diff --git a/CURRENT.md b/CURRENT.md index 18585a5..77594df 100644 --- a/CURRENT.md +++ b/CURRENT.md @@ -4,29 +4,22 @@ ## 最新结果 -Phase 4AK 已正式封存：**PASS-FROZEN-D18-INDEPENDENT-VALIDATION**。直接调用 Phase 4AJ 已冻结的 D18 实现；本轮没有再改延迟、增益、LIF、输入编码或判据。 +Phase 4AL 已封存：**PASS-CONDITIONAL-CREDIT-TRANSFER-AUDIT-NOT-LEARNING**。仍未达到“学习可用”，没有新增 learned candidate，也没有替换正式 reference/runtime。 -| 验证输入 | 模式 | 平均 KC 活跃比例 | 通过气味对 | 原完整表征门 | -|---|---|---:|---:|---| -| 原六气味、新种子 | physiological | 3.4670% | 12/15 | PASS | -| 原六气味、新种子 | matched_energy | 3.4564% | 11/15 | PASS | -| 后六气味、新种子 | physiological | 3.2767% | 14/15 | PASS | -| 后六气味、新种子 | matched_energy | 3.2579% | 14/15 | PASS | +- 固定 D18 的 120 条主轨迹、24 次重复，全部 MBON 基线 events/counts/final V/g/ref 逐位复现。 +- 全部 60 组气味对都有各自特有的 KC 与候选边，但完整 active-set overlap 仍明显。 +- 一次固定 25% mask 减弱，在 120/120 主试验中改变了 MBON count 或首次 latency。它只是钳制上游的条件性诊断，不是学习、不是真实闭环反馈，也不是响应上界。 +- 原有 14,232 条 mask 边保持不变，只覆盖 12 个 MBON；这次审计仍保留全部 97 个 MBON 及其 86,039 条入边。 +- 29/29 模型合成测试通过；五组旧参考重新运行逐位一致；原 230,239 文件及完整性链 26 个根全部通过，无 mismatch。 -120 条主轨迹、24 次逐位重复完整通过；两个旧 D18 对照精确复现，四个预定 Brian probes 和六项 APL 组件审计通过。五组旧冻结参考的事件、计数和最终 V/g 逐位一致，所有旧登记文件校验通过，无 mismatch。 - -后六气味未参与 AG/AJ 校准，但旧 4L 曾模拟全十二气味；不声称它们历史从未被模拟。matched_energy 匹配预期输入，不是实际接受事件数完全相等。种子审计仅覆盖列出的静态来源，不证明所有历史或随机流的绝对独立性。 - -1.8 ms 仍是工程时序假设，不是 MaleCNS APL 实测延迟。Brian 独立 LIF/FIFO 仍共享冻结 APL 算术，不能称全组件独立证明。既有 5845 条 fast-APL 出边置零约定及其中 1212 条非 KC 边未替代的限制保持不变。 - -**表征验证通过不等于学习可用。** 没有更新权重、没有 learned candidate，也未替换正式 reference/runtime；所有旧 PASS/FAIL 原样保留。完整新轨迹仍只在服务器。 +Phase 4AK 的 D18 表征验证 PASS 原样保留。1.8 ms 是工程时序假设，不是实测 APL 延迟；matched_energy 匹配预期而非每次实际输入数；旧 1212 条非 KC fast-APL 出边未被 graded 路径替代的限制仍存在。 ## 下一步 -冻结当前成功分支，先验证气味特异的 eligibility/credit 分配与真实 KC→MBON 功能传递，再考虑带控制的 conditioning。不能仅凭 KC 稀疏、距离指标或 delta-weight 变化宣布记忆成功；不直接进入游戏、decoder、RL、视觉或 Web。 +本轮排除了“这些候选边在固定回放中完全无法影响 MBON”的解释，但未证明气味特异记忆。下一关需单独预注册 whole-brain plastic-overlay：零更新必须精确复现 D18，反馈真实闭环，信用按实际 KC/DAN 与 compartment 记录；然后才检验独立 evaluation seeds 和严格对照下的关联记忆、保持。 -下一关尚未执行，须先明确协议与停止条件。raw/base CSR/W_syn/sign、既有 APL 参数、eligibility-v2、14232-edge mask 与所有历史封存产物继续只读。 +继续冻结 raw/base CSR/W_syn/sign、既有 APL 参数、eligibility-v2、14,232-edge mask 和所有已封存产物。不调参挽救结果，不接游戏、视觉、decoder、RL 或 Web。 -新实验 payload 为 6,154,144,988 bytes（约 6.15 GB），已生成 SHA-256 与 manifest。Git 同步代码、小报告和校验，不是全量异机备份。 +本轮实验 payload 1,336,493,035 bytes（约 1.34 GB）。所有正式文件有 SHA-256/manifest；大型轨迹仍在服务器，Git/本地小证据同步不等于全量异机备份。 -[结果解释](docs/progress/phase4ak-interpretation.md) · [正式状态](registry/phase4ak-apl-timing-validation/evidence/audit/final-status.json) · [新种子验证](registry/phase4ak-apl-timing-validation/evidence/validation/seed_validation/summary.json) · [后六气味验证](registry/phase4ak-apl-timing-validation/evidence/validation/novel_to_aj/summary.json) · [封存校验](registry/phase4ak-apl-timing-validation/seal-verification.json) +[结果解释](docs/progress/phase4al-interpretation.md) · [正式状态](registry/phase4al-mb-credit-transfer/evidence/audit/final-status.json) · [60 组气味对](registry/phase4al-mb-credit-transfer/evidence/audit/pair-identities.json) · [封存校验](registry/phase4al-mb-credit-transfer/seal-verification.json) · [上一轮 D18 验证](docs/progress/phase4ak-interpretation.md) diff --git a/docs/progress/phase4al-interpretation.md b/docs/progress/phase4al-interpretation.md new file mode 100644 index 0000000..610ca68 --- /dev/null +++ b/docs/progress/phase4al-interpretation.md @@ -0,0 +1,74 @@ +# Phase 4AL — KC credit / MBON 条件性传递审计 + +日期：2026-09-30。上一提交：`c6444255fe90fe1bdd5b862e63265587c15df442`。 + +正式状态：`PASS-CONDITIONAL-CREDIT-TRANSFER-AUDIT-NOT-LEARNING`。 +这里的 PASS 指算术、身份和覆盖审计通过，不是学习通过。 + +## 实际完成 + +- 保留固定 D18，读取全部 120 条 AK 主轨迹和 24 条技术重复，不挑气味、种子或 compartment。 +- 全部 144 次 MBON 条件基线重构的事件、逐神经元计数、最终 V/g/ref 与封存 AK 逐位一致。 +- 对实际 KC 发放只读重放冻结 float32 eligibility-v2，在 tick 900 更新后采样，包含该 tick 发放；这是虚拟 gate，没有输入 DAN，没有写入 plastic_delta。 +- 全部基线通过后，才执行一次预定的全既有 mask 25% 减弱。只改临时权重副本；所有上游/反馈发放钳制，目标 MBON 的阈值、复位和 refractory 独立重算。 +- 24 次技术重复的基线、credit、分解和条件性结果全部精确一致；不把它们当成额外独立种子。 + +## 真实边范围 + +全图 166,700 neurons / 25,582,938 edges。4,064 KC、97 MBON；MBON 共 86,039 条入边，其中全部 KC→MBON 61,210 条。冻结候选 mask 为 14,232 条，目标只有 12 个 MBON。 + +| compartment 原始字符串 | 候选边 | MBON 目标 | +|---|---:|---:| +| `B2B'2a` | 4,346 | 2 | +| `a1` | 3,651 | 4 | +| `y2a'1` | 4,126 | 4 | +| `y5B'2a` | 2,109 | 2 | + +95 条 DAN→MBON 边具有已封存的显式 compartment 原文匹配。这是 annotation token 与实际边的依据，不是突触 ROI 的独立定位。其他身份没有凭名称补齐；120 条 fast-APL→MBON 入边仍依冻结分支约定置零，未在本轮修正。 + +## 结果与边界 + +| 分组 | 各自特有 KC/候选边的气味对 | 候选边 active-set Jaccard 均值 | 25% 条件性试验改变 count 或首次 latency | +|---|---:|---:|---:| +| seed_validation / physiological | 15/15 | 0.57575 | 30/30 | +| seed_validation / matched_energy | 15/15 | 0.61094 | 30/30 | +| novel_to_aj / physiological | 15/15 | 0.54014 | 30/30 | +| novel_to_aj / matched_energy | 15/15 | 0.57905 | 30/30 | + +分类使用各条件五种子中至少三次 trace>0。Jaccard 比较完整 A-active/B-active 集合，包含 shared，不再把互斥 specific 集合的零交集误当特异性证据。60 对均非空；共享成分仍明显。这里只验证每侧存在 specific KC/边，没有设新的整体学习成功阈值。 + +候选边占全部 97 个 MBON 的已接受正向名义输入增量，四组逐试验比例均值为 **1.075%–1.115%**。这个全 MBON 分母不能当作 12 个塑性目标的输入比例。 + +补充的封存后描述性复算：固定这 12 个既有候选目标，以每个 trial 的 `sum(accepted_plastic_positive_V)/sum(accepted_total_positive_V)` 求比例，再按组取平均，得到 **11.14%–11.46%**。12×120=1,440 个目标/试验单元中，964 个 count 或首次 latency 改变；其余 85 个 MBON 的这些指标没有改变。此复算只解释分母，不是新增或替代门槛，未改动封存报告。 + +该复算输入为 `experiments/phase4al-mb-credit-transfer/audit/per-MBON-primary.parquet`，SHA-256 `fd194e5af084527798b2a651bbc0b16eb772f208ccbf1aae5b1ef3e7520c7b30`。使用 `candidate_target == true` 的全部行，按 `cohort, mode, name` 分组；没有择优子集。 + +这些量是模型中已接受边增量或 source-state 的记账，不是能量、真实电导或 dopamine 浓度。分组 g 记账的最大舍入残差为 5.274e-16 SI V，未回写状态或归给某个神经元来源。 + +**可作出的判断：** 在这个固定条件回放中，14,232 边的改变能够影响 MBON 功能性发放；不能说 MBON 对它们完全无响应。 + +**尚不能作出的判断：** 25% 一致减弱不是气味特异训练得到的 delta，不是响应上界，且 MBON→DAN/MBON/其他反馈没有在反事实中闭环重算。因此不能声称关联记忆、行为学习或完整全脑 credit 已通过，也不能自动解锁 conditioning。 + +## 完整性与工程交付 + +- 29/29 服务器合成测试通过，包括冻结 NumPy AST / Torch CPU trace 的逐位比较；本地此前缺 Torch 的跳过项在服务器已执行。 +- 五组旧 deterministic-v2 参考重新运行，事件/count/final V/g 全部逐位一致。这不是宣称新 D18 与旧动力学等价。 +- 原有 230,239 个登记文件和完整性链共 26 个根全部通过；旧 frozen/reference 产物零差异。 +- 封存前重新核验所有输出清单/哈希，144 次基线与原始 AK、24 次重复、60 对身份和全部汇总绑定。 +- 模型 payload 14 文件 / 109,946 bytes；实验 payload 2,166 文件 / 1,336,493,035 bytes。 +- 发布/下载/Git blob 验证工具 51/51 合成测试通过（本地和服务器）。Git 和本地证据同步不含大型轨迹，**不是全量异机备份**。 +- 准备阶段仅遇到新实验目录创建权限，已在任何注册/科学计算前处理，并记录于模型 `PREPARATION.md`；旧目录权限未改变。 +- 原样保存的编译日志有两行行尾空格，导致 `git diff --check` 返回 2；不为排版修改封存字节。它不是数值回归失败；实际 Git blob 已逐个对照 SHA 校验。 +- 旧 `phase4c.py:308` 仍提示只读 NumPy 数组转 Torch 的警告；本轮没有改旧实现。五组输出仍逐位一致，旧文件校验无变化，警告原样保留。 + +模型 manifest SHA-256：`72e4b4e2c53c258939ca355f31eeba2cd6381e126a61efeea651d8bac8df5328`。 + +实验 manifest SHA-256：`a22de7d85cbfe760070ff55f5666e74475a3335c63bbd37b41241a94be7e3eea`。 + +## 下一关 + +先建立单独、预注册的 whole-brain plastic-overlay 验证：零更新必须逐位等同 D18；使用真实 compartment mapping 和固定 eligibility-v2；明确人工 reinforcement 接口，记录实际 KC/DAN 状态与每条边的信用。随后才在新分支评价独立种子的 CS+/CS− 前后 MBON/downstream 差异、完整反馈、零更新/未配对等控制与保持。不能由本轮条件性敏感性直接宣布学习可用。 + +保持 raw/base CSR/W_syn/sign、APL 设置、eligibility-v2、mask 和所有既有封存字节只读。没有游戏、视觉、decoder、RL 或 Web。 + +文献支持、工程假设和不适用边界见 [EVIDENCE.md](../../models/male-cns-lif/mb-credit-transfer-audit-v1/EVIDENCE.md)。正式结果见 [final-status](../../registry/phase4al-mb-credit-transfer/evidence/audit/final-status.json)。上一轮 D18 表征结果仍见 [Phase 4AK](phase4ak-interpretation.md)。 diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/EVIDENCE.md b/models/male-cns-lif/mb-credit-transfer-audit-v1/EVIDENCE.md new file mode 100644 index 0000000..eecd591 --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/EVIDENCE.md @@ -0,0 +1,201 @@ +# Phase 4AL — credit specificity and conditional KC→MBON transfer + +## Purpose and frozen boundary + +This is a diagnostic audit of the already sealed Phase 4AK D18 branch, not +conditioning, training, or a new learning candidate. Phase 4AK established its +predeclared 100 ms KC representation gate; it did not establish appropriate +credit assignment, functional associative memory, or biological fidelity of +every omitted mechanism. + +Use all 120 Phase 4AK primary trials and all 24 exact-repeat trials. Keep the +two cohorts and their two input modes separate. Repeats check reproducibility; +they are not extra independent observations in the five-seed statistics. Do +not replace seeds, select favorable odors, choose a best pair or compartment, +or inspect old held-out dynamic outcomes to change this design. +The inherited matched-energy mode matches expected input, not necessarily the +realized event count of every stochastic trial; do not relabel it exact +realized-count matching. + +All earlier raw, processed, frozen/reference, model and experiment artifacts +remain read-only. Preserve the base CSR, anatomical counts, transmitter signs, +LIF parameters, D18 operator, APL settings, eligibility-v2, and existing 14,232 +plastic-edge mask. All new records belong only to this new audit. No DAN +stimulus is injected; no reinforcement is delivered to a brain; no learned +`plastic_delta` is written. No decoder, action selection, game, RL, or visual +interface is introduced. + +## Three distinct evidence levels + +1. **Exact baseline reconstruction.** Reconstruct target MBONs from the actual + frozen full-network events using real edges, original arithmetic/order, + initial states, arrivals, refractory acceptance, resets, and applicable APL + handling. Require bitwise identity of events, per-neuron counts, and final + V/g/ref against Phase 4AK D18. A failed or incomplete reconstruction blocks + scientific interpretation of that replay; it is never rescued by plausible + plots or by agreement of aggregate firing rates. Complete-audit integrity + requires all 144 baseline replays; do not silently drop failed cases and + report the remaining subset as the complete predeclared audit. +2. **Virtual credit audit.** Replay the unchanged, existing float32 eligibility + operator and inspect its state at the fixed tick-900 virtual gate, after + that tick's original `mul → add → clamp` sequence. Tick-900 spikes are + included. This is shadow accounting only, not dopamine delivery or weight + updating; a before/after-update change is a different experiment. Do not + treat virtual gate amplitude as measured dopamine concentration. +3. **One fixed conditional sensitivity test.** Compare the exact baseline with + one temporary replay applying uniform 25% depression to the whole existing + plastic-edge mask. This uses the pre-existing maximum allowed fractional + depression as a single declared diagnostic intervention. It is not a + fraction scan, an eligibility-trained delta, a selected successful memory, + or permission to enlarge the mask. The base weights remain unchanged; only + the diagnostic effective amplitudes change, preserving edge identity and + transmitter sign. On an independent incoming-weight copy, apply + `weights[plastic] *= 0.75` throughout the full 100 ms replay, not only after + tick 900. All presynaptic spike trains, including those of other MBONs and + DANs, remain the original recorded trains. Do not save the overlay as a + learned or official model. + +The 25% intervention is **not an upper bound on functional response**. LIF +threshold, reset, refractory gating, and recurrent influences make responses +nonlinear; the largest permitted fractional depression does not establish the +largest attainable change in spikes, latency, or downstream activity. + +## Incoming-drive and overlap accounting + +Decompose actual MBON incoming drive into six mutually exclusive groups: + +- plastic KC→MBON; +- non-plastic KC→MBON; +- DAN; +- MBON; +- APL; +- other. + +Use the frozen canonical IDs, mask membership and audited metadata, not guessed +names or transmitter-to-cell-role substitutions. Preserve unknown role +provenance inside the residual `other` group. Establish each edge's group once; +do not reclassify it to improve the result. Report accepted/rejected arrivals, +signed contributions, and roundoff/reset effects as the implementation makes +available. The model's variable `g` is a model state; do not rename it a measured +biophysical conductance or dopamine signal. A source's share of accepted drive +is not its necessity, sufficiency, or unique causal contribution to a spike. +Any ratio with a zero/undefined denominator must remain explicitly undefined. +The sole set-similarity convention is empty/empty Jaccard = 1 with an explicit +`empty_union` flag. Such pairs are counted separately and excluded from block +overlap aggregates; this convention is never evidence of useful credit. + +For each cohort × mode, retain all 15 unordered pairs of its six odors: 60 +pair records in total. Report two separate three-of-five-seeds memberships for +each odor: (1) a strictly positive frozen eligibility trace sampled after the +tick-900 update, including tick-900 spikes, and (2) a strictly positive spike +count anywhere in the full 100 ms trial. The primary virtual-credit grouping +uses the first definition. The whole-window activity grouping is auxiliary; +it cannot replace the primary grouping to rescue a result. These are +descriptive reliability rules, not biological thresholds, top-K filters, or +ways to delete cells/edges from replay. Preserve per-trial activity and +eligibility alongside both aggregate memberships. + +Compute overlap on the actual A-active and B-active sets. In particular, +`Jaccard(A_active, B_active)` must use their real intersection and union; never +substitute the already disjoint sets `A_only` and `B_only`, whose zero +intersection is true by construction. Shared, A-only, B-only, and inactive +strata are useful descriptive partitions, not proof of stimulus-specific +causation. Shared representations can support biological generalization; +nonzero B effects are not automatically a defect, nor are they automatically +evidence of valid generalization. + +Keep arithmetic/integrity checks separate from scientific results. Report all +pairwise and trial-level outcomes without inventing an overall 120-trial +biological PASS fraction, post hoc effect threshold, or pooled rescue gate. +An absence of MBON spike change may coexist with a subthreshold change and +does not mean the entire biological pathway is incapable of plasticity. + +## What a conditional replay can and cannot establish + +The baseline can establish that the saved events and the frozen operator +reconstruct the saved MBON trajectory exactly. Virtual eligibility can reveal +which real candidate edges would receive credit under that declared rule. +The single depression replay can measure how the selected MBONs respond to +that fixed intervention **with the external network event history held fixed**. + +It cannot establish closed-loop whole-brain necessity/sufficiency or learned +behavior. If an MBON's replayed spikes change while its outgoing effects and +the other neurons' events remain clamped to the old trial, MBON→DAN, MBON→MBON, +and other feedback are not recomputed self-consistently. Their fixed incoming +traces must not be described as counterfactual feedback responses. If the +replay instead also clamps the target MBON's original reset/refractory gates, +its result is narrower still: conditional drive/state accounting, not an +independently recomputed functional spike response. State these scopes +explicitly for each reported quantity. + +The anatomical D18 arrival delay is 18 × 0.1 ms = 1.8 ms. It is not the +eligibility lifetime, a measured dopamine latency, or the CS–reinforcer +association window. A 100 ms observation does not test memory retention, +consolidation, extinction, reversal, or behavioral recall. Do not promote any +successful replay to a dopamine-plasticity or learning candidate. + +## Primary evidence and non-measured assumptions + +- **Hige et al., Neuron (2015), DOI 10.1016/j.neuron.2015.11.003.** Pairing an + odor with selected DAN activation produced odor-specific, compartment-local + KC→MBON depression with order dependence. The reported induction did not + require postsynaptic MBON spiking; overlapping KC representations predicted + reduced specificity/generalization. This supports auditing the correct + presynaptic and compartment credit, not requiring MBON spikes to define all + plasticity. It does not specify MaleCNS per-edge learning parameters. + [Author publication and paper](https://www.janelia.org/publication/heterosynaptic-plasticity-underlies-aversive-olfactory-learning-drosophila). +- **Handler et al., Cell (2019), DOI 10.1016/j.cell.2019.05.040.** DopR1/DopR2 + pathways support opposing plasticity associated with different cue–DAN + timing. This establishes why time ordering matters, not that the frozen + float32 trace is a measured biochemical state or that one rule applies to + every compartment. [Primary paper](https://www.sciencedirect.com/science/article/pii/S0092867419306117). +- **Aso and Rubin, eLife (2016), DOI 10.7554/eLife.16135.** DAN cell types differ + in memory formation, updating and persistence. PAM/PPL1 labels alone are + not a license to assign a universal valence or a common temporal rule. + [Primary paper](https://elifesciences.org/articles/16135). +- **Aso et al., eLife (2014), DOI 10.7554/eLife.04580.** Different MBON types + bias approach/avoidance, with combined activation supporting population + integration. Assessing a population response is more appropriate than + equating greater weight or total firing with positive memory. The current + audit nevertheless has no behavioral decoder or demonstrated behavior. + [Primary paper](https://elifesciences.org/articles/04580.pdf). +- **Huang et al., Nature (2024), DOI 10.1038/s41586-024-07819-w.** Physiological + measurements and a constrained model show heterogeneous, bidirectional + PPL1 signaling and feedback interactions among memory units. This motivates + explicit closed-loop limitations. Its fitted model weights and plasticity + parameters are not MaleCNS anatomical counts or measurements to import into + this frozen branch. [Primary paper](https://www.nature.com/articles/s41586-024-07819-w). +- **Manoim et al., Current Biology (2022), DOI 10.1016/j.cub.2022.09.007, and + Manoim Wolkovitz et al. (2026), DOI 10.1016/j.cub.2026.01.014.** KC lateral + axonal mAChR-B modulation contributes to stimulus specificity; subsequent + work identifies voltage-dependent modulation relevant to active versus + inactive KCs. Sparse coding plus a timed reinforcer is therefore not, by + itself, proof of appropriate credit. These studies do not prove that an + omitted receptor mechanism caused any result in this fixed model, and do + not authorize a sign, gain, threshold, or receptor-parameter change. + [2022 paper](https://www.sciencedirect.com/science/article/pii/S0960982222014518); + [2026 paper](https://www.sciencedirect.com/science/article/pii/S096098222600014X). + +The frozen eligibility operator, tick-900 virtual gate, three-of-five activity +summary, 25% uniform diagnostic depression, clamped event history, and chosen +observation window are engineering/model assumptions. None is relabelled as a +MaleCNS single-cell or synaptic measurement by citing the papers above. + +## Deferred functional-memory controls — not executed here + +A later explicitly authorized learning experiment would need pre/post CS+ +and CS− responses, reciprocal cue assignment, independent evaluation seeds, +and reinforcement-free probes with updates disabled. CS-only, DAN-only, +unpaired/yoked, D(t)=0, and frozen/delta=0 conditions distinguish associative +effects from exposure, transient state, adaptation and unrelated modulation. +Real DAN-only stimulation is not universally expected to have zero effect; +that prediction depends on the declared model and compartment. Retention +requires its own observation interval, and any model-specific output effect +must remain distinct from a behavioral-memory claim. No such controls are +silently replaced by virtual credit or the 25% sensitivity test. + +Google/DeepMind's [FlyBody work](https://www.nature.com/articles/s41586-025-09029-4) +provides body physics and artificial RL controllers, not evidence for this +KC→MBON credit rule. Google's [MaleCNS author resource](https://research.google/blog/a-connectomics-milestone-mapping-the-complete-male-fruit-fly-brain/) +supports the anatomical resource, not measured dopamine kinetics or successful +learning in this model. Neither permits bypassing the present mechanism audit. diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/PREPARATION.md b/models/male-cns-lif/mb-credit-transfer-audit-v1/PREPARATION.md new file mode 100644 index 0000000..fac7503 --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/PREPARATION.md @@ -0,0 +1,13 @@ +# Preparation record + +The first preparation invocation stopped before experiment creation or +registration: the ordinary account could not create a child of the protected +experiments directory. No trajectory, credit calculation or conditional replay +was executed. The fix provisions only the new, empty Phase 4AL directory with +the ordinary account as owner; preparation permits an absent or empty directory +but still refuses any populated experiment. No old directory permission is +changed. This is an execution-environment correction, not a scientific change. + +Local synthetic tests initially had no Torch installation and explicitly +skipped the Torch arithmetic comparison. Server testing includes this comparison +and preparation rejects skipped tests. diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/checksums.sha256 b/models/male-cns-lif/mb-credit-transfer-audit-v1/checksums.sha256 new file mode 100644 index 0000000..b89abb1 --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/checksums.sha256 @@ -0,0 +1,15 @@ +cda2d810eada83ea33c96c1ce9d16102d1af22d1862bce84c47f0e7415863eca EVIDENCE.md +8259428a56721ba8174039846623998ef11a1d8e9e14f123dfe0a0e4849c71ee PREPARATION.md +b996e175731a920ad19e2c8989bd267cdbb71c14aa4558a8f1ef7486454c4b44 config.json +1626873baa224fab5d427a1fab1d6f840f14814152914ac4c2d6aa7a4f0bb1f6 context.py +e03d3e1f64328058273e8364990e7a2c7f1527a31822ea7594a9e8914aa43497 credit.py +9356587aa8811a3db50daee9bca22cf4114e06c6669cc80c69cd0dd2224b0130 finalize.py +825e9e60cb579479ddb2860a36f8dee0715b9b44d624cbad59ce0d279550d17f mbon_accounting.py +9e7532bc4a564b0a0c0384ba2f3a7bfc0559c16bb256510dde7c97cce9036c0c prepare.py +3ece589f0f6ce1bff2cde94494e896a58fa4154106e613ee7e60549094304071 run_audit.py +62432fe7b068eafae99396c4a9231adf8ef8e9d340ab64517f618fc794e7fd78 summarize.py +4c473ce709ed9496b7ce1b5bedd6964c780715ff41dd54977489fbd2b99f998e test_credit.py +23c4e9138b326e1a84fed88d771a6c2044a6abf72ecc7a1b829f604bcdde215d test_integration.py +d192dd357db96e628c21b9bcde617eaf6c6bc1efe5920ec55cc9cc1e4b549454 test_mbon_accounting.py +85442fcefa93c64a2fac7f0a4b60ce505ddb9edab7a63cb0e25cb20f013d3850 verify_frozen.py +72e4b4e2c53c258939ca355f31eeba2cd6381e126a61efeea651d8bac8df5328 manifest.json diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/config.json b/models/male-cns-lif/mb-credit-transfer-audit-v1/config.json new file mode 100644 index 0000000..a91df82 --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/config.json @@ -0,0 +1,24 @@ +{ + "phase": "4AL", + "purpose": "read-only D18 credit and conditional MBON transfer audit; not learning", + "neurons": 166700, + "edges": 25582938, + "candidate_edges": 14232, + "primary_trials": 120, + "technical_repeats": 24, + "steps": 1000, + "dt_ms": 0.1, + "virtual_gate_tick": 900, + "kc_trace_tau_ms": 100.0, + "trace_cap": 1.0, + "stable_seed_count": 3, + "conditional_depression_fraction": 0.25, + "groups": ["plastic_KC", "nonplastic_KC", "DAN", "MBON", "APL", "other"], + "workers": 4, + "output_budget_bytes": 4294967296, + "training": false, + "candidate_generation": false, + "gate_meaning": "Post-update tick 900 virtual assay, not a DAN or dopamine measurement", + "conditional_meaning": "Recorded all-source events clamped, target MBON spikes independently predicted; not whole-brain counterfactual", + "no_new_overall_credit_threshold": true +} diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/context.py b/models/male-cns-lif/mb-credit-transfer-audit-v1/context.py new file mode 100644 index 0000000..109529d --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/context.py @@ -0,0 +1,116 @@ +"""New read-only audit envelope. All old payloads are hash-anchored inputs.""" +import hashlib +import importlib.util +import json +import sys +from pathlib import Path + +sys.dont_write_bytecode = True +ROOT = Path('/data/digital-drosophila') +MODEL = Path(__file__).resolve().parent +EXP = ROOT / 'experiments/phase4al-mb-credit-transfer' +AK = ROOT / 'experiments/phase4ak-apl-timing-validation' +AK_MODEL = ROOT / 'models/male-cns-lif/apl-timing-validation-v1' +H = ROOT / 'experiments/phase4h-dopamine-plasticity' +AG = ROOT / 'experiments/phase4ag-author-apl-r2' +CORE = ROOT / 'models/male-cns-lif/kc-drive-audit-v1/replay_core.py' +META = ROOT / 'datasets/male-cns-v1.0/processed/neuron-only/neuron-index/unified-metadata.parquet' +COEFF = ROOT / 'experiments/phase4af-author-fullgraph/oracle/no_input/coefficients.json' +CFG = json.loads((MODEL / 'config.json').read_text(encoding='utf-8')) +PINS = { + 'models/male-cns-lif/runtime-credit-v1/phase4o_event_replay.py': 'b169937bab495c77d8ee6c1013877e7500e7354140d9fcc90595d984238ba44e', + 'models/male-cns-lif/phase4l.py': 'e97d58d8c1f44920d0e953f8f5831ddc86fa0198784e86460e315de4116ac553', + 'models/male-cns-lif/apl-timing-validation-v1/manifest.json': '3206a8666718b4a99e09b8384c87dd25895b5d7038d23fad7b93e40379183ccb', + 'experiments/phase4ak-apl-timing-validation/manifest.json': '25eb7e467eb17c3fa83ffee2e4e82b754f161fd8891e515bed23eeb500c5656d', + 'models/male-cns-lif/apl-timing-validation-v1/context.py': '5e4e500d5ec777bb8ae7ff77ac9a7279bfe995b1a17be2baededdbe065c98b73', + 'experiments/phase4ak-apl-timing-validation/protocol/validation-cases.json': '50d7b3aa7b0235e8f7bc1e21ef693cd5c554272ef3bd205c72f61e8e07ad1fd9', + 'experiments/phase4ak-apl-timing-validation/audit/final-status.json': 'c49181086ecbd19511b9f1e783afea8f66d0f74348a7b70d7f6c5fa99b4337fc', + 'models/male-cns-lif/kc-drive-audit-v1/replay_core.py': 'aa3187cb23712c09ab603e27e60424294db92de8086d60a95cf7a629d0521fdc', + 'models/male-cns-lif/mb-physiology-v1/phase4j.py': 'abb4574da85f00bd9ef61024c65993ef81d42651ff8d8d63c15dd69c6222471e', + 'models/male-cns-lif/mb-physiology-v1/phase4j.yaml': 'b35e4332a91b8489f69348cedf5ac675e9c3902c7e8c7beec5d053773c6529a3', + 'experiments/phase4h-dopamine-plasticity/manifests/checksums.sha256': '1ea0394fd0477bb40d656ed0854108964f3809d633b5561bed9de43cda630ba1', + 'datasets/male-cns-v1.0/processed/neuron-only/neuron-index/unified-metadata.parquet': '922af16846a065c3dbfca7c11146b83ca217fcbd7392edc745f444a04eae8c63' +} + + +def digest(path): + h = hashlib.sha256() + with Path(path).open('rb') as f: + for block in iter(lambda: f.read(8 << 20), b''): + h.update(block) + return h.hexdigest() + + +def read(path): + return json.loads(Path(path).read_text(encoding='utf-8')) + + +def save(path, value): + path = Path(path) + path.parent.mkdir(parents=True, exist_ok=True) + with path.open('x', encoding='utf-8') as f: + json.dump(value, f, indent=2, ensure_ascii=False, allow_nan=False) + f.write('\n') + + +def write_npz(path, **values): + import numpy as np + with Path(path).open('xb') as f: + np.savez_compressed(f, **values) + + +def load_module(name, path, expected_hash): + data = Path(path).read_bytes() + assert hashlib.sha256(data).hexdigest() == expected_hash, str(path) + spec = importlib.util.spec_from_file_location(name, path) + module = importlib.util.module_from_spec(spec) + sys.modules[name] = module + exec(compile(data, str(path), 'exec'), module.__dict__) + return module + + +def sources(): + return {p.relative_to(MODEL).as_posix(): digest(p) for p in sorted(MODEL.rglob('*')) + if p.is_file() and '__pycache__' not in p.parts and p.name not in ('manifest.json', 'checksums.sha256')} + + +def integrity(): + previous = load_module('sealed_ak_context_al', AK_MODEL / 'context.py', + PINS['models/male-cns-lif/apl-timing-validation-v1/context.py']) + result = previous.integrity() + sys.path.insert(0, str(ROOT / 'models/male-cns-lif/terminal-scope-diagnostic-v1')) + from diagnostic import manifest_check + for path in (AK_MODEL, AK): + result[path.relative_to(ROOT).as_posix()] = manifest_check(path, digest) + assert all(row['pass'] for row in result.values()) + return result + + +def check(): + reg = read(EXP / 'protocol/preregistered.json') + assert reg['sources'] == sources() and reg['config'] == CFG + for row in reg['inputs']: + assert digest(ROOT / row['path']) == row['sha256'], row['path'] + for row in read(EXP / 'protocol/prepared-hashes.json'): + assert digest(EXP / row['path']) == row['sha256'], row['path'] + return reg + + +def bit_equal(a, b): + return a.dtype == b.dtype and a.shape == b.shape and a.tobytes() == b.tobytes() + + +def budget(): + size = sum(p.stat().st_size for p in EXP.rglob('*') if p.is_file()) + assert size < CFG['output_budget_bytes'], 'Audit output budget exceeded; stop, preserve partials' + return size + + +def seal(root): + rows = [dict(path=p.relative_to(root).as_posix(), bytes=p.stat().st_size, sha256=digest(p)) + for p in sorted(root.rglob('*')) if p.is_file() and '__pycache__' not in p.parts] + save(root / 'manifest.json', dict(root=str(root), files=rows)) + with (root / 'checksums.sha256').open('x', encoding='utf-8') as f: + for row in rows: + f.write(row['sha256'] + ' ' + row['path'] + '\n') + f.write(digest(root / 'manifest.json') + ' manifest.json\n') diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/credit.py b/models/male-cns-lif/mb-credit-transfer-audit-v1/credit.py new file mode 100644 index 0000000..e37d1af --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/credit.py @@ -0,0 +1,171 @@ +"""Read-only, float32 TemporalEligibility-v2 trace and fixed A/B identities. + +This module consumes already observed full-graph spike events. It neither +simulates neurons nor generates a weight delta. A gate is a virtual readout +after the same-tick KC trace update, not evidence of an actual DAN event. +""" +from __future__ import annotations + +import math + +import numpy as np + + +N_GLOBAL = 166700 +CATEGORY_CODES = {'inactive': 0, 'A_specific': 1, 'B_specific': 2, 'shared': 3} +MAJORITY = 3 +REPLICATES = 5 + + +def _require(condition, message): + if not condition: + raise ValueError(message) + + +def _vector(value, name, dtype): + _require(isinstance(value, np.ndarray) and value.ndim == 1 and value.dtype == np.dtype(dtype), + name + ' must be a one-dimensional ' + dtype + ' ndarray; no implicit dtype conversion') + return value + + +def _frozen_scalar(value, expected, name): + _require(not isinstance(value, (bool, np.bool_)) and isinstance(value, (int, float, np.number)) and + np.ndim(value) == 0 and math.isfinite(float(value)) and float(value) == expected, + name + ' must retain its frozen value ' + str(expected)) + + +def replay_credit(step, neuron_idx, kc_globals, steps=1000, gate_tick=900, + dt_ms=.1, tau_ms=100, cap=1): + """Replay the frozen trace without touching the caller's arrays. + + ``step`` and ``neuron_idx`` are equal-length int32 vectors for the complete + observed graph (or its KC-only subset), ordered uniquely by (tick, global + neuron). Non-KC events are validated then ignored. ``kc_globals`` is sorted + unique int32. The trace starts at +0 and, on every tick including tick zero, + performs separate float32 multiply, add current spikes, then clamp to 1. + + No 18-tick shift is applied: the recorded KC emission tick is the trace + event tick. Gate counts include gate_tick; final counts cover [0, steps). + dt/tau/cap are exposed for explicit provenance but may not be changed. + Shorter steps/gates are allowed for synthetic contract tests. + + Returns owned trace_gate/trace_final float32[K] and + spike_count_gate/spike_count_total int32[K], plus scalar audit metadata. + Memory is O(events + KC + global-neuron count), never a dense T-by-K trace. + """ + ticks = _vector(step, 'step', 'int32') + nodes = _vector(neuron_idx, 'neuron_idx', 'int32') + kc = _vector(kc_globals, 'kc_globals', 'int32') + _require(type(steps) is int and 0 < steps <= np.iinfo(np.int32).max, 'steps must be a positive int32-range integer') + _require(type(gate_tick) is int and 0 <= gate_tick < steps, 'gate_tick must lie in [0, steps)') + _frozen_scalar(dt_ms, .1, 'dt_ms') + _frozen_scalar(tau_ms, 100., 'tau_ms') + _frozen_scalar(cap, 1., 'cap') + _require(ticks.shape == nodes.shape, 'Event vectors have different lengths') + _require(np.all((ticks >= 0) & (ticks < steps)), 'Event tick outside the observed window') + _require(np.all((nodes >= 0) & (nodes < N_GLOBAL)), 'Event neuron outside the frozen global graph') + _require(len(ticks) < 2 or np.all((ticks[1:] > ticks[:-1]) | + ((ticks[1:] == ticks[:-1]) & (nodes[1:] > nodes[:-1]))), + 'Events must be sorted and unique by (tick, global neuron); duplicates are not extra spikes') + _require(len(kc) > 0 and kc[0] >= 0 and kc[-1] < N_GLOBAL and np.all(kc[1:] > kc[:-1]), + 'kc_globals must be nonempty, sorted, unique, in-range global identities') + + lookup = np.full(N_GLOBAL, -1, np.int32) + lookup[kc] = np.arange(len(kc), dtype=np.int32) + local = lookup[nodes] + selected = local >= 0 + kc_ticks, kc_local = ticks[selected], local[selected] + counts_total = np.bincount(kc_local, minlength=len(kc)).astype(np.int32) + counts_gate = np.bincount(kc_local[kc_ticks <= gate_tick], minlength=len(kc)).astype(np.int32) + decay = np.float32(math.exp(-float(dt_ms) / float(tau_ms))) + trace = np.zeros(len(kc), np.float32) + trace_gate = None + begin = 0 + for tick in range(steps): + # Preserve the source's separate rounding operations; do not substitute + # float64 exponentiation by elapsed time or shift spikes to arrivals. + np.multiply(trace, decay, out=trace) + end = int(np.searchsorted(kc_ticks, tick, side='right')) + if end > begin: + firing = kc_local[begin:end] + trace[firing] = np.add(trace[firing], np.float32(1.0)) + np.minimum(trace, np.float32(1.0), out=trace) + if tick == gate_tick: + trace_gate = trace.copy() + begin = end + _require(begin == len(kc_ticks) and trace_gate is not None and np.isfinite(trace).all(), 'Incomplete or nonfinite trace replay') + return { + 'trace_gate': trace_gate, 'trace_final': trace.copy(), + 'spike_count_gate': counts_gate, 'spike_count_total': counts_total, + 'steps': steps, 'gate_tick': gate_tick, 'dt_ms': float(dt_ms), 'tau_ms': float(tau_ms), 'cap': float(cap), + 'decay_f32_bits': f'{int(decay.view(np.uint32)):08x}', + 'total_input_events': int(len(ticks)), 'total_KC_events': int(len(kc_ticks)), + 'KC_events_through_gate': int(counts_gate.sum(dtype=np.int64)), + 'gate_includes_same_tick_spikes': True, 'event_shift_steps': 0, + 'gate_is_virtual_readout_not_DAN_activity': True, + 'weights_modified': False, 'weight_delta_generated': False, + } + + +def _traces(value, name): + _require(isinstance(value, np.ndarray) and value.ndim == 2 and value.dtype == np.dtype('float32') and + value.shape[0] == REPLICATES and value.shape[1] > 0, + name + ' must have exact shape (5, KC) and float32 dtype') + _require(np.isfinite(value).all() and np.all((value >= 0) & (value <= 1)), + name + ' must contain finite frozen-cap traces in [0, 1]') + return value + + +def _set_summary(active_a, active_b, category): + intersection = int(np.count_nonzero(active_a & active_b)) + union = int(np.count_nonzero(active_a | active_b)) + return { + 'total': int(len(category)), 'A_active': int(np.count_nonzero(active_a)), + 'B_active': int(np.count_nonzero(active_b)), 'intersection': intersection, 'union': union, + 'active_set_jaccard': float(intersection / union) if union else 1.0, + 'empty_union': union == 0, + 'category_counts': {name: int(np.count_nonzero(category == code)) for name, code in CATEGORY_CODES.items()}, + } + + +def pair_identity(traces_a, traces_b, edge_source_local): + """Classify fixed paired five-seed A/B traces, without installing plasticity. + + A KC is A-active/B-active if its gate trace is strictly positive in at + least 3 of 5 corresponding trials. Categories are int8: inactive=0, + A_specific=1, B_specific=2, shared=3. Every candidate edge inherits its + source KC's category in the supplied edge order. Multiple edges sharing + a KC are retained as separate rows, not independent neural observations. + + ``edge_source_local`` is int32[E] indexing the common KC axis of both + trace matrices. The caller must bind that axis and the five paired seed + rows to the frozen identities; this pure function cannot infer labels. + Jaccard uses COMPLETE active A/B sets, not the disjoint specific sets. + Empty/empty Jaccard is 1 with empty_union=True, never evidence of useful + credit. Compartment stratification and any success gate belong to caller. + """ + a, b = _traces(traces_a, 'traces_a'), _traces(traces_b, 'traces_b') + _require(a.shape == b.shape, 'A and B trace matrices use different KC axes') + source = _vector(edge_source_local, 'edge_source_local', 'int32') + _require(np.all((source >= 0) & (source < a.shape[1])), 'Candidate edge source is not a valid KC-local index') + positive_a = np.count_nonzero(a > np.float32(0), axis=0).astype(np.int32) + positive_b = np.count_nonzero(b > np.float32(0), axis=0).astype(np.int32) + active_a, active_b = positive_a >= MAJORITY, positive_b >= MAJORITY + category = active_a.astype(np.int8) + np.int8(2) * active_b.astype(np.int8) + edge_a, edge_b, edge_category = active_a[source].copy(), active_b[source].copy(), category[source].copy() + return { + 'kc_category': category, 'edge_category': edge_category, + 'kc_active_a': active_a, 'kc_active_b': active_b, + 'edge_active_a': edge_a, 'edge_active_b': edge_b, + 'kc_positive_trials_a': positive_a, 'kc_positive_trials_b': positive_b, + 'summary': { + 'replicates_per_condition': REPLICATES, 'majority_required': MAJORITY, + 'positivity_rule': 'float32 trace > 0; no fitted epsilon', 'category_codes': dict(CATEGORY_CODES), + 'KC': _set_summary(active_a, active_b, category), + 'edges': _set_summary(edge_a, edge_b, edge_category), + 'jaccard_scope': 'complete majority-active A and B sets, including shared members', + 'empty_union_jaccard_convention': 1.0, + 'edge_counts_are_source_degree_weighted': True, + 'actual_DAN_credit_claimed': False, 'weights_modified': False, 'weight_delta_generated': False, + }, + } diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/finalize.py b/models/male-cns-lif/mb-credit-transfer-audit-v1/finalize.py new file mode 100644 index 0000000..97a5caf --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/finalize.py @@ -0,0 +1,37 @@ +"""Seal all evidence without mistaking diagnostic coverage for learning.""" +from context import MODEL, EXP, read, save, digest, check, integrity, budget, seal + + +def main(): + check() + from summarize import run + summary = run(verify_only=True) + assert summary['arithmetic_and_coverage_pass'] and summary['primary_trials'] == 120 and summary['exact_repeats'] == 24 + refs = read(EXP / 'regression/frozen-five.json') + assert refs['pass_all'] and len(refs['trials']) == 5 and all(all(r['exact'].values()) for r in refs['trials']) + old = integrity() + save(EXP / 'regression/old-integrity-after.json', old) + status = 'PASS-CONDITIONAL-CREDIT-TRANSFER-AUDIT-NOT-LEARNING' + result = dict(status=status, **summary, old_integrity_pass=all(r['pass'] for r in old.values()), + frozen_five_reference_pass=refs['pass_all'], payload_bytes_before_manifest=budget(), + frozen_eligibility_and_mask_unchanged=True, base_weights_unchanged=True, + scientific_summary_sha256=digest(EXP / 'audit/scientific-summary.json'), + summary_all_144_baseline_raw_states_and_repeat_pair_metrics_reverified=True, + next_required_gate='Only if the diagnostic evidence supports it, separately preregister compartment-specific reinforcement and independent whole-brain evaluation; no automatic conditioning unlock') + save(EXP / 'audit/final-status.json', result) + with (EXP / 'REPORT.md').open('x', encoding='utf-8') as f: + f.write('# Phase 4AL — conditional credit/MBON transfer audit\n\nStatus: `' + status + '`.\n\n') + f.write('All 120 primary trials and 24 repeats are retained. Full events/counts/final V/g/ref baseline exactness is required.\n') + f.write('Virtual eligibility is sampled after tick 900; no DAN is injected, no delta is learned.\n') + f.write('Uniform 25% mask depression is a temporary conditional replay; every source train, including feedback, is clamped.\n') + f.write('All 60 odor pair-mode records and all 97 MBON targets are reported; no best pair/parameter selection.\n\n') + for name, block in summary['blocks'].items(): + f.write(f"- {name}: specific KC/edge sets {block['pairs_with_both_specific_KC_and_edge_sets']}/15; conditional event change {block['conditional25_event_changed_trials']}/30; count/first-latency change {block['conditional25_count_or_first_latency_changed_trials']}/30.\n") + f.write('\nNo biological learning PASS or candidate. This does not complete the learning goal.\n') + f.write('Read EVIDENCE.md in the model for provenance, unmatched biology and conditional/closed-loop distinctions.\n') + check(); seal(MODEL); seal(EXP) + print(status, flush=True) + + +if __name__ == '__main__': + main() diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/manifest.json b/models/male-cns-lif/mb-credit-transfer-audit-v1/manifest.json new file mode 100644 index 0000000..8eefe75 --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/manifest.json @@ -0,0 +1,75 @@ +{ + "root": "/data/digital-drosophila/models/male-cns-lif/mb-credit-transfer-audit-v1", + "files": [ + { + "path": "EVIDENCE.md", + "bytes": 12770, + "sha256": "cda2d810eada83ea33c96c1ce9d16102d1af22d1862bce84c47f0e7415863eca" + }, + { + "path": "PREPARATION.md", + "bytes": 755, + "sha256": "8259428a56721ba8174039846623998ef11a1d8e9e14f123dfe0a0e4849c71ee" + }, + { + "path": "config.json", + "bytes": 864, + "sha256": "b996e175731a920ad19e2c8989bd267cdbb71c14aa4558a8f1ef7486454c4b44" + }, + { + "path": "context.py", + "bytes": 5478, + "sha256": "1626873baa224fab5d427a1fab1d6f840f14814152914ac4c2d6aa7a4f0bb1f6" + }, + { + "path": "credit.py", + "bytes": 9109, + "sha256": "e03d3e1f64328058273e8364990e7a2c7f1527a31822ea7594a9e8914aa43497" + }, + { + "path": "finalize.py", + "bytes": 2743, + "sha256": "9356587aa8811a3db50daee9bca22cf4114e06c6669cc80c69cd0dd2224b0130" + }, + { + "path": "mbon_accounting.py", + "bytes": 18376, + "sha256": "825e9e60cb579479ddb2860a36f8dee0715b9b44d624cbad59ce0d279550d17f" + }, + { + "path": "prepare.py", + "bytes": 9844, + "sha256": "9e7532bc4a564b0a0c0384ba2f3a7bfc0559c16bb256510dde7c97cce9036c0c" + }, + { + "path": "run_audit.py", + "bytes": 9755, + "sha256": "3ece589f0f6ce1bff2cde94494e896a58fa4154106e613ee7e60549094304071" + }, + { + "path": "summarize.py", + "bytes": 12067, + "sha256": "62432fe7b068eafae99396c4a9231adf8ef8e9d340ab64517f618fc794e7fd78" + }, + { + "path": "test_credit.py", + "bytes": 12924, + "sha256": "4c473ce709ed9496b7ce1b5bedd6964c780715ff41dd54977489fbd2b99f998e" + }, + { + "path": "test_integration.py", + "bytes": 3016, + "sha256": "23c4e9138b326e1a84fed88d771a6c2044a6abf72ecc7a1b829f604bcdde215d" + }, + { + "path": "test_mbon_accounting.py", + "bytes": 9241, + "sha256": "d192dd357db96e628c21b9bcde617eaf6c6bc1efe5920ec55cc9cc1e4b549454" + }, + { + "path": "verify_frozen.py", + "bytes": 3004, + "sha256": "85442fcefa93c64a2fac7f0a4b60ce505ddb9edab7a63cb0e25cb20f013d3850" + } + ] +} diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/mbon_accounting.py b/models/male-cns-lif/mb-credit-transfer-audit-v1/mbon_accounting.py new file mode 100644 index 0000000..e2a6718 --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/mbon_accounting.py @@ -0,0 +1,267 @@ +"""Read-only CPU accounting for the sealed AH replay callback. + +Source/sign lanes are conditional, non-feedback bookkeeping, not additional +neurons, conductances, energies, or a whole-brain causal intervention. The +caller supplies anatomical groups and must independently verify the original +events/state and due/pending coverage. No files, Torch, or simulation entry +points are used here. +""" +from collections.abc import Mapping +import json + +import numpy as np + + +DT_MS = .1 +COEFF_KEYS = ("gd", "c0", "cg", "cv", "threshold", "reset", "seed_volt") +FLOAT_KEYS = ("old_v", "old_g", "v_integrated", "g_decayed", "v_threshold", + "v_after_reset", "g_after_reset", "v_pre_apl", "g_pre_apl", "delta_si", "v", "g") +INT_KEYS = ("ref_before", "ref_after_reset", "ref_pre_apl", "ref") +BOOL_KEYS = ("available", "request", "request_accepted", "request_rejected", "fired") + + +def require(value, message): + if not value: + raise ValueError(message) + + +def bit_equal(a, b): + return (a.dtype == b.dtype and a.shape == b.shape and + np.array_equal(np.ascontiguousarray(a).view(np.uint8), np.ascontiguousarray(b).view(np.uint8))) + + +class MBONAccounting: + """callback(tick, stage); finish() -> (per_target, per_edge, JSON summary). + + Group arrays have shape (N,G), sign lanes (N,G,2), with sign order positive, + negative. Negative increments/integrals retain their negative sign. + Histories use (T,N), or (T,N,G,2) for history_group_g. Target indices are + incoming.dst_local, not global IDs; the caller joins the verified target + list. Float64 lanes retain their own canonical additions; summing lanes + is not the runtime's interleaved accumulation, so residuals are reported + without correcting them or assigning them to an anatomical source. + """ + + def __init__(self, incoming, groups, group_names, coeff, steps): + require(isinstance(steps, (int, np.integer)) and not isinstance(steps, (bool, np.bool_)) + and 0 < steps <= np.iinfo(np.int32).max, "steps must be a positive int32-range integer") + require(isinstance(group_names, tuple) and group_names and + all(isinstance(x, str) and x for x in group_names) and len(set(group_names)) == len(group_names), + "group_names must be a nonempty tuple of unique names") + require(isinstance(coeff, Mapping), "coeff must be a mapping") + self.coeff = {} + for key in COEFF_KEYS: + value = coeff.get(key) + require(not isinstance(value, (bool, np.bool_)) and + isinstance(value, (int, float, np.integer, np.float64)) and np.isfinite(value), + "Missing/non-double/nonfinite coefficient: " + key) + self.coeff[key] = np.float64(value) + require(self.coeff["seed_volt"] > self.coeff["threshold"], "seed_volt must exceed threshold") + require("dt_ms" not in coeff or coeff["dt_ms"] == DT_MS, "AH time step is fixed at .1 ms") + require(isinstance(incoming.target_count, (int, np.integer)) and 0 < incoming.target_count <= 166700, + "Invalid incoming target count") + self.n, self.steps, self.names = int(incoming.target_count), int(steps), group_names + self.e = len(incoming.edge_id) + for name, dtype in (("src_global", "int32"), ("dst_local", "int32"), + ("edge_id", "int64"), ("weights", "float64")): + value = np.asarray(getattr(incoming, name)) + require(value.dtype == np.dtype(dtype) and value.shape == (self.e,), "Invalid incoming " + name) + setattr(self, name, value.copy()) + require(np.all((self.src_global >= 0) & (self.src_global < 166700)) and + np.all(self.src_global[1:] >= self.src_global[:-1]), "Noncanonical incoming sources") + require(np.all(self.edge_id >= 0) and np.all(self.edge_id[1:] > self.edge_id[:-1]), "Noncanonical edge IDs") + require(np.all((self.dst_local >= 0) & (self.dst_local < self.n)) and + np.isfinite(self.weights).all(), "Invalid incoming destination/weight") + codes = np.asarray(groups) + require(codes.dtype == np.int32 and codes.shape == (self.e,) and + np.all((codes >= 0) & (codes < len(self.names))), "groups must be int32 per incoming row") + self.groups = codes.copy() + self.ticks, self.finished, self.previous = 0, False, None + shape = (self.n, len(self.names)) + self.counts = {key: np.zeros(shape, np.int64) for key in + ("due_count", "accepted_count", "rejected_count", "accepted_zero_count", "rejected_zero_count")} + self.increments = {key: np.zeros(shape, np.float64) for key in + ("accepted_positive_V", "accepted_negative_V", "rejected_positive_V", "rejected_negative_V")} + self.edge_due = np.zeros(self.e, np.int64) + self.edge_accepted = np.zeros(self.e, np.int64) + self.spike_count = np.zeros(self.n, np.int32) + self.first = np.full(self.n, -1, np.int32) + self.requests = {key: np.zeros(self.n, np.int64) for key in + ("request_count", "request_accepted_count", "request_rejected_count")} + self.sg = np.zeros(shape + (2,), np.float64) + self.sv = np.zeros_like(self.sg) + self.bg = np.zeros(self.n, np.float64) + self.bv = np.zeros(self.n, np.float64) + self.integral_g = np.zeros_like(self.sg) + self.integral_v = np.zeros_like(self.sg) + self.max_g_residual = np.zeros(self.n, np.float64) + self.max_v_residual = np.zeros(self.n, np.float64) + self.history_v = np.empty((self.steps, self.n), np.float64) + self.history_g = np.empty_like(self.history_v) + self.history_ref = np.empty((self.steps, self.n), np.int32) + self.history_group_g = np.empty((self.steps,) + self.sg.shape, np.float64) + self.history_baseline_g = np.empty_like(self.history_v) + self.history_g_residual = np.empty_like(self.history_v) + + def _validate(self, tick, s): + require(not self.finished and isinstance(tick, (int, np.integer)) and + not isinstance(tick, (bool, np.bool_)) and tick == self.ticks and tick < self.steps, + "Missing, duplicate or out-of-order callback") + require(isinstance(s, Mapping), "stage must be a mapping") + for keys, dtype in ((FLOAT_KEYS, np.float64), (INT_KEYS, np.int32), (BOOL_KEYS, np.bool_)): + for key in keys: + value = s.get(key) + require(isinstance(value, np.ndarray) and value.shape == (self.n,) and value.dtype == dtype + and np.isfinite(value).all(), "Missing/invalid stage field: " + key) + h = s.get("h32") + require(isinstance(h, np.ndarray) and h.dtype == np.float32 and h.shape == (self.n,) + and np.all(h == 0) and np.all(s["delta_si"] == 0), "MBON requires zero graded APL h/delta") + require(np.all((s["ref_before"] >= 0) & (s["ref_before"] <= 22)), "Invalid refractory value") + if self.previous is not None: + require(all(bit_equal(s[a], self.previous[b]) for a, b in + (("old_v", "v"), ("old_g", "g"), ("ref_before", "ref"))), "Discontinuous observed state") + else: + require(np.all(s["ref_before"] == 0), "AH replay starts nonrefractory") + ref = np.maximum(s["ref_before"] - np.int32(1), np.int32(0)) + available = ref == 0 + require(np.array_equal(s["available"], available), "Availability mismatch") + require(np.array_equal(s["request_accepted"], s["request"] & available) and + np.array_equal(s["request_rejected"], s["request"] & ~available), "Request guard mismatch") + c = self.coeff + v, g = s["old_v"].copy(), s["old_g"].copy() + g[available] = np.multiply(c["gd"], s["old_g"][available]) + v[available] = np.add(c["c0"], np.add(np.multiply(c["cg"], s["old_g"][available]), + np.multiply(c["cv"], s["old_v"][available]))) + require(bit_equal(v, s["v_integrated"]) and bit_equal(g, s["g_decayed"]), "Integration mismatch") + v[s["request_accepted"]] = c["seed_volt"] + require(bit_equal(v, s["v_threshold"]), "Request override mismatch") + fired = available & (v > c["threshold"]) + require(np.array_equal(s["fired"], fired), "Strict threshold mismatch") + v[fired], g[fired], ref[fired] = c["reset"], np.float64(0), np.int32(22) + for key, value in (("v_after_reset", v), ("g_after_reset", g), ("ref_after_reset", ref)): + require(bit_equal(s[key], value), "Reset mismatch: " + key) + due, accepted = s.get("due_edge_indices"), s.get("arrival_accepted") + require(isinstance(due, np.ndarray) and due.dtype == np.int64 and due.ndim == 1 and + np.all((due >= 0) & (due < self.e)) and np.all(due[1:] > due[:-1]), "Noncanonical due edge rows") + require(isinstance(s.get("due_edge_id"), np.ndarray) and + bit_equal(s["due_edge_id"], self.edge_id[due]), "Due edge-ID mismatch") + require(isinstance(accepted, np.ndarray) and accepted.dtype == np.bool_ and accepted.shape == due.shape + and np.array_equal(accepted, ref[self.dst_local[due]] == 0), "Arrival acceptance mismatch") + require(tick >= 18 or not len(due), "Arrival before delay 18") + rows = due[accepted] + np.add.at(g, self.dst_local[rows], self.weights[rows]) + for key, value in (("g_pre_apl", g), ("v_pre_apl", v), ("ref_pre_apl", ref), ("v", v), ("ref", ref)): + require(bit_equal(s[key], value), "Arrival/final mismatch: " + key) + require(bit_equal(s["g"], np.subtract(g, s["delta_si"])), "Final g mismatch") + return due, accepted + + def _residual(self, voltage, g): + # No repair: anatomical lanes are never contaminated with roundoff. + vr = voltage - np.add(self.bv, self.sv.sum(axis=(1, 2))) + gr = g - np.add(self.bg, self.sg.sum(axis=(1, 2))) + self.max_v_residual = np.maximum(self.max_v_residual, np.abs(vr)) + self.max_g_residual = np.maximum(self.max_g_residual, np.abs(gr)) + return gr + + def __call__(self, tick, s): + due, accepted = self._validate(tick, s) + if self.previous is None: + self.bv, self.bg = s["old_v"].copy(), s["old_g"].copy() + c, available, fired = self.coeff, s["available"], s["fired"] + self.sv[available] = np.add(np.multiply(c["cg"], self.sg[available]), + np.multiply(c["cv"], self.sv[available])) + self.bv[available] = np.add(c["c0"], np.add(np.multiply(c["cg"], self.bg[available]), + np.multiply(c["cv"], self.bv[available]))) + self.sg[available] = np.multiply(c["gd"], self.sg[available]) + self.bg[available] = np.multiply(c["gd"], self.bg[available]) + self._residual(s["v_integrated"], s["g_decayed"]) + req = s["request_accepted"] + self.sv[req], self.bv[req] = 0., c["seed_volt"] + self._residual(s["v_threshold"], s["g_decayed"]) + self.sv[fired], self.sg[fired] = 0., 0. + self.bv[fired], self.bg[fired] = c["reset"], 0. + self.first[(self.first < 0) & fired] = np.int32(tick) + self.spike_count += fired.astype(np.int32) + for key, stage_key in (("request_count", "request"), ("request_accepted_count", "request_accepted"), + ("request_rejected_count", "request_rejected")): + self.requests[key] += s[stage_key].astype(np.int64) + dst, codes, weights = self.dst_local[due], self.groups[due], self.weights[due] + self.edge_due[due] += 1 + self.edge_accepted[due[accepted]] += 1 + for key, keep in (("due_count", np.ones(len(due), bool)), ("accepted_count", accepted), + ("rejected_count", ~accepted), ("accepted_zero_count", accepted & (weights == 0)), + ("rejected_zero_count", ~accepted & (weights == 0))): + np.add.at(self.counts[key], (dst[keep], codes[keep]), 1) + for key, keep in (("accepted_positive_V", accepted & (weights > 0)), + ("accepted_negative_V", accepted & (weights < 0)), + ("rejected_positive_V", ~accepted & (weights > 0)), + ("rejected_negative_V", ~accepted & (weights < 0))): + np.add.at(self.increments[key], (dst[keep], codes[keep]), weights[keep]) + nonzero = accepted & (weights != 0) + # add.at is sequential for repeated lane indices, preserving every + # lane's relative canonical edge order. Never pre-sum edge weights. + np.add.at(self.sg, (dst[nonzero], codes[nonzero], (weights[nonzero] < 0).astype(np.int32)), weights[nonzero]) + gr = self._residual(s["v"], s["g"]) + self.integral_g += np.multiply(self.sg, np.float64(DT_MS)) + self.integral_v += np.multiply(self.sv, np.float64(DT_MS)) + for value in (self.sg, self.sv, self.bg, self.bv, self.integral_g, self.integral_v, + self.max_v_residual, self.max_g_residual, *self.increments.values()): + require(np.isfinite(value).all(), "Nonfinite source accounting") + self.history_v[tick], self.history_g[tick], self.history_ref[tick] = s["v"], s["g"], s["ref"] + self.history_group_g[tick] = self.sg + self.history_baseline_g[tick], self.history_g_residual[tick] = self.bg, gr + self.previous = {key: s[key].copy() for key in ("v", "g", "ref")} + self.ticks += 1 + + def finish(self): + require(not self.finished and self.ticks == self.steps and self.previous is not None, + "Observer must cover exactly all ticks before finish") + require(np.array_equal(self.counts["due_count"], self.counts["accepted_count"] + self.counts["rejected_count"]), + "Group count conservation mismatch") + for key, edge in (("due_count", self.edge_due), ("accepted_count", self.edge_accepted)): + grouped = np.zeros_like(self.counts[key]) + np.add.at(grouped, (self.dst_local, self.groups), edge) + require(np.array_equal(grouped, self.counts[key]), "Per-edge/group count mismatch") + data = {"target_local": np.arange(self.n, dtype=np.int32), "spike_count": self.spike_count.copy(), + "first_spike_tick": self.first.copy(), **{key: value.copy() for key, value in self.requests.items()}, + **{key: value.copy() for key, value in self.counts.items()}, + **{key: value.copy() for key, value in self.increments.items()}, + **{"final_" + key: value.copy() for key, value in self.previous.items()}, + "final_group_g": self.sg.copy(), "final_group_v": self.sv.copy(), + "g_integral_V_ms": self.integral_g.sum(axis=2), "g_sign_integral_V_ms": self.integral_g.copy(), + "v_sign_integral_V_ms": self.integral_v.copy(), + "max_g_lane_residual_V": self.max_g_residual.copy(), "max_v_lane_residual_V": self.max_v_residual.copy(), + "history_v": self.history_v.copy(), "history_g": self.history_g.copy(), "history_ref": self.history_ref.copy(), + "history_group_g": self.history_group_g.copy(), "history_baseline_g": self.history_baseline_g.copy(), + "history_g_residual": self.history_g_residual.copy()} + edges = {"edge_id": self.edge_id.copy(), "source_neuron_idx": self.src_global.copy(), + "target_local": self.dst_local.copy(), "group": self.groups.copy(), "weight_V": self.weights.copy(), + "due_count": self.edge_due.copy(), "accepted_count": self.edge_accepted.copy(), + "rejected_count": self.edge_due - self.edge_accepted} + groups = {name: {**{key: int(value[:, gi].sum()) for key, value in self.counts.items()}, + **{key: float(value[:, gi].sum()) for key, value in self.increments.items()}, + "g_integral_V_ms": float(self.integral_g[:, gi].sum()), + "g_positive_integral_V_ms": float(self.integral_g[:, gi, 0].sum()), + "g_negative_integral_V_ms": float(self.integral_g[:, gi, 1].sum())} + for gi, name in enumerate(self.names)} + summary = {"complete": True, "pass_all": True, + "pass_all_scope": "Observer callback coverage and internal count/state-accounting checks only", + "steps": self.steps, "callback_count": self.ticks, "targets": self.n, "incoming_edges": self.e, + "group_names": list(self.names), "sign_order": ["positive", "negative"], "dt_ms": DT_MS, + "due_count": int(self.edge_due.sum()), "accepted_count": int(self.edge_accepted.sum()), + "rejected_count": int((self.edge_due - self.edge_accepted).sum()), "groups": groups, + "max_g_lane_residual_V": float(self.max_g_residual.max(initial=0.)), + "max_v_lane_residual_V": float(self.max_v_residual.max(initial=0.)), + "residual_policy": "Observed state minus uncorrected float64 lane sum; no fitted tolerance or anatomical reassignment", + "integral_contract": "Sum of end-of-tick source g or v lanes times dt_ms; units V*ms, not conductance or energy", + "increment_contract": "Nominal accepted/rejected signed per-edge increments; negative fields retain negative sign", + "lane_contract": "Observed availability controls decay/integration; observed request/reset clears voltage/source history; fired clears g; canonical accepted adds only", + "pending_coverage_checked_by_observer": False, "original_events_verified_by_observer": False, + "caller_must_verify_original_events_final_and_queue_coverage": True, + "nonfeedback": True, "parameter_changes": False, "learning": False, + "functional_transfer_claim": False, "whole_brain_intervention_claim": False} + # Includes aggregate overflows: a finite per-target array alone must + # never permit an Infinity/NaN JSON report with pass_all=True. + json.dumps(summary, allow_nan=False) + self.finished = True + return data, edges, summary diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/prepare.py b/models/male-cns-lif/mb-credit-transfer-audit-v1/prepare.py new file mode 100644 index 0000000..210fc11 --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/prepare.py @@ -0,0 +1,136 @@ +"""Preregister all AK trials before credit/MBON outcomes; never train.""" +from datetime import datetime, timezone +import platform +import shutil +import subprocess +import sys +import numpy as np +import pandas as pd +import yaml +from context import (ROOT, MODEL, EXP, AK, H, AG, META, CORE, COEFF, CFG, PINS, + read, save, digest, sources, integrity, write_npz) + + +def main(): + assert not EXP.exists() or (EXP.is_dir() and not any(EXP.iterdir())), 'Populated experiment exists: preserve it, do not regenerate' + assert shutil.disk_usage(EXP.parent).free > CFG['output_budget_bytes'] + 10 * 1024**3 + for relative, expected in PINS.items(): + assert digest(ROOT / relative) == expected, relative + assert read(AK / 'audit/final-status.json')['status'] == 'PASS-FROZEN-D18-INDEPENDENT-VALIDATION' + assert not CFG['training'] and not CFG['candidate_generation'] + jc = yaml.safe_load((ROOT / 'models/male-cns-lif/mb-physiology-v1/phase4j.yaml').read_text()) + j = jc['eligibility_v2'] + assert j['kc_trace_tau_ms'] == CFG['kc_trace_tau_ms'] and j['trace_cap'] == CFG['trace_cap'] + assert j['max_fractional_depression'] == CFG['conditional_depression_fraction'] == .25 + assert jc['direct_kc']['dan_time_ms'] / CFG['dt_ms'] == CFG['virtual_gate_tick'] + inventory = read(AK / 'protocol/validation-cases.json') + assert len(inventory) == CFG['primary_trials'] + seeds = sorted({r['seed'] for r in inventory}) + assert len(seeds) == 5 + planned = [] + for row in inventory: + for repeat in (0, 1) if row['seed'] == seeds[0] else (0,): + planned.append(dict(row, repeat=repeat)) + assert len(planned) == CFG['primary_trials'] + CFG['technical_repeats'] + inputs = dict(PINS) + h_manifest = {line.split(' ', 1)[1]: line.split(' ', 1)[0] + for line in (H / 'manifests/checksums.sha256').read_text().splitlines()} + static_h = ('plastic-mask/plastic-edge-candidates.parquet', 'plastic-mask/plastic-edge-ids.int64.npy', + 'plastic-mask/plastic-edge-mask.bool.npy', 'mappings/dan-to-mbon-confirmed.parquet', + 'mappings/mbon-to-compartment.parquet', 'mappings/kc-to-mbon-actual-edges.parquet') + for rel in static_h: + assert digest(H / rel) == h_manifest[rel] + inputs[(H / rel).relative_to(ROOT).as_posix()] = h_manifest[rel] + for row in planned: + case = AK / 'cases' / row['cohort'] / row['name'] + trial = AK / 'gpu' / row['cohort'] / (row['name'] + '-r' + str(row['repeat'])) + for p in (case / 'spec.json', case / 'requests.npz', trial / 'state.npz', trial / 'summary.json'): + inputs[p.relative_to(ROOT).as_posix()] = digest(p) + paths = [COEFF] + list((AG / 'graphs/full').glob('*.npy')) + list((AG / 'apl-bundle').glob('*.npy')) + raw_path = ROOT / 'datasets/male-cns-v1.0/processed/neuron-only/gpu/csr-weights.int64.npy' + for p in paths + [raw_path]: + inputs[p.relative_to(ROOT).as_posix()] = digest(p) + for name in ('protocol', 'trials', 'audit', 'regression', 'logs', 'pairs'): + (EXP / name).mkdir(parents=True, exist_ok=False) + test = subprocess.run([sys.executable, '-B', '-m', 'unittest', 'discover', '-v', '-s', str(MODEL)], + cwd=MODEL, text=True, capture_output=True) + with (EXP / 'regression/unit-tests.log').open('x', encoding='utf-8') as f: + f.write(test.stdout + test.stderr) + assert test.returncode == 0, 'Unit tests failed; preserve incomplete experiment' + assert 'skipped=' not in test.stderr, 'Server arithmetic comparison must not be skipped' + save(EXP / 'protocol/preregistered.json', dict(timestamp_utc=datetime.now(timezone.utc).isoformat(), + sources=sources(), config=CFG, inputs=[dict(path=k, sha256=v) for k, v in sorted(inputs.items())], + parent_commit=subprocess.check_output(['git', '-C', str(ROOT), 'rev-parse', 'HEAD'], text=True).strip(), + planned=planned, prior_AK_representation_known=True, before_new_credit_and_MBON_outcomes=True, + training=False, learning_achieved=False, virtual_gate_is_dopamine_measurement=False, + MBON_recurrent_and_all_other_presynaptic_events_clamped=True, + expected_functional_effect_not_a_preregistered_learning_gate=True, + python=sys.version, platform=platform.platform(), numpy=np.__version__)) + save(EXP / 'regression/old-integrity-before.json', integrity()) + meta = pd.read_parquet(META).sort_values('neuron_idx').reset_index(drop=True) + assert np.array_equal(meta.neuron_idx, np.arange(CFG['neurons'], dtype=np.int32)) + kc = np.flatnonzero(meta.annotation_class.eq('Kenyon_Cell')).astype(np.int32) + mbon = np.flatnonzero(meta.annotation_class.eq('MBON')).astype(np.int32) + apl = np.flatnonzero(meta.annotation_type.eq('APL')).astype(np.int32) + assert len(kc) == 4064 and len(mbon) == 97 + assert np.array_equal(kc, np.load(AG / 'apl-bundle/kc_globals.npy')) + assert np.array_equal(apl, np.load(AG / 'apl-bundle/apl_globals.npy')) + folder = AG / 'graphs/full' + arrays = {k: np.load(folder / (k + '.npy'), mmap_mode='r') for k in ('nodes', 'src', 'dst', 'edge_id', 'weights')} + assert np.array_equal(arrays['nodes'], np.arange(CFG['neurons'], dtype=np.int32)) + assert np.array_equal(arrays['edge_id'], np.arange(CFG['edges'], dtype=np.int64)) + raw = np.load(raw_path, mmap_mode='r') + candidate = pd.read_parquet(H / static_h[0]) + ids = np.load(H / static_h[1]); mask = np.load(H / static_h[2]) + assert ids.dtype == np.int64 and ids.shape == (CFG['candidate_edges'],) + assert np.array_equal(candidate.edge_id, ids) and np.array_equal(np.flatnonzero(mask), ids) + for prefix, key in (('source', 'src'), ('target', 'dst')): + assert np.array_equal(candidate[prefix + '_neuron_idx'], arrays[key][ids]) + assert np.array_equal(candidate[prefix + '_body_id'], meta.iloc[arrays[key][ids]].body_id) + assert np.array_equal(candidate.raw_synapse_count, raw[ids]) + assert np.isin(candidate.source_neuron_idx, kc).all() and np.isin(candidate.target_neuron_idx, mbon).all() + assert (candidate.plasticity_polarity == -1).all() and candidate.target_compartment_verbatim.notna().all() + confirmed = pd.read_parquet(H / static_h[3]) + assert confirmed.exact_compartment_match.all() + assert np.array_equal(confirmed.source_compartment_verbatim, confirmed.target_compartment_verbatim) + for row in confirmed.itertuples(): + assert arrays['src'][row.edge_id] == row.source_neuron_idx and arrays['dst'][row.edge_id] == row.target_neuron_idx + assert raw[row.edge_id] == row.raw_synapse_count and meta.iloc[row.source_neuron_idx].annotation_class == 'DAN' + assert set(candidate.target_neuron_idx).issubset(set(confirmed.target_neuron_idx)) + compartments = pd.read_parquet(H / static_h[4]).sort_values('neuron_idx').reset_index(drop=True) + assert np.array_equal(compartments.neuron_idx, mbon) + compartments.to_parquet(EXP / 'protocol/mbon-metadata.parquet', index=False) + candidate.to_parquet(EXP / 'protocol/candidate-static.parquet', index=False) + lookup = np.full(CFG['neurons'], -1, np.int32); lookup[mbon] = np.arange(len(mbon), dtype=np.int32) + selected = np.flatnonzero(lookup[arrays['dst']] >= 0) + src, dst = arrays['src'][selected], lookup[arrays['dst'][selected]] + weights = arrays['weights'][selected].copy() + assert weights.dtype == np.float64 and raw.dtype == np.int64 + weights[np.isin(src, apl)] = 0.0 + is_candidate = mask[selected] + assert int(is_candidate.sum()) == CFG['candidate_edges'] and (weights[is_candidate] > 0).all() + groups = np.full(len(selected), CFG['groups'].index('other'), np.int32) + for name, chosen in (('nonplastic_KC', np.isin(src, kc)), ('DAN', meta.iloc[src].annotation_class.eq('DAN').to_numpy()), + ('MBON', np.isin(src, mbon)), ('APL', np.isin(src, apl)), ('plastic_KC', is_candidate)): + groups[chosen] = CFG['groups'].index(name) + kcall = pd.read_parquet(H / static_h[5]) + assert np.array_equal(selected[np.isin(src, kc)], kcall.edge_id.to_numpy()) + assert np.array_equal(raw[kcall.edge_id.to_numpy()], kcall.raw_synapse_count.to_numpy()) + write_npz(EXP / 'protocol/incoming.npz', src_global=src, dst_local=dst, edge_id=selected.astype(np.int64), + weights=weights, raw_contacts=raw[selected], groups=groups, is_candidate=is_candidate, + targets=mbon, kc_globals=kc, edge_source_local=np.searchsorted(kc, candidate.source_neuron_idx).astype(np.int32)) + save(EXP / 'protocol/graph-audit.json', dict(neurons=len(meta), all_edges=CFG['edges'], KC=len(kc), MBON=len(mbon), + all_MBON_incoming_edges=len(selected), all_KC_MBON_edges=len(kcall), candidate_edges=len(ids), + candidate_targets=int(candidate.target_neuron_idx.nunique()), confirmed_DAN_MBON_edges=len(confirmed), + compartments={str(c): dict(edges=len(g), targets=int(g.target_neuron_idx.nunique()), sources=int(g.source_neuron_idx.nunique())) + for c, g in candidate.groupby('target_compartment_verbatim')}, + fast_APL_incoming_edges_zeroed=int(np.isin(src, apl).sum()), groups={name: int((groups == i).sum()) for i, name in enumerate(CFG['groups'])}, + mask_all_edges_identity_verified=True, mapping_basis='Frozen explicit annotation token + real DAN-to-MBON edge; not synapse ROI', + feedback_neuron_class_not_inferred=True, weight_units='float64 SI volts; not measured conductance')) + save(EXP / 'protocol/prepared-hashes.json', [dict(path=p.relative_to(EXP).as_posix(), bytes=p.stat().st_size, sha256=digest(p)) + for p in sorted((EXP / 'protocol').iterdir()) if p.is_file() and p.name != 'prepared-hashes.json']) + print('PREREGISTERED 120 primary +24 repeats; static edge identities validated; no new trajectory or training', flush=True) + + +if __name__ == '__main__': + main() diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/run_audit.py b/models/male-cns-lif/mb-credit-transfer-audit-v1/run_audit.py new file mode 100644 index 0000000..35d47df --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/run_audit.py @@ -0,0 +1,160 @@ +"""CPU-only read-only baseline and one predeclared conditional sensitivity.""" +from concurrent.futures import ProcessPoolExecutor, as_completed +from functools import lru_cache +import time +import traceback +import numpy as np +from context import (ROOT, EXP, AK, CORE, COEFF, CFG, PINS, read, save, digest, + load_module, check, budget, bit_equal, write_npz) +from credit import replay_credit +from mbon_accounting import MBONAccounting + + +@lru_cache(maxsize=1) +def prepared(): + core = load_module('sealed_ah_core_al', CORE, PINS[CORE.relative_to(ROOT).as_posix()]) + with np.load(EXP / 'protocol/incoming.npz', allow_pickle=False) as f: + data = {k: f[k].copy() for k in f.files} + incoming = core.IncomingIndex(data['src_global'], data['dst_local'], data['edge_id'], data['weights'], len(data['targets'])) + altered = data['weights'].copy() + altered[data['is_candidate']] *= np.float64(1.0 - CFG['conditional_depression_fraction']) + assert bit_equal(data['weights'][~data['is_candidate']], altered[~data['is_candidate']]) + assert np.array_equal(np.sign(data['weights']), np.sign(altered)) + depressed = core.IncomingIndex(data['src_global'], data['dst_local'], data['edge_id'], altered, len(data['targets'])) + for array in data.values(): + array.setflags(write=False) + return core, data, incoming, depressed, read(COEFF) + + +def compare_results(base, changed, base_history, changed_history): + event_equal = all(bit_equal(base[k], changed[k]) for k in ('step', 'neuron_idx')) + count_changes = base['counts'] != changed['counts'] + latency_changes = base['first_spike'] != changed['first_spike'] + return dict(event_sequence_changed=not event_equal, + spike_count_L1=int(np.abs(base['counts'].astype(np.int64) - changed['counts']).sum()), + neurons_with_count_change=int(count_changes.sum()), neurons_with_first_latency_change=int(latency_changes.sum()), + baseline_spikes=int(base['counts'].sum()), depressed_spikes=int(changed['counts'].sum()), + max_abs_V_difference_SI=float(np.max(np.abs(base_history['history_v'] - changed_history['history_v']))), + max_abs_g_difference_SI=float(np.max(np.abs(base_history['history_g'] - changed_history['history_g']))), + final_V_max_abs_difference_SI=float(np.max(np.abs(base['v'] - changed['v']))), + final_g_max_abs_difference_SI=float(np.max(np.abs(base['g'] - changed['g']))), + functional_count_or_first_latency_change=bool(count_changes.any() or latency_changes.any()), + result_scope='Conditional clamped-upstream replay only; all target threshold/reset/ref recalculated; not whole-brain or learning') + + +def audit_trial(row, stage): + start = time.perf_counter() + key = row['name'] + '-r' + str(row['repeat']) + out = EXP / 'trials' / key + assert stage in ('baseline', 'conditional25') + if stage == 'baseline': + out.mkdir(exist_ok=False) + else: + assert read(EXP / 'audit/baselines-complete.json')['pass_all'], 'All 144 baseline replays must pass first' + assert out.is_dir() and not (out / 'summary.json').exists() + case = AK / 'cases' / row['cohort'] / row['name'] + trial = AK / 'gpu' / row['cohort'] / key + spec = read(case / 'spec.json') + assert spec['steps'] == CFG['steps'] and spec['dt_ms'] == CFG['dt_ms'] and spec['apl_delay_steps'] == 18 + assert all(spec[k] == row[k] for k in ('name', 'seed', 'mode', 'odor_id')) + assert read(trial / 'summary.json')['complete'] and read(trial / 'summary.json')['pass_all'] + with np.load(trial / 'state.npz', allow_pickle=False) as f: + state = {k: f[k].copy() for k in f.files} + assert set(state) == {'step', 'neuron_idx', 'counts', 'v', 'g', 'ref'} + with np.load(case / 'requests.npz', allow_pickle=False) as f: + requests = {k: f[k].copy() for k in f.files} + core, data, incoming, depressed, coeff = prepared() + targets, steps = data['targets'], spec['steps'] + assert not np.isin(requests['neuron_idx'], targets).any(), 'Unexpected MBON injection: do not reinterpret it' + v0 = np.full(len(targets), spec['model']['resting_potential_mv'], np.float64) * np.float64(.001) + g0 = np.zeros(len(targets), np.float64) + events = dict(step=state['step'], neuron_idx=state['neuron_idx']) + if stage == 'baseline': + observer = MBONAccounting(incoming, data['groups'], tuple(CFG['groups']), coeff, steps) + result = core.replay(v0, g0, coeff, steps, targets, requests, events, incoming, + np.zeros((steps, len(targets)), np.float32), observer) + selected = np.isin(state['neuron_idx'], targets) + exact = {k: bit_equal(result[k], state[k][targets]) for k in ('counts', 'v', 'g', 'ref')} + exact.update({k: bit_equal(result[k], state[k][selected]) for k in ('step', 'neuron_idx')}) + assert all(exact.values()), 'Baseline MBON divergence: ' + str(exact) + bt, be, bs = observer.finish() + write_npz(out / 'baseline-replay.npz', **result) + write_npz(out / 'baseline-target-accounting.npz', **bt) + pending = np.zeros(len(incoming.edge_id), np.int64) + for tick in range(steps - 18, steps): + due = incoming.due(state['neuron_idx'][state['step'] == tick]) + pending[due] += 1 + be['pending_after_window_count'] = pending + # Independent source-spike multiplicity covers due plus pending events. + source_counts = np.bincount(state['neuron_idx'], minlength=CFG['neurons']) + assert np.array_equal(be['due_count'] + pending, source_counts[incoming.src_global]) + write_npz(out / 'baseline-edge-accounting.npz', **be) + save(out / 'baseline-accounting.json', bs) + trace = replay_credit(state['step'], state['neuron_idx'], data['kc_globals'], + steps=steps, gate_tick=CFG['virtual_gate_tick'], dt_ms=CFG['dt_ms'], + tau_ms=CFG['kc_trace_tau_ms'], cap=CFG['trace_cap']) + arrays = {k: value for k, value in trace.items() if isinstance(value, np.ndarray)} + write_npz(out / 'credit.npz', **arrays) + save(out / 'credit.json', {k: value for k, value in trace.items() if not isinstance(value, np.ndarray)}) + report = dict(**row, pass_all=True, baseline_exact=exact, due_plus_pending_source_events_exact=True, + CPU_wall_seconds=time.perf_counter() - start) + save(out / 'baseline-summary.json', report) + return report + with np.load(out / 'baseline-replay.npz', allow_pickle=False) as f: + result = {k: f[k].copy() for k in f.files} + with np.load(out / 'baseline-target-accounting.npz', allow_pickle=False) as f: + bt = {k: f[k].copy() for k in f.files} + baseline_report = read(out / 'baseline-summary.json') + assert baseline_report['pass_all'] and all(baseline_report['baseline_exact'].values()) + exact = baseline_report['baseline_exact'] + d_observer = MBONAccounting(depressed, data['groups'], tuple(CFG['groups']), coeff, steps) + changed = core.replay(v0, g0, coeff, steps, targets, requests, events, depressed, + np.zeros((steps, len(targets)), np.float32), d_observer) + dt, de, ds = d_observer.finish() + write_npz(out / 'conditional25-replay.npz', **changed) + write_npz(out / 'conditional25-target-accounting.npz', **dt) + write_npz(out / 'conditional25-edge-accounting.npz', **de) + save(out / 'conditional25-accounting.json', ds) + sensitivity = compare_results(result, changed, bt, dt) + save(out / 'sensitivity.json', sensitivity) + report = dict(**row, pass_all=True, baseline_exact=exact, sensitivity=sensitivity, + credit_gate='Virtual tick900 post-update; no DAN injection or plastic update', + biological_duration_ms=spec['duration_ms'], CPU_wall_seconds=time.perf_counter() - start, + baseline_CPU_wall_seconds=baseline_report['CPU_wall_seconds'], + source_sha256={f: digest(trial / f) for f in ('state.npz', 'summary.json')}, + conditional_weight_copy_only=True, training=False, candidate_generated=False) + save(out / 'summary.json', report) + save(out / 'output-hashes.json', [dict(path=p.name, bytes=p.stat().st_size, sha256=digest(p)) + for p in sorted(out.iterdir()) if p.is_file()]) + return report + + +def main(): + reg = check() + assert not any((EXP / 'trials').iterdir()), 'No automatic resume/overwrite of diagnostic outputs' + complete = [] + try: + for stage in ('baseline', 'conditional25'): + complete = [] + with ProcessPoolExecutor(max_workers=CFG['workers']) as pool: + futures = {pool.submit(audit_trial, row, stage): row for row in reg['planned']} + for task in as_completed(futures): + result = task.result() + complete.append(dict(name=result['name'], repeat=result['repeat'], pass_all=True)) + budget() + print(stage, len(complete), result['name'], result['repeat'], + round(result['CPU_wall_seconds'], 3), 'CPU s', flush=True) + assert len(complete) == 144 + if stage == 'baseline': + save(EXP / 'audit/baselines-complete.json', dict(pass_all=True, trials=complete, primary=120, repeats=24)) + except Exception as error: + save(EXP / 'audit/failure.json', dict(error=type(error).__name__, message=str(error), + traceback=traceback.format_exc(), stage=stage, completed=complete)) + raise + assert len(complete) == 144 + save(EXP / 'audit/replays-complete.json', dict(pass_all=True, trials=complete, primary=120, repeats=24, + meaning='All exact conditional baseline reconstructions; not an overall biological or learning PASS')) + + +if __name__ == '__main__': + main() diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/summarize.py b/models/male-cns-lif/mb-credit-transfer-audit-v1/summarize.py new file mode 100644 index 0000000..97c2f36 --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/summarize.py @@ -0,0 +1,177 @@ +"""All predeclared pairs and all trial outputs; never choose a winning odor.""" +from itertools import combinations +import numpy as np +import pandas as pd +from context import EXP, AK, CFG, read, save as _save, digest, bit_equal, write_npz as _write_npz +from credit import pair_identity + + +def load_arrays(path): + with np.load(path, allow_pickle=False) as data: + return {key: data[key].copy() for key in data.files} + + +def metrics(values): + values = np.asarray(values, np.float64) + if not len(values): + return dict(min=None, mean=None, max=None, undefined_reason='No defined denominator observations') + return dict(min=float(values.min()), mean=float(values.mean()), max=float(values.max())) + + +def primary_rows(reg): + rows = [r for r in reg['planned'] if r['repeat'] == 0] + assert len(rows) == CFG['primary_trials'] and len({r['name'] for r in rows}) == len(rows) + return rows + + +def run(verify_only=False): + def save(path, value): + if verify_only: + assert read(path) == value, 'Summary JSON differs from recomputed evidence: ' + str(path) + else: + _save(path, value) + + def write_npz(path, **value): + if verify_only: + old = load_arrays(path) + assert set(old) == set(value) and all(bit_equal(old[k], value[k]) for k in old) + else: + _write_npz(path, **value) + + reg = read(EXP / 'protocol/preregistered.json') + assert read(EXP / 'audit/replays-complete.json')['pass_all'] + data = load_arrays(EXP / 'protocol/incoming.npz') + for row in reg['planned']: + folder = EXP / 'trials' / (row['name'] + '-r' + str(row['repeat'])) + hashes = read(folder / 'output-hashes.json') + assert {r['path'] for r in hashes} == {p.name for p in folder.iterdir() if p.name != 'output-hashes.json'} + for entry in hashes: + assert digest(folder / entry['path']) == entry['sha256'] + original = load_arrays(AK / 'gpu' / row['cohort'] / (row['name'] + '-r' + str(row['repeat'])) / 'state.npz') + base = load_arrays(folder / 'baseline-replay.npz') + selected = np.isin(original['neuron_idx'], data['targets']) + assert all(bit_equal(base[k], original[k][data['targets']]) for k in ('v', 'g', 'ref', 'counts')) + assert all(bit_equal(base[k], original[k][selected]) for k in ('step', 'neuron_idx')) + candidate = pd.read_parquet(EXP / 'protocol/candidate-static.parquet') + target_meta = pd.read_parquet(EXP / 'protocol/mbon-metadata.parquet') + primary = primary_rows(reg) + repeats = [] + for row in reg['planned']: + if row['repeat'] != 1: + continue + paths = [EXP / 'trials' / (row['name'] + '-r' + str(i)) for i in (0, 1)] + checks = {} + for filename in ('baseline-replay.npz', 'baseline-target-accounting.npz', 'baseline-edge-accounting.npz', + 'conditional25-replay.npz', 'conditional25-target-accounting.npz', 'conditional25-edge-accounting.npz', 'credit.npz'): + a, b = (load_arrays(p / filename) for p in paths) + checks[filename] = set(a) == set(b) and all(bit_equal(a[k], b[k]) for k in a) + for filename in ('baseline-accounting.json', 'conditional25-accounting.json', 'credit.json', 'sensitivity.json'): + checks[filename] = read(paths[0] / filename) == read(paths[1] / filename) + assert all(checks.values()), 'Repeat accounting differs: ' + row['name'] + repeats.append(dict(name=row['name'], checks=checks, pass_all=True)) + assert len(repeats) == CFG['technical_repeats'] + save(EXP / 'audit/repeat-checks.json', dict(pass_all=True, repeats=repeats)) + summaries, target_rows, trial_metrics = [], [], [] + for row in primary: + folder = EXP / 'trials' / (row['name'] + '-r0') + report = read(folder / 'summary.json') + assert report['pass_all'] and all(report['baseline_exact'].values()) + summaries.append(report) + targets = load_arrays(folder / 'baseline-target-accounting.npz') + change = load_arrays(folder / 'conditional25-target-accounting.npz') + edges = load_arrays(folder / 'baseline-edge-accounting.npz') + exc = targets['accepted_positive_V'].sum(axis=1) + plastic_exc = targets['accepted_positive_V'][:, 0] + area_exc = targets['g_sign_integral_V_ms'][:, :, 0].sum(axis=1) + area_plastic = targets['g_sign_integral_V_ms'][:, 0, 0] + for i, meta in enumerate(target_meta.itertuples()): + entry = dict(name=row['name'], cohort=row['cohort'], mode=row['mode'], odor_id=row['odor_id'], seed=row['seed'], + neuron_idx=int(meta.neuron_idx), body_id=int(meta.body_id), annotation_type=meta.annotation_type, + compartment_verbatim=meta.mb_compartment_verbatim, + candidate_target=bool(np.any(candidate.target_neuron_idx.to_numpy() == meta.neuron_idx)), + accepted_total_positive_V=float(exc[i]), accepted_plastic_positive_V=float(plastic_exc[i]), + plastic_accepted_positive_fraction=None if exc[i] == 0 else float(plastic_exc[i] / exc[i]), + positive_source_g_area_V_ms=float(area_exc[i]), plastic_positive_g_area_V_ms=float(area_plastic[i]), + plastic_positive_g_area_fraction=None if area_exc[i] == 0 else float(area_plastic[i] / area_exc[i]), + baseline_spikes=int(targets['spike_count'][i]), conditional25_spikes=int(change['spike_count'][i]), + baseline_first_tick=int(targets['first_spike_tick'][i]), conditional25_first_tick=int(change['first_spike_tick'][i]), + max_abs_V_delta_SI=float(np.max(np.abs(targets['history_v'][:, i] - change['history_v'][:, i]))), + max_abs_g_delta_SI=float(np.max(np.abs(targets['history_g'][:, i] - change['history_g'][:, i])))) + target_rows.append(entry) + pick = data['is_candidate'] + summary = dict(name=row['name'], cohort=row['cohort'], mode=row['mode'], odor_id=row['odor_id'], seed=row['seed'], + plastic_due_events=int(edges['due_count'][pick].sum()), plastic_accepted_events=int(edges['accepted_count'][pick].sum()), + plastic_rejected_events=int(edges['rejected_count'][pick].sum()), + plastic_pending_events=int(edges['pending_after_window_count'][pick].sum()), + plastic_edges_with_accepted_events=int(np.count_nonzero(edges['accepted_count'][pick])), + accepted_positive_V=float(exc.sum()), plastic_accepted_positive_V=float(plastic_exc.sum()), + plastic_accepted_positive_fraction=None if exc.sum() == 0 else float(plastic_exc.sum() / exc.sum()), + plastic_positive_g_area_fraction=None if area_exc.sum() == 0 else float(area_plastic.sum() / area_exc.sum()), + **report['sensitivity']) + trial_metrics.append(summary) + target_table = pd.DataFrame(target_rows) + if verify_only: + assert target_table.equals(pd.read_parquet(EXP / 'audit/per-MBON-primary.parquet')) + else: + target_table.to_parquet(EXP / 'audit/per-MBON-primary.parquet', index=False) + save(EXP / 'audit/primary-trial-metrics.json', trial_metrics) + pair_reports = [] + for cohort in sorted({r['cohort'] for r in primary}): + for mode in sorted({r['mode'] for r in primary}): + rows = [r for r in primary if r['cohort'] == cohort and r['mode'] == mode] + odors = sorted({r['odor_index'] for r in rows}) + assert len(rows) == 30 and len(odors) == 6 + traces = {}; whole = {}; ids = {} + for odor in odors: + series = sorted((r for r in rows if r['odor_index'] == odor), key=lambda r: r['seed']) + assert len(series) == 5 + ids[odor] = series[0]['odor_id'] + credit = [load_arrays(EXP / 'trials' / (r['name'] + '-r0') / 'credit.npz') for r in series] + traces[odor] = np.stack([c['trace_gate'] for c in credit]) + whole[odor] = np.stack([(c['spike_count_total'] > 0).astype(np.float32) for c in credit]) + for a, b in combinations(odors, 2): + name = f'{cohort}-{mode}-{a:02d}-vs-{b:02d}' + result = dict(cohort=cohort, mode=mode, odor_a=ids[a], odor_b=ids[b], odor_index_a=a, odor_index_b=b) + for definition, series in (('virtual_gate900', traces), ('whole_window_auxiliary', whole)): + identities = pair_identity(series[a], series[b], data['edge_source_local']) + save_arrays = {k: v for k, v in identities.items() if isinstance(v, np.ndarray)} + write_npz(EXP / 'pairs' / (name + '-' + definition + '.npz'), **save_arrays) + summary = identities['summary'] + # Historic local existence criterion only, no new overall pass rate. + summary['local_specific_KC_and_edges_exist_both_sides'] = all( + summary[unit]['category_counts'][side] >= 1 for unit in ('KC', 'edges') for side in ('A_specific', 'B_specific')) + summary['compartments'] = {} + for comp, group in candidate.groupby('target_compartment_verbatim', sort=True): + sub = pair_identity(series[a], series[b], data['edge_source_local'][group.index.to_numpy()]) + summary['compartments'][str(comp)] = sub['summary']['edges'] + result[definition] = summary + pair_reports.append(result) + assert len(pair_reports) == 60 + save(EXP / 'audit/pair-identities.json', pair_reports) + blocks = {} + for cohort in sorted({r['cohort'] for r in primary}): + for mode in sorted({r['mode'] for r in primary}): + trials = [r for r in trial_metrics if r['cohort'] == cohort and r['mode'] == mode] + pairs = [p for p in pair_reports if p['cohort'] == cohort and p['mode'] == mode] + blocks[cohort + '/' + mode] = dict(trials=len(trials), pairs=len(pairs), + pairs_with_both_specific_KC_and_edge_sets=sum(p['virtual_gate900']['local_specific_KC_and_edges_exist_both_sides'] for p in pairs), + KC_empty_union_pairs=sum(p['virtual_gate900']['KC']['empty_union'] for p in pairs), + edge_empty_union_pairs=sum(p['virtual_gate900']['edges']['empty_union'] for p in pairs), + KC_active_set_Jaccard=metrics([p['virtual_gate900']['KC']['active_set_jaccard'] for p in pairs if not p['virtual_gate900']['KC']['empty_union']]), + candidate_edge_active_set_Jaccard=metrics([p['virtual_gate900']['edges']['active_set_jaccard'] for p in pairs if not p['virtual_gate900']['edges']['empty_union']]), + plastic_accepted_events=metrics([r['plastic_accepted_events'] for r in trials]), + plastic_fraction_of_all_MBON_accepted_positive=metrics([r['plastic_accepted_positive_fraction'] for r in trials if r['plastic_accepted_positive_fraction'] is not None]), + conditional25_event_changed_trials=sum(r['event_sequence_changed'] for r in trials), + conditional25_count_or_first_latency_changed_trials=sum(r['functional_count_or_first_latency_change'] for r in trials), + max_abs_V_difference_SI=max(r['max_abs_V_difference_SI'] for r in trials), + max_abs_g_difference_SI=max(r['max_abs_g_difference_SI'] for r in trials)) + outcome = dict(arithmetic_and_coverage_pass=True, primary_trials=120, exact_repeats=24, pairs=60, blocks=blocks, + candidate_generated=False, learning_achieved=False, conditioning_executed=False, scientific_overall_PASS_threshold_defined=False, + maximum_observed_g_lane_roundoff_residual_SI=max(read(EXP / 'trials' / (r['name'] + '-r0') / 'baseline-accounting.json')['max_g_lane_residual_V'] for r in primary), + interpretation='Read-only credit delivery and fixed conditional sensitivity; not closed-loop memory or dopamine measurement') + save(EXP / 'audit/scientific-summary.json', outcome) + return outcome + + +if __name__ == '__main__': + print(run(), flush=True) diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/test_credit.py b/models/male-cns-lif/mb-credit-transfer-audit-v1/test_credit.py new file mode 100644 index 0000000..387a923 --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/test_credit.py @@ -0,0 +1,237 @@ +"""Pure synthetic credit tests; no brain execution or historical dynamic read.""" +import ast +import hashlib +import math +from pathlib import Path +import types +import unittest + +import numpy as np + +from credit import CATEGORY_CODES, N_GLOBAL, pair_identity, replay_credit + + +SOURCE_PINS = { + 'phase4o_event_replay.py': 'b169937bab495c77d8ee6c1013877e7500e7354140d9fcc90595d984238ba44e', + 'phase4l.py': 'e97d58d8c1f44920d0e953f8f5831ddc86fa0198784e86460e315de4116ac553', +} + + +def frozen_tree(filename): + """Only static source bytes are read; never import the old script or its main.""" + here = Path(__file__).absolute().parent + candidates = [here.parent / 'models/male-cns-lif' / filename, + here.parent / filename, + here.parent / ('runtime-credit-v1' if filename.startswith('phase4o') else 'olfactory-grounding-v1') / filename] + path = next((path for path in candidates if path.is_file()), None) + if path is None: + raise unittest.SkipTest('Frozen arithmetic source not installed at declared static paths: ' + filename) + source = path.read_bytes() + if hashlib.sha256(source).hexdigest() != SOURCE_PINS[filename]: + raise AssertionError('Frozen arithmetic source SHA mismatch: ' + str(path)) + return ast.parse(source, filename=str(path)), path + + +def assert_bits(test, first, second): + test.assertEqual(first.dtype, second.dtype) + test.assertEqual(first.shape, second.shape) + np.testing.assert_array_equal(first.view(np.uint8), second.view(np.uint8)) + + +def events(rows): + if not rows: + return np.empty(0, np.int32), np.empty(0, np.int32) + array = np.asarray(rows, np.int32) + return array[:, 0].copy(), array[:, 1].copy() + + +class ReplayTests(unittest.TestCase): + def setUp(self): + self.kc = np.array([3, 9, 12], np.int32) + + def test_gate_900_includes_same_tick_901_is_final_only_no_18_shift(self): + ticks, nodes = events([(882, 12), (900, 3), (901, 9)]) + result = replay_credit(ticks, nodes, self.kc) + self.assertEqual(result['trace_gate'][0], np.float32(1)) + self.assertEqual(result['trace_gate'][1], np.float32(0)) + decay = np.float32(math.exp(-.1 / 100)) + expected = np.float32(1) + for _ in range(18): + expected = np.float32(expected * decay) + self.assertEqual(result['trace_gate'][2].view(np.uint32), expected.view(np.uint32)) + self.assertTrue(np.all(result['trace_final'] > 0)) + np.testing.assert_array_equal(result['spike_count_gate'], [1, 0, 1]) + np.testing.assert_array_equal(result['spike_count_total'], [1, 1, 1]) + self.assertEqual(result['event_shift_steps'], 0) + self.assertTrue(result['gate_is_virtual_readout_not_DAN_activity']) + + def test_spike_cap_resets_recency_not_accumulated_count(self): + ticks, nodes = events([(0, 3), (7, 3), (7, 9)]) + result = replay_credit(ticks, nodes, self.kc, steps=15, gate_tick=7) + np.testing.assert_array_equal(result['trace_gate'], np.array([1, 1, 0], np.float32)) + self.assertEqual(result['trace_final'][0].view(np.uint32), result['trace_final'][1].view(np.uint32)) + np.testing.assert_array_equal(result['spike_count_total'], [2, 1, 0]) + + def test_tick_zero_gate_and_last_tick_have_no_extra_decay(self): + ticks, nodes = events([(0, 3), (2, 9)]) + result = replay_credit(ticks, nodes, self.kc, steps=3, gate_tick=0) + self.assertEqual(result['trace_gate'][0], np.float32(1)) + self.assertEqual(result['trace_final'][1], np.float32(1)) + self.assertEqual(result['spike_count_gate'].tolist(), [1, 0, 0]) + + def test_empty_events_are_positive_zero_with_exact_dtypes(self): + ticks, nodes = events([]) + result = replay_credit(ticks, nodes, self.kc, steps=2, gate_tick=1) + for key in ('trace_gate', 'trace_final'): + self.assertEqual(result[key].dtype, np.dtype('float32')) + self.assertTrue(np.all(result[key].view(np.uint32) == 0)) + for key in ('spike_count_gate', 'spike_count_total'): + self.assertEqual(result[key].dtype, np.dtype('int32')) + self.assertFalse(result[key].any()) + + def test_non_kc_events_ignored_only_after_full_validation(self): + ticks, nodes = events([(0, 2), (0, 3), (1, 4)]) + for value in (ticks, nodes, self.kc): + value.flags.writeable = False + before = [value.tobytes() for value in (ticks, nodes, self.kc)] + result = replay_credit(ticks, nodes, self.kc, steps=2, gate_tick=1) + self.assertEqual(result['total_input_events'], 3) + self.assertEqual(result['total_KC_events'], 1) + self.assertEqual(before, [value.tobytes() for value in (ticks, nodes, self.kc)]) + result['trace_gate'][0] = 0 + self.assertGreater(result['trace_final'][0], 0) + + def test_invalid_event_order_duplicate_ranges_and_dtype(self): + bad_rows = [[(-1, 3)], [(1000, 3)], [(0, -1)], [(0, N_GLOBAL)], + [(1, 3), (0, 3)], [(0, 9), (0, 3)], [(0, 3), (0, 3)], [(0, 2), (0, 2)]] + for rows in bad_rows: + with self.subTest(rows=rows), self.assertRaises(ValueError): + replay_credit(*events(rows), self.kc) + for dtype in (np.int64, np.float32, np.float64): + with self.subTest(dtype=dtype), self.assertRaises(ValueError): + replay_credit(np.array([], dtype), np.array([], dtype), self.kc) + with self.assertRaises(ValueError): + replay_credit(np.array([0], np.int32), np.array([], np.int32), self.kc) + with self.assertRaises(ValueError): + replay_credit(np.array([np.nan]), np.array([3], np.int32), self.kc) + + def test_invalid_kc_identities_and_frozen_parameters(self): + empty = np.empty(0, np.int32) + for kc in (empty, np.array([9, 3], np.int32), np.array([3, 3], np.int32), + np.array([-1], np.int32), np.array([N_GLOBAL], np.int32), self.kc.astype(np.int64)): + with self.subTest(kc=kc.tolist()), self.assertRaises(ValueError): + replay_credit(empty, empty, kc) + for keyword, value in (('steps', 0), ('steps', True), ('gate_tick', -1), ('gate_tick', 1000), + ('gate_tick', 900.), ('dt_ms', .2), ('tau_ms', 20), ('tau_ms', np.inf), + ('cap', .5), ('cap', True)): + with self.subTest(keyword=keyword, value=value), self.assertRaises(ValueError): + replay_credit(empty, empty, self.kc, **{keyword: value}) + + def test_independent_frozen_numpy_loop_ast_matches_all_trace_bits(self): + tree, path = frozen_tree('phase4o_event_replay.py') + loops = [node for node in ast.walk(tree) if isinstance(node, ast.For) and isinstance(node.target, ast.Name) + and node.target.id == 'step' and any(isinstance(child, ast.AugAssign) and + isinstance(child.target, ast.Name) and child.target.id == 'trace' for child in node.body)] + self.assertEqual(len(loops), 1) + self.assertEqual(len(loops[0].body), 4) + code = compile(ast.fix_missing_locations(ast.Module(body=[loops[0]], type_ignores=[])), str(path), 'exec') + ticks, nodes = events([(0, 3), (0, 12), (1, 9), (22, 3), (899, 9), (900, 3), (901, 12), (999, 3)]) + result = replay_credit(ticks, nodes, self.kc) + lookup = {int(node): index for index, node in enumerate(self.kc)} + for gate, field in ((900, 'trace_gate'), (999, 'trace_final')): + by_step = {} + for tick, node in zip(ticks, nodes): + by_step.setdefault(int(tick), []).append(lookup[int(node)]) + namespace = dict(np=np, trace=np.zeros(len(self.kc), np.float32), + decay=np.float32(math.exp(-.1 / 100)), by_step=by_step, step_gate=gate) + exec(code, namespace) + assert_bits(self, result[field], namespace['trace']) + + def test_independent_frozen_torch_cpu_statement_matches_when_available(self): + try: + import torch + except (ImportError, OSError) as error: + self.skipTest('Torch CPU unavailable; comparison explicitly not performed: ' + str(error)) + tree, path = frozen_tree('phase4l.py') + expressions = [node for node in ast.walk(tree) if isinstance(node, ast.Expr) and + 'trace.mul_(trace_decay).add_' in ast.unparse(node)] + self.assertEqual(len(expressions), 1) + code = compile(ast.fix_missing_locations(ast.Module(body=expressions, type_ignores=[])), str(path), 'exec') + ticks, nodes = events([(0, 3), (22, 3), (899, 9), (900, 3), (901, 12), (999, 9)]) + result = replay_credit(ticks, nodes, self.kc) + trace = torch.zeros(len(self.kc), dtype=torch.float32, device='cpu') + namespace = dict(trace=trace, trace_decay=math.exp(-.1 / 100), torch=torch, + self=types.SimpleNamespace(kc_gpu=torch.tensor(self.kc.astype(np.int64), device='cpu'))) + gate = None + for tick in range(1000): + spikes = torch.zeros(13, dtype=torch.bool, device='cpu') + active = nodes[ticks == tick] + if len(active): + spikes[torch.tensor(active.astype(np.int64), device='cpu')] = True + namespace['spikes'] = spikes + exec(code, namespace) + if tick == 900: + gate = trace.numpy().copy() + assert_bits(self, result['trace_gate'], gate) + assert_bits(self, result['trace_final'], trace.numpy()) + + +class IdentityTests(unittest.TestCase): + def setUp(self): + self.a, self.b = np.zeros((5, 4), np.float32), np.zeros((5, 4), np.float32) + self.a[:3, 0] = 1 # A specific + self.a[:3, 1] = .1; self.b[:4, 1] = .2 # shared + self.b[:3, 2] = .3 # B specific + self.a[:2, 3] = 1; self.b[:2, 3] = 1 # no majority + self.source = np.array([0, 1, 1, 2, 3], np.int32) + + def test_three_of_five_categories_and_full_set_jaccard(self): + result = pair_identity(self.a, self.b, self.source) + np.testing.assert_array_equal(result['kc_category'], np.array([1, 3, 2, 0], np.int8)) + np.testing.assert_array_equal(result['edge_category'], np.array([1, 3, 3, 2, 0], np.int8)) + self.assertEqual(result['summary']['KC']['active_set_jaccard'], 1 / 3) + self.assertEqual(result['summary']['edges']['active_set_jaccard'], .5) + self.assertEqual(result['summary']['KC']['category_counts'], {name: 1 for name in CATEGORY_CODES}) + self.assertTrue(result['summary']['edge_counts_are_source_degree_weighted']) + + def test_tiny_positive_no_epsilon_and_no_weight_update_outputs(self): + self.a[:3, 0] = np.nextafter(np.float32(0), np.float32(1)) + result = pair_identity(self.a, self.b, self.source) + self.assertTrue(result['kc_active_a'][0]) + self.assertFalse(result['summary']['weights_modified']) + self.assertFalse(result['summary']['weight_delta_generated']) + self.assertFalse(any('delta' in key or 'weight' in key for key in result if key != 'summary')) + + def test_empty_union_and_empty_edge_mapping_explicit(self): + result = pair_identity(np.zeros_like(self.a), np.zeros_like(self.b), np.empty(0, np.int32)) + self.assertTrue(result['summary']['KC']['empty_union']) + self.assertEqual(result['summary']['KC']['active_set_jaccard'], 1.) + self.assertTrue(result['summary']['edges']['empty_union']) + self.assertEqual(result['edge_category'].dtype, np.dtype('int8')) + + def test_readonly_inputs_and_returned_mapping_owns_memory(self): + for value in (self.a, self.b, self.source): + value.flags.writeable = False + before = [value.tobytes() for value in (self.a, self.b, self.source)] + result = pair_identity(self.a, self.b, self.source) + result['edge_category'][0] = 0 + self.assertEqual(result['kc_category'][0], 1) + self.assertEqual(before, [value.tobytes() for value in (self.a, self.b, self.source)]) + + def test_reject_wrong_dtype_shape_nonfinite_negative_cap_and_source(self): + for bad in (self.a.astype(np.float64), self.a[:4], np.zeros((5, 0), np.float32)): + with self.subTest(shape=bad.shape), self.assertRaises(ValueError): + pair_identity(bad, self.b, self.source) + for value in (np.nan, np.inf, -.1, 1.01): + bad = self.a.copy(); bad[0, 0] = value + with self.subTest(value=value), self.assertRaises(ValueError): + pair_identity(bad, self.b, self.source) + with self.assertRaises(ValueError): + pair_identity(self.a, self.b[:, :3], self.source) + for source in (np.array([-1], np.int32), np.array([4], np.int32), self.source.astype(np.int64)): + with self.subTest(source=source.tolist()), self.assertRaises(ValueError): + pair_identity(self.a, self.b, source) + + +if __name__ == '__main__': + unittest.main() diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/test_integration.py b/models/male-cns-lif/mb-credit-transfer-audit-v1/test_integration.py new file mode 100644 index 0000000..fe9b580 --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/test_integration.py @@ -0,0 +1,56 @@ +"""Synthetic interface and fail-closed schedule checks, no scientific records.""" +import ast +from pathlib import Path +import unittest +import numpy as np +from run_audit import compare_results +from summarize import metrics, primary_rows + + +class IntegrationTests(unittest.TestCase): + def test_per_neuron_count_difference_not_cancelled_by_equal_total(self): + a = dict(step=np.array([0, 1], np.int32), neuron_idx=np.array([1, 1], np.int32), + counts=np.array([2, 0], np.int32), first_spike=np.array([0, -1], np.int32), + v=np.array([-.052, -.052], np.float64), g=np.zeros(2, np.float64)) + b = {k: v.copy() for k, v in a.items()} + b['neuron_idx'][:] = 2; b['counts'][:] = [0, 2]; b['first_spike'][:] = [-1, 0] + h = dict(history_v=np.zeros((2, 2)), history_g=np.zeros((2, 2))) + result = compare_results(a, b, h, h) + self.assertEqual(result['spike_count_L1'], 4) + self.assertEqual(result['neurons_with_count_change'], 2) + self.assertTrue(result['functional_count_or_first_latency_change']) + + def test_event_difference_with_same_counts_and_first_is_retained(self): + a = dict(step=np.array([0, 3], np.int32), neuron_idx=np.array([1, 1], np.int32), + counts=np.array([2], np.int32), first_spike=np.array([0], np.int32), + v=np.zeros(1), g=np.zeros(1)) + b = {k: v.copy() for k, v in a.items()}; b['step'][1] = 4 + h = dict(history_v=np.zeros((5, 1)), history_g=np.zeros((5, 1))) + result = compare_results(a, b, h, h) + self.assertTrue(result['event_sequence_changed']) + self.assertFalse(result['functional_count_or_first_latency_change']) + + def test_undefined_denominator_is_not_silently_zero(self): + self.assertIsNone(metrics([])['mean']) + + def test_repeat_not_an_independent_primary_trial(self): + rows = [dict(name=str(i), repeat=0) for i in range(120)] + [dict(name=str(i), repeat=1) for i in range(24)] + self.assertEqual(len(primary_rows(dict(planned=rows))), 120) + rows[1]['name'] = '0' + with self.assertRaises(AssertionError): + primary_rows(dict(planned=rows)) + + def test_all_baseline_gate_precedes_conditional_schedule(self): + tree = ast.parse((Path(__file__).parent / 'run_audit.py').read_text()) + main = next(n for n in tree.body if isinstance(n, ast.FunctionDef) and n.name == 'main') + loops = [n for n in ast.walk(main) if isinstance(n, ast.For) and isinstance(n.target, ast.Name) and n.target.id == 'stage'] + self.assertEqual(len(loops), 1) + self.assertEqual(ast.literal_eval(loops[0].iter), ('baseline', 'conditional25')) + audit = next(n for n in tree.body if isinstance(n, ast.FunctionDef) and n.name == 'audit_trial') + source = ast.unparse(audit) + self.assertIn("baselines-complete.json", source) + self.assertLess(source.index("baselines-complete.json"), source.index('core.replay')) + + +if __name__ == '__main__': + unittest.main() diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/test_mbon_accounting.py b/models/male-cns-lif/mb-credit-transfer-audit-v1/test_mbon_accounting.py new file mode 100644 index 0000000..09dcbd7 --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/test_mbon_accounting.py @@ -0,0 +1,179 @@ +"""Synthetic-only tests; no recorded scientific data, GPU, or file writes.""" +import importlib.util +import json +from pathlib import Path +import unittest + +import numpy as np + +from mbon_accounting import MBONAccounting, bit_equal + + +_source = Path(__file__).resolve().parents[1] / "kc-drive-audit-v1" / "replay_core.py" +_spec = importlib.util.spec_from_file_location("_mbon_test_frozen_ah_replay", _source) +ah = importlib.util.module_from_spec(_spec) +_spec.loader.exec_module(ah) + + +def coeff(**changes): + values = dict(gd=.5, c0=0., cg=1., cv=1., threshold=100., reset=0., seed_volt=101.) + values.update(changes) + return values + + +def events(rows=()): + array = np.asarray(rows, np.int32).reshape(-1, 2) + return dict(tick=array[:, 0], neuron_idx=array[:, 1]) + + +def graph(weights=(), destinations=None, n=1): + e = len(weights) + return ah.IncomingIndex(np.arange(10, 10 + e, dtype=np.int32), + np.zeros(e, np.int32) if destinations is None else np.array(destinations, np.int32), + np.arange(1000, 1000 + e, dtype=np.int64), np.array(weights, np.float64), n) + + +def run(index, *, groups=None, names=("plastic_KC",), steps=25, constants=None, + spikes=(), requests=(), v=None, g=None, observer_hook=None): + constants = coeff() if constants is None else constants + groups = np.zeros(len(index.edge_id), np.int32) if groups is None else np.array(groups, np.int32) + obs = MBONAccounting(index, groups, names, constants, steps) + seen = [] + + def callback(tick, stage): + # Read-only views also catch accidental assignments to callback data. + original = {key: value.copy() for key, value in stage.items()} + for value in stage.values(): + value.setflags(write=False) + obs(tick, stage) + for key in original: + if not bit_equal(stage[key], original[key]): + raise AssertionError("Observer modified callback field " + key) + if observer_hook: + observer_hook(tick, stage) + seen.append(original) + + result = ah.replay(np.zeros(index.target_count, np.float64) if v is None else np.asarray(v, np.float64), + np.zeros(index.target_count, np.float64) if g is None else np.asarray(g, np.float64), + constants, steps, np.arange(100, 100 + index.target_count, dtype=np.int32), + events(requests), events(spikes), index, + np.zeros((steps, index.target_count), np.float32), callback) + data, edges, summary = obs.finish() + return data, edges, summary, result, seen, obs + + +class AccountingTests(unittest.TestCase): + def test_empty_graph_initial_baseline_and_json_summary(self): + data, edge, summary, result, _, _ = run(graph(), steps=3, g=[2.], v=[-.052]) + self.assertEqual(summary["due_count"], 0) + self.assertEqual(len(edge["edge_id"]), 0) + np.testing.assert_array_equal(data["history_group_g"], 0.) + np.testing.assert_array_equal(data["history_g"], data["history_baseline_g"]) + self.assertTrue(bit_equal(data["final_g"], result["g"])) + json.dumps(summary, allow_nan=False) + self.assertFalse(summary["functional_transfer_claim"]) + self.assertFalse(summary["original_events_verified_by_observer"]) + + def test_real_delay_old_g_for_voltage_and_end_tick_integral(self): + data, edge, summary, _, _, _ = run(graph([2.]), steps=21, spikes=[(0, 10)]) + np.testing.assert_array_equal(data["history_g"][:18], 0.) + np.testing.assert_array_equal(data["history_g"][18:, 0], [2., 1., .5]) + np.testing.assert_array_equal(data["history_v"][18:, 0], [0., 2., 3.]) + self.assertAlmostEqual(data["g_integral_V_ms"][0, 0], .35) + np.testing.assert_array_equal(edge["accepted_count"], [1]) + self.assertEqual(summary["max_g_lane_residual_V"], 0.) + + def test_arrival_rejected_on_fire_and_refractory_release(self): + data, edge, summary, result, _, _ = run(graph([2., -1.]), steps=41, + spikes=[(t, source) for t in (0, 1, 22) for source in (10, 11)], requests=[(18, 100)]) + np.testing.assert_array_equal(edge["due_count"], [3, 3]) + np.testing.assert_array_equal(edge["accepted_count"], [1, 1]) + np.testing.assert_array_equal(edge["rejected_count"], [2, 2]) + np.testing.assert_array_equal(data["history_g"][18:40], 0.) + self.assertEqual(data["history_g"][40, 0], 1.) + self.assertEqual(data["rejected_positive_V"][0, 0], 4.) + self.assertEqual(data["rejected_negative_V"][0, 0], -2.) + self.assertEqual(data["accepted_negative_V"][0, 0], -1.) + np.testing.assert_array_equal(data["spike_count"], result["counts"]) + self.assertEqual(summary["accepted_count"], 2) + + def test_firing_clears_source_g_and_voltage_lanes(self): + data, _, _, result, _, _ = run(graph([2.]), steps=21, constants=coeff(threshold=1., seed_volt=2.), + spikes=[(0, 10)]) + self.assertEqual(data["first_spike_tick"][0], 19) + np.testing.assert_array_equal(data["history_group_g"][19:], 0.) + np.testing.assert_array_equal(data["final_group_v"], 0.) + self.assertEqual(data["history_ref"][19, 0], 22) + self.assertEqual(data["history_ref"][20, 0], 21) + self.assertTrue(bit_equal(data["final_ref"], result["ref"])) + + def test_group_sign_totals_and_zero_weight_event_counts(self): + index = graph([2., -3., 0., 4.], destinations=[0, 0, 1, 1], n=2) + data, edge, summary, _, _, _ = run(index, groups=[0, 1, 0, 1], names=("plastic_KC", "other"), + steps=19, spikes=[(0, x) for x in range(10, 14)]) + np.testing.assert_array_equal(data["accepted_count"], [[1, 1], [1, 1]]) + np.testing.assert_array_equal(data["accepted_zero_count"], [[0, 0], [1, 0]]) + np.testing.assert_array_equal(data["accepted_positive_V"], [[2., 0.], [0., 4.]]) + np.testing.assert_array_equal(data["accepted_negative_V"], [[0., -3.], [0., 0.]]) + self.assertEqual(summary["groups"]["other"]["accepted_negative_V"], -3.) + self.assertEqual(int(edge["due_count"].sum()), 4) + + def test_cross_lane_roundoff_is_visible_not_reassigned(self): + data, _, summary, _, _, _ = run(graph([1.e16, 1., -1.e16]), groups=[0, 1, 0], + names=("plastic_KC", "other"), steps=19, constants=coeff(threshold=1.e30, seed_volt=2.e30), + spikes=[(0, 10), (0, 11), (0, 12)]) + self.assertEqual(data["history_g"][18, 0], 0.) + self.assertEqual(data["history_group_g"][18, 0, 1, 0], 1.) + self.assertEqual(data["history_g_residual"][18, 0], -1.) + self.assertEqual(summary["max_g_lane_residual_V"], 1.) + + def test_callback_and_constructor_inputs_never_modified(self): + index = graph([1., -.25]) + snapshots = {name: getattr(index, name).copy() for name in ("src_global", "dst_local", "edge_id", "weights")} + run(index, spikes=[(0, 10), (0, 11)], requests=[(1, 100)]) + for name, original in snapshots.items(): + self.assertTrue(bit_equal(getattr(index, name), original)) + + def test_incomplete_duplicate_tick_and_repeated_finish_fail(self): + index = graph() + with self.assertRaises(ValueError): + MBONAccounting(index, np.empty(0, np.int32), ("other",), coeff(), 2).finish() + _, _, _, _, stages, finished = run(index, steps=2) + with self.assertRaises(ValueError): + finished.finish() + obs = MBONAccounting(index, np.empty(0, np.int32), ("other",), coeff(), 2) + obs(0, stages[0]) + with self.assertRaises(ValueError): + obs(0, stages[0]) + + def test_bad_dtype_groups_coefficients_and_nonfinite_fail(self): + index = graph([1.]) + for codes in (np.array([0], np.int64), np.array([1], np.int32), np.array([], np.int32)): + with self.assertRaises(ValueError): + MBONAccounting(index, codes, ("other",), coeff(), 2) + for bad in (coeff(gd=np.float32(.5)), coeff(gd=float("nan")), coeff(dt_ms=.2)): + with self.assertRaises(ValueError): + MBONAccounting(index, np.array([0], np.int32), ("other",), bad, 2) + + def test_stage_guard_apl_and_canonical_order_corruption_fail(self): + index = graph([1., 2.]) + _, _, _, _, stages, _ = run(index, steps=19, spikes=[(0, 10), (0, 11)]) + for corruption in ("guard", "order", "apl", "state"): + obs = MBONAccounting(index, np.array([0, 0], np.int32), ("other",), coeff(), 19) + for tick in range(18): + obs(tick, stages[tick]) + stage = {k: v.copy() for k, v in stages[18].items()} + if corruption == "guard": + stage["arrival_accepted"][0] = False + elif corruption == "order": + stage["due_edge_indices"] = stage["due_edge_indices"][::-1].copy() + elif corruption == "apl": + stage["h32"][0] = 1. + else: + stage["g_pre_apl"][0] += 1. + with self.subTest(corruption=corruption), self.assertRaises(ValueError): + obs(18, stage) + + +if __name__ == "__main__": + unittest.main() diff --git a/models/male-cns-lif/mb-credit-transfer-audit-v1/verify_frozen.py b/models/male-cns-lif/mb-credit-transfer-audit-v1/verify_frozen.py new file mode 100644 index 0000000..abff8ad --- /dev/null +++ b/models/male-cns-lif/mb-credit-transfer-audit-v1/verify_frozen.py @@ -0,0 +1,61 @@ +"""Rerun old deterministic-v2 references without changing their semantics.""" +import json +import os +import sys +import time +import urllib.request +import numpy as np +import pandas as pd +import yaml +from context import ROOT, EXP, check, save, bit_equal + + +def preflight(): + os.environ['CUDA_VISIBLE_DEVICES'] = 'GPU-79f3a85d-adce-7833-7003-6488140ca596' + os.environ['CUDA_HOME'] = '/usr/local/cuda' + os.environ['PATH'] = str(ROOT / 'models/male-cns-lif/.venv/bin') + ':/usr/local/cuda/bin:' + os.environ['PATH'] + os.environ['MAX_JOBS'] = '2' + os.environ['TORCH_CUDA_ARCH_LIST'] = '8.9' + for port in (8188, 8189, 8190): + with urllib.request.urlopen(f'http://192.168.10.51:{port}/queue', timeout=5) as response: + queue = json.load(response) + assert not queue['queue_running'] and not queue['queue_pending'], 'Comfy busy: defer, do not evict' + + +def main(): + check(); preflight() + assert not (EXP / 'regression/frozen-five.json').exists() + runtime_path = ROOT / 'models/male-cns-lif/deterministic-runtime-v2' + config = yaml.safe_load((runtime_path / 'phase4p.yaml').read_text()) + sys.path.insert(0, str(ROOT / 'models/male-cns-lif')) + sys.path.insert(0, str(runtime_path)) + import torch + import phase4p + assert torch.cuda.mem_get_info()[0] > 2 * 1024**3 + torch.cuda.reset_peak_memory_stats() + started = time.perf_counter() + runtime = phase4p.CanonicalRuntime(config, runtime_path, EXP) + rows = [] + for spec in config['reference_trials']: + preflight() + reference_dir = ROOT / 'experiments/phase4p-deterministic-runtime/phase4c-v2/reference' / spec['name'] + events = pd.read_parquet(reference_dir / 'spike-events.parquet') + reference = dict(step=events.step.to_numpy(), neuron_idx=events.neuron_idx.to_numpy(), + counts=np.load(reference_dir / 'per-neuron-spike-counts.int32.npy'), + v=np.load(reference_dir / 'final-voltage.float32.npy'), g=np.load(reference_dir / 'final-g.float32.npy')) + result = runtime.run(np.flatnonzero(runtime.pops[spec['population']]), spec['rate_hz'], spec['seed'], spec['duration_ms']) + row = dict(trial=spec['name'], exact={k: bit_equal(v, result[k]) for k, v in reference.items()}, + dtype_shape={k: dict(reference_dtype=str(v.dtype), actual_dtype=str(result[k].dtype), + reference_shape=list(v.shape), actual_shape=list(result[k].shape)) for k, v in reference.items()}, + wall_seconds=result['metrics']['wall_seconds']) + rows.append(row) + print(row, flush=True) + passed = len(rows) == 5 and all(all(row['exact'].values()) for row in rows) 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`PASS-CONDITIONAL-CREDIT-TRANSFER-AUDIT-NOT-LEARNING`. + +All 120 primary trials and 24 repeats are retained. Full events/counts/final V/g/ref baseline exactness is required. +Virtual eligibility is sampled after tick 900; no DAN is injected, no delta is learned. +Uniform 25% mask depression is a temporary conditional replay; every source train, including feedback, is clamped. +All 60 odor pair-mode records and all 97 MBON targets are reported; no best pair/parameter selection. + +- novel_to_aj/matched_energy: specific KC/edge sets 15/15; conditional event change 30/30; count/first-latency change 30/30. +- novel_to_aj/physiological: specific KC/edge sets 15/15; conditional event change 30/30; count/first-latency change 30/30. +- seed_validation/matched_energy: specific KC/edge sets 15/15; conditional event change 30/30; count/first-latency change 30/30. +- seed_validation/physiological: specific KC/edge sets 15/15; conditional event change 30/30; count/first-latency change 30/30. + +No biological learning PASS or candidate. 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+0a3944c5a046e1e62de4aaa906655c397db8cd220f47a1eb76cf1d8fe949ffaa trials/seed_validation-physiological-05-s1073741829-r0/output-hashes.json +ceead142964e5ead610d2fda40769d0bd4d197220a7a0caa5975cdfcd054f66b trials/seed_validation-physiological-05-s1073741829-r0/sensitivity.json +8d9fa9923bfc1f6730e6b63c0822cac0785aa54f81162fa8c55b7c9cb40dc458 trials/seed_validation-physiological-05-s1073741829-r0/summary.json +a22de7d85cbfe760070ff55f5666e74475a3335c63bbd37b41241a94be7e3eea manifest.json diff --git a/registry/phase4al-mb-credit-transfer/evidence/gpu-reference/extension.json b/registry/phase4al-mb-credit-transfer/evidence/gpu-reference/extension.json new file mode 100644 index 0000000..2932b59 --- /dev/null +++ b/registry/phase4al-mb-credit-transfer/evidence/gpu-reference/extension.json @@ -0,0 +1,17 @@ +{ + "binary": "/data/digital-drosophila/experiments/phase4al-mb-credit-transfer/gpu-reference/extension-build/male_cns_lif_deterministic_v2_ext.so", + "binary_sha256": "3e6655c02a85c21fd4370771dc7e07c5157f223e2ae4aa3d91c926b0e3022a62", + "build_seconds": 54.55150726200009, + "flags": { + "cuda": [ + "-O3", + "--fmad=false", + "-std=c++20" + ], + "cxx": [ + "-O3", + "-ffp-contract=off" + ] + }, + "status": "PASS" +} diff --git a/registry/phase4al-mb-credit-transfer/evidence/logs/reference-console.log b/registry/phase4al-mb-credit-transfer/evidence/logs/reference-console.log new file mode 100644 index 0000000..44a5ed9 --- /dev/null +++ b/registry/phase4al-mb-credit-transfer/evidence/logs/reference-console.log @@ -0,0 +1,10 @@ +/data/digital-drosophila/models/male-cns-lif/phase4c.py:308: UserWarning: The given NumPy array is not writable, and PyTorch does not support non-writable tensors. This means writing to this tensor will result in undefined behavior. You may want to copy the array to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /__w/pytorch/pytorch/torch/csrc/utils/tensor_numpy.cpp:213.) + self.indptr = torch.as_tensor(np.asarray(indptr_np), dtype=torch.int64, device=device) +[1/3] c++ -MMD -MF phase4p_ext.o.d -DTORCH_EXTENSION_NAME=male_cns_lif_deterministic_v2_ext -DTORCH_API_INCLUDE_EXTENSION_H -isystem /data/digital-drosophila/models/male-cns-lif/.venv/lib/python3.10/site-packages/torch/include -isystem /data/digital-drosophila/models/male-cns-lif/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /usr/include/python3.10 -fPIC -std=c++20 -O3 -ffp-contract=off -c /data/digital-drosophila/models/male-cns-lif/deterministic-runtime-v2/phase4p_ext.cpp -o phase4p_ext.o +[2/3] /usr/local/cuda/bin/nvcc -MD -MF phase4p_ext.cuda.o.d -DTORCH_EXTENSION_NAME=male_cns_lif_deterministic_v2_ext -DTORCH_API_INCLUDE_EXTENSION_H -isystem /data/digital-drosophila/models/male-cns-lif/.venv/lib/python3.10/site-packages/torch/include -isystem /data/digital-drosophila/models/male-cns-lif/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /usr/include/python3.10 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_89,code=sm_89 --compiler-options '-fPIC' -O3 --fmad=false -std=c++20 -c /data/digital-drosophila/models/male-cns-lif/deterministic-runtime-v2/phase4p_ext.cu -o phase4p_ext.cuda.o +[3/3] c++ phase4p_ext.o phase4p_ext.cuda.o -shared -L/data/digital-drosophila/models/male-cns-lif/.venv/lib/python3.10/site-packages/torch/lib -lc10 -lc10_cuda -ltorch_cpu -ltorch_cuda -ltorch -ltorch_python -L/usr/local/cuda/lib64 -lcudart -o male_cns_lif_deterministic_v2_ext.so +{'trial': 'auditory-10hz', 'exact': {'step': True, 'neuron_idx': True, 'counts': True, 'v': True, 'g': True}, 'dtype_shape': {'step': {'reference_dtype': 'int32', 'actual_dtype': 'int32', 'reference_shape': [609920], 'actual_shape': [609920]}, 'neuron_idx': {'reference_dtype': 'int32', 'actual_dtype': 'int32', 'reference_shape': [609920], 'actual_shape': [609920]}, 'counts': {'reference_dtype': 'int32', 'actual_dtype': 'int32', 'reference_shape': [166700], 'actual_shape': [166700]}, 'v': {'reference_dtype': 'float32', 'actual_dtype': 'float32', 'reference_shape': [166700], 'actual_shape': [166700]}, 'g': {'reference_dtype': 'float32', 'actual_dtype': 'float32', 'reference_shape': [166700], 'actual_shape': [166700]}}, 'wall_seconds': 2.686470789998566} +{'trial': 'auditory-100hz', 'exact': {'step': True, 'neuron_idx': True, 'counts': True, 'v': True, 'g': True}, 'dtype_shape': {'step': {'reference_dtype': 'int32', 'actual_dtype': 'int32', 'reference_shape': [2321608], 'actual_shape': [2321608]}, 'neuron_idx': {'reference_dtype': 'int32', 'actual_dtype': 'int32', 'reference_shape': [2321608], 'actual_shape': [2321608]}, 'counts': {'reference_dtype': 'int32', 'actual_dtype': 'int32', 'reference_shape': [166700], 'actual_shape': [166700]}, 'v': {'reference_dtype': 'float32', 'actual_dtype': 'float32', 'reference_shape': [166700], 'actual_shape': [166700]}, 'g': {'reference_dtype': 'float32', 'actual_dtype': 'float32', 'reference_shape': [166700], 'actual_shape': [166700]}}, 'wall_seconds': 4.9066673909983365} +{'trial': 'olfactory-50hz', 'exact': {'step': True, 'neuron_idx': True, 'counts': True, 'v': True, 'g': True}, 'dtype_shape': {'step': {'reference_dtype': 'int32', 'actual_dtype': 'int32', 'reference_shape': [2806702], 'actual_shape': [2806702]}, 'neuron_idx': {'reference_dtype': 'int32', 'actual_dtype': 'int32', 'reference_shape': [2806702], 'actual_shape': [2806702]}, 'counts': {'reference_dtype': 'int32', 'actual_dtype': 'int32', 'reference_shape': [166700], 'actual_shape': [166700]}, 'v': {'reference_dtype': 'float32', 'actual_dtype': 'float32', 'reference_shape': [166700], 'actual_shape': [166700]}, 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'counts': True, 'v': True, 'g': True}, 'dtype_shape': {'step': {'reference_dtype': 'int32', 'actual_dtype': 'int32', 'reference_shape': [2452226], 'actual_shape': [2452226]}, 'neuron_idx': {'reference_dtype': 'int32', 'actual_dtype': 'int32', 'reference_shape': [2452226], 'actual_shape': [2452226]}, 'counts': {'reference_dtype': 'int32', 'actual_dtype': 'int32', 'reference_shape': [166700], 'actual_shape': [166700]}, 'v': {'reference_dtype': 'float32', 'actual_dtype': 'float32', 'reference_shape': [166700], 'actual_shape': [166700]}, 'g': {'reference_dtype': 'float32', 'actual_dtype': 'float32', 'reference_shape': [166700], 'actual_shape': [166700]}}, 'wall_seconds': 4.939488880001591} diff --git a/registry/phase4al-mb-credit-transfer/evidence/logs/replay-console.log b/registry/phase4al-mb-credit-transfer/evidence/logs/replay-console.log new file mode 100644 index 0000000..a8e0469 --- /dev/null +++ b/registry/phase4al-mb-credit-transfer/evidence/logs/replay-console.log @@ -0,0 +1,288 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2899, + "mismatches": [], + "manifest_sha256": "25eb7e467eb17c3fa83ffee2e4e82b754f161fd8891e515bed23eeb500c5656d", + "checksums_sha256": "65c9ee6e90a49fd22282a977d3770a07567c47f4303e12359239dd9c77246af2" + } +} diff --git a/registry/phase4al-mb-credit-transfer/evidence/regression/unit-tests.log b/registry/phase4al-mb-credit-transfer/evidence/regression/unit-tests.log new file mode 100644 index 0000000..9eec4fb --- /dev/null +++ b/registry/phase4al-mb-credit-transfer/evidence/regression/unit-tests.log @@ -0,0 +1,34 @@ +test_empty_union_and_empty_edge_mapping_explicit (test_credit.IdentityTests) ... ok +test_readonly_inputs_and_returned_mapping_owns_memory (test_credit.IdentityTests) ... ok +test_reject_wrong_dtype_shape_nonfinite_negative_cap_and_source (test_credit.IdentityTests) ... ok +test_three_of_five_categories_and_full_set_jaccard (test_credit.IdentityTests) ... ok +test_tiny_positive_no_epsilon_and_no_weight_update_outputs (test_credit.IdentityTests) ... ok +test_empty_events_are_positive_zero_with_exact_dtypes (test_credit.ReplayTests) ... ok +test_gate_900_includes_same_tick_901_is_final_only_no_18_shift (test_credit.ReplayTests) ... ok +test_independent_frozen_numpy_loop_ast_matches_all_trace_bits (test_credit.ReplayTests) ... ok +test_independent_frozen_torch_cpu_statement_matches_when_available (test_credit.ReplayTests) ... ok +test_invalid_event_order_duplicate_ranges_and_dtype (test_credit.ReplayTests) ... ok +test_invalid_kc_identities_and_frozen_parameters (test_credit.ReplayTests) ... ok +test_non_kc_events_ignored_only_after_full_validation (test_credit.ReplayTests) ... ok +test_spike_cap_resets_recency_not_accumulated_count (test_credit.ReplayTests) ... ok +test_tick_zero_gate_and_last_tick_have_no_extra_decay (test_credit.ReplayTests) ... ok +test_all_baseline_gate_precedes_conditional_schedule (test_integration.IntegrationTests) ... ok +test_event_difference_with_same_counts_and_first_is_retained (test_integration.IntegrationTests) ... ok +test_per_neuron_count_difference_not_cancelled_by_equal_total (test_integration.IntegrationTests) ... ok +test_repeat_not_an_independent_primary_trial (test_integration.IntegrationTests) ... ok +test_undefined_denominator_is_not_silently_zero (test_integration.IntegrationTests) ... ok +test_arrival_rejected_on_fire_and_refractory_release (test_mbon_accounting.AccountingTests) ... ok +test_bad_dtype_groups_coefficients_and_nonfinite_fail (test_mbon_accounting.AccountingTests) ... ok +test_callback_and_constructor_inputs_never_modified (test_mbon_accounting.AccountingTests) ... ok +test_cross_lane_roundoff_is_visible_not_reassigned (test_mbon_accounting.AccountingTests) ... ok +test_empty_graph_initial_baseline_and_json_summary (test_mbon_accounting.AccountingTests) ... ok +test_firing_clears_source_g_and_voltage_lanes (test_mbon_accounting.AccountingTests) ... ok +test_group_sign_totals_and_zero_weight_event_counts (test_mbon_accounting.AccountingTests) ... ok +test_incomplete_duplicate_tick_and_repeated_finish_fail (test_mbon_accounting.AccountingTests) ... ok +test_real_delay_old_g_for_voltage_and_end_tick_integral (test_mbon_accounting.AccountingTests) ... ok +test_stage_guard_apl_and_canonical_order_corruption_fail (test_mbon_accounting.AccountingTests) ... ok + +---------------------------------------------------------------------- +Ran 29 tests in 1.596s + +OK diff --git a/registry/phase4al-mb-credit-transfer/evidence/trials/novel_to_aj-matched_energy-00-s1073741825-r0/baseline-accounting.json b/registry/phase4al-mb-credit-transfer/evidence/trials/novel_to_aj-matched_energy-00-s1073741825-r0/baseline-accounting.json new file mode 100644 index 0000000..566946c --- /dev/null +++ b/registry/phase4al-mb-credit-transfer/evidence/trials/novel_to_aj-matched_energy-00-s1073741825-r0/baseline-accounting.json @@ -0,0 +1,125 @@ +{ + "complete": true, + "pass_all": true, + "pass_all_scope": "Observer callback coverage and internal count/state-accounting checks only", + "steps": 1000, + "callback_count": 1000, + "targets": 97, + "incoming_edges": 86039, + "group_names": [ + "plastic_KC", + "nonplastic_KC", + "DAN", + "MBON", + "APL", + "other" + ], + "sign_order": [ + "positive", + "negative" + ], + "dt_ms": 0.1, + "due_count": 45313, + "accepted_count": 41768, + "rejected_count": 3545, + "groups": { + "plastic_KC": { + "due_count": 540, + "accepted_count": 497, + "rejected_count": 43, + "accepted_zero_count": 0, + "rejected_zero_count": 0, + "accepted_positive_V": 0.9410499999999999, + "accepted_negative_V": 0.0, + "rejected_positive_V": 0.23430000000000004, + "rejected_negative_V": 0.0, + "g_integral_V_ms": 2.4881413537483574, + "g_positive_integral_V_ms": 2.4881413537483574, + "g_negative_integral_V_ms": 0.0 + }, + "nonplastic_KC": { + "due_count": 1830, + "accepted_count": 1553, + "rejected_count": 277, + "accepted_zero_count": 0, + "rejected_zero_count": 0, + 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4.371503159461554e-16, + "max_v_lane_residual_V": 1.2490009027033011e-15, + "residual_policy": "Observed state minus uncorrected float64 lane sum; no fitted tolerance or anatomical reassignment", + "integral_contract": "Sum of end-of-tick source g or v lanes times dt_ms; units V*ms, not conductance or energy", + "increment_contract": "Nominal accepted/rejected signed per-edge increments; negative fields retain negative sign", + "lane_contract": "Observed availability controls decay/integration; observed request/reset clears voltage/source history; fired clears g; canonical accepted adds only", + "pending_coverage_checked_by_observer": false, + "original_events_verified_by_observer": false, + "caller_must_verify_original_events_final_and_queue_coverage": true, + "nonfeedback": true, + "parameter_changes": false, + "learning": false, + "functional_transfer_claim": false, + "whole_brain_intervention_claim": false +} diff --git a/registry/phase4al-mb-credit-transfer/evidence/trials/novel_to_aj-matched_energy-00-s1073741825-r0/baseline-summary.json b/registry/phase4al-mb-credit-transfer/evidence/trials/novel_to_aj-matched_energy-00-s1073741825-r0/baseline-summary.json new file mode 100644 index 0000000..7ba0817 --- /dev/null +++ b/registry/phase4al-mb-credit-transfer/evidence/trials/novel_to_aj-matched_energy-00-s1073741825-r0/baseline-summary.json @@ -0,0 +1,26 @@ +{ + "name": "novel_to_aj-matched_energy-00-s1073741825", + "cohort": "novel_to_aj", + "source_panel_split": "heldout", + "source_panel_row": 6, + "mode": "matched_energy", + "odor_id": "YSNWHRKJEKWJNY-UHFFFAOYSA-N", + "odor_index": 0, + "seed": 1073741825, + "targets": 35, + "requests": 109, + "expected_external_events": 102.2443115234375, + "rates_sum": 1022.443115234375, + "repeat": 0, + "pass_all": true, + "baseline_exact": { + "counts": true, + "v": true, + "g": true, + "ref": true, + "step": true, + "neuron_idx": true + }, + "due_plus_pending_source_events_exact": true, + "CPU_wall_seconds": 1.030301637998491 +} diff --git a/registry/phase4al-mb-credit-transfer/evidence/trials/novel_to_aj-matched_energy-00-s1073741825-r0/conditional25-accounting.json b/registry/phase4al-mb-credit-transfer/evidence/trials/novel_to_aj-matched_energy-00-s1073741825-r0/conditional25-accounting.json new file mode 100644 index 0000000..ca519de --- /dev/null +++ b/registry/phase4al-mb-credit-transfer/evidence/trials/novel_to_aj-matched_energy-00-s1073741825-r0/conditional25-accounting.json @@ -0,0 +1,125 @@ +{ + "complete": true, + "pass_all": true, + "pass_all_scope": "Observer callback coverage and internal count/state-accounting checks only", + "steps": 1000, + "callback_count": 1000, + "targets": 97, + "incoming_edges": 86039, + "group_names": [ + "plastic_KC", + "nonplastic_KC", + "DAN", + "MBON", + "APL", + "other" + ], + "sign_order": [ + "positive", + "negative" + ], + "dt_ms": 0.1, + "due_count": 45313, + 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b/registry/phase4al-mb-credit-transfer/evidence/trials/novel_to_aj-matched_energy-00-s1073741825-r0/summary.json new file mode 100644 index 0000000..f32c77e --- /dev/null +++ b/registry/phase4al-mb-credit-transfer/evidence/trials/novel_to_aj-matched_energy-00-s1073741825-r0/summary.json @@ -0,0 +1,49 @@ +{ + "name": "novel_to_aj-matched_energy-00-s1073741825", + "cohort": "novel_to_aj", + "source_panel_split": "heldout", + "source_panel_row": 6, + "mode": "matched_energy", + "odor_id": "YSNWHRKJEKWJNY-UHFFFAOYSA-N", + "odor_index": 0, + "seed": 1073741825, + "targets": 35, + "requests": 109, + "expected_external_events": 102.2443115234375, + "rates_sum": 1022.443115234375, + "repeat": 0, + "pass_all": true, + "baseline_exact": { + "counts": true, + "v": true, + "g": true, + "ref": true, + "step": true, + "neuron_idx": true + }, + "sensitivity": { + "event_sequence_changed": true, + "spike_count_L1": 3, + "neurons_with_count_change": 3, + "neurons_with_first_latency_change": 10, + 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a/registry/phase4al-mb-credit-transfer/evidence/trials/novel_to_aj-matched_energy-00-s1073741825-r1/baseline-accounting.json b/registry/phase4al-mb-credit-transfer/evidence/trials/novel_to_aj-matched_energy-00-s1073741825-r1/baseline-accounting.json new file mode 100644 index 0000000..566946c --- /dev/null +++ b/registry/phase4al-mb-credit-transfer/evidence/trials/novel_to_aj-matched_energy-00-s1073741825-r1/baseline-accounting.json @@ -0,0 +1,125 @@ +{ + "complete": true, + "pass_all": true, + "pass_all_scope": "Observer callback coverage and internal count/state-accounting checks only", + "steps": 1000, + "callback_count": 1000, + "targets": 97, + "incoming_edges": 86039, + "group_names": [ + "plastic_KC", + "nonplastic_KC", + "DAN", + "MBON", + "APL", + "other" + ], + "sign_order": [ + "positive", + "negative" + ], + "dt_ms": 0.1, + "due_count": 45313, + "accepted_count": 41768, + "rejected_count": 3545, + "groups": { + "plastic_KC": { + "due_count": 540, + "accepted_count": 497, + 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"experiments/phase4al-mb-credit-transfer", + "complete_bulk_backup": false, + "scientific_gate_executed_by_publisher": false, + "scientific_gate_certified_by_publication": false, + "publication_success_is_not_scientific_pass": true, + "candidate_generated": false, + "learning_achieved": false, + "full_scientific_goal_achieved": false, + "old_heldout_dynamic_results_parsed": false, + "existing_files_modified": false, + "receipt_self_hash": "Not self-referential; returned by publish() and printed by main()", + "limits": { + "max_selected_evidence_file_bytes": 4194304, + "selected_suffixes": [ + ".csv", + ".json", + ".log", + ".md", + ".sha256" + ] + } +} diff --git a/registry/phase4al-mb-credit-transfer/seal-verification.json b/registry/phase4al-mb-credit-transfer/seal-verification.json new file mode 100644 index 0000000..7410495 --- /dev/null +++ b/registry/phase4al-mb-credit-transfer/seal-verification.json @@ -0,0 +1,22 @@ +{ + "model": { + "pass_all": true, + "root": "/data/digital-drosophila/models/male-cns-lif/mb-credit-transfer-audit-v1", + "payload_file_count": 14, + "payload_bytes": 109946, + "manifest_sha256": "72e4b4e2c53c258939ca355f31eeba2cd6381e126a61efeea651d8bac8df5328", + "checksums_sha256": "56f2d7817795ab763dc78c82b101ef6ee6d92d9fca482c2a3e970936048aecb3", + "excluded_pycache_files": 0, + "verification_scope": "All sealed payload bytes/SHA-256, exact checksum inventory, and manifest self-SHA; no scientific gate execution" + }, + "experiment": { + "pass_all": true, + "root": "/data/digital-drosophila/experiments/phase4al-mb-credit-transfer", + "payload_file_count": 2166, + "payload_bytes": 1336493035, + "manifest_sha256": "a22de7d85cbfe760070ff55f5666e74475a3335c63bbd37b41241a94be7e3eea", + "checksums_sha256": "8b7320af2c2c3ec7f6e1a28faf14849cbca0cc0326d4d34bb509e3ed9e0b3bc7", + "excluded_pycache_files": 0, + "verification_scope": "All sealed payload bytes/SHA-256, exact checksum inventory, and manifest self-SHA; no scientific gate execution" + } +} diff --git a/tools/phase4al-publication/fetch_phase4al.py b/tools/phase4al-publication/fetch_phase4al.py new file mode 100644 index 0000000..ab82d6f --- /dev/null +++ b/tools/phase4al-publication/fetch_phase4al.py @@ -0,0 +1,337 @@ +"""Fetch only externally anchored Phase 4AL small evidence and model source. + +No SSH connection is made at import. The API accepts an already authenticated +SFTP client; the CLI rejects unknown host keys. This is not a trajectory backup +or a local re-verification of remote bulk payloads/scientific gates. +""" +from __future__ import annotations + +import argparse +import hashlib +import json +import os +from pathlib import Path, PurePosixPath +import re +import stat + +REMOTE_ROOT = '/data/digital-drosophila' +MODEL_RELATIVE = 'models/male-cns-lif/mb-credit-transfer-audit-v1' +EXPERIMENT_RELATIVE = 'experiments/phase4al-mb-credit-transfer' +REGISTRY_RELATIVE = 'registry/phase4al-mb-credit-transfer' +MODEL_ROOT = REMOTE_ROOT + '/' + MODEL_RELATIVE +REGISTRY_ROOT = REMOTE_ROOT + '/' + REGISTRY_RELATIVE +DEFAULT_DESTINATION = Path(__file__).resolve().parents[2] / 'reports/phase4al-mb-credit-transfer' +MAX_FILE_BYTES = 4 * 1024**2 +MAX_TOTAL_BYTES = 1024**3 +EVIDENCE_SUFFIXES = frozenset(('.json', '.csv', '.md', '.log', '.sha256')) +SOURCE_SUFFIXES = frozenset(('.py', '.json', '.md', '.yaml', '.yml', '.toml', '.txt', '.sha256', '.cpp', '.cu', '.h', '.hpp')) +CONTROLS = ('manifest.json', 'checksums.sha256') +GENERATED = ('seal-verification.json', 'evidence-index.json') +SHA = re.compile(r'[0-9a-f]{64}\Z') + + +def require(condition, message): + if not condition: + raise ValueError(message) + + +def sha(data): + return hashlib.sha256(data).hexdigest() + + +def unique_object(pairs): + result = {} + for key, value in pairs: + require(key not in result, 'Duplicate JSON key: ' + key) + result[key] = value + return result + + +def json_bytes(data): + def bad(value): + raise ValueError('Nonfinite JSON constant: ' + value) + return json.loads(data.decode('utf-8'), object_pairs_hook=unique_object, parse_constant=bad) + + +def relative_name(value): + require(isinstance(value, str) and value and not any(c in value for c in ('\\', '\0', '\r', '\n', ':')), + 'Invalid relative filename') + path = PurePosixPath(value) + require(not path.is_absolute() and path.as_posix() == value and + all(part not in ('', '.', '..', '__pycache__') and not part.endswith((' ', '.')) for part in path.parts), + 'Noncanonical/escaping/cache filename: ' + value) + devices = {'CON', 'PRN', 'AUX', 'NUL', *(f'COM{i}' for i in range(1, 10)), *(f'LPT{i}' for i in range(1, 10))} + require(all(part.split('.')[0].upper() not in devices for part in path.parts), 'Reserved local filename') + return path + + +def file_row(row, *, small=False): + require(isinstance(row, dict) and set(row) == {'path', 'bytes', 'sha256'}, 'Invalid hash-inventory row') + relative_name(row['path']) + require(type(row['bytes']) is int and row['bytes'] >= 0 and isinstance(row['sha256'], str) and + SHA.fullmatch(row['sha256']), 'Invalid file size/SHA') + if small: + require(row['bytes'] <= MAX_FILE_BYTES, 'Receipt file exceeds 4 MiB: ' + row['path']) + return row + + +class BoundedSFTP: + def __init__(self, sftp): + self.sftp = sftp + self.directories = set() + + def read(self, remote, size=None, checksum=None): + require(remote.startswith(REGISTRY_ROOT + '/') or remote.startswith(MODEL_ROOT + '/'), + 'Remote request outside fixed AL registry/model scope') + # Never list a remote directory or discover unregistered sidecars. + parent = PurePosixPath(remote).parent + for directory in reversed((parent, *parent.parents)): + name = str(directory) + if name not in self.directories: + require(stat.S_ISDIR(self.sftp.lstat(name).st_mode), 'Remote symlink/non-directory: ' + name) + self.directories.add(name) + info = self.sftp.lstat(remote) + require(stat.S_ISREG(info.st_mode), 'Remote symlink/nonregular file: ' + remote) + require(0 <= info.st_size <= MAX_FILE_BYTES and (size is None or info.st_size == size), + 'Remote size outside expected small-file limit: ' + remote) + chunks, count = [], 0 + with self.sftp.open(remote, 'rb') as source: + while True: + block = source.read(min(1 << 20, MAX_FILE_BYTES + 1 - count)) + if not block: + break + count += len(block) + require(count <= MAX_FILE_BYTES, 'Remote file grew beyond download limit') + chunks.append(block) + data = b''.join(chunks) + require(len(data) == info.st_size and (size is None or len(data) == size), 'Remote size changed during read') + if checksum is not None: + require(sha(data) == checksum, 'Remote file SHA mismatch: ' + remote) + return data + + +def validate_receipt(data, expected_sha): + require(sha(data) == expected_sha, 'External publication-receipt SHA mismatch') + receipt = json_bytes(data) + require(isinstance(receipt, dict) and receipt.get('publication_complete') is True and + receipt.get('registry') == REGISTRY_RELATIVE and receipt.get('project_root') == REMOTE_ROOT, + 'Wrong/incomplete AL publication receipt') + for key in ('source_trees_verified_before_and_after_copy', 'publication_success_is_not_scientific_pass'): + require(receipt.get(key) is True, 'Missing publication qualification: ' + key) + for key in ('complete_bulk_backup', 'scientific_gate_executed_by_publisher', + 'scientific_gate_certified_by_publication', 'candidate_generated', 'learning_achieved'): + require(receipt.get(key) is False, 'Unexpected publication claim: ' + key) + require(receipt.get('limits') == dict(max_selected_evidence_file_bytes=MAX_FILE_BYTES, + selected_suffixes=sorted(EVIDENCE_SUFFIXES)), 'Unexpected publication selection limits') + for key in ('model_manifest_sha256', 'experiment_manifest_sha256'): + require(isinstance(receipt.get(key), str) and SHA.fullmatch(receipt[key]), 'Missing manifest anchor: ' + key) + rows = {} + require(isinstance(receipt.get('files'), list) and receipt['files'], 'Empty receipt inventory') + for row in receipt['files']: + file_row(row, small=True) + name = row['path'] + require(name not in rows, 'Duplicate receipt file: ' + name) + allowed = name in GENERATED or name in ('model/manifest.json', 'model/checksums.sha256') or ( + name.startswith('evidence/') and PurePosixPath(name).suffix.lower() in EVIDENCE_SUFFIXES) + require(allowed, 'Receipt attempts a non-evidence/sidecar download: ' + name) + rows[name] = row + required = {'model/manifest.json', 'model/checksums.sha256', 'evidence/manifest.json', + 'evidence/checksums.sha256', 'evidence/audit/final-status.json', + 'evidence/regression/old-integrity-after.json', *GENERATED} + require(required.issubset(rows), 'Receipt omits required AL evidence/seal controls') + return receipt, rows + + +def validate_manifest(manifest_data, checksums_data, expected_root, expected_sha): + require(sha(manifest_data) == expected_sha, 'Receipt/manifest SHA mismatch') + manifest = json_bytes(manifest_data) + require(isinstance(manifest, dict) and set(manifest) == {'root', 'files'} and + manifest['root'] == expected_root and isinstance(manifest['files'], list) and manifest['files'], + 'Wrong seal manifest schema/root') + rows = {} + for row in manifest['files']: + file_row(row) + require(row['path'] not in rows and row['path'] not in CONTROLS, 'Duplicate/control manifest payload') + rows[row['path']] = row + checksums = {} + for line in checksums_data.decode('utf-8').splitlines(): + require(len(line) >= 67 and line[64:66] == ' ' and SHA.fullmatch(line[:64]), 'Invalid checksum line') + name = line[66:] + relative_name(name) + require(name not in checksums, 'Duplicate checksum filename') + checksums[name] = line[:64] + require(checksums == {**{name: row['sha256'] for name, row in rows.items()}, 'manifest.json': expected_sha}, + 'Manifest self-SHA/checksum inventory mismatch') + return rows + + +def local_name(registry_name): + if registry_name.startswith('evidence/'): + return registry_name[len('evidence/'):] + if registry_name.startswith('model/'): + return registry_name + return 'registry/' + registry_name + + +def _check_local_target(destination): + require(destination.is_absolute(), 'Report destination must be absolute') + for part in (destination, *destination.parents): + require(not part.is_symlink() and not getattr(part, 'is_junction', lambda: False)(), + 'Local symlink/junction destination is forbidden') + require(not destination.exists(), 'Report destination exists; no overwrite/resume') + + +def _write(path, data): + path.parent.mkdir(parents=True, exist_ok=True) + with path.open('xb') as output: + output.write(data) + require(path.stat().st_size == len(data) and sha(path.read_bytes()) == sha(data), 'Local write verification failed') + + +def fetch(sftp, destination, receipt_sha256, *, max_total_bytes=MAX_TOTAL_BYTES): + """SFTP read-only API. Destination is exclusive; receipt SHA is out-of-band. + +Registry evidence/* mirrors into the report root, model/* into model/, and +receipt/generated publication metadata into registry/. Only source-whitelisted +model payloads are added; every transferred file is individually SHA checked. +""" + require(isinstance(receipt_sha256, str) and SHA.fullmatch(receipt_sha256.lower()), 'External receipt SHA256 is required') + receipt_sha256 = receipt_sha256.lower() + require(type(max_total_bytes) is int and max_total_bytes > 0, 'Invalid total download budget') + destination = Path(destination) + _check_local_target(destination) + remote = BoundedSFTP(sftp) + receipt_bytes = remote.read(REGISTRY_ROOT + '/publication-receipt.json', checksum=receipt_sha256) + receipt, rows = validate_receipt(receipt_bytes, receipt_sha256) + cached = {} + for prefix in ('model/', 'evidence/'): + for control in CONTROLS: + name = prefix + control; row = rows[name] + cached[name] = remote.read(REGISTRY_ROOT + '/' + name, row['bytes'], row['sha256']) + model_rows = validate_manifest(cached['model/manifest.json'], cached['model/checksums.sha256'], + MODEL_ROOT, receipt['model_manifest_sha256']) + experiment_rows = validate_manifest(cached['evidence/manifest.json'], cached['evidence/checksums.sha256'], + REMOTE_ROOT + '/' + EXPERIMENT_RELATIVE, receipt['experiment_manifest_sha256']) + # Model source is fetched from its sealed model path, not the registry. Bind + # its current controls to the receipt before reading any source payload. + for control in CONTROLS: + row = rows['model/' + control] + remote.read(MODEL_ROOT + '/' + control, row['bytes'], row['sha256']) + for name, row in rows.items(): + if name.startswith('evidence/') and name[len('evidence/'):] not in CONTROLS: + original = experiment_rows.get(name[len('evidence/'):]) + require(original is not None and all(row[key] == original[key] for key in ('bytes', 'sha256')), + 'Registry evidence disagrees with experiment seal: ' + name) + for name in GENERATED: + row = rows[name] + cached[name] = remote.read(REGISTRY_ROOT + '/' + name, row['bytes'], row['sha256']) + proof = json_bytes(cached['seal-verification.json']) + for key, root, manifest_rows, prefix in (('model', MODEL_ROOT, model_rows, 'model/'), + ('experiment', REMOTE_ROOT + '/' + EXPERIMENT_RELATIVE, experiment_rows, 'evidence/')): + item = proof.get(key, {}) + require(item.get('pass_all') is True and item.get('root') == root and + item.get('manifest_sha256') == receipt[key + '_manifest_sha256'] and + item.get('checksums_sha256') == rows[prefix + 'checksums.sha256']['sha256'] and + item.get('payload_file_count') == len(manifest_rows) and + item.get('payload_bytes') == sum(row['bytes'] for row in manifest_rows.values()), + 'Publication seal-verification disagrees with manifest: ' + key) + index = json_bytes(cached['evidence-index.json']) + require(isinstance(index, list), 'Invalid publication evidence index') + indexed = set() + for item in index: + require(isinstance(item, dict) and set(item) == {'source', 'copy', 'bytes', 'sha256'}, 'Invalid evidence-index row') + name = item['copy'] + require(name in rows and name not in GENERATED and name not in indexed, 'Duplicate/unexpected evidence-index copy') + indexed.add(name) + expected_source = (EXPERIMENT_RELATIVE + '/' + name[len('evidence/'):] if name.startswith('evidence/') + else MODEL_RELATIVE + '/' + name[len('model/'):]) + require(item['source'] == expected_source and all(item[key] == rows[name][key] for key in ('bytes', 'sha256')), + 'Evidence-index source/hash mismatch') + require(indexed == set(rows) - set(GENERATED), 'Evidence-index coverage mismatch') + plan = [(REGISTRY_ROOT + '/' + name, local_name(name), row, cached.get(name)) for name, row in sorted(rows.items())] + omitted = [] + for name, row in sorted(model_rows.items()): + if PurePosixPath(name).suffix.lower() in SOURCE_SUFFIXES and row['bytes'] <= MAX_FILE_BYTES: + plan.append((MODEL_ROOT + '/' + name, 'model/' + name, row, None)) + else: + omitted.append(dict(row, reason='model_non_source_or_over_4_MiB')) + paths = ['registry/publication-receipt.json', 'fetch-verification.json', 'fetch-failure.json'] + [entry[1] for entry in plan] + lowered = [relative_name(name).as_posix().casefold() for name in paths] + require(len(set(lowered)) == len(lowered) and not any( + parent.as_posix().casefold() in set(lowered) for name in paths for parent in PurePosixPath(name).parents if str(parent) != '.'), + 'Local case-insensitive/path-prefix collision') + planned_bytes = len(receipt_bytes) + sum(entry[2]['bytes'] for entry in plan) + require(planned_bytes <= max_total_bytes, 'Selected evidence exceeds total download budget') + _check_local_target(destination) + destination.mkdir(parents=True, exist_ok=False) + try: + _write(destination / 'registry/publication-receipt.json', receipt_bytes) + downloaded = [] + for source, local, row, data in plan: + if data is None: + data = remote.read(source, row['bytes'], row['sha256']) + require(len(data) == row['bytes'] and sha(data) == row['sha256'], 'Cached/downloaded file hash mismatch') + _write(destination / local, data) + downloaded.append(dict(remote=source, local=local, bytes=len(data), sha256=sha(data))) + final = json_bytes((destination / 'audit/final-status.json').read_bytes()) + require(final.get('status') == receipt.get('declared_audit_status'), 'Receipt/final-status declaration mismatch') + for key, value in receipt.get('declared_gate_results', {}).items(): + require(final.get(key) == value and type(final.get(key)) is type(value), 'Receipt/final gate flag mismatch') + for key, value in receipt.get('declared_audit_counts', {}).items(): + require(final.get(key) == value and type(final.get(key)) is type(value), 'Receipt/final coverage mismatch') + # Re-read immutable anchors, not unselected experiment payloads. + remote.read(REGISTRY_ROOT + '/publication-receipt.json', len(receipt_bytes), receipt_sha256) + for control in CONTROLS: + row = rows['model/' + control] + remote.read(MODEL_ROOT + '/' + control, row['bytes'], row['sha256']) + result = dict(fetch_complete=True, publication_receipt_sha256=receipt_sha256, + external_receipt_anchor_required=True, declared_audit_status=final['status'], + model_manifest_sha256=receipt['model_manifest_sha256'], experiment_manifest_sha256=receipt['experiment_manifest_sha256'], + both_manifest_self_checksums_verified=True, every_downloaded_file_sha256_verified=True, + files=downloaded, file_count=len(downloaded), selected_bytes=planned_bytes, + model_payload_not_downloaded=omitted, all_remote_experiment_bulk_rehashed_locally=False, + full_remote_seal_verification_is_publisher_receipt_claim=True, complete_bulk_backup=False, + scientific_gate_executed=False, scientific_pass_certified_by_fetch=False, + fetch_success_is_not_scientific_pass=True, candidate_generated=False, learning_achieved=False, + unregistered_sidecar_requested=False, existing_files_modified=False) + _write(destination / 'fetch-verification.json', (json.dumps(result, ensure_ascii=False, indent=2, allow_nan=False) + '\n').encode()) + return result + except Exception as error: + failure = destination / 'fetch-failure.json' + if not failure.exists(): + _write(failure, (json.dumps(dict(fetch_complete=False, type=type(error).__name__, message=str(error), + partial_outputs_preserved=True, existing_files_modified=False), allow_nan=False) + '\n').encode()) + raise + + +def main(): + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument('--receipt-sha256', required=True, help='Out-of-band SHA printed by the verified AL publisher') + parser.add_argument('--destination', type=Path, default=DEFAULT_DESTINATION) + parser.add_argument('--host', default='192.168.10.51') + parser.add_argument('--user', default='qishizhe') + parser.add_argument('--port', type=int, default=22) + parser.add_argument('--password-env', default='MALECNS_REMOTE_PASSWORD') + parser.add_argument('--known-hosts', type=Path, default=Path.home() / '.ssh/known_hosts', + help='Explicit existing user known_hosts; unknown hosts are always rejected') + args = parser.parse_args() + require(SHA.fullmatch(args.receipt_sha256.lower()), 'External receipt SHA256 is required') + _check_local_target(args.destination) + require(args.known_hosts.is_file(), 'Known-hosts file is missing; configure trust externally, never auto-add') + import paramiko + client = paramiko.SSHClient() + client.load_system_host_keys(str(args.known_hosts)) + client.set_missing_host_key_policy(paramiko.RejectPolicy()) + try: + client.connect(args.host, port=args.port, username=args.user, password=os.environ.get(args.password_env), + timeout=15, auth_timeout=15, banner_timeout=15) + with client.open_sftp() as sftp: + result = fetch(sftp, args.destination, args.receipt_sha256) + print(json.dumps({key: result[key] for key in ('fetch_complete', 'publication_receipt_sha256', + 'declared_audit_status', 'file_count', 'fetch_success_is_not_scientific_pass')}), flush=True) + finally: + client.close() + + +if __name__ == '__main__': + main() diff --git a/tools/phase4al-publication/publish_phase4al.py b/tools/phase4al-publication/publish_phase4al.py new file mode 100644 index 0000000..8bff65f --- /dev/null +++ b/tools/phase4al-publication/publish_phase4al.py @@ -0,0 +1,253 @@ +"""Exclusive small-evidence publication after both Phase 4AL seals verify. + +Publication verifies and copies bytes. It never runs a brain, re-evaluates a +scientific gate, converts FAIL/INCOMPLETE into PASS, or changes frozen sources. +The source-pinned Phase 4AI verification/copy helpers are executed unchanged. +""" +from __future__ import annotations + +import hashlib +import importlib.util +import json +from pathlib import Path, PurePosixPath + + +ROOT = Path('/data/digital-drosophila') +MODEL_RELATIVE = Path('models/male-cns-lif/mb-credit-transfer-audit-v1') +EXPERIMENT_RELATIVE = Path('experiments/phase4al-mb-credit-transfer') +REGISTRY_RELATIVE = Path('registry/phase4al-mb-credit-transfer') +HELPER_RELATIVE = Path('models/male-cns-lif/pn-recruitment-audit-v1/publication.py') +HELPER_SHA256 = '7a79c499098b74163e7bb16adabcbc54e7069dafa204d0b99c7f4c03d79f8016' +MAX_EVIDENCE_BYTES = 4 * 1024 ** 2 +EVIDENCE_SUFFIXES = frozenset(('.json', '.csv', '.md', '.log', '.sha256')) +FINAL_STATUS = 'PASS-CONDITIONAL-CREDIT-TRANSFER-AUDIT-NOT-LEARNING' +# Finalize currently seals only this completed diagnostic status. A partial +# run is not promoted; future failure sealing needs an explicit new contract. +FINAL_STATUSES = frozenset((FINAL_STATUS,)) +REQUIRED_EVIDENCE = ('audit/final-status.json', 'regression/old-integrity-after.json', + 'audit/scientific-summary.json') +REFERENCE_EVIDENCE = 'regression/frozen-five.json' +GATE_FIELDS = ('arithmetic_and_coverage_pass', 'old_integrity_pass', 'frozen_five_reference_pass', + 'frozen_eligibility_and_mask_unchanged', 'base_weights_unchanged', + 'summary_all_144_baseline_raw_states_and_repeat_pair_metrics_reverified', + 'scientific_overall_PASS_threshold_defined') +COUNT_FIELDS = ('primary_trials', 'exact_repeats', 'pairs') +COHORTS = ('seed_validation', 'novel_to_aj') +MODES = ('physiological', 'matched_energy') + + +def require(condition, message): + if not condition: + raise ValueError(message) + + +def load_helpers(path): + """Instantiate the unchanged module from its exact pinned source bytes. + +Using module_from_spec plus the source bytes avoids writing/importing a pyc +inside the sealed old model, even if the publisher was invoked without -B. +No old module global is redirected or modified after module initialization. +""" + path = Path(path) + require(path.is_absolute() and path.is_file() and not path.is_symlink(), 'Invalid frozen helper path') + data = path.read_bytes() + require(hashlib.sha256(data).hexdigest() == HELPER_SHA256, 'Frozen AI publication helper hash mismatch') + spec = importlib.util.spec_from_file_location('phase4al_frozen_ai_publication_helpers', path) + require(spec is not None and spec.loader is not None, 'Unable to define frozen helper module') + module = importlib.util.module_from_spec(spec) + exec(compile(data, str(path), 'exec'), module.__dict__) + require(module._digest(path) == HELPER_SHA256, 'Helper source changed while loading') + return module + + +def _copy(helper, source, destination, size, checksum): + """Separate local delegation point for interruption-only synthetic tests.""" + helper._copy_verified(source, destination, size, checksum) + + +def _write_small_json(helper, path, value): + data = (json.dumps(value, indent=2, ensure_ascii=False, allow_nan=False) + '\n').encode('utf-8') + require(len(data) <= MAX_EVIDENCE_BYTES, 'Generated registry evidence exceeds 4 MiB: ' + str(path)) + with Path(path).open('xb') as stream: + stream.write(data) + require(Path(path).stat().st_size == len(data), 'Generated registry evidence size changed') + + +def _status_evidence(helper, experiment, rows, model): + """Check declaration consistency only, not the scientific gate itself.""" + for relative in REQUIRED_EVIDENCE: + require(relative in rows, 'Required finalized evidence absent from seal: ' + relative) + require(rows[relative]['bytes'] <= MAX_EVIDENCE_BYTES, 'Required finalized evidence exceeds 4 MiB') + status, integrity, science = [helper._json_bytes((experiment / relative).read_bytes()) + for relative in REQUIRED_EVIDENCE] + config = helper._json_bytes((model / 'config.json').read_bytes()) + expected = dict(phase='4AL', neurons=166700, edges=25582938, candidate_edges=14232, + primary_trials=120, technical_repeats=24, steps=1000, dt_ms=.1, + virtual_gate_tick=900, kc_trace_tau_ms=100., trace_cap=1., stable_seed_count=3, + conditional_depression_fraction=.25, groups=['plastic_KC', 'nonplastic_KC', 'DAN', 'MBON', 'APL', 'other'], + training=False, candidate_generation=False, no_new_overall_credit_threshold=True) + require(isinstance(config, dict) and all(type(config.get(k)) is type(v) and config[k] == v + for k, v in expected.items()), 'Changed Phase 4AL configuration/design contract') + reference = None + if REFERENCE_EVIDENCE in rows: + require(rows[REFERENCE_EVIDENCE]['bytes'] <= MAX_EVIDENCE_BYTES, 'Frozen reference evidence exceeds 4 MiB') + reference = helper._json_bytes((experiment / REFERENCE_EVIDENCE).read_bytes()) + require(isinstance(reference, dict) and type(reference.get('pass_all')) is bool and + isinstance(reference.get('trials'), list), 'Invalid frozen reference report') + if reference['pass_all']: + require(len(reference['trials']) == 5 and all(isinstance(r, dict) and isinstance(r.get('exact'), dict) + and set(r['exact']) == {'step', 'neuron_idx', 'counts', 'v', 'g'} + and all(value is True for value in r['exact'].values()) for r in reference['trials']), + 'Declared frozen-five PASS must contain five exact trial records') + require(isinstance(status, dict) and status.get('status') in FINAL_STATUSES, + 'Unrecognized Phase 4AL final status') + for key in GATE_FIELDS: + require(type(status.get(key)) is bool, 'Missing/non-Boolean finalized result: ' + key) + for key in COUNT_FIELDS: + require(type(status.get(key)) is int and status[key] >= 0, 'Missing/invalid finalized count: ' + key) + for key in ('candidate_generated', 'learning_achieved', 'conditioning_executed', + 'scientific_overall_PASS_threshold_defined'): + require(status.get(key) is False, 'Unexpected finalized scope claim: ' + key) + require(isinstance(science, dict) and science and all(k in status and status[k] == value + and type(status[k]) is type(value) for k, value in science.items()), + 'Final status contradicts its scientific summary') + require(status.get('scientific_summary_sha256') == rows['audit/scientific-summary.json']['sha256'], + 'Final status scientific-summary SHA mismatch') + require(isinstance(integrity, dict) and bool(integrity) and all( + isinstance(row, dict) and type(row.get('pass')) is bool for row in integrity.values()), + 'Missing/invalid frozen-integrity report') + require(status['old_integrity_pass'] == all(row['pass'] for row in integrity.values()), + 'Final status contradicts its frozen-integrity report') + reference_pass = bool(reference is not None and reference['pass_all']) + require(status['frozen_five_reference_pass'] == reference_pass, + 'Final status contradicts its frozen-reference report/presence') + if status['status'].startswith('PASS-'): + require(all(status[key] for key in GATE_FIELDS if key != 'scientific_overall_PASS_threshold_defined') + and reference_pass and status['primary_trials'] == 120 and status['exact_repeats'] == 24 + and status['pairs'] == 60, + 'Declared PASS contradicts finalized gate/coverage flags') + blocks = status.get('blocks') + require(isinstance(blocks, dict) and set(blocks) == {c + '/' + m for c in COHORTS for m in MODES}, + 'Missing/extra cohort-mode blocks') + for block in blocks.values(): + require(isinstance(block, dict) and type(block.get('trials')) is int and block['trials'] == 30 + and type(block.get('pairs')) is int and block['pairs'] == 15, 'Incomplete cohort-mode block') + for key, maximum in (('pairs_with_both_specific_KC_and_edge_sets', 15), + ('conditional25_event_changed_trials', 30), + ('conditional25_count_or_first_latency_changed_trials', 30)): + require(type(block.get(key)) is int and 0 <= block[key] <= maximum, + 'Invalid diagnostic count: ' + key) + # Zero observed specificity/functional changes is publishable. This + # is not a new minimum scientific effect or pair-success criterion. + return status, reference, integrity + + +def publish(root=ROOT, helper_path=None): + """Publish the fixed AL registry exclusively; root override is for tests. + +Only sealed small experiment evidence and the two model seal controls are +copied. Every bulk payload is nevertheless verified before and after copying. +An interrupted registry is preserved and cannot be overwritten or resumed. +""" + root = Path(root) + require(root.is_absolute() and root.is_dir() and not root.is_symlink(), 'Invalid project root') + root = root.resolve(strict=True) + model, experiment, registry = (root / part for part in + (MODEL_RELATIVE, EXPERIMENT_RELATIVE, REGISTRY_RELATIVE)) + require(not registry.exists() and not registry.is_symlink(), 'Registry already exists; no overwrite/resume') + helper_path = root / HELPER_RELATIVE if helper_path is None else Path(helper_path) + helper = load_helpers(helper_path) + for path in (model, experiment, registry.parent): + current = root + for part in path.relative_to(root).parts: + current = current / part + require(not current.is_symlink(), 'Symlink in publication root path: ' + str(current)) + verified = {'model': helper.verify_seal(model), 'experiment': helper.verify_seal(experiment)} + experiment_rows = {row['path']: row for row in verified['experiment']['files']} + status, reference, integrity = _status_evidence(helper, experiment, experiment_rows, model) + plans, omitted = [], [] + for row in verified['experiment']['files'] + helper._control_rows(experiment, verified['experiment']): + if PurePosixPath(row['path']).suffix.lower() in EVIDENCE_SUFFIXES and row['bytes'] <= MAX_EVIDENCE_BYTES: + plans.append((experiment, row, 'evidence/' + row['path'])) + else: + omitted.append(dict(path=row['path'], bytes=row['bytes'], sha256=row['sha256'], + reason='exceeds_4_MiB' if row['bytes'] > MAX_EVIDENCE_BYTES else 'bulk_or_non_evidence_extension')) + for row in helper._control_rows(model, verified['model']): + require(row['bytes'] <= MAX_EVIDENCE_BYTES, 'Model seal control exceeds small-evidence limit') + plans.append((model, row, 'model/' + row['path'])) + destinations = {target for _, _, target in plans} + required_copies = ['manifest.json', 'checksums.sha256', *REQUIRED_EVIDENCE] + if reference is not None: + required_copies.append(REFERENCE_EVIDENCE) + for relative in required_copies: + require('evidence/' + relative in destinations, 'Required experiment evidence cannot be copied: ' + relative) + require(len(destinations) == len(plans), 'Duplicate planned evidence destination') + registry.parent.mkdir(parents=True, exist_ok=True) + registry.mkdir(exist_ok=False) + try: + records = [] + for source_root, row, relative in plans: + source = helper._regular_file(source_root.resolve(), row['path']) + _copy(helper, source, registry / relative, row['bytes'], row['sha256']) + records.append(dict(source=source.relative_to(root).as_posix(), copy=relative, + bytes=row['bytes'], sha256=row['sha256'])) + after = {'model': helper.verify_seal(model), 'experiment': helper.verify_seal(experiment)} + require(after == verified, 'A sealed tree changed during publication') + require(helper._digest(helper_path) == HELPER_SHA256, 'Frozen helper changed during publication') + proof = {name: {key: value for key, value in report.items() if key != 'files'} + for name, report in verified.items()} + _write_small_json(helper, registry / 'seal-verification.json', proof) + _write_small_json(helper, registry / 'evidence-index.json', records) + files = [dict(path=path.relative_to(registry).as_posix(), bytes=path.stat().st_size, + sha256=helper._digest(path)) for path in sorted(registry.rglob('*')) if path.is_file()] + receipt = dict(publication_complete=True, registry=registry.relative_to(root).as_posix(), + project_root=str(root), declared_audit_status=status['status'], + declared_gate_results={key: status[key] for key in GATE_FIELDS}, + declared_audit_counts={key: status[key] for key in COUNT_FIELDS}, + declared_diagnostic_scope='Read-only credit and fixed 25-percent conditional MBON replay; not learning or whole-brain intervention', + scientific_overall_PASS_threshold_defined=False, + scientific_summary_sha256=status['scientific_summary_sha256'], + frozen_reference_report=dict(present=reference is not None, + path='evidence/' + REFERENCE_EVIDENCE if reference is not None else None, + sha256=experiment_rows[REFERENCE_EVIDENCE]['sha256'] if reference is not None else None, + declared_pass_all=reference['pass_all'] if reference is not None else None, + reported_trial_count=len(reference['trials']) if reference is not None else None, + missing_is_not_a_success_or_fabricated_trial_failure=True), + frozen_integrity_report=dict(path='evidence/regression/old-integrity-after.json', + sha256=experiment_rows['regression/old-integrity-after.json']['sha256'], + declared_pass_by_root={name: row['pass'] for name, row in integrity.items()}), + frozen_helper_source=str(helper_path), frozen_helper_sha256=HELPER_SHA256, + publisher_sha256=helper._digest(Path(__file__)), helper_globals_redirected=False, + model_manifest_sha256=verified['model']['manifest_sha256'], + experiment_manifest_sha256=verified['experiment']['manifest_sha256'], + source_trees_verified_before_and_after_copy=True, + copied_evidence_files=len(records), copied_evidence_bytes=sum(row['bytes'] for row in records), + files=files, experiment_payload_not_copied=omitted, + model_payload_not_duplicated=True, model_payload_remains_at=MODEL_RELATIVE.as_posix(), + bulk_remains_at=EXPERIMENT_RELATIVE.as_posix(), complete_bulk_backup=False, + scientific_gate_executed_by_publisher=False, scientific_gate_certified_by_publication=False, + publication_success_is_not_scientific_pass=True, candidate_generated=False, + learning_achieved=False, full_scientific_goal_achieved=False, + old_heldout_dynamic_results_parsed=False, existing_files_modified=False, + receipt_self_hash='Not self-referential; returned by publish() and printed by main()', + limits=dict(max_selected_evidence_file_bytes=MAX_EVIDENCE_BYTES, + selected_suffixes=sorted(EVIDENCE_SUFFIXES))) + receipt_path = registry / 'publication-receipt.json' + _write_small_json(helper, receipt_path, receipt) + return dict(publication_complete=True, registry=str(registry), declared_audit_status=status['status'], + copied_evidence_files=len(records), receipt_sha256=helper._digest(receipt_path), + scientific_gate_executed_by_publisher=False, publication_success_is_not_scientific_pass=True) + except Exception as error: + failure = registry / 'publication-failure.json' + if not failure.exists(): + _write_small_json(helper, failure, dict(publication_complete=False, type=type(error).__name__, + message=str(error), partial_outputs_preserved=True, existing_files_modified=False)) + raise + + +def main(): + print(json.dumps(publish(), ensure_ascii=False, allow_nan=False), flush=True) + + +if __name__ == '__main__': + main() diff --git a/tools/phase4al-publication/test_fetch_phase4al.py b/tools/phase4al-publication/test_fetch_phase4al.py new file mode 100644 index 0000000..4f164fc --- /dev/null +++ b/tools/phase4al-publication/test_fetch_phase4al.py @@ -0,0 +1,239 @@ +"""Pure in-memory SFTP plus temporary local destinations, never a real server.""" +import io +import json +from pathlib import Path +import stat +import tempfile +import types +import unittest + +import fetch_phase4al as fetcher + + +def data(value): + return (json.dumps(value, sort_keys=True, allow_nan=False) + '\n').encode() + + +def row(name, content): + return dict(path=name, bytes=len(content), sha256=fetcher.sha(content)) + + +def sealed(root, payload): + rows = [row(name, content) for name, content in sorted(payload.items())] + manifest = data(dict(root=root, files=rows)) + checksums = '\n'.join([entry['sha256'] + ' ' + entry['path'] for entry in rows] + + [fetcher.sha(manifest) + ' manifest.json']).encode() + b'\n' + return dict(payload, **{'manifest.json': manifest, 'checksums.sha256': checksums}), dict( + pass_all=True, root=root, payload_file_count=len(rows), payload_bytes=sum(x['bytes'] for x in rows), + manifest_sha256=fetcher.sha(manifest), checksums_sha256=fetcher.sha(checksums)) + + +class FakeSFTP: + def __init__(self, files): + self.files = files + self.opened = [] + self.hook = None + self.symlinks = set() + + def lstat(self, name): + if name in self.symlinks: + return types.SimpleNamespace(st_mode=stat.S_IFLNK | 0o777, st_size=1) + if name in self.files: + return types.SimpleNamespace(st_mode=stat.S_IFREG | 0o644, st_size=len(self.files[name])) + if any(path.startswith(name.rstrip('/') + '/') for path in self.files): + return types.SimpleNamespace(st_mode=stat.S_IFDIR | 0o755, st_size=0) + raise FileNotFoundError(name) + + def open(self, name, mode): + if mode != 'rb': + raise AssertionError('Remote write attempted') + self.opened.append(name) + if self.hook: + self.hook(name) + return io.BytesIO(self.files[name]) + + +def fixture(extra_experiment=None, extra_model=None): + status = dict(status='INCOMPLETE-SYNTHETIC-AL-EVIDENCE', arithmetic_and_coverage_pass=False, + primary_trials=120, candidate_generated=False, learning_achieved=False) + mp = {'module.py': b'# synthetic, not model execution\n', 'config.json': data({'synthetic': True}), + 'never-download.npy': b'raw model bulk'} + mp.update(extra_model or {}) + ep = {'audit/final-status.json': data(status), 'regression/old-integrity-after.json': data({'tree': {'pass': True}}), + 'REPORT.md': b'Synthetic incomplete evidence.\n', 'tests.log': b'Synthetic test log.\n', + 'gpu/example/state.npz': b'large trajectory placeholder not requested', + 'gpu/example/tick-state-hashes.jsonl': b'non-whitelisted suffix'} + ep.update(extra_experiment or {}) + model, model_proof = sealed(fetcher.MODEL_ROOT, mp) + experiment, exp_proof = sealed(fetcher.REMOTE_ROOT + '/' + fetcher.EXPERIMENT_RELATIVE, ep) + registry = {} + index = [] + for name, content in experiment.items(): + if Path(name).suffix.lower() in fetcher.EVIDENCE_SUFFIXES and len(content) <= fetcher.MAX_FILE_BYTES: + dest = 'evidence/' + name + registry[dest] = content + index.append(dict(source=fetcher.EXPERIMENT_RELATIVE + '/' + name, + copy=dest, bytes=len(content), sha256=fetcher.sha(content))) + for name in fetcher.CONTROLS: + dest = 'model/' + name; content = model[name] + registry[dest] = content + index.append(dict(source=fetcher.MODEL_RELATIVE + '/' + name, + copy=dest, bytes=len(content), sha256=fetcher.sha(content))) + registry['seal-verification.json'] = data(dict(model=model_proof, experiment=exp_proof)) + registry['evidence-index.json'] = data(index) + receipt = dict(publication_complete=True, registry=fetcher.REGISTRY_RELATIVE, project_root=fetcher.REMOTE_ROOT, + source_trees_verified_before_and_after_copy=True, publication_success_is_not_scientific_pass=True, + complete_bulk_backup=False, scientific_gate_executed_by_publisher=False, + scientific_gate_certified_by_publication=False, candidate_generated=False, learning_achieved=False, + model_manifest_sha256=model_proof['manifest_sha256'], experiment_manifest_sha256=exp_proof['manifest_sha256'], + files=[row(name, content) for name, content in sorted(registry.items())], + limits=dict(max_selected_evidence_file_bytes=fetcher.MAX_FILE_BYTES, selected_suffixes=sorted(fetcher.EVIDENCE_SUFFIXES)), + declared_audit_status=status['status'], declared_gate_results={'arithmetic_and_coverage_pass': False}, + declared_audit_counts={'primary_trials': 120}) + registry['publication-receipt.json'] = data(receipt) + files = {fetcher.MODEL_ROOT + '/' + name: content for name, content in model.items()} + files.update({fetcher.REGISTRY_ROOT + '/' + name: content for name, content in registry.items()}) + return FakeSFTP(files), fetcher.sha(registry['publication-receipt.json']) + + +class FetchTests(unittest.TestCase): + def setUp(self): + self.temp = tempfile.TemporaryDirectory(prefix='phase4al-fetch-synthetic-') + self.addCleanup(self.temp.cleanup) + self.destination = Path(self.temp.name).resolve() / 'report' + self.sftp, self.receipt_sha = fixture() + + def receipt(self): + return fetcher.json_bytes(self.sftp.files[fetcher.REGISTRY_ROOT + '/publication-receipt.json']) + + def resign(self, receipt): + raw = data(receipt) + self.sftp.files[fetcher.REGISTRY_ROOT + '/publication-receipt.json'] = raw + self.receipt_sha = fetcher.sha(raw) + + def get(self, **kwargs): + return fetcher.fetch(self.sftp, self.destination, self.receipt_sha, **kwargs) + + def test_only_receipt_small_files_and_model_source_with_hashes(self): + result = self.get() + self.assertTrue(result['fetch_complete']) + self.assertTrue(result['both_manifest_self_checksums_verified']) + self.assertTrue(result['fetch_success_is_not_scientific_pass']) + self.assertFalse(result['complete_bulk_backup']) + self.assertFalse(result['all_remote_experiment_bulk_rehashed_locally']) + self.assertEqual(result['declared_audit_status'], 'INCOMPLETE-SYNTHETIC-AL-EVIDENCE') + self.assertTrue((self.destination / 'audit/final-status.json').is_file()) + self.assertTrue((self.destination / 'model/module.py').is_file()) + self.assertTrue((self.destination / 'registry/publication-receipt.json').is_file()) + self.assertFalse((self.destination / 'gpu/example/state.npz').exists()) + self.assertFalse((self.destination / 'model/never-download.npy').exists()) + self.assertFalse(any('interpretation' in path or 'phase4aj' in path or path.endswith(('.npy', '.npz', '.jsonl')) + for path in self.sftp.opened)) + for entry in result['files']: + self.assertEqual(fetcher.sha((self.destination / entry['local']).read_bytes()), entry['sha256']) + + def test_out_of_band_sha_is_mandatory_and_checked_before_other_remote_reads(self): + for checksum in ('', 'g' * 64, '0' * 64): + self.sftp.opened.clear() + with self.subTest(checksum=checksum), self.assertRaises(ValueError): + fetcher.fetch(self.sftp, self.destination, checksum) + self.assertFalse(self.destination.exists()) + self.assertTrue(all(path.endswith('/publication-receipt.json') for path in self.sftp.opened)) + + def test_no_overwrite_or_resume_even_empty_existing_directory(self): + self.destination.mkdir() + with self.assertRaisesRegex(ValueError, 'exists'): + self.get() + self.assertFalse(self.sftp.opened) + self.assertEqual(list(self.destination.iterdir()), []) + + def test_malformed_or_non_small_receipt_paths_fail_without_download(self): + for name, size in (('../escape.json', 1), ('evidence/bulk.npy', 1), ('interpretation-metrics.json', 1), + ('evidence/huge.json', fetcher.MAX_FILE_BYTES + 1), ('evidence/C:/escape.json', 1)): + with self.subTest(name=name): + self.sftp, self.receipt_sha = fixture() + receipt = self.receipt() + receipt['files'].append(dict(path=name, bytes=size, sha256='a' * 64)) + self.resign(receipt) + with self.assertRaises(ValueError): + self.get() + self.assertFalse(self.destination.exists()) + self.assertEqual(self.sftp.opened, [fetcher.REGISTRY_ROOT + '/publication-receipt.json']) + + def test_manifest_self_checksum_is_not_trusted_from_receipt_alone(self): + name = 'evidence/checksums.sha256'; path = fetcher.REGISTRY_ROOT + '/' + name + lines = self.sftp.files[path].decode().splitlines() + lines[-1] = '0' * 64 + ' manifest.json' + changed = ('\n'.join(lines) + '\n').encode() + self.sftp.files[path] = changed + receipt = self.receipt() + next(entry for entry in receipt['files'] if entry['path'] == name).update(bytes=len(changed), sha256=fetcher.sha(changed)) + self.resign(receipt) + with self.assertRaisesRegex(ValueError, 'self-SHA'): + self.get() + self.assertFalse(self.destination.exists()) + + def test_model_original_seal_must_equal_registry_anchor(self): + self.sftp.files[fetcher.MODEL_ROOT + '/manifest.json'] += b' ' + with self.assertRaises(ValueError): + self.get() + self.assertFalse(self.destination.exists()) + + def test_corrupt_selected_payload_preserves_partial_and_blocks_resume(self): + path = fetcher.REGISTRY_ROOT + '/evidence/REPORT.md' + self.sftp.files[path] = b'x' * len(self.sftp.files[path]) + with self.assertRaisesRegex(ValueError, 'SHA'): + self.get() + self.assertTrue((self.destination / 'fetch-failure.json').is_file()) + self.assertFalse((self.destination / 'fetch-verification.json').exists()) + with self.assertRaisesRegex(ValueError, 'exists'): + self.get() + + def test_model_source_hash_is_verified_without_fetching_other_payloads(self): + path = fetcher.MODEL_ROOT + '/module.py' + self.sftp.files[path] = b'x' * len(self.sftp.files[path]) + with self.assertRaisesRegex(ValueError, 'SHA'): + self.get() + self.assertTrue((self.destination / 'fetch-failure.json').is_file()) + self.assertFalse(any(path.endswith('never-download.npy') for path in self.sftp.opened)) + + def test_local_path_collision_and_total_budget_fail_before_destination(self): + self.sftp, self.receipt_sha = fixture(extra_experiment={'model/module.py.json': data({'not_source': True}), + 'model/config.json': data({'collision': True})}) + with self.assertRaisesRegex(ValueError, 'collision'): + self.get() + self.assertFalse(self.destination.exists()) + self.sftp, self.receipt_sha = fixture() + with self.assertRaisesRegex(ValueError, 'total download budget'): + self.get(max_total_bytes=1) + self.assertFalse(self.destination.exists()) + + def test_remote_symlink_rejected_without_open(self): + path = fetcher.REGISTRY_ROOT + '/publication-receipt.json' + self.sftp.symlinks.add(path) + with self.assertRaisesRegex(ValueError, 'symlink'): + self.get() + self.assertFalse(self.sftp.opened) + + def test_anchor_changed_during_copy_fails_final_check(self): + receipt_path = fetcher.REGISTRY_ROOT + '/publication-receipt.json' + def change_on_source(name): + if name == fetcher.MODEL_ROOT + '/module.py': + self.sftp.files[receipt_path] += b' ' + self.sftp.hook = change_on_source + with self.assertRaises(ValueError): + self.get() + self.assertTrue((self.destination / 'fetch-failure.json').is_file()) + self.assertFalse((self.destination / 'fetch-verification.json').exists()) + + def test_no_import_network_and_cli_rejects_unknown_hosts(self): + source = Path(fetcher.__file__).read_text(encoding='utf-8') + self.assertIn('paramiko.RejectPolicy()', source) + self.assertIn('client.load_system_host_keys(str(args.known_hosts))', source) + self.assertIn("default=Path.home() / '.ssh/known_hosts'", source) + self.assertNotIn('AutoAddPolicy', source) + self.assertNotIn('interpretation-metrics.json', source) + + +if __name__ == '__main__': + unittest.main() diff --git a/tools/phase4al-publication/test_publish_phase4al.py b/tools/phase4al-publication/test_publish_phase4al.py new file mode 100644 index 0000000..94735fb --- /dev/null +++ b/tools/phase4al-publication/test_publish_phase4al.py @@ -0,0 +1,253 @@ +"""Temporary synthetic seals only; never publish/register any real evidence.""" +import hashlib +import json +from pathlib import Path +import tempfile +import unittest +from unittest import mock + +import publish_phase4al as publication + + +HELPER = Path(__file__).resolve().parents[1] / 'pn-recruitment-audit-v1/publication.py' +if not HELPER.is_file(): + HELPER = publication.ROOT / publication.HELPER_RELATIVE + + +def sha(path): + return hashlib.sha256(path.read_bytes()).hexdigest() + + +def write(path, value): + path.parent.mkdir(parents=True, exist_ok=True) + path.write_text(json.dumps(value, indent=2), encoding='utf-8') + + +def seal(root): + rows = [dict(path=path.relative_to(root).as_posix(), bytes=path.stat().st_size, sha256=sha(path)) + for path in sorted(root.rglob('*')) if path.is_file() and + path.name not in ('manifest.json', 'checksums.sha256') and '__pycache__' not in path.parts] + write(root / 'manifest.json', dict(root=str(root), files=rows)) + lines = [row['sha256'] + ' ' + row['path'] for row in rows] + lines.append(sha(root / 'manifest.json') + ' manifest.json') + (root / 'checksums.sha256').write_text('\n'.join(lines) + '\n', encoding='utf-8') + + +class PublicationTests(unittest.TestCase): + def setUp(self): + temporary = tempfile.TemporaryDirectory(prefix='phase4al-publication-synthetic-') + self.addCleanup(temporary.cleanup) + self.root = Path(temporary.name).resolve() + self.model = self.root / publication.MODEL_RELATIVE + self.experiment = self.root / publication.EXPERIMENT_RELATIVE + self.registry = self.root / publication.REGISTRY_RELATIVE + self.model.mkdir(parents=True) + self.experiment.mkdir(parents=True) + (self.model / 'module.py').write_text('# synthetic, not a model\n', encoding='utf-8') + self.config = dict(phase='4AL', neurons=166700, edges=25582938, candidate_edges=14232, + primary_trials=120, technical_repeats=24, steps=1000, dt_ms=.1, virtual_gate_tick=900, + kc_trace_tau_ms=100., trace_cap=1., stable_seed_count=3, conditional_depression_fraction=.25, + groups=['plastic_KC', 'nonplastic_KC', 'DAN', 'MBON', 'APL', 'other'], + training=False, candidate_generation=False, no_new_overall_credit_threshold=True) + write(self.model / 'config.json', self.config) + self.science = dict(arithmetic_and_coverage_pass=True, primary_trials=120, exact_repeats=24, + pairs=60, candidate_generated=False, learning_achieved=False, conditioning_executed=False, + scientific_overall_PASS_threshold_defined=False, + blocks={c + '/' + m: dict(trials=30, pairs=15, pairs_with_both_specific_KC_and_edge_sets=0, + conditional25_event_changed_trials=0, conditional25_count_or_first_latency_changed_trials=0) + for c in publication.COHORTS for m in publication.MODES}) + write(self.experiment / 'audit/scientific-summary.json', self.science) + self.status = dict(status=publication.FINAL_STATUS, **self.science, old_integrity_pass=True, + frozen_five_reference_pass=True, frozen_eligibility_and_mask_unchanged=True, + base_weights_unchanged=True, summary_all_144_baseline_raw_states_and_repeat_pair_metrics_reverified=True, + scientific_summary_sha256=sha(self.experiment / 'audit/scientific-summary.json')) + write(self.experiment / 'audit/final-status.json', self.status) + write(self.experiment / 'regression/frozen-five.json', dict(pass_all=True, + trials=[dict(trial=str(i), exact={k: True for k in ('step', 'neuron_idx', 'counts', 'v', 'g')}) for i in range(5)])) + write(self.experiment / 'regression/old-integrity-after.json', {'synthetic-old-tree': {'pass': True}}) + write(self.experiment / 'nested/case/summary.json', {'synthetic': True}) + (self.experiment / 'REPORT.md').write_text('Synthetic zero-effect diagnostic.\n', encoding='utf-8') + (self.experiment / 'tests.log').write_text('Synthetic log\n', encoding='utf-8') + for suffix in ('.npy', '.npz', '.parquet'): + (self.experiment / ('bulk' + suffix)).write_bytes(b'synthetic bulk bytes, not scientific data') + seal(self.model) + seal(self.experiment) + + def publish(self): + return publication.publish(self.root, HELPER) + + def test_completed_zero_effect_diagnostic_is_not_regraded_as_learning(self): + before = {str(p): sha(p) for base in (self.model, self.experiment) for p in base.rglob('*') if p.is_file()} + result = self.publish() + self.assertTrue(result['publication_complete']) + receipt = json.loads((self.registry / 'publication-receipt.json').read_text(encoding='utf-8')) + self.assertEqual(receipt['declared_audit_status'], publication.FINAL_STATUS) + self.assertFalse(receipt['scientific_overall_PASS_threshold_defined']) + self.assertFalse(receipt['learning_achieved']) + self.assertTrue(receipt['publication_success_is_not_scientific_pass']) + self.assertEqual(receipt['scientific_summary_sha256'], self.status['scientific_summary_sha256']) + for suffix in ('.npy', '.npz', '.parquet'): + self.assertFalse((self.registry / ('evidence/bulk' + suffix)).exists()) + for row in receipt['files']: + self.assertEqual(sha(self.registry / row['path']), row['sha256']) + self.assertEqual(before, {str(p): sha(p) for base in (self.model, self.experiment) for p in base.rglob('*') if p.is_file()}) + + def test_changed_config_blocks_before_destination(self): + for key, value in (('phase', '4AK'), ('primary_trials', 119), ('candidate_edges', 14231), + ('conditional_depression_fraction', .5), ('training', True), ('virtual_gate_tick', 901)): + with self.subTest(key=key): + write(self.model / 'config.json', dict(self.config, **{key: value})) + seal(self.model) + with self.assertRaisesRegex(ValueError, 'configuration/design'): + self.publish() + self.assertFalse(self.registry.exists()) + + def test_summary_hash_counts_and_scope_must_match(self): + for changed in ({'scientific_summary_sha256': '0' * 64}, {'primary_trials': 119}, + {'pairs': 59}, {'learning_achieved': True}, {'arithmetic_and_coverage_pass': 'true'}, + {'old_integrity_pass': False}, {'base_weights_unchanged': False}): + with self.subTest(changed=changed): + write(self.experiment / 'audit/final-status.json', dict(self.status, **changed)) + seal(self.experiment) + with self.assertRaises(ValueError): + self.publish() + self.assertFalse(self.registry.exists()) + + def test_missing_or_corrupt_scientific_summary_is_rejected(self): + path = self.experiment / 'audit/scientific-summary.json' + path.unlink() + seal(self.experiment) + with self.assertRaisesRegex(ValueError, 'Required finalized evidence absent'): + self.publish() + self.assertFalse(self.registry.exists()) + + def test_complete_status_requires_all_four_complete_blocks(self): + value = dict(self.science, blocks={}) + write(self.experiment / 'audit/scientific-summary.json', value) + write(self.experiment / 'audit/final-status.json', dict(self.status, **value, + scientific_summary_sha256=sha(self.experiment / 'audit/scientific-summary.json'))) + seal(self.experiment) + with self.assertRaisesRegex(ValueError, 'cohort-mode blocks'): + self.publish() + + def test_false_reference_exactness_is_not_hidden_by_pass_all(self): + write(self.experiment / 'regression/frozen-five.json', dict(pass_all=True, + trials=[dict(exact={'step': False})] * 5)) + seal(self.experiment) + with self.assertRaisesRegex(ValueError, 'five exact trial'): + self.publish() + self.assertFalse(self.registry.exists()) + + def test_unknown_or_unfinalized_status_is_not_promoted(self): + for status in ('INCOMPLETE-NOT-SEALED', 'PASS-FROZEN-D18-INDEPENDENT-VALIDATION'): + write(self.experiment / 'audit/final-status.json', dict(self.status, status=status)) + seal(self.experiment) + with self.assertRaisesRegex(ValueError, 'Unrecognized Phase 4AL'): + self.publish() + self.assertFalse(self.registry.exists()) + + def test_manifest_path_escape_rejected_before_destination(self): + path = self.experiment / 'manifest.json' + manifest = json.loads(path.read_text(encoding='utf-8')) + manifest['files'][0]['path'] = '../escape.json' + write(path, manifest) + controls = self.experiment / 'checksums.sha256' + controls.write_text('\n'.join([r['sha256'] + ' ' + r['path'] for r in manifest['files']] + + [sha(path) + ' manifest.json']) + '\n', encoding='utf-8') + with self.assertRaisesRegex(ValueError, 'escaping relative path'): + self.publish() + self.assertFalse(self.registry.exists()) + + def test_completed_status_without_frozen_reference_is_not_publishable(self): + (self.experiment / 'regression/frozen-five.json').unlink() + seal(self.experiment) + with self.assertRaisesRegex(ValueError, 'frozen-reference report/presence'): + self.publish() + self.assertFalse(self.registry.exists()) + + def test_existing_registry_never_overwritten_or_resumed(self): + self.registry.mkdir(parents=True) + sentinel = self.registry / 'keep.txt' + sentinel.write_bytes(b'keep these bytes') + with self.assertRaisesRegex(ValueError, 'Registry already exists'): + self.publish() + self.assertEqual(sentinel.read_bytes(), b'keep these bytes') + self.assertEqual(list(self.registry.iterdir()), [sentinel]) + + def test_missing_integrity_report_blocks_before_destination(self): + (self.experiment / 'regression/old-integrity-after.json').unlink() + seal(self.experiment) + with self.assertRaisesRegex(ValueError, 'Required finalized evidence absent'): + self.publish() + self.assertFalse(self.registry.exists()) + + def test_bulk_corruption_blocks_even_though_bulk_is_not_copied(self): + path = self.experiment / 'bulk.npy' + path.write_bytes(b'x' * path.stat().st_size) + with self.assertRaisesRegex(ValueError, 'Payload SHA-256 mismatch'): + self.publish() + self.assertFalse(self.registry.exists()) + + def test_unlisted_payload_and_bad_manifest_self_hash_fail(self): + extra = self.experiment / 'unlisted.csv' + extra.write_text('unlisted\n') + with self.assertRaisesRegex(ValueError, 'unlisted/missing'): + self.publish() + extra.unlink() + controls = self.experiment / 'checksums.sha256' + lines = controls.read_text().splitlines() + lines[-1] = '0' * 64 + ' manifest.json' + controls.write_text('\n'.join(lines) + '\n') + with self.assertRaisesRegex(ValueError, 'manifest self-checksum'): + self.publish() + self.assertFalse(self.registry.exists()) + + def test_large_json_verified_but_not_copied(self): + path = self.experiment / 'large.json' + path.write_bytes(b' ' * (publication.MAX_EVIDENCE_BYTES + 1)) + seal(self.experiment) + self.publish() + self.assertFalse((self.registry / 'evidence/large.json').exists()) + receipt = json.loads((self.registry / 'publication-receipt.json').read_text(encoding='utf-8')) + self.assertEqual(next(r for r in receipt['experiment_payload_not_copied'] if r['path'] == 'large.json')['reason'], + 'exceeds_4_MiB') + + def test_interrupted_copy_retained_and_cannot_resume(self): + with mock.patch.object(publication, '_copy', side_effect=OSError('synthetic interrupted copy')): + with self.assertRaisesRegex(OSError, 'synthetic interrupted copy'): + self.publish() + self.assertTrue((self.registry / 'publication-failure.json').is_file()) + self.assertFalse((self.registry / 'publication-receipt.json').exists()) + with self.assertRaisesRegex(ValueError, 'Registry already exists'): + self.publish() + + def test_after_copy_full_verification_detects_bulk_change(self): + original = publication._copy + changed = False + + def copy_then_change(helper, source, destination, size, checksum): + nonlocal changed + original(helper, source, destination, size, checksum) + if not changed: + changed = True + (self.experiment / 'bulk.npy').write_bytes(b'changed after initial seal check') + + with mock.patch.object(publication, '_copy', side_effect=copy_then_change): + with self.assertRaises(ValueError): + self.publish() + self.assertTrue((self.registry / 'publication-failure.json').is_file()) + self.assertFalse((self.registry / 'publication-receipt.json').exists()) + + def test_helper_pin_checked_without_modifying_old_globals_or_cache(self): + helper = publication.load_helpers(HELPER) + self.assertEqual(helper.MODEL_RELATIVE, Path('models/male-cns-lif/pn-recruitment-audit-v1')) + self.assertEqual(helper.FINAL_STATUS, 'PASS-CONDITIONAL-PN-APL-SOURCE-AUDIT') + wrong = self.root / 'wrong-helper.py' + wrong.write_bytes(b'raise RuntimeError("must never execute")\n') + with self.assertRaisesRegex(ValueError, 'helper hash mismatch'): + publication.publish(self.root, wrong) + self.assertFalse(self.registry.exists()) + + +if __name__ == '__main__': + unittest.main() diff --git a/tools/phase4al-publication/test_verify_git_payload.py b/tools/phase4al-publication/test_verify_git_payload.py new file mode 100644 index 0000000..0b01eae --- /dev/null +++ b/tools/phase4al-publication/test_verify_git_payload.py @@ -0,0 +1,269 @@ +"""Synthetic temporary Git repositories only; no real publication or science.""" +import contextlib +import io +import json +import os +from pathlib import Path +import shutil +import subprocess +import tempfile +import unittest + +import verify_git_payload as verifier + + +def encoded(value): + return (json.dumps(value, sort_keys=True, indent=2) + '\n').encode('utf-8') + + +def sealed(relative, payload): + rows = [dict(path=path, bytes=len(data), sha256=verifier.sha(data)) for path, data in sorted(payload.items())] + manifest = encoded(dict(root=verifier.PROJECT + '/' + relative, files=rows)) + checksums = ''.join(row['sha256'] + ' ' + row['path'] + '\n' for row in rows) + checksums += verifier.sha(manifest) + ' manifest.json\n' + controls = {'manifest.json': manifest, 'checksums.sha256': checksums.encode('utf-8')} + proof = dict(pass_all=True, root=verifier.PROJECT + '/' + relative, + payload_file_count=len(rows), payload_bytes=sum(row['bytes'] for row in rows), + manifest_sha256=verifier.sha(manifest), checksums_sha256=verifier.sha(controls['checksums.sha256']), + excluded_pycache_files=0, verification_scope='synthetic test only') + return rows, controls, proof + + +@unittest.skipUnless(shutil.which('git'), 'Git executable is required') +class GitPayloadTests(unittest.TestCase): + def setUp(self): + temporary = tempfile.TemporaryDirectory(prefix='phase4al-git-payload-synthetic-') + self.addCleanup(temporary.cleanup) + self.repo = Path(temporary.name).resolve() + self.git('init', '--quiet') + self.git('config', 'user.name', 'Synthetic Test') + self.git('config', 'user.email', 'synthetic@example.invalid') + self.git('config', 'core.autocrlf', 'false') + self.git('config', 'commit.gpgsign', 'false') + self.model = {'module.py': b'# synthetic, not a brain\nx = 1\n', 'config.json': b'{"synthetic": true}\n'} + self.exp = {'audit/final-status.json': encoded(dict(status='FAIL-SEED-VALIDATION-REPRESENTATION')), + 'case/summary.json': b'{"synthetic": true}\n', 'bulk.npy': b'not-a-real-array\x00'} + self.build() + + def git(self, *args, data=None): + env = os.environ.copy() + for key in ('GIT_DIR', 'GIT_WORK_TREE', 'GIT_INDEX_FILE', 'GIT_COMMON_DIR', + 'GIT_OBJECT_DIRECTORY', 'GIT_ALTERNATE_OBJECT_DIRECTORIES'): + env.pop(key, None) + result = subprocess.run(['git', '-C', str(self.repo), *args], input=data, + stdout=subprocess.PIPE, stderr=subprocess.PIPE, env=env, check=False) + self.assertEqual(result.returncode, 0, result.stderr.decode('utf-8', 'replace')) + return result.stdout + + def write(self, path, data): + target = self.repo / path + target.parent.mkdir(parents=True, exist_ok=True) + target.write_bytes(data) + + def build(self): + _, model_controls, model_proof = sealed(verifier.MODEL, self.model) + exp_rows, exp_controls, exp_proof = sealed(verifier.EXPERIMENT, self.exp) + for path, data in {**self.model, **model_controls}.items(): + self.write(verifier.MODEL + '/' + path, data) + registry = {} + index = [] + omitted = [] + for path, data in {**self.exp, **exp_controls}.items(): + row = dict(path=path, bytes=len(data), sha256=verifier.sha(data)) + if Path(path).suffix in verifier.SUFFIXES and len(data) <= verifier.MAX_EVIDENCE: + registry['evidence/' + path] = data + index.append(dict(source=verifier.EXPERIMENT + '/' + path, copy='evidence/' + path, + bytes=len(data), sha256=verifier.sha(data))) + else: + omitted.append(dict(row, reason='bulk_or_non_evidence_extension')) + for path, data in model_controls.items(): + registry['model/' + path] = data + index.append(dict(source=verifier.MODEL + '/' + path, copy='model/' + path, + bytes=len(data), sha256=verifier.sha(data))) + registry['evidence-index.json'] = encoded(index) + registry['seal-verification.json'] = encoded(dict(model=model_proof, experiment=exp_proof)) + self.receipt = dict(publication_complete=True, registry=verifier.REGISTRY, project_root=verifier.PROJECT, + model_payload_remains_at=verifier.MODEL, bulk_remains_at=verifier.EXPERIMENT, + model_manifest_sha256=model_proof['manifest_sha256'], + experiment_manifest_sha256=exp_proof['manifest_sha256'], + copied_evidence_files=len(index), copied_evidence_bytes=sum(row['bytes'] for row in index), + files=[dict(path=path, bytes=len(data), sha256=verifier.sha(data)) for path, data in sorted(registry.items())], + experiment_payload_not_copied=omitted, declared_audit_status='FAIL-SEED-VALIDATION-REPRESENTATION') + for path, data in registry.items(): + self.write(verifier.REGISTRY + '/' + path, data) + self.receipt_write() + self.git('add', '--', verifier.MODEL, verifier.REGISTRY) + + def receipt_write(self): + data = encoded(self.receipt) + self.write(verifier.REGISTRY + '/publication-receipt.json', data) + self.anchor = verifier.sha(data) + + def anchored_registry_change(self, relative, data): + self.write(verifier.REGISTRY + '/' + relative, data) + row = next(row for row in self.receipt['files'] if row['path'] == relative) + row.update(bytes=len(data), sha256=verifier.sha(data)) + self.receipt_write() + self.git('add', '--', verifier.REGISTRY) + + def verify(self, **kwargs): + return verifier.verify_git_payload(self.repo, self.anchor, **({'staged': True} if not kwargs else kwargs)) + + def test_staged_verifies_blob_bytes_and_leaves_index_unchanged(self): + before = (self.repo / '.git/index').read_bytes() + result = self.verify() + self.assertTrue(result['pass_all']) + self.assertEqual(result['model_payload_files'], 2) + self.assertEqual(result['declared_audit_status'], 'FAIL-SEED-VALIDATION-REPRESENTATION') + self.assertFalse(result['experiment_bulk_verified_by_this_tool']) + self.assertFalse(result['scientific_gate_executed']) + self.assertTrue(result['publication_integrity_is_not_scientific_pass']) + self.assertEqual(before, (self.repo / '.git/index').read_bytes()) + self.assertFalse((self.repo / verifier.EXPERIMENT).exists()) + + def test_dirty_or_missing_worktree_payload_does_not_replace_good_index(self): + (self.repo / verifier.MODEL / 'module.py').write_bytes(b'working copy differs') + (self.repo / verifier.REGISTRY / 'publication-receipt.json').unlink() + self.assertTrue(self.verify()['pass_all']) + + def test_correct_worktree_cannot_hide_corrupt_staged_blob(self): + relative = verifier.MODEL + '/module.py' + self.write(relative, self.model['module.py'].replace(b'x = 1', b'x = 2')) + self.git('add', '--', relative) + self.write(relative, self.model['module.py']) + with self.assertRaisesRegex(ValueError, 'Git blob SHA-256 mismatch'): + self.verify() + + def test_commit_verifies_immutable_commit_not_current_index(self): + self.git('commit', '--quiet', '-m', 'synthetic only') + commit = self.git('rev-parse', 'HEAD').decode().strip() + self.write(verifier.MODEL + '/module.py', b'bad newer index') + self.git('add', '--', verifier.MODEL) + result = self.verify(commit='HEAD') + self.assertEqual(result['commit'], commit) + self.assertEqual(result['source'], 'commit') + self.assertTrue(result['pass_all']) + + def test_external_receipt_anchor_is_mandatory_and_checked(self): + for anchor in (None, '', '0' * 64, self.anchor.upper()): + with self.subTest(anchor=anchor), self.assertRaises(ValueError): + verifier.verify_git_payload(self.repo, anchor, staged=True) + + def test_extra_model_file_is_rejected_but_outside_scope_is_ignored(self): + self.write('unrelated/old-file.txt', b'outside audit scope') + self.git('add', '--', 'unrelated') + self.assertTrue(self.verify()['pass_all']) + self.write(verifier.MODEL + '/extra.py', b'extra') + self.git('add', '--', verifier.MODEL) + with self.assertRaisesRegex(ValueError, 'Model Git inventory'): + self.verify() + + def test_extra_registry_file_is_rejected(self): + self.write(verifier.REGISTRY + '/unlisted.json', b'{}') + self.git('add', '--', verifier.REGISTRY) + with self.assertRaisesRegex(ValueError, 'Registry Git inventory'): + self.verify() + + def test_missing_staged_model_file_is_rejected(self): + self.git('update-index', '--force-remove', verifier.MODEL + '/module.py') + with self.assertRaisesRegex(ValueError, 'Model Git inventory'): + self.verify() + + def test_symlink_blob_mode_is_rejected_without_following_it(self): + path = verifier.MODEL + '/module.py' + oid = self.git('rev-parse', ':' + path).decode().strip() + self.git('update-index', '--cacheinfo', '120000,' + oid + ',' + path) + with self.assertRaisesRegex(ValueError, 'Symlink/gitlink/nonregular'): + self.verify() + + def test_gitlink_is_rejected(self): + self.git('commit', '--quiet', '-m', 'synthetic only') + oid = self.git('rev-parse', 'HEAD').decode().strip() + self.git('update-index', '--add', '--cacheinfo', '160000,' + oid + ',' + verifier.MODEL + '/submodule') + with self.assertRaisesRegex(ValueError, 'Symlink/gitlink/nonregular'): + self.verify() + + def test_unmerged_index_is_rejected(self): + path = verifier.MODEL + '/module.py' + oid = self.git('rev-parse', ':' + path).decode().strip() + self.git('update-index', '--force-remove', path) + self.git('update-index', '--index-info', data=('100644 ' + oid + ' 1\t' + path + '\n').encode()) + with self.assertRaisesRegex(ValueError, 'Unmerged index'): + self.verify() + + def test_anchored_index_source_escape_is_rejected(self): + data = json.loads((self.repo / verifier.REGISTRY / 'evidence-index.json').read_bytes()) + data[0]['source'] = 'experiments/another-phase/audit/final-status.json' + self.anchored_registry_change('evidence-index.json', encoded(data)) + with self.assertRaisesRegex(ValueError, 'Evidence index differs'): + self.verify() + + def test_anchored_registry_copy_cannot_disagree_with_model(self): + data = (self.repo / verifier.REGISTRY / 'model/checksums.sha256').read_bytes() + self.anchored_registry_change('model/checksums.sha256', b'0' * 64 + data[64:]) + with self.assertRaisesRegex(ValueError, 'Checksum inventory'): + self.verify() + + def test_anchored_receipt_cannot_change_model_manifest_anchor(self): + self.receipt['model_manifest_sha256'] = '0' * 64 + self.receipt_write(); self.git('add', '--', verifier.REGISTRY) + with self.assertRaisesRegex(ValueError, 'Receipt-bound manifest'): + self.verify() + + def test_registry_payload_corruption_is_rejected(self): + path = verifier.REGISTRY + '/evidence/case/summary.json' + self.write(path, b'{"synthetic":false}\n') + self.git('add', '--', path) + with self.assertRaisesRegex(ValueError, 'Git blob (byte count|SHA-256) mismatch'): + self.verify() + + def test_anchored_receipt_path_escape_and_duplicate_fail(self): + self.receipt['files'][0]['path'] = '../outside.json' + self.receipt_write(); self.git('add', '--', verifier.REGISTRY) + with self.assertRaisesRegex(ValueError, 'Noncanonical or escaping path'): + self.verify() + + def test_duplicate_json_key_fails_even_with_external_anchor(self): + data = encoded(self.receipt).replace(b'{\n', b'{\n "publication_complete": true,\n', 1) + self.write(verifier.REGISTRY + '/publication-receipt.json', data) + self.anchor = verifier.sha(data) + self.git('add', '--', verifier.REGISTRY) + with self.assertRaisesRegex(ValueError, 'Duplicate JSON key'): + self.verify() + + def test_incomplete_status_is_preserved_not_regraded(self): + self.receipt['declared_audit_status'] = 'INCOMPLETE-VALIDATION-EXECUTION' + self.receipt_write(); self.git('add', '--', verifier.REGISTRY) + result = self.verify() + self.assertEqual(result['declared_audit_status'], 'INCOMPLETE-VALIDATION-EXECUTION') + self.assertTrue(result['publication_integrity_is_not_scientific_pass']) + + def test_anchored_bulk_omission_inventory_mismatch_fails(self): + self.receipt['experiment_payload_not_copied'] = [] + self.receipt_write(); self.git('add', '--', verifier.REGISTRY) + with self.assertRaisesRegex(ValueError, 'omitted-bulk inventory mismatch'): + self.verify() + + def test_anchored_seal_proof_contradiction_fails(self): + proof = json.loads((self.repo / verifier.REGISTRY / 'seal-verification.json').read_bytes()) + proof['model']['payload_file_count'] += 1 + self.anchored_registry_change('seal-verification.json', encoded(proof)) + with self.assertRaisesRegex(ValueError, 'Seal-verification evidence contradicts'): + self.verify() + + def test_both_or_neither_git_sources_fail(self): + for kwargs in ({}, {'staged': True, 'commit': 'HEAD'}): + with self.subTest(kwargs=kwargs), self.assertRaisesRegex(ValueError, 'Select exactly one'): + verifier.verify_git_payload(self.repo, self.anchor, **kwargs) + + def test_cli_success_and_failure_are_json_with_exit_status(self): + for anchor, expected in ((self.anchor, 0), ('0' * 64, 1)): + with self.subTest(expected=expected), contextlib.redirect_stdout(io.StringIO()) as output: + code = verifier.main(['--repo', str(self.repo), '--staged', '--receipt-sha256', anchor]) + result = json.loads(output.getvalue()) + self.assertEqual(code, expected) + self.assertEqual(result['pass_all'], expected == 0) + + +if __name__ == '__main__': + unittest.main() diff --git a/tools/phase4al-publication/verify_git_payload.py b/tools/phase4al-publication/verify_git_payload.py new file mode 100644 index 0000000..f4011bb --- /dev/null +++ b/tools/phase4al-publication/verify_git_payload.py @@ -0,0 +1,324 @@ +"""Verify fixed Phase 4AL Git blobs, not working-tree files or scientific gates. + +The publication receipt SHA-256 must come from an external trusted record. +Only the index or one resolved commit is read. No publish, checkout, index +mutation, network fetch, or scientific execution is performed. +""" +from __future__ import annotations + +import argparse +import hashlib +import json +import os +from pathlib import Path, PurePosixPath +import re +import subprocess +import sys + + +PROJECT = '/data/digital-drosophila' +MODEL = 'models/male-cns-lif/mb-credit-transfer-audit-v1' +EXPERIMENT = 'experiments/phase4al-mb-credit-transfer' +REGISTRY = 'registry/phase4al-mb-credit-transfer' +CONTROLS = frozenset(('manifest.json', 'checksums.sha256')) +SHA256 = re.compile(r'[0-9a-f]{64}\Z') +OID = re.compile(r'(?:[0-9a-f]{40}|[0-9a-f]{64})\Z') +MAX_EVIDENCE = 4 * 1024 ** 2 +MAX_BLOB = 64 * 1024 ** 2 +SUFFIXES = frozenset(('.json', '.csv', '.md', '.log', '.sha256')) + + +def require(condition, message): + if not condition: + raise ValueError(message) + + +def sha(data): + return hashlib.sha256(data).hexdigest() + + +def relative(value): + require(isinstance(value, str) and bool(value) and + not any(char in value for char in '\\\x00\n\r\t'), 'Invalid relative path') + path = PurePosixPath(value) + require(not path.is_absolute() and str(path) == value and + all(part not in ('', '.', '..') and ':' not in part for part in path.parts), + 'Noncanonical or escaping path: ' + value) + return value + + +def unique_object(pairs): + value = {} + for key, item in pairs: + require(key not in value, 'Duplicate JSON key: ' + key) + value[key] = item + return value + + +def json_bytes(data): + def nonfinite(value): + raise ValueError('Nonfinite JSON value: ' + value) + return json.loads(data.decode('utf-8'), object_pairs_hook=unique_object, + parse_constant=nonfinite) + + +def rows_by_path(rows, label): + require(isinstance(rows, list) and bool(rows), 'Missing/empty ' + label) + result = {} + for row in rows: + require(isinstance(row, dict) and set(row) == {'path', 'bytes', 'sha256'}, + 'Invalid ' + label + ' row schema') + path = relative(row['path']) + require(path not in result and '__pycache__' not in PurePosixPath(path).parts, + 'Duplicate/cache ' + label + ' path: ' + path) + require(type(row['bytes']) is int and row['bytes'] >= 0 and + isinstance(row['sha256'], str) and SHA256.fullmatch(row['sha256']), + 'Invalid bytes/SHA-256 in ' + label + ': ' + path) + result[path] = row + return result + + +class GitBlobs: + """Snapshot inventory plus immutable object reads; no work-tree fallback.""" + + def __init__(self, repo, *, staged, commit): + require(type(staged) is bool and (staged != (commit is not None)), + 'Select exactly one of staged or commit') + self.repo = Path(repo).resolve(strict=True) + require(self.repo.is_dir(), 'Repository must be a directory') + self.env = os.environ.copy() + # The explicitly supplied repo/index must not be redirected by caller env. + for key in ('GIT_DIR', 'GIT_WORK_TREE', 'GIT_INDEX_FILE', 'GIT_COMMON_DIR', + 'GIT_OBJECT_DIRECTORY', 'GIT_ALTERNATE_OBJECT_DIRECTORIES'): + self.env.pop(key, None) + self.env.update(GIT_OPTIONAL_LOCKS='0', GIT_NO_REPLACE_OBJECTS='1', GIT_NO_LAZY_FETCH='1') + self.base = ['git', '--no-optional-locks', '-c', 'core.fsmonitor=false', + '-c', 'gc.auto=0', '-C', str(self.repo)] + top = self.command('rev-parse', '--show-toplevel').decode('utf-8').strip() + require(Path(top).resolve(strict=True) == self.repo, 'Supply the Git repository top-level directory') + if staged: + self.commit = None + else: + require(isinstance(commit, str) and bool(commit) and not commit.startswith('-') and + not any(c in commit for c in '\x00\n\r'), 'Invalid commit selector') + self.commit = self.command('rev-parse', '--verify', '--end-of-options', + commit + '^{commit}').decode('ascii').strip() + require(OID.fullmatch(self.commit), 'Commit did not resolve to a full object ID') + self.staged = staged + self.inventory_bytes = self.inventory() + self.entries = self.parse_inventory(self.inventory_bytes) + self.verified = {} + + def command(self, *args): + result = subprocess.run(self.base + list(args), env=self.env, stdout=subprocess.PIPE, + stderr=subprocess.PIPE, check=False) + require(result.returncode == 0, 'Git read failed: ' + result.stderr.decode('utf-8', 'replace').strip()) + return result.stdout + + def inventory(self): + if self.staged: + return self.command('ls-files', '--stage', '--full-name', '-z', '--', MODEL, REGISTRY) + return self.command('ls-tree', '-r', '-z', '--full-tree', self.commit, '--', MODEL, REGISTRY) + + def parse_inventory(self, data): + result = {} + require(data.endswith(b'\x00'), 'Empty/malformed scoped Git inventory') + for entry in data[:-1].split(b'\x00'): + metadata, raw_path = entry.split(b'\t', 1) + fields = metadata.decode('ascii').split(' ') + require(len(fields) == 3, 'Malformed Git entry') + if self.staged: + mode, oid, stage = fields + require(stage == '0', 'Unmerged index entry is forbidden') + else: + mode, kind, oid = fields + require(kind == 'blob', 'Non-blob Git entry is forbidden') + path = relative(raw_path.decode('utf-8')) + require(path.startswith(MODEL + '/') or path.startswith(REGISTRY + '/'), + 'Git entry escapes the fixed AL scopes: ' + path) + require(mode in ('100644', '100755') and OID.fullmatch(oid), + 'Symlink/gitlink/nonregular Git entry is forbidden: ' + path) + require(path not in result, 'Duplicate Git path: ' + path) + result[path] = dict(mode=mode, oid=oid) + return result + + def read(self, path): + relative(path) + require(path in self.entries, 'Missing Git blob: ' + path) + oid = self.entries[path]['oid'] + size = int(self.command('cat-file', '-s', oid).decode('ascii').strip()) + require(0 <= size <= MAX_BLOB, 'Git blob exceeds publication verifier limit: ' + path) + # cat-file blob addresses the object, so attributes/filters/autocrlf do + # not turn a corrupt staged blob into a good working-tree substitute. + data = self.command('cat-file', 'blob', oid) + require(len(data) == size, 'Git object size changed: ' + path) + self.verified[path] = dict(path=path, bytes=len(data), sha256=sha(data), + git_oid=oid, git_mode=self.entries[path]['mode']) + return data + + def match(self, path, row): + data = self.read(path) + require(len(data) == row['bytes'], 'Git blob byte count mismatch: ' + path) + require(sha(data) == row['sha256'], 'Git blob SHA-256 mismatch: ' + path) + return data + + def finish(self): + require(self.inventory() == self.inventory_bytes, 'Scoped Git inventory changed during verification') + + +def seal_controls(manifest_data, checksum_data, expected_relative, expected_sha): + """Validate control syntax/inventory; does not claim absent bulk was read.""" + require(sha(manifest_data) == expected_sha, 'Receipt-bound manifest SHA-256 mismatch') + manifest = json_bytes(manifest_data) + require(isinstance(manifest, dict) and set(manifest) == {'root', 'files'} and + manifest['root'] == PROJECT + '/' + expected_relative, 'Wrong seal manifest schema/root') + rows = rows_by_path(manifest['files'], 'manifest') + require(not (set(rows) & CONTROLS), 'Seal controls listed as payload') + checksums = {} + for line in checksum_data.decode('utf-8').splitlines(): + require(len(line) >= 67 and line[64:66] == ' ' and SHA256.fullmatch(line[:64]), + 'Malformed checksum line') + path = relative(line[66:]) + require(path not in checksums, 'Duplicate checksum path: ' + path) + checksums[path] = line[:64] + require(checksums == {**{name: row['sha256'] for name, row in rows.items()}, + 'manifest.json': sha(manifest_data)}, + 'Checksum inventory or manifest self-checksum mismatch') + return rows + + +def control_rows(manifest_data, checksum_data): + return {name: dict(path=name, bytes=len(data), sha256=sha(data)) for name, data in + (('manifest.json', manifest_data), ('checksums.sha256', checksum_data))} + + +def verify_git_payload(repo, receipt_sha256, *, staged=False, commit=None): + require(isinstance(receipt_sha256, str) and SHA256.fullmatch(receipt_sha256), + 'External publication receipt SHA-256 is required') + blobs = GitBlobs(repo, staged=staged, commit=commit) + receipt_data = blobs.read(REGISTRY + '/publication-receipt.json') + require(len(receipt_data) <= MAX_EVIDENCE and sha(receipt_data) == receipt_sha256, + 'External publication receipt SHA-256 mismatch') + receipt = json_bytes(receipt_data) + require(isinstance(receipt, dict) and receipt.get('publication_complete') is True and + receipt.get('registry') == REGISTRY and receipt.get('project_root') == PROJECT and + receipt.get('model_payload_remains_at') == MODEL and receipt.get('bulk_remains_at') == EXPERIMENT, + 'Wrong/incomplete AL publication receipt or fixed scope') + for key in ('model_manifest_sha256', 'experiment_manifest_sha256'): + require(isinstance(receipt.get(key), str) and SHA256.fullmatch(receipt[key]), + 'Invalid receipt manifest anchor: ' + key) + registry_rows = rows_by_path(receipt.get('files'), 'receipt files') + require('publication-receipt.json' not in registry_rows, 'Receipt must not list itself') + require({'evidence-index.json', 'seal-verification.json', 'model/manifest.json', + 'model/checksums.sha256', 'evidence/manifest.json', 'evidence/checksums.sha256'} <= set(registry_rows), + 'Required registry evidence/control missing') + observed_registry = {path[len(REGISTRY) + 1:] for path in blobs.entries if path.startswith(REGISTRY + '/')} + require(observed_registry == set(registry_rows) | {'publication-receipt.json'}, + 'Registry Git inventory has unlisted/missing files: ' + repr(sorted( + observed_registry ^ (set(registry_rows) | {'publication-receipt.json'})))) + controls_data = {} + for path, row in registry_rows.items(): + require(row['bytes'] <= MAX_EVIDENCE, 'Registry receipt file exceeds 4 MiB') + data = blobs.match(REGISTRY + '/' + path, row) + if path in ('evidence-index.json', 'seal-verification.json', 'model/manifest.json', + 'model/checksums.sha256', 'evidence/manifest.json', 'evidence/checksums.sha256'): + controls_data[path] = data + model_manifest, model_checksums = (controls_data['model/' + name] for name in ('manifest.json', 'checksums.sha256')) + model_rows = seal_controls(model_manifest, model_checksums, MODEL, receipt['model_manifest_sha256']) + model_controls = control_rows(model_manifest, model_checksums) + observed_model = {path[len(MODEL) + 1:] for path in blobs.entries if path.startswith(MODEL + '/')} + require(observed_model == set(model_rows) | CONTROLS, + 'Model Git inventory has unlisted/missing files: ' + repr(sorted(observed_model ^ (set(model_rows) | CONTROLS)))) + for path, row in {**model_rows, **model_controls}.items(): + blobs.match(MODEL + '/' + path, row) + exp_manifest, exp_checksums = (controls_data['evidence/' + name] for name in ('manifest.json', 'checksums.sha256')) + exp_rows = seal_controls(exp_manifest, exp_checksums, EXPERIMENT, receipt['experiment_manifest_sha256']) + exp_controls = control_rows(exp_manifest, exp_checksums) + expected_index = {} + omitted = [] + for path, row in {**exp_rows, **exp_controls}.items(): + if PurePosixPath(path).suffix.lower() in SUFFIXES and row['bytes'] <= MAX_EVIDENCE: + expected_index['evidence/' + path] = dict(source=EXPERIMENT + '/' + path, + copy='evidence/' + path, bytes=row['bytes'], sha256=row['sha256']) + else: + omitted.append(dict(row, reason='exceeds_4_MiB' if row['bytes'] > MAX_EVIDENCE + else 'bulk_or_non_evidence_extension')) + for path, row in model_controls.items(): + expected_index['model/' + path] = dict(source=MODEL + '/' + path, + copy='model/' + path, bytes=row['bytes'], sha256=row['sha256']) + index = json_bytes(controls_data['evidence-index.json']) + require(isinstance(index, list), 'Evidence index must be a list') + actual_index = {} + for row in index: + require(isinstance(row, dict) and set(row) == {'source', 'copy', 'bytes', 'sha256'}, + 'Invalid evidence-index row schema') + path = relative(row['copy']); relative(row['source']) + require(path not in actual_index and type(row['bytes']) is int and row['bytes'] >= 0 and + isinstance(row['sha256'], str) and SHA256.fullmatch(row['sha256']), + 'Invalid/duplicate evidence-index row') + actual_index[path] = row + require(actual_index == expected_index, 'Evidence index differs from receipt-bound seals/selection policy') + require(set(registry_rows) == set(expected_index) | {'evidence-index.json', 'seal-verification.json'}, + 'Receipt files disagree with copied evidence index') + for path, row in expected_index.items(): + require(registry_rows[path] == dict(path=path, bytes=row['bytes'], sha256=row['sha256']), + 'Evidence-index SHA/bytes disagree with receipt files: ' + path) + require(type(receipt.get('copied_evidence_files')) is int and + receipt['copied_evidence_files'] == len(expected_index) and + type(receipt.get('copied_evidence_bytes')) is int and + receipt['copied_evidence_bytes'] == sum(row['bytes'] for row in expected_index.values()), + 'Receipt copied-evidence totals mismatch') + omitted_receipt = receipt.get('experiment_payload_not_copied') + require(isinstance(omitted_receipt, list) and all(isinstance(row, dict) for row in omitted_receipt) and + sorted(omitted_receipt, key=lambda row: row.get('path', '')) == sorted(omitted, key=lambda row: row['path']), + 'Receipt omitted-bulk inventory mismatch') + proof = json_bytes(controls_data['seal-verification.json']) + require(isinstance(proof, dict) and set(proof) == {'model', 'experiment'}, 'Invalid seal-verification evidence') + for name, prefix, payload, controls in (('model', MODEL, model_rows, model_controls), + ('experiment', EXPERIMENT, exp_rows, exp_controls)): + record = proof[name] + require(isinstance(record, dict) and record.get('pass_all') is True and + record.get('root') == PROJECT + '/' + prefix and + record.get('payload_file_count') == len(payload) and + record.get('payload_bytes') == sum(row['bytes'] for row in payload.values()) and + record.get('manifest_sha256') == controls['manifest.json']['sha256'] and + record.get('checksums_sha256') == controls['checksums.sha256']['sha256'], + 'Seal-verification evidence contradicts receipt-bound ' + name + ' controls') + blobs.finish() + return dict(pass_all=True, verification='Phase 4AL actual Git blob publication integrity', + source='staged-index' if staged else 'commit', commit=blobs.commit, + fixed_scopes=[MODEL, REGISTRY], receipt_sha256=receipt_sha256, + model_manifest_sha256=receipt['model_manifest_sha256'], + experiment_manifest_sha256=receipt['experiment_manifest_sha256'], + declared_audit_status=receipt.get('declared_audit_status'), + model_payload_files=len(model_rows), registry_receipt_files=len(registry_rows), + verified_blob_count=len(blobs.verified), verified_bytes=sum(row['bytes'] for row in blobs.verified.values()), + scoped_inventory_sha256=sha(blobs.inventory_bytes), + verified_blobs=[blobs.verified[path] for path in sorted(blobs.verified)], + working_tree_payload_used=False, git_index_modified=False, + experiment_bulk_verified_by_this_tool=False, scientific_gate_executed=False, + publication_integrity_is_not_scientific_pass=True) + + +def main(argv=None): + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument('--repo', required=True, help='Git repository top-level directory') + parser.add_argument('--receipt-sha256', required=True, help='Trusted external publication-receipt.json SHA-256') + choice = parser.add_mutually_exclusive_group(required=True) + choice.add_argument('--staged', action='store_true', help='Verify the actual stage-0 index blobs') + choice.add_argument('--commit', help='Resolve and verify this commit without checking it out') + args = parser.parse_args(argv) + try: + result = verify_git_payload(args.repo, args.receipt_sha256, staged=args.staged, commit=args.commit) + except (ValueError, OSError, UnicodeError) as error: + result = dict(pass_all=False, verification='Phase 4AL actual Git blob publication integrity', + error_type=type(error).__name__, error=str(error), scientific_gate_executed=False, + publication_integrity_is_not_scientific_pass=True) + print(json.dumps(result, ensure_ascii=False, allow_nan=False)) + return 1 + print(json.dumps(result, ensure_ascii=False, allow_nan=False)) + return 0 + + +if __name__ == '__main__': + sys.exit(main())