation_v3.py new file mode 100644 index 0000000000000000000000000000000000000000..3eabddcf7cd0e7024687b6532d21765587d7d76a --- /dev/null +++ b/stage7/stage7b_v3_source_gate_l40s_v3a/frozen/test_stage7b_per_vehicle_vs_shared_continuation_v3.py @@ -0,0 +1,291 @@ +from __future__ import annotations + +import copy +from decimal import Decimal +import hashlib +import json +from pathlib import Path + +import pytest + +from tools import run_stage7b_per_vehicle_vs_shared_continuation as stage7b_v2 +from tools import run_stage7b_per_vehicle_vs_shared_continuation_v3 as stage7b_v3 + + +ROOT = Path(__file__).resolve().parents[1] +PROTOCOL_PATH = ( + ROOT + / "experiments/protocols/stage7b_per_vehicle_vs_shared_continuation_control_v3.json" +) + + +def _load(path: Path): + return json.loads(path.read_text(encoding="utf-8")) + + +def _sha256(path: Path) -> str: + return hashlib.sha256(path.read_bytes()).hexdigest() + + +def _protocols(): + protocol = _load(PROTOCOL_PATH) + base_path = ROOT / protocol["base_scientific_protocol"]["path"] + return protocol, _load(base_path) + + +def test_v3_protocol_is_static_reviewed_and_treatment_inputs_are_hash_inherited(): + protocol, base = _protocols() + stage7b_v3.validate_protocol_static(protocol) + assert protocol["status"] == stage7b_v3.EXECUTION_READY_STATUS + assert _sha256(ROOT / protocol["base_scientific_protocol"]["path"]) == ( + protocol["base_scientific_protocol"]["sha256"] + ) + stage7b_v2.validate_protocol_static(base) + assert protocol["source_gate_amendment"]["formal_v2a_status"] == ( + "permanently_indeterminate_not_repaired_or_reused" + ) + assert protocol["external_review_gate"]["optimization_updates_before_review"] == 0 + assert ( + protocol["external_review_gate"]["treatment_outcomes_observed_before_review"] + == 0 + ) + + +def test_literal_clean_and_texture_references_match_sealed_diagnostic(): + protocol, _ = _protocols() + specification = protocol["source_gate_reference_artifacts"][ + "sealed_diagnostic_decision" + ] + diagnostic_path = ROOT / specification["path"] + assert _sha256(diagnostic_path) == specification["sha256"] + diagnostic = _load(diagnostic_path) + assert diagnostic["optimization_updates"] == 0 + assert diagnostic["training_authorized"] is False + for vehicle in stage7b_v3.ALLOWED_VEHICLES: + record = diagnostic["repeatability"]["per_vehicle"][vehicle] + assert set(record["clean_prediction_hashes"]) == { + protocol["source_gate_reference_artifacts"][ + "clean_prediction_row_sha256_by_vehicle" + ][vehicle] + } + assert set(record["texture_hashes"]) == { + protocol["source_gate_reference_artifacts"][ + "source_texture_sha256_by_vehicle" + ][vehicle] + } + + +def test_nuisance_budget_is_derived_from_the_frozen_treatment_threshold(): + protocol, base = _protocols() + minimum = base["decision_rule"]["capacity_improvement_pass"][ + "minimum_per_vehicle_improvement" + ] + amendment = protocol["source_gate_amendment"] + assert minimum == 0.003 + assert Decimal(str(amendment["total_contrast_numerical_nuisance_budget"])) == ( + Decimal("0.1") * Decimal(str(minimum)) + ) + assert Decimal(str(amendment["endpoint_attacked_ap50_95_spread_limit"])) == ( + Decimal(str(amendment["total_contrast_numerical_nuisance_budget"])) / 2 + ) + + +def _endpoint_record( + protocol, + vehicle, + treatment, + ap, + *, + clean_hash=None, + texture_hash=None, + recall=None, + valid=True, +): + references = protocol["source_gate_reference_artifacts"] + if clean_hash is None: + clean_hash = references["clean_prediction_row_sha256_by_vehicle"][vehicle] + if texture_hash is None: + texture_hash = references["source_texture_sha256_by_vehicle"][vehicle] + if recall is None: + _, base = _protocols() + arm = {item["vehicle"]: item for item in base["arms"]}[vehicle] + recall = arm["source_metrics"]["attacked"]["recall"] + else: + _, base = _protocols() + checkpoint_sha256 = ( + base["frozen_inputs"]["source_checkpoint"]["sha256"] + if treatment == "source" + else f"checkpoint-{treatment}" + ) + return { + "vehicle": vehicle, + "treatment": treatment, + "metrics": { + "attacked": {"mean_ap_50_95": ap, "ap50": ap + 0.2, "recall": recall} + }, + "prediction_rows": { + "clean_sha256": clean_hash, + "attacked_sha256": f"attacked-{ap}", + "sample_order_sha256": f"order-{vehicle}", + }, + "texture": {"sha256": texture_hash}, + "evaluated_checkpoint_sha256": checkpoint_sha256, + "all_per_execution_validity_gates_pass": valid, + "runtime_file_access": {"excluded_runtime_path_open_count": 0}, + } + + +def test_endpoint_summary_uses_exactly_three_middle_value_and_inclusive_spread_bound(): + protocol, base = _protocols() + vehicle = "audi.etron" + records = [ + _endpoint_record(protocol, vehicle, "specialist", value) + for value in (0.20015, 0.2, 0.20005) + ] + summary = stage7b_v3._summarize_endpoint( + protocol, base, vehicle, "specialist", records + ) + assert summary["attacked_ap50_95"][ + "median_second_order_statistic" + ] == pytest.approx(0.20005) + assert summary["attacked_ap50_95"]["spread_max_minus_min"] == pytest.approx(0.00015) + assert summary["validity_gates"]["attacked_ap50_95_spread_at_most_0_00015"] is True + assert summary["all_validity_gates_pass"] is True + + too_wide = [ + _endpoint_record(protocol, vehicle, "specialist", value) + for value in (0.2, 0.20005, 0.200151) + ] + failed = stage7b_v3._summarize_endpoint( + protocol, base, vehicle, "specialist", too_wide + ) + assert failed["validity_gates"]["attacked_ap50_95_spread_at_most_0_00015"] is False + assert failed["all_validity_gates_pass"] is False + + +def test_endpoint_summary_rejects_extra_execution_without_outlier_fallback(): + protocol, base = _protocols() + vehicle = "tesla.model3" + historical = base["arms"][1]["source_metrics"]["attacked"]["mean_ap_50_95"] + records = [ + _endpoint_record(protocol, vehicle, "source", historical + 0.00001 * index) + for index in range(4) + ] + with pytest.raises(ValueError, match="exactly three finite values"): + stage7b_v3._summarize_endpoint(protocol, base, vehicle, "source", records) + + +def test_source_historical_and_pre_to_final_bounds_are_separate_gates(): + protocol, base = _protocols() + vehicle = "ford.mustang" + historical = base["arms"][2]["source_metrics"]["attacked"]["mean_ap_50_95"] + records = [ + _endpoint_record(protocol, vehicle, "source", historical + offset) + for offset in (0.00028, 0.00029, 0.0003) + ] + summary = stage7b_v3._summarize_endpoint( + protocol, + base, + vehicle, + "source", + records, + pre_source_median=historical, + ) + assert ( + summary["validity_gates"]["source_median_matches_historical_within_0_0003"] + is True + ) + assert ( + summary["validity_gates"][ + "final_source_median_matches_pre_source_within_0_0003" + ] + is True + ) + + drifted = stage7b_v3._summarize_endpoint( + protocol, + base, + vehicle, + "source", + records, + pre_source_median=historical - 0.00002, + ) + assert ( + drifted["validity_gates"]["source_median_matches_historical_within_0_0003"] + is True + ) + assert ( + drifted["validity_gates"][ + "final_source_median_matches_pre_source_within_0_0003" + ] + is False + ) + + +def test_final_orders_are_position_balanced_and_forward_reverse_paired(): + protocol, _ = _protocols() + observed = { + vehicle: tuple(tuple(block) for block in blocks) + for vehicle, blocks in protocol["final_endpoint_evaluation"][ + "evaluation_order_by_vehicle" + ].items() + } + assert observed == stage7b_v3.FINAL_ORDER + for blocks in observed.values(): + for treatment in ("source", "specialist", "shared"): + positions = [block.index(treatment) for block in blocks] + assert sorted(positions) == [0, 1, 2] + assert observed["audi.etron"] == observed["ford.mustang"] + assert observed["tesla.model3"] == observed["jeep.wrangler_rubicon"] + assert observed["audi.etron"] != observed["tesla.model3"] + + +def test_source_gate_tree_manifest_detects_additions_and_mutations(tmp_path): + root = tmp_path / "executions" + root.mkdir() + artifact = root / "endpoint.json" + artifact.write_text("first", encoding="utf-8") + manifest = tmp_path / "manifest.json" + stage7b_v3._write_json(manifest, stage7b_v3._hash_tree(root)) + assert stage7b_v3._tree_matches_manifest(root, manifest) is True + artifact.write_text("second", encoding="utf-8") + assert stage7b_v3._tree_matches_manifest(root, manifest) is False + artifact.write_text("first", encoding="utf-8") + (root / "extra.json").write_text("extra", encoding="utf-8") + assert stage7b_v3._tree_matches_manifest(root, manifest) is False + + +def test_static_validation_rejects_tolerance_order_or_reference_changes(): + protocol, _ = _protocols() + changed = copy.deepcopy(protocol) + changed["source_gate_amendment"]["endpoint_attacked_ap50_95_spread_limit"] = 0.0003 + with pytest.raises(ValueError, match="amendment field changed"): + stage7b_v3.validate_protocol_static(changed) + + changed = copy.deepcopy(protocol) + changed["final_endpoint_evaluation"]["evaluation_order_by_vehicle"]["audi.etron"][ + 0 + ] = ["shared", "specialist", "source"] + with pytest.raises(ValueError, match="balanced final endpoint order"): + stage7b_v3.validate_protocol_static(changed) + + changed = copy.deepcopy(protocol) + changed["source_gate_reference_artifacts"][ + "clean_prediction_row_sha256_by_vehicle" + ]["jeep.wrangler_rubicon"] = ("0" * 64) + with pytest.raises(ValueError, match="Frozen clean-row reference changed"): + stage7b_v3.validate_protocol_static(changed) + + +def test_internal_endpoint_phase_requires_all_identity_arguments(tmp_path): + with pytest.raises(ValueError, match="requires runtime, vehicle, and treatment"): + stage7b_v3.main( + [ + "--phase", + "_endpoint", + "--protocol", + str(PROTOCOL_PATH), + "--output", + str(tmp_path / "endpoint"), + ] + )