diff --git a/CURRENT.md b/CURRENT.md index 77594df..b4cf048 100644 --- a/CURRENT.md +++ b/CURRENT.md @@ -2,24 +2,45 @@ 更新：2026-09-30。独立分支：`codex/lif-author-semantics-lab`。 -## 最新结果 +## 最近已封存结果 -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。 +Phase 4AM：**PASS-EXACT-WHOLEBRAIN-PLASTIC-INTERFACE-NOT-LEARNING**。 -- 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。 +独立建立 D18 whole-brain plastic-overlay 接口，不覆盖或替换旧 reference/runtime。 +75/75 服务器单元测试通过；完整性链 28 个根运行前后全部通过，五组旧参考重新运行全部精确。 +预注册 SHA-256：`465886b78ada08092c2c83de278844707499718977fb6dc6a7608391da0e5304`。 -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。 +- 零 delta 门完成：120 个固定主输入及 24 次技术重复，共 **144/144 与 Phase 4AK D18 精确一致**。 +- 同一库存 static25 的 144 次闭环运行完成，24 次技术重复精确一致；真实反馈重新计算，不钳制源事件。 +- static25 是原 float32 候选权重的 25% floor 经明确 SI 精度桥接，不是学习结果，也不声称等于 float64 基础权重的精确 25%。 +- 120/120 主试验的 MBON、实际 downstream、descending、motor 事件序列及逐细胞计数有变化；12 个 mask 目标的计数变化为 119/120、事件变化为 120/120；KC 事件变化 120/120、计数变化 32/120。这不是每个细胞都变化，也不是学习或行为 PASS。 +- 两阶段都不训练，未产生 learned candidate。zero/static25 阶段墙时分别约 1665.34/1471.04 秒；主试验最大已分配显存 526,523,392 bytes。 -## 下一步 +运行目录：`experiments/phase4am-wholebrain-plastic-interface/`。 +[AM 结果解释](docs/progress/phase4am-interpretation.md) · [正式状态](registry/phase4am-wholebrain-plastic-interface/evidence/audit/final-status.json) · [预注册设计](models/male-cns-lif/wholebrain-plastic-interface-v1/PROTOCOL.md) -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。 +## 前序结论保持不变 -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。 +Phase 4AL：**PASS-CONDITIONAL-CREDIT-TRANSFER-AUDIT-NOT-LEARNING**。 -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。 +固定 D18 的 120 条主轨迹及 24 次重复全部 MBON 基线逐位复现；60 组气味对都有各自特有的 KC/候选边。固定 25% 减弱在 120/120 主试验中改变了 MBON count 或首次 latency，但那是钳制源事件的条件性回放，不是真实全脑反馈、不代表气味特异记忆或响应上界。 -[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) +14,232 条 mask 边、12 个 mask-recipient MBON 和全部 97 个 MBON 保留。 +Phase 4AK D18 表征验证 PASS 原样保留。1.8 ms 为工程 APL 时序假设，不是实测延迟；matched_energy 匹配预期而非每次实际事件数；旧 1212 条非 KC fast-APL 出边未被 graded 路径替代的限制仍存在。 + +[AL 结果解释](docs/progress/phase4al-interpretation.md) · [AL 正式状态](registry/phase4al-mb-credit-transfer/evidence/audit/final-status.json) · [AK 结果解释](docs/progress/phase4ak-interpretation.md) + +## 当前准备与学习边界 + +Phase 4AN 工程计划仍为 **UNREGISTERED**：32 calls / 11,074 ticks，拟比较精简报告运行及 checkpoint 连续性。实际脑运行数为 **0**。学习草案未登记，没有候选；这些工程测试不是条件化实验。 + +目标仍是“学习可以使用”，当前没有达到。接口验证或静态权重效果不能替代真实条件化。 +后续须预注册固定 olfactory A/B、具体 DAN type/compartment、至少五个互不重叠训练种子流及独立 evaluation streams；保留原 eligibility-v2、人工 US 与实际 DAN 放电的明确区分，以及配对/控制、反转、延迟奖励、保持等功能验证。 + +继续冻结 raw/base CSR/W_syn/sign、既有 APL 参数、eligibility-v2、14,232-edge mask 和全部已封存产物。不调参挽救结果，不接游戏、视觉、decoder、RL 或 Web。 + +AM 已正式封存并在服务器发布 3,020 份小证据；本地已按发布收据逐项验收 3,040 个文件（含控制与清单文件）。Git 同步范围仅为源码、文档及小证据，须单独验证提交载荷。大型轨迹保留在服务器，小证据同步不等于全量异机备份。 + +模型 manifest SHA-256：`7edeb251ecbeac5a64805fefe171a0a0bf8bba2675919ef922cc1a329c203ea8`。 +实验 manifest SHA-256：`9e24b682935a9b18e05db7a933080c5f63ddbeb8a0c85cc0df1cfe1d06d88ab4`。 +正式状态 SHA-256：`18b12c832e156bd6e5ba950f48a49fb908c62104b91bb3e78213f523c8fdc8f9`。 diff --git a/docs/progress/phase4am-interpretation.md b/docs/progress/phase4am-interpretation.md new file mode 100644 index 0000000..966f1c5 --- /dev/null +++ b/docs/progress/phase4am-interpretation.md @@ -0,0 +1,54 @@ +# Phase 4AM — D18 全脑塑性权重接口 + +日期：2026-09-30。正式状态：`PASS-EXACT-WHOLEBRAIN-PLASTIC-INTERFACE-NOT-LEARNING`。 + +本轮通过的是固定权重接口、闭环运行与记录的一致性验证，不是学习或行为验证。实际运行和正式封存已完成；服务器发布了 3,020 份小证据，本地已按发布收据逐项验收 3,040 个文件（含控制与清单文件）。Git 发布范围仅为源码、文档及小证据。 + +## 已完成的固定门 + +- zero：120 个固定主输入及 24 次技术重复，共 144/144 与封存 Phase 4AK D18 精确一致；覆盖状态、事件、计数、延迟队列、请求接受及 APL generated/applied/pending 记录。 +- static25：同一完整库存共 144 次闭环运行完成，24 次技术重复精确一致。每条轨迹的上游、反馈和目标发放都重新计算，没有沿用 AL 的钳制源事件。 +- 五组旧 deterministic-v2 参考重新运行全部精确；28 个旧完整性根运行前后全部通过。旧参考回归不表示新 D18 与旧动力学等价。 +- zero / static25 阶段墙时分别为 1665.339973549002 / 1471.0373302119988 秒。主试验报告的最大已分配显存为 526,523,392 bytes；不是全机内存或全部进程峰值。 + +每阶段统计样本仍为 120 个主试验，24 次重复不增加独立样本数。两种输入模式和两个原定 cohort 均保留；`novel_to_aj` 仅指相对于 AJ 新增，不宣称历史从未见过。`matched_energy` 仍匹配预期随机输入，不保证每次实际事件数相同。 + +## 静态干预的实际含义 + +候选 mask 保持 14,232 条边，目标为 12 个 MBON；报告同时覆盖全部 97 个 MBON。原 raw/base CSR、sign、W_syn、APL 参数、eligibility-v2 与 mask 均未改变。 + +static25 使用原 float32 候选 base 的 `-.25 * base_candidate_mv` floor，安装时仅对非零 delta 行按独立运算加入 `float64(delta32) * .001` SI 增量。它不是 float64 D18 基础权重的精确 25%，不是训练所得 delta，也不是最大功能效应上界。每个试验开始前固定 delta，试验内不更新权重。 + +以下比较均为 static25 相对于 zero，在全部 120 个主试验上的描述性结果： + +| 群体 | 事件序列改变的试验 | 至少一个细胞计数改变的试验 | +|---|---:|---:| +| 全部 MBON | 120/120 | 120/120 | +| 实际 MBON downstream | 120/120 | 120/120 | +| descending | 120/120 | 120/120 | +| motor | 120/120 | 120/120 | +| 12 个 mask-recipient MBON | 120/120 | 119/120 | +| KC | 120/120 | 32/120 | + +这些数值不是“每个细胞都改变”，也不必表示群体总 spike count 改变。它们说明固定候选边干预能在本模型的真实全脑反馈中影响发放；不能推出气味特异关联记忆、正确行为方向、感知或运动能力。AL 的非零条件回放使用不同精度干预并钳制反馈，因此不能充当本轮非零结果的严格算术 oracle。 + +## 未跨越的边界 + +D18 的 1.8 ms APL 延迟仍是工程时序假设，不是实测生理延迟。既有 1,212 条非 KC fast-APL 出边置零、而未由 graded 路径替代的限制未修正。早期 Brian 闭环对照共享 APL 组件，不是所有组件独立实现的 CPU 等价证明。本轮没有重新标定这些假设。 + +没有训练、没有 learned candidate、没有学习 PASS；不接游戏、视觉、decoder、RL 或 Web。条件化仍需单独预注册实际 cue/US、冻结 eligibility-v2、独立评估种子、未配对等控制及真实时间保持，不能把静态响应当作已获得记忆。 + +下一项 AN 目前仅有 **UNREGISTERED** 工程计划：32 calls、11,074 ticks，用于精简报告运行与 checkpoint 续跑的精确对照；实际脑运行数为 0。学习草案也未登记，没有由本轮结果自动解锁训练或产生候选。 + +## 证据与交付 + +[正式状态](../../registry/phase4am-wholebrain-plastic-interface/evidence/audit/final-status.json) · [科学汇总](../../registry/phase4am-wholebrain-plastic-interface/evidence/audit/scientific-summary.json) · [固定协议](../../models/male-cns-lif/wholebrain-plastic-interface-v1/PROTOCOL.md) · [发布收据](../../registry/phase4am-wholebrain-plastic-interface/publication-receipt.json) + +- 预注册 SHA-256：`465886b78ada08092c2c83de278844707499718977fb6dc6a7608391da0e5304` +- 科学汇总 SHA-256：`03f229fc0768d38bb7c2a3c558dbd68c2c3a622cbf96b1b16aef2819b6b67b77` +- 正式状态 SHA-256：`18b12c832e156bd6e5ba950f48a49fb908c62104b91bb3e78213f523c8fdc8f9` +- 模型 manifest SHA-256：`7edeb251ecbeac5a64805fefe171a0a0bf8bba2675919ef922cc1a329c203ea8` +- 实验 manifest SHA-256：`9e24b682935a9b18e05db7a933080c5f63ddbeb8a0c85cc0df1cfe1d06d88ab4` +- 发布收据 SHA-256：`7bb7c8edc1d1c09e9c5aa37c0fb367431ee9b8afe83dbcaff0f3cec5d22017f7` + +大型轨迹保留在服务器。小证据发布不等于全量异机备份；Git 暂存载荷及提交载荷须另外使用发布收据 SHA 校验，不能由本地下载成功推断远端 Git 已同步。 diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/PREPARATION.md b/models/male-cns-lif/wholebrain-plastic-interface-v1/PREPARATION.md new file mode 100644 index 0000000..db76e90 --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/PREPARATION.md @@ -0,0 +1,28 @@ +# Pre-registration engineering checks + +No new brain trajectory or conditioning result existed during these repairs. +Only the new, unregistered AM code was changed; all prior models remained +read-only. The new experiment root was provisioned empty and owned by the +existing project user before preparation. + +The first server-only unit test run had 74 tests: 73 passed, one failed +(`test_static25_repeat_and_single_validation`, copied-input SHA mismatch). +The local machine had not reproduced that failure. A direct synthetic probe +established the cause, rather than changing a tolerance or expected result: + +- A temporary NPZ was overwritten with different, same-size (556-byte) data. +- Its device, inode, length, mtime_ns and ctime_ns were identical before/after. +- The fresh SHA changed from + `38219e908f1b500423c9fe1a70b6070103f878903c5f005c79e387fca8b449c4` to + `fa45373dd04bf5f9d574a5329d42f8259c99c70aa69b077673aaef8c95bf0a02`. +- The timestamp-keyed digest cache returned the former SHA for the latter + bytes. Both timestamps were `1790749632756475909` in the observed probe. + +The new comparator was corrected to read fresh bytes for SHA verification and +to include content hashes in static cache identity. A deliberate same-stat, +same-length rewrite test guards this issue. No waiting/sleep workaround, relaxed +hash equality, modified old data, or scientific rerun is used to hide it. + +This note is a human-readable preparation record, not a saved raw unit-test +transcript. The subsequent complete server test transcript is recorded during +formal preparation and must pass without skipped Torch compatibility tests. diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/PROTOCOL.md b/models/male-cns-lif/wholebrain-plastic-interface-v1/PROTOCOL.md new file mode 100644 index 0000000..9497fbb --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/PROTOCOL.md @@ -0,0 +1,85 @@ +# Phase 4AM — D18 whole-brain plastic interface + +This is a separate, non-trained branch. All Phase 1–4AL files remain read-only. +The user authorized independent new-model dynamics hypothesis tests. No base +CSR, transmitter sign, W_syn, neuron threshold, APL calibration, eligibility-v2, +or 14,232-edge mask is changed. No game, decoder, RL, or visual input is used. + +## Fixed test order and scope + +1. All 120 sealed AK inputs and their 24 predeclared repeats run with exactly + zero plastic_delta. Compare every recorded state bit, event, count, delayed + edge queue, request acceptance, and APL generated/applied/pending sample + against AK. All must pass before any nonzero overlay runs. +2. The same complete input inventory runs with one fixed diagnostic overlay: + the original float32 eligibility-v2 floor, `-.25 * base_candidate_mv`. + All 14,232 mask edges are included; all other weights remain identical. + Twenty-four technical repeats must be exact. This is not learned memory. + All presynaptic events are recomputed by the whole brain, unlike AL's + clamped-source MBON replay. No outcome selects an odor, compartment, dose, + parameter, or number of training pairings. +3. Pure-function compatibility tests validate the frozen eligibility trace and + original additive apply_v2 rule. No reinforcement or weight update occurs + in any of these GPU trials. Fixed delta is installed only before tick zero. + +Report both cohorts, both modes, all odors and all seeds. Technical repeats do +not increase the statistical sample. Matched-energy retains its inherited +meaning: expected stochastic input, not exactly matched realized event counts. +Simulation remains 100 ms, including its unadvanced delay/APL tail. + +## Explicit precision bridge — a new interface assumption + +The existing D18 brain uses float64 SI voltage weights. Frozen eligibility-v2 +uses float32 mV deltas and float32 candidate base amplitudes. The adapter keeps +the original D18 base bytes and adds `float64(delta32) * float64(.001)` using +separate non-fused operations, only on nonzero delta rows. Zero delta must not +reconstruct the base through float32. Positive original mask weights must +remain positive. This is not a claim of bitwise nonzero equivalence to the old +float32 brain, nor of precisely 25% of float64 D18 amplitudes. The base candidate +is reproduced from the pinned original Phase 4C NumPy expression, not converted +back from the float64 brain. The mask and all units are recorded. + +Only the pre-loop weight-install hook is inserted in an AST-derived copy of +the SHA-pinned AJ function. Its timestep loop AST and original CUDA operators +remain identical. The old module is not patched and its original __file__ is +not fabricated. Inherited AJ source metadata describes the parent; additional +AM adapter provenance explicitly describes the new overlay. The original spike +delay queue stores spike identities and reads fixed weights at arrival. No +mid-trial update or implicit weight-snapshot delay rule is introduced. + +## Interpretation and next experiment boundary + +Record MBON, KC, DAN, actual MBON downstream, descending and motor output +changes separately, as well as first divergence and recruited/lost KC cells. +Static transfer is neither associative acquisition nor a maximal functional +effect bound. A weak static response does not prove all sparse overlays fail. +The full-brain response is not compared with AL as a strict arithmetic oracle: +AL clamps feedback and its float64 0.75 multiplication is a different fixed +precision intervention. Any side-by-side descriptive result states both. + +Conditioning must be separately preregistered. Keep the original 4L static +ODOR_A (4-ethylphenol) and ODOR_B (3-hexanone), reciprocal cue assignments, +type/compartment-specific US and frozen eligibility-v2. PAM/PPL1 alone never +defines valence. The original D scalar is an artificial unconditioned-signal +interface, not measured dopamine or the number of actually emitted DAN spikes. +Log requests, acceptance, and actual DAN spikes separately. Multiplying D by +actual accepted spikes would be a different explicitly registered hypothesis, +not an unnoticed repair of eligibility-v2. No such change is made here. + +Later functional learning requires independent evaluation seeds, actual paired +and control trajectories, MBON and downstream specificity, reversal and real +time retention. Neither file validity, delta change nor a static response +completes the learning goal. This stage creates no learned candidate. + +## Integrity + +Exclusive-create outputs, a pre-outcome source/input/config manifest, fixed +trial inventory, unit-test records, complete per-trial recording hashes, +pre/post frozen integrity, and the five unchanged deterministic-v2 reference +trials are required. Partial outputs are preserved and never overwritten. +No queued ComfyUI job is evicted. Only the declared RTX 4090 is used. The old +references are regression checks of the old runtime, not proof of D18 biology. + +The biological limitations and primary-paper evidence are inherited unchanged +from sealed AL EVIDENCE.md; this precision/interface implementation introduces +no new single-cell physiological measurement or universal dopamine rule. diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/adapter.py b/models/male-cns-lif/wholebrain-plastic-interface-v1/adapter.py new file mode 100644 index 0000000..c23bba6 --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/adapter.py @@ -0,0 +1,248 @@ +"""One pre-loop overlay hook in the SHA-pinned AJ function; no old global patch. + +run_gpu_overlay(case_dir, out_dir, build_root, overlay_file, overlay_manifest) +retains AJ's output/summary schema. overlay-audit.json and adapter-provenance.json +are mandatory additional evidence. The inherited source-audit.json describes +the unchanged AJ source only, NOT the complete Phase 4AM adapter semantics. +Delta is fixed during the whole trial; this interface never trains or updates +eligibility. The original CUDA arrival operator still samples current weights +at arrival, and no emission-time weight snapshot is introduced. +""" +from __future__ import annotations + +import ast +import copy +import hashlib +import importlib.util +import json +from pathlib import Path +import sys + +import numpy as np + +import overlay + + +AJ_SHA256 = 'af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b' +PINS = { + 'apl-timing-lab-v1/gpu_timing.py': AJ_SHA256, + 'apl-timing-lab-v1/timing_queue.py': '54df6d4818e2a0c26e96fb0aaf5d9b71cd964981706da937562d48af79aca14e', + 'author-apl-lab-v2/gpu_apl.py': '69f5d893f47dafff4ef7c3186c3df0b9014666b32c8f4e943b57016bec92b18a', + 'author-apl-lab-v2/legacy_apl_worker.py': '21ceec65fe42581dc55872010e0025d660e80358905f1cf4df1dadf341a3b291', + 'author-runtime-lab-v1/gpu_backend.py': '03758d07572f4b44d272059d9308fac534268ad201b57bdd77d69fee95e67278', + 'author-runtime-lab-v1/author_ext.cpp': '208a937d17bbb041b9bf6b25b89264ee566830b60609e58491b44583d8541f15', + 'author-runtime-lab-v1/author_ext.cu': '669f166e18ce9a3f63fc723db8b0a8b74f7fa4757194b1bd65b4cf6008a7787e', + 'author-fullgraph-lab-v1/oracle_full.py': 'd72003d98f0f1624b12126eff50bd361c43d888f4a64d90ba9247a58976f1961', +} +HOOK_NAME = '_phase4am_install_overlay' +HOOK_CODE = HOOK_NAME + '(weights, graph, apl_out_mask, upload, out_dir, source_provenance)' +_LOADED = {} + + +def _save(path, value): + with Path(path).open('x', encoding='utf-8') as stream: + json.dump(value, stream, ensure_ascii=False, sort_keys=True, indent=2, allow_nan=False) + stream.write('\n') + + +def verify_sources(aj_model_dir): + directory = Path(aj_model_dir).absolute() + overlay.require(directory.name == 'apl-timing-lab-v1', 'AJ must be loaded from its actual original model directory') + paths = {key: directory.parent / key for key in PINS} + for key, path in paths.items(): + overlay.require(overlay.file_hash(path) == PINS[key], 'Sealed source SHA mismatch: ' + str(path)) + return {key: {'path': str(paths[key]), 'sha256': value} for key, value in PINS.items()} + + +def _load_checked(name, path, expected): + path = Path(path).absolute() + data = path.read_bytes() + overlay.require(hashlib.sha256(data).hexdigest() == expected, 'Source changed before loading: ' + str(path)) + if name in sys.modules: + existing = sys.modules[name] + overlay.require(_LOADED.get(name) == (path, expected, existing), 'Refusing an existing unverified module binding: ' + name) + return existing + spec = importlib.util.spec_from_file_location(name, path) + overlay.require(spec is not None and spec.loader is not None, 'No source loader') + module = importlib.util.module_from_spec(spec) + sys.modules[name] = module + try: + # Execute precisely the checked source bytes; do not write frozen pyc. + exec(compile(data, str(path), 'exec'), module.__dict__) + except BaseException: + sys.modules.pop(name, None) + raise + _LOADED[name] = (path, expected, module) + return module + + +def _dump(node): + return ast.dump(node, annotate_fields=True, include_attributes=False) + + +def derive_ast(source_bytes): + """Pure AST adapter: one inserted Expr, every other original node unchanged.""" + overlay.require(hashlib.sha256(source_bytes).hexdigest() == AJ_SHA256, 'Cannot derive from unpinned AJ source') + module = ast.parse(source_bytes) + matches = [node for node in module.body if isinstance(node, ast.FunctionDef) and node.name == 'run_gpu'] + overlay.require(len(matches) == 1, 'Expected exactly one sealed AJ run_gpu') + original = matches[0] + adapted = copy.deepcopy(original) + tries = [node for node in adapted.body if isinstance(node, ast.Try)] + overlay.require(len(tries) == 1, 'Unexpected run_gpu try structure') + statements = tries[0].body + anchor = ast.parse('effective_hash = hashlib.sha256()').body[0] + positions = [i for i, node in enumerate(statements) if _dump(node) == _dump(anchor)] + overlay.require(len(positions) == 1, 'Effective-weight hash insertion anchor is not unique') + position = positions[0] + previous = ast.parse('if bool(np.any(apl_out_mask)):\n weights[upload(apl_out_mask, torch.bool)] = 0.0').body[0] + overlay.require(position > 0 and _dump(statements[position - 1]) == _dump(previous), + 'Overlay hook must immediately follow frozen fast-APL zeroing') + hook = ast.copy_location(ast.parse(HOOK_CODE).body[0], statements[position]) + statements.insert(position, hook) + tick_loops = lambda tree: [node for node in ast.walk(tree) if isinstance(node, ast.For) and + isinstance(node.target, ast.Name) and node.target.id == 'tick'] + old_loops, new_loops = tick_loops(original), tick_loops(adapted) + overlay.require(len(old_loops) == len(new_loops) == 1 and _dump(old_loops[0]) == _dump(new_loops[0]), + 'Entire simulation loop AST must remain identical') + restored = copy.deepcopy(adapted) + restored_try = next(node for node in restored.body if isinstance(node, ast.Try)) + restored_try.body.pop(position) + overlay.require(_dump(restored) == _dump(original), 'Adapter changed more than its single pre-loop hook') + ast.fix_missing_locations(adapted) + sha = lambda value: hashlib.sha256(value.encode('utf-8')).hexdigest() + audit = {'original_run_ast_sha256': sha(_dump(original)), 'adapted_run_ast_sha256': sha(_dump(adapted)), + 'loop_ast_sha256': sha(_dump(old_loops[0])), 'entire_tick_loop_ast_identical': True, + 'only_ast_change': HOOK_CODE, 'inserted_ast_statements': 1, + 'hook_after_apl_zero_before_effective_hash': True} + return adapted, audit + + +def compile_derived(aj_module, install_hook): + """Compile only the derived function into a NEW namespace, never old globals.""" + source_path = Path(aj_module.__file__).absolute() + function_ast, audit = derive_ast(source_path.read_bytes()) + namespace = dict(aj_module.__dict__) + # Real adapter location, not AJ's __file__ masquerading as a new module. + namespace.update(__name__=__name__ + '.derived_run', __file__=str(Path(__file__).absolute())) + overlay.require(HOOK_NAME not in namespace, 'Hook name collides with sealed globals') + namespace[HOOK_NAME] = install_hook + tree = ast.fix_missing_locations(ast.Module(body=[function_ast], type_ignores=[])) + exec(compile(tree, str(Path(__file__).absolute()) + '::AST-derived-AJ-run_gpu', 'exec'), namespace) + audit.update(derived_namespace_file=namespace['__file__'], original_module_file=str(source_path), + original_module_globals_patched=False, fake_original_file_used=False) + return namespace['run_gpu'], audit + + +def _copy_input(source, destination, expected): + with Path(source).open('rb') as incoming, Path(destination).open('xb') as outgoing: + for block in iter(lambda: incoming.read(8 << 20), b''): + outgoing.write(block) + overlay.require(overlay.file_hash(destination) == expected, 'Copied input hash mismatch') + + +def run_gpu_overlay(case_dir, out_dir, build_root, overlay_file, overlay_manifest): + """Fresh D18 constant-weight interface run; no learning/update inside trial. + + This is the ONLY GPU entry point; importing/testing the module is CPU-only. + Output is exclusive. The caller still owns preregistration, case/graph and + frozen-mask authority, resource checks, budgets, and scientific gate choice. + Success requires the added complete adapter-provenance.json, not merely an + inherited AJ summary that may precede a failed final wrapper verification. + """ + case_dir, out_dir = Path(case_dir).absolute(), Path(out_dir).absolute() + overlay.require(not out_dir.exists(), 'Refusing an existing output directory') + overlay.require(sys.dont_write_bytecode, 'Invoke with python -B so inherited loaders cannot write frozen __pycache__') + own_sources = {'adapter': overlay.file_hash(__file__), 'overlay': overlay.file_hash(overlay.__file__)} + plan = overlay.load_overlay(overlay_file, overlay_manifest) + spec = json.loads((case_dir / 'spec.json').read_text(encoding='utf-8')) + overlay.require(type(spec.get('apl_delay_steps')) is int and spec['apl_delay_steps'] == 18, + 'Phase 4AM interface requires fixed D18') + overlay.require(spec.get('training', False) is False and spec.get('learning', False) is False, + 'This interface does not authorize a learning run') + aj_dir = Path(plan['metadata']['aj_model_dir']) + sources = verify_sources(aj_dir) + _load_checked('timing_queue', aj_dir / 'timing_queue.py', PINS['apl-timing-lab-v1/timing_queue.py']) + aj = _load_checked('phase4am_sealed_aj_gpu', aj_dir / 'gpu_timing.py', AJ_SHA256) + base_file = Path(spec['graph_dir']) / 'weights.npy' + base_file_sha = overlay.file_hash(base_file) + calls = [] + + def install(weights, graph, apl_out_mask, upload, output, inherited_provenance): + overlay.require(not calls, 'Plastic overlay hook must run exactly once') + mapping = overlay.map_installation(graph['weights'], graph['edge_id'], apl_out_mask, plan) + if len(graph['nodes']) == 166700: + overlay.require(int(apl_out_mask.sum()) == 5845, 'Frozen fullgraph fast-APL mask changed') + torch = aj.torch + overlay.require(weights.dtype == torch.float64 and weights.ndim == 1 and weights.numel() == len(graph['edge_id']), + 'Runtime weight tensor must retain float64 SI edge order') + rows = mapping['rows'] + if len(rows): + local = upload(rows, torch.int64) + # Separate eager f64 multiply and addition, never base->f32 roundtrip. + delta32 = plan['plastic_delta_mv'][plan['plastic_delta_mv'] != np.float32(0)] + delta_si = upload(delta32, torch.float64) * 0.001 + weights[local] = weights[local] + delta_si + actual = weights[local].cpu().numpy().copy() + overlay.require(overlay.bit_equal(actual, mapping['expected_si']), 'GPU installation differs from independent CPU SI arithmetic') + # With zero delta no indexing assignment or +0 arithmetic happens. + base_raw_sha, expected_sha = overlay.expected_hashes(graph['weights'], apl_out_mask, mapping) + actual_hash = hashlib.sha256() + for start in range(0, weights.numel(), 1 << 20): + actual_hash.update(weights[start:start + (1 << 20)].cpu().numpy().astype('= 0) & (ticks < STEPS)) and np.all((nodes >= 0) & (nodes < N)), 'Invalid sparse requests') + keys = ticks.astype(np.int64) * N + nodes + require(np.all(keys[1:] > keys[:-1]), 'Requests must be sorted unique; no silently deduplicated requests') + coeff_path = Path(spec['coefficients_path']) + require(coeff_path.is_absolute(), 'Coefficient path must be absolute') + coeff = _json(coeff_path, used) + for key in ('gd', 'c0', 'cg', 'cv', 'threshold', 'reset', 'seed_volt'): + require(type(coeff[key]) in (int, float) and math.isfinite(coeff[key]), 'Invalid author coefficient: ' + key) + require(coeff['threshold'] == model['threshold_mv'] * .001 and + coeff['reset'] == model['reset_potential_mv'] * .001 and coeff['seed_volt'] > coeff['threshold'], + 'Author coefficient units/threshold mismatch') + input_hashes = {'spec.json': file_hash(case_dir / 'spec.json'), + 'requests.npz': file_hash(case_dir / 'requests.npz'), 'base_weights.npy': file_hash(graph_dir / 'weights.npy'), + 'coefficients.json': file_hash(coeff_path)} + if (case_dir / 'arrays.npz').exists(): + used.add(case_dir / 'arrays.npz') + input_hashes['arrays.npz'] = file_hash(case_dir / 'arrays.npz') + return dict(spec=spec, graph=graph, bundle=bundle, token=token, input_hashes=input_hashes, + requested=list(zip(map(int, ticks), map(int, nodes))), graph_dir=graph_dir, bundle_dir=bundle_dir) + + +_VALIDATED_STATIC = set() + + +def _validate_static(graph, bundle, token): + if token in _VALIDATED_STATIC: + return + for key, dtype, shape in (('nodes', np.int32, (N,)), ('ptr', np.int64, (N + 1,)), + ('edge_id', np.int64, (E,)), ('src', np.int32, (E,)), ('dst', np.int32, (E,)), + ('signed_raw', np.int64, (E,)), ('weights', np.float64, (E,))): + require(graph[key].dtype == dtype and graph[key].shape == shape, 'Canonical graph schema changed: ' + key) + require(np.array_equal(graph['nodes'], np.arange(N, dtype=np.int32)), 'Global neuron identity changed') + ptr = graph['ptr'] + require(ptr[0] == 0 and ptr[-1] == E and np.all(np.diff(ptr) >= 0), 'Invalid canonical CSR') + for start in range(0, E, 1 << 20): + stop = min(E, start + (1 << 20)) + expected_ids = np.arange(start, stop, dtype=np.int64) + require(np.array_equal(graph['edge_id'][start:stop], expected_ids), 'Original edge identity changed') + require(np.array_equal(graph['src'][start:stop], np.searchsorted(ptr[1:], expected_ids, side='right')), + 'CSR source order changed') + require(np.all((graph['dst'][start:stop] >= 0) & (graph['dst'][start:stop] < N)), 'Invalid edge targets') + original = graph['weights'][start:stop] + expected = graph['signed_raw'][start:stop] * (.275 * .001) + require(np.isfinite(original).all() and raw_hash(original) == raw_hash(expected), 'Original signed SI weights changed') + for name, dtype, shape in (('kc_globals.npy', np.int32, (K,)), ('apl_globals.npy', np.int32, (2,)), + ('input_matrix.npy', np.float32, (2, N)), ('output_matrix.npy', np.float32, (2, K))): + a = bundle[name] + require(a.dtype == dtype and a.shape == shape and np.isfinite(a).all(), 'Invalid APL bundle ' + name) + if dtype == np.int32: + require(np.all((a >= 0) & (a < N)) and np.all(a[1:] > a[:-1]), 'Invalid APL/KC IDs') + else: + require(np.all(a >= 0), 'Negative normalized APL matrix') + require(not np.intersect1d(bundle['kc_globals.npy'], bundle['apl_globals.npy']).size, 'APL/KC overlap') + _VALIDATED_STATIC.add(token) + + +def _effective_hash(case, ids=None, delta=None): + """Independent static bridge, cached per immutable graph/delta identity.""" + key = (case['token'], None if ids is None else raw_hash(ids), None if delta is None else raw_hash(delta)) + if key in _WEIGHT_CACHE: + return _WEIGHT_CACHE[key] + graph, apl = case['graph'], case['bundle']['apl_globals.npy'] + baseline, effective = hashlib.sha256(), hashlib.sha256() + masked = 0 + for start in range(0, len(graph['edge_id']), 1 << 20): + stop = min(len(graph['edge_id']), start + (1 << 20)) + value = graph['weights'][start:stop].copy() + fast = np.isin(graph['src'][start:stop], apl) + masked += int(fast.sum()) + value[fast] = np.float64(0) + baseline.update(value.astype(' 0), 'Static overlay changes candidate sign') + effective.update(value.astype(' keys[:-1]), 'Duplicate or unordered actual events') + require(np.array_equal(np.bincount(local, minlength=n), state['counts']), 'Event counts do not match per-neuron counts') + require([(r['tick'], r['neuron_idx']) for r in run['requests']] == requested, 'Request input identity differs') + bounds = np.searchsorted(state['step'], np.arange(steps + 1)) + rq_bounds = np.searchsorted([r['tick'] for r in run['requests']], np.arange(steps + 1)) + last = np.full(n, -1_000_000_000, np.int64) + failures = {} + expected_due_total = expected_accepted_total = 0 + for tick in range(steps): + fired = local[bounds[tick]:bounds[tick + 1]] + if np.any(tick - last[fired] < 22): + failures.setdefault('refractory_spike_violation', tick) + for row in run['requests'][rq_bounds[tick]:rq_bounds[tick + 1]]: + target = int(np.searchsorted(nodes, row['neuron_idx'])) + require(target < n and nodes[target] == row['neuron_idx'], 'Request outside canonical graph') + accepted = tick - last[target] >= 22 + if row['accepted'] != int(accepted) or row['rejected'] != int(not accepted): + failures.setdefault('request_refractory_gate', tick) + if bool(np.any(fired == target)) != bool(accepted): + failures.setdefault('request_actual_spike', tick) + last[fired] = tick + ref = np.maximum(22 - (tick - last), 0).astype(np.int32) + if helper.raw_hash(ref, '= 18 else np.empty(0, np.int64) + pieces = [np.arange(ptr[source], ptr[source + 1], dtype=np.int64) for source in sources] + rows = np.concatenate(pieces) if pieces else np.empty(0, np.int64) + accepted = (ref[graph['dst'][rows]] == 0).astype(np.uint8) + expected = helper._queue_digest(tick, graph['edge_id'][rows], accepted) + expected_due_total += len(rows) + expected_accepted_total += int(accepted.sum()) + if expected != run['queues'][tick]: + failures.setdefault('full_queue_edge_order_and_acceptance', tick) + if not np.array_equal(ref, state['ref']): + failures['final_ref_from_events'] = steps - 1 + summary = run['summary'] + if summary.get('arriving_edges') != expected_due_total or summary.get('accepted_arriving_edges') != expected_accepted_total: + failures['queue_summary_counts'] = 'mismatch' + checks[role + '.full_event_queue_request_accounting'] = not failures + if failures: + differences[role + '.independent_accounting'] = failures + + +def _overlay(run, case, used, zero_required=False): + folder = run['directory'] + audit = _json(folder / 'overlay-audit.json', used) + require(audit['schema'] == 'phase4am-overlay-audit-v1' and audit['complete'] is True, 'Incomplete overlay audit') + source = audit['input'] + inputs = {} + for label in ('overlay', 'manifest', 'mask', 'base_candidate'): + filename, sha = source[label + '_file'], source[label + '_sha256'] + if filename is None: + require(label == 'base_candidate' and sha is None, 'Required overlay input absent') + inputs[label] = None + continue + path = Path(filename) + require(path.is_absolute(), 'Overlay provenance input must be absolute') + used.add(path) + require(file_hash(path) == sha, 'Overlay input hash mismatch: ' + label) + inputs[label] = path + manifest = _json(inputs['manifest'], used) + require(manifest['schema'] == 'phase4am-overlay-v1' and manifest['overlay_sha256'] == source['overlay_sha256'] and + manifest['mask_sha256'] == source['mask_sha256'] and Path(manifest['mask_path']).resolve() == inputs['mask'].resolve(), + 'Overlay manifest linkage mismatch') + require(manifest['base_candidate_sha256'] == source['base_candidate_sha256'] and + (manifest['base_candidate_path'] is None if inputs['base_candidate'] is None else + Path(manifest['base_candidate_path']).resolve() == inputs['base_candidate'].resolve()), 'Candidate floor provenance mismatch') + require(Path(manifest['aj_model_dir']).resolve() == Path(__file__).resolve().parent.parent / 'apl-timing-lab-v1', + 'Overlay is not bound to the sealed AJ model') + require(audit['copied_overlay_file'] == 'overlay-input.npz' and audit['copied_manifest_file'] == 'overlay-manifest.json', + 'Unexpected copied overlay filenames') + for label, name in (('overlay', 'overlay-input.npz'), ('manifest', 'overlay-manifest.json')): + used.add(folder / name) + require(file_hash(folder / name) == source[label + '_sha256'], 'Copied input mismatch') + arrays = _npz(inputs['overlay'], used) + require(set(arrays) in ({'edge_id', 'plastic_delta_mv'}, {'edge_id', 'plastic_delta_mv', 'base_candidate_mv'}), 'Overlay NPZ schema changed') + ids, delta = arrays['edge_id'], arrays['plastic_delta_mv'] + require(ids.dtype == np.int64 and ids.shape == (CANDIDATES,) and np.all(ids[1:] > ids[:-1]) and + np.all((ids >= 0) & (ids < len(case['graph']['edge_id']))), 'Invalid original plastic edge IDs') + mask = np.load(inputs['mask'], allow_pickle=False) + require(mask.dtype == np.int64 and mask.shape == ids.shape and np.array_equal(mask, ids), 'Frozen plastic mask identity mismatch') + require(delta.dtype == np.float32 and delta.shape == ids.shape and np.isfinite(delta).all() and np.all(delta <= 0), 'Invalid LTD delta') + audit_arrays = dict(arrays) + name = manifest['overlay_name'] + require(name in ('zero', 'static25') and audit['overlay_name'] == name, 'Unknown overlay intervention') + if zero_required: + require(name == 'zero', 'Zero-regression cannot use a nonzero intervention') + if name == 'zero': + require(not np.any(delta != 0), 'Zero overlay contains nonzero delta') + else: + require(inputs['base_candidate'] is not None, 'Static25 requires its frozen float32 mV floor') + if inputs['base_candidate'] is not None: + base = np.load(inputs['base_candidate'], allow_pickle=False) + require(base.dtype == np.float32 and base.shape == ids.shape and np.isfinite(base).all() and np.all(base > 0), 'Invalid old float32 base') + floor = np.multiply(base, np.float32(-.25)) + require(np.all(delta >= floor), 'Delta exceeds the existing depression bound') + if 'base_candidate_mv' in arrays: + require(arrays['base_candidate_mv'].dtype == np.float32 and raw_hash(arrays['base_candidate_mv']) == raw_hash(base), 'Embedded old base differs') + if name == 'static25': + require(raw_hash(delta) == raw_hash(floor), 'Static25 is not the declared old float32 floor') + audit_arrays['base_candidate_mv'] = base + else: + require('base_candidate_mv' not in arrays, 'Embedded unanchored old base is forbidden') + expected_arrays = {key: dict(dtype=str(value.dtype), shape=list(value.shape), raw_sha256=raw_hash(value)) + for key, value in audit_arrays.items()} + require(audit['arrays'] == expected_arrays, 'Overlay array audit differs from actual bytes') + require(np.isin(case['graph']['src'][ids], case['bundle']['kc_globals.npy']).all() and + np.all(case['graph']['weights'][ids] > 0), 'Plastic edge source/sign changed') + baseline_sha, effective_sha, apl_count = _effective_hash(case, ids, delta) + graph = case['graph'] + for key, value in {'candidate_count': CANDIDATES, 'nonzero_delta_count': int(np.count_nonzero(delta)), + 'mapped_candidate_count': CANDIDATES, 'missing_candidate_count': 0, + 'installed_nonzero_count': int(np.count_nonzero(delta)), 'delta_dtype': 'float32', 'delta_units': 'mV', + 'state_dtype': 'float64', 'bridge': BRIDGE, 'installation_schedule': SCHEDULE, + 'weights_updated_during_run': False, 'learning': False, 'zero_delta_no_write': True, + 'frozen_mask_exact': True, 'bounds_pass': True, 'apl_overlap_count': 0, + 'apl_fast_edges_zeroed': apl_count, 'base_graph_files_modified': False, + 'untouched_weights_bitwise_preserved': True, + 'base_weights_file_sha256': file_hash(case['graph_dir'] / 'weights.npy'), + 'base_weights_raw_sha256': _base_raw_hash(case), + 'effective_weights_raw_sha256': effective_sha, 'expected_effective_weights_raw_sha256': effective_sha}.items(): + require(type(audit.get(key)) is type(value) and audit[key] == value, 'Overlay audit mismatch: ' + key) + require(run['summary']['effective_weights_raw_sha256'] == effective_sha, 'Installed effective-weight hash differs from independent bridge') + if zero_required: + require(effective_sha == baseline_sha, 'Zero overlay changed the baseline effective weights') + require(audit['inherited_aj_source_provenance'] == run['summary']['source_provenance'] and + audit['inherited_source_audit_scope'] == 'AJ source provenance only; AM overlay semantics are recorded separately' and + audit['static25_is_exact_fraction_of_float64_base_claimed'] is False and + audit['arrival_weight_sampling'] == 'arrival time; delta fixed for entire trial', 'Overlay semantic scope mismatch') + return audit + + +def _expected_ast(source_path, adapter_path): + """Independently derive just the declared Expr insertion; no adapter import.""" + tree = ast.parse(Path(source_path).read_bytes()) + original = [node for node in tree.body if isinstance(node, ast.FunctionDef) and node.name == 'run_gpu'] + require(len(original) == 1, 'Pinned AJ run_gpu not unique') + original = original[0] + adapted = copy.deepcopy(original) + tries = [node for node in adapted.body if isinstance(node, ast.Try)] + require(len(tries) == 1, 'Pinned run_gpu try not unique') + statements = tries[0].body + dump = lambda node: ast.dump(node, annotate_fields=True, include_attributes=False) + anchor = dump(ast.parse('effective_hash = hashlib.sha256()').body[0]) + indices = [i for i, node in enumerate(statements) if dump(node) == anchor] + require(len(indices) == 1, 'Pinned hook anchor not unique') + index = indices[0] + previous = ast.parse('if bool(np.any(apl_out_mask)):\n weights[upload(apl_out_mask, torch.bool)] = 0.0').body[0] + require(index > 0 and dump(statements[index - 1]) == dump(previous), 'Hook is not immediately after APL zeroing') + statements.insert(index, ast.parse(HOOK_CODE).body[0]) + loops = lambda node: [item for item in ast.walk(node) if isinstance(item, ast.For) and + isinstance(item.target, ast.Name) and item.target.id == 'tick'] + before, after = loops(original), loops(adapted) + require(len(before) == len(after) == 1 and dump(before[0]) == dump(after[0]), 'Hook changed loop AST') + sha = lambda node: hashlib.sha256(dump(node).encode('utf-8')).hexdigest() + return dict(original_run_ast_sha256=sha(original), adapted_run_ast_sha256=sha(adapted), + loop_ast_sha256=sha(before[0]), entire_tick_loop_ast_identical=True, only_ast_change=HOOK_CODE, + inserted_ast_statements=1, hook_after_apl_zero_before_effective_hash=True, + derived_namespace_file=str(adapter_path.absolute()), original_module_file=str(Path(source_path).absolute()), + original_module_globals_patched=False, fake_original_file_used=False) + + +def _adapter_receipt(run, used): + folder = run['directory'] + require(not (folder / 'adapter-error.json').exists(), 'Adapter recorded an error') + receipt = _json(folder / 'adapter-provenance.json', used) + require(receipt['schema'] == 'phase4am-adapter-provenance-v1' and receipt['complete'] is True, + 'Completed inherited AJ summary is insufficient without completed AM receipt') + model = Path(__file__).resolve().parent + for label, filename in (('adapter', 'adapter.py'), ('overlay_module', 'overlay.py')): + path = Path(receipt[label + '_file']) + require(path.is_absolute() and path.resolve() == model / filename, 'Unexpected new wrapper source path') + used.add(path) + require(file_hash(path) == receipt[label + '_sha256'], 'Wrapper source hash changed') + source_rows = {} + for relative, sha in ADAPTER_PINS.items(): + path = model.parent / relative + used.add(path) + require(file_hash(path) == sha, 'Frozen source changed: ' + relative) + source_rows[relative] = {'path': str(path.absolute()), 'sha256': sha} + require(receipt['sealed_sources'] == source_rows, 'Wrapper sealed-source inventory differs') + require(receipt['ast'] == _expected_ast(model.parent / 'apl-timing-lab-v1/gpu_timing.py', model / 'adapter.py'), + 'Wrapper AST does not match independently reconstructed single pre-loop hook') + for key, value in dict(installation_calls=1, weights_updated_during_run=False, learning=False, apl_delay_steps=18, + original_module_globals_patched=False, delta_constant_for_entire_trial=True, + inherited_source_audit_describes_AM_semantics=False).items(): + require(type(receipt.get(key)) is type(value) and receipt[key] == value, 'Wrapper receipt mismatch: ' + key) + require(receipt['scope'] == 'constant sparse overlay installation only; no within-trial plasticity or learning', 'Wrapper scope changed') + require(receipt['overlay_audit_sha256'] == file_hash(folder / 'overlay-audit.json') and + receipt['inherited_summary_sha256'] == file_hash(folder / 'summary.json') and + receipt['effective_weights_raw_sha256'] == run['summary']['effective_weights_raw_sha256'], 'Wrapper receipt not bound to output') + return {key: value for key, value in receipt.items() if key != 'inherited_summary_sha256'} + + +def _provenance(run, case, helper, used): + summary, component = run['summary'], run['component'] + require(summary['input_sha256'] == case['input_hashes'], 'Actual case/weight/coefficient input hash differs') + require(summary['all_finite'] is True and summary['counts_match_sparse_events'] is True and + summary['learning'] is False and summary['state_units'] == 'SI volts', 'Invalid finite/state/learning declaration') + require(summary['sealed_ae_backend_sha256'] == SEALED['ae_backend'], 'Frozen backend changed') + build = summary['build'] + require(build['sources'] == {'author_ext.cpp': CPP_SHA, 'author_ext.cu': CUDA_SHA} and + build['cuda_flags'] == ['-O2', '--fmad=false', '--ftz=false', '--prec-div=true', '--prec-sqrt=true'] and + build['arch_list'] == '8.9', 'Build arithmetic/source contract changed') + source = _json(run['directory'] / 'source-audit.json', used) + require(source == summary['source_provenance'] and source['sealed_source_sha256'] == SEALED and + source['candidate_sha256'] == AJ_SHA and source['module_globals_patched'] is False, 'Inherited AJ source audit changed') + diff = run['directory'] / 'sealed-gpu-source.diff' + used.add(diff) + require(file_hash(diff) == source['source_diff_sha256'], 'Inherited source diff hash mismatch') + bundle = case['bundle'] + require(component['files_sha256'] == {name: file_hash(case['bundle_dir'] / name) for name in bundle} and + component['array_sha256'] == {name: raw_hash(value) for name, value in bundle.items()}, 'Actual APL bundle bytes changed') + require(component['ok'] is True and component['protocol'] == 'phase4ag-apl-v1' and + component['n_neurons'] == N and component['n_apl'] == 2 and component['n_kc'] == K and + component['dt_ms'] == .1, 'APL component dimensions/clock changed') + for key, value in (('decay_f32_bits', np.float32(math.exp(-.1 / 20.))), ('gain_f32_bits', np.float32(.01))): + require(component[key] == f'{int(value.view(np.uint32)):08x}', 'APL constant changed: ' + key) + env = component['environment'] + require(env['cuda_matmul_allow_tf32'] is False and env['float32_matmul_precision'] == 'highest' and + env['precision_configuration_changed_by_component'] is False and '4090' in env['device_name'], + 'GPU precision environment changed') + require(summary['apl_schedule'] == 'end, after threshold/reset and guarded arrivals, unconditional all KC' and + summary['apl_si_conversion'] == 'applied h32 -> float64 -> multiply float64 0.001 -> separate float64 subtraction', + 'APL scheduling or SI conversion changed') + for key in PERFORMANCE: + require(type(summary[key]) in (int, float) and math.isfinite(summary[key]) and summary[key] >= 0, 'Invalid performance field: ' + key) + + +def _summary_pair(left, right, checks, differences): + a = {k: v for k, v in left.items() if k not in PERFORMANCE} + b = {k: v for k, v in right.items() if k not in PERFORMANCE} + checks['summary.nonperformance_exact'] = a == b + if a != b: + differences['summary'] = {key: {'left': a.get(key), 'right': b.get(key)} + for key in sorted(set(a) | set(b)) if a.get(key) != b.get(key) or (key in a) != (key in b)} + + +def compare_runs(case_dir, left, right, output_path=None, mode='zero'): + """Zero-vs-sealed-AK or AM repeat equality; failures return a failed report. + + ``output_path=None`` is read-only. A provided report is created exclusively, + outside both run directories and the input case. Parent protocol must bind + the case and old manifests; this comparator reports exactly the bytes read. + """ + case_dir, left, right = (Path(p).resolve() for p in (case_dir, left, right)) + if output_path is not None: + output_path = Path(output_path).resolve() + require(not output_path.exists(), 'Refusing existing comparison output') + require(not any(output_path.is_relative_to(p) for p in (case_dir, left, right)), 'Comparison must not write into input evidence') + checks, differences, used = {}, {}, {Path(__file__).resolve()} + report = dict(schema='phase4am-comparison-v1', mode=mode, case_dir=str(case_dir), left=str(left), right=str(right), + pass_all=False, learning_achieved=False, candidate_generated=False, tolerance=None, + scope='Exact declared trajectory and static overlay integrity; no physiological or learning PASS', + explicit_exclusions=sorted(PERFORMANCE), independent_cpu_wholebrain_oracle_claim=False) + try: + require(mode in ('zero', 'repeat', 'self'), 'Unknown comparison mode') + require((left == right) == (mode == 'self'), 'Only explicit single-run validation may use one directory') + helper = _helper(used) + case = _load_case(case_dir, used) + spec, graph = case['spec'], case['graph'] + n, edges, steps = len(graph['nodes']), len(graph['edge_id']), spec['steps'] + sides = ((left, 'left_gpu'),) if mode == 'self' else ((left, 'left_gpu'), (right, 'right_gpu')) + runs = [helper._load_run(path, role, n, edges, steps, False, spec['name'], 18, used, checks) + for path, role in sides] + for role, run in zip(('left_gpu', 'right_gpu'), runs): + _provenance(run, case, helper, used) + require(all(np.isfinite(a).all() for a in run['state'].values()), 'Nonfinite final state/events') + _self_consistency(run, graph, case['requested'], steps, helper, role, checks, differences) + helper._timing_sequence_checks(run['apl']['inhibition'], run['apl']['applied'], run['pending'], 18, role, checks, differences) + helper._timing_metadata_checks(run, role, 18, steps, checks) + require(not (run['directory'] / 'first-failure-state.npz').exists(), 'Recorded first numerical failure exists') + if mode != 'self': + helper._pair_outputs(*runs, checks, differences, n, steps, False) + require(runs[0]['timing'] == runs[1]['timing'], 'APL timing metadata differs') + _summary_pair(runs[0]['summary'], runs[1]['summary'], checks, differences) + baseline_sha, _, apl_count = _effective_hash(case) + for run in runs: + require(run['summary']['apl_fast_edges_zeroed'] == apl_count and run['summary']['kc_targets_present'] == K, + 'Fast APL or KC coverage changed') + if mode == 'zero': + require(not (left / 'overlay-audit.json').exists(), 'Zero reference must be the unwrapped sealed AK run') + require(runs[0]['summary']['effective_weights_raw_sha256'] == baseline_sha, 'Sealed reference effective weights changed') + audit = _overlay(runs[1], case, used, zero_required=True) + _adapter_receipt(runs[1], used) + report['overlay_name'] = audit['overlay_name'] + elif mode == 'repeat': + a, b = [_overlay(run, case, used) for run in runs] + require(a == b, 'Repeated overlay provenance/identity differs') + receipts = [_adapter_receipt(run, used) for run in runs] + require(receipts[0] == receipts[1], 'Repeated wrapper provenance differs beyond bound walltime-bearing summary') + report['overlay_name'] = a['overlay_name'] + else: + report['overlay_name'] = _overlay(runs[0], case, used)['overlay_name'] + _adapter_receipt(runs[0], used) + report['scope'] = 'Single-run event/queue/input/static-overlay self-consistency; no repeat, equivalence, physiology or learning PASS' + checks['input_overlay_and_source_provenance'] = True + report.update(nodes=n, edges=edges, steps=steps, apl_delay_steps=18, + full_queue_reconstructed=True, total_spikes=len(runs[0]['state']['step'])) + except Exception as error: + report['error'] = {'type': type(error).__name__, 'message': str(error)} + manifest = [] + try: + for path in sorted(used): + manifest.append(dict(path=str(path.resolve()), bytes=path.stat().st_size, sha256=file_hash(path))) + except Exception as error: + report['read_manifest_error'] = {'type': type(error).__name__, 'message': str(error)} + report.update(checks={key: bool(value) for key, value in checks.items()}, differences=differences, + read_manifest=manifest, failed_checks=sorted(key for key, value in checks.items() if not value)) + report['pass_all'] = bool(checks) and all(checks.values()) and 'error' not in report and 'read_manifest_error' not in report + if output_path is not None: + output_path.parent.mkdir(parents=True, exist_ok=True) + with output_path.open('x', encoding='utf-8') as target: + json.dump(report, target, indent=2, sort_keys=True, allow_nan=False) + target.write('\n') + return report + + +def validate_run(case_dir, output_dir, output_path=None): + """Single-run static-overlay integrity only; not numerical equivalence.""" + return compare_runs(case_dir, output_dir, output_dir, output_path, mode='self') + + +if __name__ == '__main__': + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument('--case', required=True) + parser.add_argument('--left', required=True) + parser.add_argument('--right', required=True) + parser.add_argument('--output', required=True) + parser.add_argument('--mode', choices=('zero', 'repeat', 'self'), required=True) + args = parser.parse_args() + result = compare_runs(args.case, args.left, args.right, args.output, args.mode) + print(json.dumps({'pass_all': result['pass_all'], 'failed_checks': result['failed_checks'], 'error': result.get('error')}, allow_nan=False)) + raise SystemExit(0 if result['pass_all'] else 1) diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/config.json b/models/male-cns-lif/wholebrain-plastic-interface-v1/config.json new file mode 100644 index 0000000..f876154 --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/config.json @@ -0,0 +1,22 @@ +{ + "phase": "4AM", + "purpose": "Exact D18 trial-boundary plastic-overlay interface and closed-loop transfer gate", + "neurons": 166700, + "edges": 25582938, + "candidate_edges": 14232, + "primary_trials": 120, + "technical_repeats": 24, + "steps": 1000, + "dt_ms": 0.1, + "apl_delay_steps": 18, + "stages": ["zero", "static25"], + "max_fractional_depression": 0.25, + "virtual_gate_tick": 900, + "gpu_uuid": "GPU-79f3a85d-adce-7833-7003-6488140ca596", + "output_budget_bytes": 17179869184, + "training": false, + "candidate_generation": false, + "static_test_is_learning": false, + "precision_bridge": "base float64 SI plus separate float64(delta float32 mV) times 0.001; zero rows untouched", + "future_learning": "Original frozen eligibility-v2 and additive trial-boundary update; artificial scalar D remains separate from actual DAN events" +} diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/context.py b/models/male-cns-lif/wholebrain-plastic-interface-v1/context.py new file mode 100644 index 0000000..515a1d5 --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/context.py @@ -0,0 +1,115 @@ +"""New branch only. Old files are hash-anchored read-only 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/phase4am-wholebrain-plastic-interface' +AK = ROOT / 'experiments/phase4ak-apl-timing-validation' +AL = ROOT / 'experiments/phase4al-mb-credit-transfer' +AL_MODEL = ROOT / 'models/male-cns-lif/mb-credit-transfer-audit-v1' +AJ_MODEL = ROOT / 'models/male-cns-lif/apl-timing-lab-v1' +AG = ROOT / 'experiments/phase4ag-author-apl-r2' +H = ROOT / 'experiments/phase4h-dopamine-plasticity' +META = ROOT / 'datasets/male-cns-v1.0/processed/neuron-only/neuron-index/unified-metadata.parquet' +CFG = json.loads((MODEL / 'config.json').read_text(encoding='utf-8')) +PINS = { + 'models/male-cns-lif/mb-credit-transfer-audit-v1/context.py': '1626873baa224fab5d427a1fab1d6f840f14814152914ac4c2d6aa7a4f0bb1f6', + 'models/male-cns-lif/mb-credit-transfer-audit-v1/manifest.json': '72e4b4e2c53c258939ca355f31eeba2cd6381e126a61efeea651d8bac8df5328', + 'experiments/phase4al-mb-credit-transfer/manifest.json': 'a22de7d85cbfe760070ff55f5666e74475a3335c63bbd37b41241a94be7e3eea', + 'experiments/phase4al-mb-credit-transfer/audit/final-status.json': 'ec846137531d3bea357f57364857b5de5ca2381a01aac3ebb1b7ade79059209e', + 'models/male-cns-lif/apl-timing-lab-v1/gpu_timing.py': 'af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b', + 'models/male-cns-lif/apl-timing-lab-v1/compare_timing.py': '9010f070fba9b7c9cf2d86187ee2abc57f3ac606ebc08a42baad4f3922b51734', + 'models/male-cns-lif/phase4c.py': '5ec83a132deb8ba20e62dab485537c2414016fe2fece546198d61c0668d75b6b', + 'models/male-cns-lif/mb-physiology-v1/phase4j.py': 'abb4574da85f00bd9ef61024c65993ef81d42651ff8d8d63c15dd69c6222471e', + 'experiments/phase4h-dopamine-plasticity/plastic-mask/plastic-edge-candidates.parquet': 'e5075ee3e5a0edf3a4d197453847163cc295b254f21c67203159bba204b12a76', + 'experiments/phase4h-dopamine-plasticity/plastic-mask/plastic-edge-ids.int64.npy': '8b0fb6eb2e6c31da4d17dc20d890aa3f367e514f05642de5bad6b42a1611c05b', + 'experiments/phase4h-dopamine-plasticity/plastic-mask/plastic-edge-mask.bool.npy': 'e8b7a439f07eae6e36729d6577a2c5e4a4c7aa4b15e97fc5266d7278db9e150e', + '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(): + old = load_module('sealed_al_context_am', AL_MODEL / 'context.py', + PINS['models/male-cns-lif/mb-credit-transfer-audit-v1/context.py']) + result = old.integrity() + sys.path.insert(0, str(ROOT / 'models/male-cns-lif/terminal-scope-diagnostic-v1')) + from diagnostic import manifest_check + for path in (AL_MODEL, AL): + result[path.relative_to(ROOT).as_posix()] = manifest_check(path, digest) + assert all(row['pass'] for row in result.values()) + return result + + +def check(full=False): + reg = read(EXP / 'protocol/preregistered.json') + assert reg['sources'] == sources() and reg['config'] == CFG + for row in reg['inputs'] if full else []: + 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'], 'Output budget exceeded; stop and preserve all 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/wholebrain-plastic-interface-v1/eligibility_bridge.py b/models/male-cns-lif/wholebrain-plastic-interface-v1/eligibility_bridge.py new file mode 100644 index 0000000..003f3f0 --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/eligibility_bridge.py @@ -0,0 +1,285 @@ +"""Pure Phase 4J eligibility adapter; no brain run, training, or artifact writes. + +D is the original artificial command scalar. Actual DAN request acceptance and +spikes are separate evidence and MUST NOT silently replace D here. All input +arrays remain unchanged. Returned arrays own their storage and are read-only. +The NumPy trace backend is a candidate compatibility implementation; only an +explicit comparison with the Torch backend establishes Torch bitwise agreement. +""" +from __future__ import annotations + +import ast +from dataclasses import dataclass +import hashlib +import math +from pathlib import Path +from types import MappingProxyType, SimpleNamespace +from typing import Any + +import numpy as np + + +PHASE4J_SHA256 = "abb4574da85f00bd9ef61024c65993ef81d42651ff8d8d63c15dd69c6222471e" +DT_MS = 0.1 +TAU_MS = 100.0 +TRACE_CAP = 1.0 +ETA_MV = 0.00275 +FLOOR_FRACTION = 0.25 +POLARITY = -1 +COMPARTMENTS = ("B2B'2a", "a1", "y2a'1", "y5B'2a") +FIXED_GATES = MappingProxyType({"negative_us_before_cs_delta_exact_zero": True, + "plus_1000_to_zero_ratio_strict_upper": 0.01, + "off_compartment_delta_exact_unchanged": True, + "zero_d_and_frozen_delta_exact_unchanged": True}) +_TRACE_EXPRESSION = ( + "kc_trace.mul_(trace_decay).add_(spikes[self.kc_gpu].to(torch.float32))" + ".clamp_max_(1.0)" +) + + +def _require(condition: bool, message: str) -> None: + if not condition: + raise ValueError(message) + + +def _readonly(array: np.ndarray) -> np.ndarray: + result = np.array(array, copy=True, order="C") + result.setflags(write=False) + return result + + +def bit_equal(left: np.ndarray, right: np.ndarray) -> bool: + a, b = np.asarray(left), np.asarray(right) + return a.dtype == b.dtype and a.shape == b.shape and a.tobytes() == b.tobytes() + + +def _integer(value: Any, name: str, minimum: int) -> int: + _require(isinstance(value, (int, np.integer)) and not isinstance(value, (bool, np.bool_)), + f"{name} must be an integer") + _require(int(value) >= minimum, f"{name} is below {minimum}") + return int(value) + + +def _array(value: Any, dtype: Any, name: str) -> np.ndarray: + result = np.asarray(value) + _require(result.ndim == 1 and result.dtype == np.dtype(dtype), + f"{name} must be a one-dimensional {np.dtype(dtype)} array") + return result + + +def _kc_array(kc: np.ndarray, n_neurons: int) -> np.ndarray: + kc = _array(kc, np.int32, "kc") + _require(len(kc) > 0 and np.all((kc >= 0) & (kc < n_neurons)), "KC IDs out of range or empty") + _require(np.all(kc[1:] > kc[:-1]), "KC IDs must be canonical sorted unique global IDs") + return kc + + +def _load_original(source: str | Path) -> tuple[Any, Any, dict[str, str]]: + """Verify the entire frozen source, then execute ONLY one function AST. + + Old imports, globals, class initialization and main are never executed. + The trace expression is also checked against the exact frozen expression. + """ + raw = Path(source).read_bytes() + actual_sha = hashlib.sha256(raw).hexdigest() + _require(actual_sha == PHASE4J_SHA256, "frozen Phase 4J source SHA256 mismatch") + tree = ast.parse(raw.decode("utf-8"), filename=str(source)) + functions = [node for node in tree.body if isinstance(node, ast.FunctionDef) and node.name == "apply_v2"] + _require(len(functions) == 1, "frozen apply_v2 AST is missing or ambiguous") + function = functions[0] + classes = [node for node in tree.body if isinstance(node, ast.ClassDef) and node.name == "APLSimulator"] + runs = [node for cls in classes for node in cls.body + if isinstance(node, ast.FunctionDef) and node.name == "run"] + expected = ast.parse(_TRACE_EXPRESSION).body[0] + expected_dump = ast.dump(expected, include_attributes=False) + expressions = [node for run in runs for node in ast.walk(run) + if isinstance(node, ast.Expr) and ast.dump(node, include_attributes=False) == expected_dump] + _require(len(expressions) == 1, "frozen Torch trace expression is missing or ambiguous") + module = ast.Module(body=[function], type_ignores=[]) + namespace = {"np": np, "Validator": object, "Any": Any} + exec(compile(module, str(source) + "::apply_v2-only", "exec"), namespace) + trace_code = compile(ast.Module(body=[expressions[0]], type_ignores=[]), + str(source) + "::trace-expression-only", "exec") + evidence = dict(source_sha256=actual_sha, + apply_v2_ast_sha256=hashlib.sha256(ast.dump(function, include_attributes=False).encode()).hexdigest(), + trace_expression_ast_sha256=hashlib.sha256(expected_dump.encode()).hexdigest()) + return namespace["apply_v2"], trace_code, evidence + + +@dataclass(frozen=True) +class TraceResult: + command_steps: np.ndarray + snapshots: np.ndarray + final: np.ndarray + audit: dict[str, Any] + + @property + def last_command_trace(self) -> np.ndarray: + """Original runtime's last scheduled-US snapshot, or zero without US.""" + return _readonly(self.snapshots[-1] if len(self.snapshots) else np.zeros_like(self.final)) + + +def trace_from_events(step: np.ndarray, neuron_idx: np.ndarray, kc: np.ndarray, + steps: int, command_steps: Any, *, phase4j_source: str | Path, + backend: str = "numpy", n_neurons: int = 166700) -> TraceResult: + """Replay actual sparse spikes; snapshot AFTER the current tick's spike. + + One Boolean spike per global neuron/tick, including refractory ticks as + recorded by the caller. This function does not reconstruct brain dynamics, + infer missing events, or apply any refractory guard to eligibility. + """ + _, trace_code, evidence = _load_original(phase4j_source) + steps = _integer(steps, "steps", 1) + n_neurons = _integer(n_neurons, "n_neurons", 1) + kc = _kc_array(kc, n_neurons) + step = _array(step, np.int32, "step") + neuron_idx = _array(neuron_idx, np.int32, "neuron_idx") + _require(len(step) == len(neuron_idx), "event columns have different lengths") + _require(np.all((step >= 0) & (step < steps)), "event tick outside trial") + _require(np.all((neuron_idx >= 0) & (neuron_idx < n_neurons)), "event neuron outside graph") + _require(np.all((step[1:] > step[:-1]) | + ((step[1:] == step[:-1]) & (neuron_idx[1:] > neuron_idx[:-1]))), + "events must be sorted by tick/global ID and unique") + commands = np.asarray(command_steps) + _require(commands.ndim == 1, "command_steps must be one-dimensional") + if commands.size == 0: + commands = np.empty(0, np.int64) + _require(commands.ndim == 1 and commands.dtype.kind in "iu", "command_steps must be integers") + _require(np.all((commands >= 0) & (commands < steps)), "command tick outside trial") + _require(np.all(commands[1:] > commands[:-1]), "command_steps must be sorted unique") + commands = commands.astype(np.int64, copy=True) + _require(backend in ("numpy", "torch"), "backend must be numpy or torch") + lookup = np.full(n_neurons, -1, np.int32) + lookup[kc] = np.arange(len(kc), dtype=np.int32) + local = lookup[neuron_idx] + keep = local >= 0 + ticks, local = step[keep], local[keep] + snapshots = np.empty((len(commands), len(kc)), np.float32) + decay = math.exp(-DT_MS / TAU_MS) + command_lookup = {int(t): i for i, t in enumerate(commands)} + cursor = 0 + torch_version = None + if backend == "numpy": + trace = np.zeros(len(kc), np.float32) + spike_values = np.zeros(len(kc), np.float32) + else: + try: + import torch + except ImportError as exc: + raise RuntimeError("Torch CPU reference unavailable; compatibility is not established") from exc + torch_version = str(torch.__version__) + trace = torch.zeros(len(kc), dtype=torch.float32, device="cpu") + spike_values = torch.zeros(len(kc), dtype=torch.bool, device="cpu") + environment = dict(torch=torch, kc_trace=trace, trace_decay=decay, + spikes=spike_values, + self=SimpleNamespace(kc_gpu=torch.arange(len(kc), dtype=torch.int64))) + for tick in range(steps): + end = cursor + while end < len(ticks) and ticks[end] == tick: + end += 1 + if backend == "numpy": + spike_values.fill(0) + spike_values[local[cursor:end]] = 1 + # Separate float32 operations; never power-jump across empty ticks. + np.multiply(trace, np.float32(decay), out=trace) + np.add(trace, spike_values, out=trace) + np.minimum(trace, np.float32(TRACE_CAP), out=trace) + if tick in command_lookup: + snapshots[command_lookup[tick]] = trace + else: + spike_values.zero_() + if end > cursor: + spike_values[torch.from_numpy(local[cursor:end].astype(np.int64, copy=True))] = True + exec(trace_code, environment) + if tick in command_lookup: + snapshots[command_lookup[tick]] = trace.numpy() + cursor = end + final = trace if backend == "numpy" else trace.numpy() + audit = dict(evidence, backend=backend, torch_version=torch_version, numpy_version=str(np.__version__), + steps=steps, kc_count=len(kc), actual_kc_events=int(keep.sum()), + command_count=len(commands), dt_ms=DT_MS, trace_tau_ms=TAU_MS, + trace_cap=TRACE_CAP, decay_python_float=decay, + decay_float32_bits=int(np.asarray(np.float32(decay)).view(np.uint32)), + sampling="after_current_tick_spike", interval_skip_optimization=False, + torch_numpy_bitwise_comparison_performed=False, + d_semantics="artificial scheduled command; not measured DAN activity", + actual_dan_activity_used_to_gate=False, brain_dynamics_executed=False, + training_executed=False, learning_pass_claimed=False) + return TraceResult(_readonly(commands), _readonly(snapshots), _readonly(final), audit) + + +class _Column: + """Small immutable-array interface consumed by the frozen function.""" + def __init__(self, values: np.ndarray): + self.values = values + + def to_numpy(self, dtype: Any = None) -> np.ndarray: + return self.values.astype(dtype, copy=True) if dtype is not None else self.values.copy() + + def astype(self, dtype: Any) -> "_Column": + return _Column(self.values.astype(dtype)) + + +def apply_eligibility(trace: np.ndarray, kc: np.ndarray, candidate_sources: np.ndarray, + candidate_compartments: np.ndarray, compartment: str, + delta: np.ndarray, base_candidate: np.ndarray, *, d: float, + frozen: bool = False, phase4j_source: str | Path, + n_neurons: int = 166700) -> tuple[np.ndarray, dict[str, Any]]: + """Apply the SHA-pinned original apply_v2 AST to candidate-aligned arrays. + + delta/base_candidate are ORIGINAL float32 mV values, not SI or reconstructed + float64 D18 weights. Candidate row identity and the complete 14,232-edge mask + are verified by the coordinator; a small synthetic subset is allowed here. + Existing overlays must already obey the original floor and canonical +0. + No input is clipped, repaired, reordered, or mutated. + """ + original, _, evidence = _load_original(phase4j_source) + n_neurons = _integer(n_neurons, "n_neurons", 1) + kc = _kc_array(kc, n_neurons) + trace = _array(trace, np.float32, "trace") + sources = _array(candidate_sources, np.int32, "candidate_sources") + delta = _array(delta, np.float32, "delta") + base = _array(base_candidate, np.float32, "base_candidate") + compartments = np.asarray(candidate_compartments) + _require(compartments.ndim == 1 and compartments.dtype.kind == "U", "candidate_compartments must be Unicode strings") + _require(len(trace) == len(kc) and np.all(np.isfinite(trace)) and np.all((trace >= 0) & (trace <= TRACE_CAP)), + "trace must match KC IDs and lie in [0,1]") + _require(len(delta) == len(base) == len(sources) == len(compartments), "candidate columns have different lengths") + _require(np.all(np.isin(sources, kc)), "all candidate sources must be canonical KCs") + _require(compartment in COMPARTMENTS and np.all(np.isin(compartments, COMPARTMENTS)), + "unrecognized exact frozen compartment") + _require(isinstance(d, (float, int, np.floating, np.integer)) and not isinstance(d, (bool, np.bool_)) + and np.isfinite(d) and float(d) in (0.0, 1.0), "D must be the fixed artificial scalar 0 or 1") + _require(isinstance(frozen, (bool, np.bool_)), "frozen must be Boolean") + _require(np.all(np.isfinite(base)) and np.all(base > 0), "original candidate base must be finite positive float32 mV") + lower = -FLOOR_FRACTION * base + _require(np.all(np.isfinite(delta)) and np.all((delta >= lower) & (delta <= 0)), "delta violates original frozen floor") + _require(not np.any((delta == 0) & np.signbit(delta)), "delta zero must be canonical +0 for exact identity") + validator = SimpleNamespace(n=n_neurons, kc=kc.copy(), base_candidate=base.copy(), + cand={"source_neuron_idx": _Column(sources.copy()), + "target_compartment_verbatim": _Column(compartments.copy())}) + config = {"eligibility_v2": {"eta_effective_mv": ETA_MV, + "max_fractional_depression": FLOOR_FRACTION}} + if frozen: + result = delta.copy() + original_report = None + else: + result, original_report = original(validator, trace.copy(), compartment, float(d), delta.copy(), config) + selected = compartments == compartment + _require(result.dtype == np.float32 and np.all(np.isfinite(result)), "original update returned invalid values") + _require(bit_equal(result[~selected], delta[~selected]), "off-compartment delta changed") + if frozen or float(d) == 0: + _require(bit_equal(result, delta), "zero-D/frozen identity failed") + _require(np.all((result >= lower) & (result <= 0)), "original result violates frozen floor") + report = dict(evidence, original_apply_v2_executed=not bool(frozen), original_report=original_report, + candidate_count=len(delta), selected_compartment=compartment, + selected_candidate_count=int(selected.sum()), d_command=float(d), frozen=bool(frozen), + actual_changed_edges=int(np.count_nonzero(result != delta)), + off_compartment_exact_unchanged=True, numpy_version=str(np.__version__), + eta_effective_mv=ETA_MV, polarity=POLARITY, floor_fraction=FLOOR_FRACTION, + delta_units="mV", delta_dtype="float32", original_base_units="mV", + complete_mask_identity_verified_by_this_function=False, + actual_dan_activity_used_to_gate=False, + d_semantics="artificial scheduled command; not measured DAN activity", + brain_dynamics_executed=False, training_executed=False, learning_pass_claimed=False) + return _readonly(result), report diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/finalize.py b/models/male-cns-lif/wholebrain-plastic-interface-v1/finalize.py new file mode 100644 index 0000000..43c82f8 --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/finalize.py @@ -0,0 +1,36 @@ +"""Seal interface evidence; never promote static transfer to learned memory.""" +import yaml +from context import ROOT, MODEL, EXP, read, save, digest, check, integrity, budget, seal + + +def main(): + check(full=True) + from summarize import run + result = run(verify_only=True) + refs = read(EXP / 'regression/frozen-five.json') + names = [r['name'] for r in yaml.safe_load((ROOT / 'models/male-cns-lif/deterministic-runtime-v2/phase4p.yaml').read_text())['reference_trials']] + assert len(names) == len(set(names)) == 5 + assert refs['pass_all'] is True and [r['trial'] for r in refs['trials']] == names + assert all(set(r['exact']) == {'step', 'neuron_idx', 'counts', 'v', 'g'} and + all(v is True for v in r['exact'].values()) for r in refs['trials']) + old = integrity(); save(EXP / 'regression/old-integrity-after.json', old) + final = dict(status=result['status'], zero_overlay_exact=True, static25_repeat_exact=True, + primary_trials_per_stage=120, repeats_per_stage=24, old_integrity_pass=all(r['pass'] for r in old.values()), + frozen_five_reference_pass=True, frozen_eligibility_and_mask_unchanged=True, + base_weights_unchanged=True, training=False, learned_candidate=False, + scientific_summary_sha256=digest(EXP / 'audit/scientific-summary.json'), + payload_bytes_before_manifest=budget(), next_required='Separately preregister finite olfactory paired/control conditioning; no automatic learning PASS') + save(EXP / 'audit/final-status.json', final) + with (EXP / 'REPORT.md').open('x', encoding='utf-8') as f: + f.write('# Phase 4AM — whole-brain plastic interface\n\nStatus: `' + result['status'] + '`.\n\n') + f.write('All 144 zero-overlay runs reproduce sealed AK D18 exactly. All 120 fixed-overlay primary runs and 24 repeats are retained.\n') + f.write('The fixed overlay is the original float32 25% floor, added through the declared float64 SI bridge. No training occurred.\n\n') + for name, block in result['blocks'].items(): + f.write('- ' + name + ': ' + '; '.join(pop + ' event changes ' + str(v['trials_event_change']) + '/30' for pop, v in block['populations'].items()) + '.\n') + f.write('\nOld artifacts and five deterministic-v2 references pass integrity/regression. This does not complete the learning goal.\n') + check(full=True); seal(MODEL); seal(EXP) + print(final['status'], flush=True) + + +if __name__ == '__main__': + main() diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/manifest.json b/models/male-cns-lif/wholebrain-plastic-interface-v1/manifest.json new file mode 100644 index 0000000..a7614f9 --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/manifest.json @@ -0,0 +1,95 @@ +{ + "root": "/data/digital-drosophila/models/male-cns-lif/wholebrain-plastic-interface-v1", + "files": [ + { + "path": "PREPARATION.md", + "bytes": 1625, + "sha256": "85a3253ceb4e4c5d7bcf17b8b3294dbbf72bd1139415a892f6a90e8037785c89" + }, + { + "path": "PROTOCOL.md", + "bytes": 5223, + "sha256": "e03273995f4d5f1fc18d0af481374b8688ae735d83ae718895ffb741f8ac9399" + }, + { + "path": "adapter.py", + "bytes": 15690, + "sha256": "3daabe771d3eef6c6189827c0ee5159b266c3a058e07da5781bb863be428aef9" + }, + { + "path": "comparison.py", + "bytes": 37000, + "sha256": "4d64020af05e7fc9e535ac8532dd0e7b614b200f695ed8c6d486c6151de57175" + }, + { + "path": "config.json", + "bytes": 848, + "sha256": "c19f00c81f12c4c3503d3d557bd73d0722d4d3fed7279449408c67a89a6ffcf9" + }, + { + "path": "context.py", + "bytes": 5444, + "sha256": "0fa2e0892c973fe70ecbc0613e3cb508c256b7745042f8936edf23dedc31d166" + }, + { + "path": "eligibility_bridge.py", + "bytes": 15196, + "sha256": "174fb8d14619189e74b095e77a6db18b14c93046dc431c0b55710a5aa2dd2e61" + }, + { + "path": "finalize.py", + "bytes": 2472, + "sha256": "b8e4fb59d4efa261a8615f1456bc2ad1f1822e941af558b27074b8c41dba15a1" + }, + { + "path": "overlay.py", + "bytes": 11355, + "sha256": "7f891d0ba79b393c96e75fd2dee2eddc51e57d8213eaac2779703bc2c18712b4" + }, + { + "path": "prepare.py", + "bytes": 9824, + "sha256": "40976f0ed0b01fbf275c245de0f0a907592d23f5ca4733293b41e1d011c7ee62" + }, + { + "path": "run_suite.py", + "bytes": 6857, + "sha256": "6a6fcf4cc64d27234ab69ce5a9dcdb8bbd8b3b4965c9c08c2f9d20747025e9e7" + }, + { + "path": "summarize.py", + "bytes": 6359, + "sha256": "b4f3cacf3ab60f70d63713d5bbc3e03658f38e357a47ef219b1050003176df01" + }, + { + "path": "test_comparison.py", + "bytes": 22896, + "sha256": "a6274f338307a6961e514f565ab3e731051846caf62901e6843037755adc6fd8" + }, + { + "path": "test_eligibility_bridge.py", + "bytes": 12900, + "sha256": "113435c0f3528e3901e47421570a5f906d192826df9fc4ee600429a87ab904c5" + }, + { + "path": "test_overlay_adapter.py", + "bytes": 14389, + "sha256": "1c0536e0d0c27de6ab152ebb5aa0015ee31325417b17d3cfedc5f43bafa2ee79" + }, + { + "path": "test_workflow.py", + "bytes": 2485, + "sha256": "351a0c2887d657e1942b849d768d7efe8c52c0c3c67d0cf4d55658549c3bfe32" + }, + { + "path": "test_workflow_identity.py", + "bytes": 11771, + "sha256": "f1453a8814339ec7860ef4dee20549cc811d13cefd7aee2d308ebdfd51a839ca" + }, + { + "path": "verify_frozen.py", + "bytes": 2383, + "sha256": "5b121184ec3e666814dd440356604e96520aecdd8902d5b68c7d61caa7f224c5" + } + ] +} diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/overlay.py b/models/male-cns-lif/wholebrain-plastic-interface-v1/overlay.py new file mode 100644 index 0000000..5337bd4 --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/overlay.py @@ -0,0 +1,222 @@ +"""Read-only sparse plastic-overlay validation and independent SI arithmetic. + +This module does not calculate eligibility, generate learning updates, simulate +neurons, or alter a graph. File loading enforces the complete frozen 14,232-row +candidate identity; the array helpers also accept small synthetic identities. +The externally anchored manifest is a provenance input, not its own authority. +""" +from __future__ import annotations + +import hashlib +import json +from pathlib import Path +import re + +import numpy as np + + +CANDIDATE_COUNT = 14232 +EDGE_COUNT = 25582938 +SCHEMA = 'phase4am-overlay-v1' +BRIDGE = 'baseSI64 + (delta32 widened to float64) * float64(0.001); nonzero rows only' + + +def require(ok, message): + if not ok: + raise ValueError(message) + + +def file_hash(path): + digest = hashlib.sha256() + with Path(path).open('rb') as source: + for block in iter(lambda: source.read(8 << 20), b''): + digest.update(block) + return digest.hexdigest() + + +def raw_hash(value): + require(isinstance(value, np.ndarray), 'Raw hash requires an ndarray') + dtype = value.dtype.newbyteorder('<') + return hashlib.sha256(np.ascontiguousarray(value, dtype=dtype).tobytes()).hexdigest() + + +def bit_equal(first, second): + return (isinstance(first, np.ndarray) and isinstance(second, np.ndarray) and + first.dtype == second.dtype and first.shape == second.shape and + first.tobytes(order='C') == second.tobytes(order='C')) + + +def _vector(value, dtype, name, size=None): + require(isinstance(value, np.ndarray) and value.dtype == np.dtype(dtype) and value.ndim == 1, + name + ' requires exact ' + dtype + ' vector; no implicit conversion') + require(size is None or value.shape == (size,), name + ' length differs') + return value + + +def _ids(value, name): + _vector(value, 'int64', name) + require(np.all((value >= 0) & (value < EDGE_COUNT)) and np.all(value[1:] > value[:-1]), + name + ' must be sorted unique frozen-range global edge IDs') + return value + + +def _owned(value): + result = np.array(value, copy=True, order='C') + result.flags.writeable = False + return result + + +def validate_arrays(edge_id, plastic_delta_mv, mask_edge_id, base_candidate_mv=None): + """Validate/copy arrays; small masks are permitted only for pure unit helpers. + + The production file loader separately insists on CANDIDATE_COUNT. Every + nonzero delta needs the original, positive float32 base in legacy mV. + Its bound is the frozen float32 expression -0.25 * base_candidate, NOT + a fraction recomputed from the author's float64 SI runtime weights. + """ + ids, mask = _ids(edge_id, 'edge_id'), _ids(mask_edge_id, 'mask_edge_id') + delta = _vector(plastic_delta_mv, 'float32', 'plastic_delta_mv', len(ids)) + require(len(ids) > 0 and bit_equal(ids, mask), 'Candidate IDs must equal the complete anchored mask in order') + require(np.isfinite(delta).all() and np.all(delta <= np.float32(0)), 'Delta must be finite, nonpositive float32 mV') + base = None + if base_candidate_mv is not None: + base = _vector(base_candidate_mv, 'float32', 'base_candidate_mv', len(ids)) + require(np.isfinite(base).all() and np.all(base > np.float32(0)), 'Original candidate base must be finite, positive float32 mV') + lower = np.multiply(np.float32(-.25), base) + require(np.all(delta >= lower), 'Delta exceeds the frozen original-float32 -25% bound') + else: + require(not np.any(delta != np.float32(0)), 'Nonzero delta requires the authoritative original float32 base') + return {'edge_id': _owned(ids), 'plastic_delta_mv': _owned(delta), + 'base_candidate_mv': None if base is None else _owned(base)} + + +def _checked_file(manifest, path_key, hash_key): + path = Path(manifest[path_key]) + expected = manifest[hash_key] + require(path.is_absolute() and path.is_file(), 'Missing absolute input: ' + path_key) + require(isinstance(expected, str) and re.fullmatch('[0-9a-f]{64}', expected) is not None, + 'Malformed SHA256: ' + hash_key) + require(file_hash(path) == expected, 'Input SHA256 mismatch: ' + path_key) + return path + + +def load_overlay(overlay_file, overlay_manifest): + """Load immutable, hash-bound production inputs without importing Torch. + + Manifest keys: schema, overlay_name (zero/static25), overlay_sha256, + mask_path/mask_sha256, base_candidate_path/base_candidate_sha256 (both + null only for zero), aj_model_dir. Extra provenance fields are retained + in the copied original manifest, not treated as executable instructions. + NPZ keys: edge_id, plastic_delta_mv; optional base_candidate_mv must be + bit-identical to the authoritative external .npy, never a replacement. + """ + overlay_file, manifest_file = Path(overlay_file).absolute(), Path(overlay_manifest).absolute() + require(overlay_file.is_file() and manifest_file.is_file(), 'Missing overlay or manifest') + manifest_bytes = manifest_file.read_bytes() + manifest_sha = hashlib.sha256(manifest_bytes).hexdigest() + metadata = json.loads(manifest_bytes.decode('utf-8')) + required = {'schema', 'overlay_name', 'overlay_sha256', 'mask_path', 'mask_sha256', + 'base_candidate_path', 'base_candidate_sha256', 'aj_model_dir'} + require(isinstance(metadata, dict) and required <= metadata.keys(), 'Incomplete overlay manifest') + require(metadata['schema'] == SCHEMA and metadata['overlay_name'] in ('zero', 'static25'), 'Unregistered interface overlay kind') + require(file_hash(overlay_file) == metadata['overlay_sha256'], 'Overlay file SHA256 mismatch') + aj_dir = Path(metadata['aj_model_dir']) + require(aj_dir.is_absolute() and aj_dir.is_dir(), 'aj_model_dir must name the real sealed AJ directory') + mask_path = _checked_file(metadata, 'mask_path', 'mask_sha256') + mask = np.load(mask_path, allow_pickle=False) + _ids(mask, 'authoritative mask') + require(mask.shape == (CANDIDATE_COUNT,), 'Frozen mask must contain exactly 14,232 candidates') + base_path, base = None, None + if metadata['base_candidate_path'] is None: + require(metadata['base_candidate_sha256'] is None, 'Absent base needs a null base hash') + else: + base_path = _checked_file(metadata, 'base_candidate_path', 'base_candidate_sha256') + base = np.load(base_path, allow_pickle=False) + with np.load(overlay_file, allow_pickle=False) as archive: + require({'edge_id', 'plastic_delta_mv'} <= set(archive.files) <= + {'edge_id', 'plastic_delta_mv', 'base_candidate_mv'}, 'Unexpected overlay NPZ schema') + values = validate_arrays(archive['edge_id'], archive['plastic_delta_mv'], mask, base) + if 'base_candidate_mv' in archive.files: + require(base is not None and bit_equal(archive['base_candidate_mv'], base), + 'Embedded base is not the authoritative external original float32 base') + delta = values['plastic_delta_mv'] + if metadata['overlay_name'] == 'zero': + require(not np.any(delta != 0), 'Named zero overlay is not zero') + else: + require(base is not None and bit_equal(delta, np.multiply(np.float32(-.25), base)), + 'static25 must exactly equal the original float32 floor, not 25% of float64 runtime base') + values.update(metadata=metadata, input={ + 'overlay_file': str(overlay_file), 'overlay_sha256': metadata['overlay_sha256'], + 'manifest_file': str(manifest_file), 'manifest_sha256': manifest_sha, + 'mask_file': str(mask_path), 'mask_sha256': metadata['mask_sha256'], + 'base_candidate_file': None if base_path is None else str(base_path), + 'base_candidate_sha256': metadata['base_candidate_sha256']}) + verify_inputs(values) + return values + + +def verify_inputs(plan): + for name in ('overlay', 'manifest', 'mask', 'base_candidate'): + path, expected = plan['input'][name + '_file'], plan['input'][name + '_sha256'] + require((path is None and expected is None) or (path is not None and file_hash(path) == expected), + 'Overlay input changed: ' + name) + + +def map_installation(base_si, graph_edge_id, apl_out_mask, plan): + """Return sparse nonzero installation rows and independently computed values. + + Missing zero-delta mask members are permitted in a small fixture. Missing + nonzero members fail closed. APL/candidate overlap is always rejected. + Neither base nor any caller array is changed. Zero delta has no write row. + """ + ids = _ids(graph_edge_id, 'graph_edge_id') + base = _vector(base_si, 'float64', 'base_si', len(ids)) + apl = _vector(apl_out_mask, 'bool', 'apl_out_mask', len(ids)) + require(np.isfinite(base).all(), 'Nonfinite graph SI base') + candidates = plan['edge_id'] + delta = plan['plastic_delta_mv'] + rows = np.searchsorted(ids, candidates) + present = rows < len(ids) + present[present] &= ids[rows[present]] == candidates[present] + nonzero = delta != np.float32(0) + require(not np.any(nonzero & ~present), 'A nonzero plastic candidate is absent from this graph') + mapped = rows[present] + require(not np.any(apl[mapped]), 'Plastic candidate overlaps the frozen fast-APL output mask') + require(np.all(base[mapped] > np.float64(0)), 'Candidate graph SI base must remain positive') + selected = rows[nonzero].astype(np.int64) + delta_si = np.multiply(delta[nonzero].astype(np.float64), np.float64(.001)) + expected = np.add(base[selected], delta_si) + require(np.isfinite(expected).all() and np.all(expected > 0), 'Overlay would change a candidate sign or create nonfinite weights') + return {'rows': _owned(selected), 'delta_si': _owned(delta_si), 'expected_si': _owned(expected), + 'mapped_candidate_count': int(present.sum()), 'missing_candidate_count': int((~present).sum()), + 'installed_nonzero_count': int(nonzero.sum()), 'apl_overlap_count': 0} + + +def materialize_numpy(base_si, graph_edge_id, apl_out_mask, plan): + """Independent pure CPU reference; used by unit tests, not a brain run.""" + mapping = map_installation(base_si, graph_edge_id, apl_out_mask, plan) + result = np.array(base_si, copy=True, order='C') + result[apl_out_mask] = np.float64(0) + result[mapping['rows']] = mapping['expected_si'] + return result, mapping + + +def expected_hashes(base_si, apl_out_mask, mapping, chunk_elements=1 << 20): + """Bounded-memory base/effective raw hashes, preserving untouched signed bits.""" + require(type(chunk_elements) is int and chunk_elements > 0, 'Invalid hash chunk size') + base_hash, effective_hash = hashlib.sha256(), hashlib.sha256() + rows = mapping['rows'] + for start in range(0, len(base_si), chunk_elements): + stop = min(start + chunk_elements, len(base_si)) + original = np.ascontiguousarray(base_si[start:stop], dtype=' 0) + tree = ast.parse(source_path.read_text()) + runtime = next(n for n in tree.body if isinstance(n, ast.ClassDef) and n.name == 'Runtime') + init = next(n for n in runtime.body if isinstance(n, ast.FunctionDef) and n.name == '__init__') + selected = [n for n in ast.walk(init) if isinstance(n, ast.Assign) and any( + isinstance(t, ast.Subscript) and isinstance(t.value, ast.Name) and t.value.id == 'effective' + for t in n.targets)] + assert len(selected) == 1 + value = selected[0].value + assert ast.unparse(value) == "raw_np[a:b].astype(np.float32) * signs[src] * float(cfg['model']['w_syn_mv_per_anatomical_synapse'])" + env = dict(raw_np=raw, a=0, b=len(raw), np=np, signs=np.array([1], np.int8), src=0, + cfg={'model': {'w_syn_mv_per_anatomical_synapse': .275}}, float=float) + out = eval(compile(ast.Expression(value), str(source_path), 'eval'), {'__builtins__': {}}, env) + assert out.dtype == np.float32 and np.isfinite(out).all() and np.all(out > 0) + return out, hashlib.sha256(ast.dump(value, include_attributes=False).encode()).hexdigest() + + +def main(): + assert not EXP.exists() or (EXP.is_dir() and not any(EXP.iterdir())), 'Never reuse a populated experiment' + assert shutil.disk_usage(EXP.parent).free > CFG['output_budget_bytes'] + 10 * 1024**3 + for relative, sha in PINS.items(): + assert digest(ROOT / relative) == sha, relative + assert read(AL / 'audit/final-status.json')['status'] == 'PASS-CONDITIONAL-CREDIT-TRANSFER-AUDIT-NOT-LEARNING' + assert CFG['stages'] == ['zero', 'static25'] and not CFG['training'] and not CFG['candidate_generation'] + records = read(AK / 'protocol/validation-cases.json') + assert len(records) == 120 and len({r['name'] for r in records}) == 120 + first_seed = min(r['seed'] for r in records) + planned = [dict(row, repeat=repeat) for row in records + for repeat in ((0, 1) if row['seed'] == first_seed else (0,))] + assert len(planned) == 144 + inputs = dict(PINS) + static = [AK / 'protocol/validation-cases.json', + H / 'mappings/mbon-to-downstream-actual-edges.parquet', + ROOT / 'experiments/phase4l-olfactory-grounding/odor-encoder/selection.json', + ROOT / 'experiments/phase4af-author-fullgraph/oracle/no_input/coefficients.json'] + static += 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' + static.append(raw_path) + for row in planned: + case = AK / 'cases' / row['cohort'] / row['name'] + spec = read(case / 'spec.json') + assert spec['steps'] == 1000 and spec['dt_ms'] == .1 and spec['apl_delay_steps'] == 18 + assert spec['model']['w_syn_mv_per_anatomical_synapse'] == .275 + static += [case / 'spec.json', case / 'requests.npz'] + for p in static: + inputs[p.relative_to(ROOT).as_posix()] = digest(p) + for name in ('protocol', 'overlays', 'gpu', 'audit', 'regression', 'logs', 'extension-build', 'summaries'): + (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) + save(EXP / 'regression/unit-tests.json', dict(pass_all=test.returncode == 0, + exit_code=test.returncode, log_sha256=digest(EXP / 'regression/unit-tests.log'))) + assert test.returncode == 0, 'Unit tests failed; preserve partial experiment' + assert 'skipped=' not in test.stderr, 'All server compatibility tests must execute' + save(EXP / 'protocol/preregistered.json', dict(timestamp_utc=datetime.now(timezone.utc).isoformat(), + sources=sources(), config=CFG, planned=planned, + 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(), + before_new_brain_trajectories=True, prior_AK_AL_results_known=True, + no_dynamic_pair_selection=True, training=False, candidate_generated=False, + python=sys.version, numpy=np.__version__, platform=platform.platform())) + save(EXP / 'regression/old-integrity-before.json', integrity()) + candidate = pd.read_parquet(H / 'plastic-mask/plastic-edge-candidates.parquet') + mask_path = H / 'plastic-mask/plastic-edge-ids.int64.npy' + ids = np.load(mask_path, allow_pickle=False) + mask = np.load(H / 'plastic-mask/plastic-edge-mask.bool.npy', allow_pickle=False) + assert ids.dtype == np.int64 and ids.shape == (14232,) + assert np.array_equal(candidate.edge_id, ids) and np.array_equal(np.flatnonzero(mask), ids) + graph = {k: np.load(AG / 'graphs/full' / (k + '.npy'), mmap_mode='r') + for k in ('src', 'dst', 'edge_id', 'weights', 'signed_raw', 'nodes')} + assert np.array_equal(graph['nodes'], np.arange(166700, dtype=np.int32)) + assert np.array_equal(graph['edge_id'], np.arange(25582938, dtype=np.int64)) + assert np.array_equal(graph['src'][ids], candidate.source_neuron_idx) + assert np.array_equal(graph['dst'][ids], candidate.target_neuron_idx) + raw = np.load(raw_path, mmap_mode='r') + assert np.array_equal(raw[ids], candidate.raw_synapse_count) + assert np.array_equal(graph['signed_raw'][ids], raw[ids]), 'Original candidate sign must be +1' + assert np.all(graph['weights'][ids] > 0) and (candidate.plasticity_polarity == -1).all() + base, rhs_sha = old_base_candidate(raw[ids], ROOT / 'models/male-cns-lif/phase4c.py') + base_path = EXP / 'protocol/base-candidate.float32-mV.npy' + with base_path.open('xb') as f: + np.save(f, base, allow_pickle=False) + for stage in CFG['stages']: + delta = np.zeros(len(ids), np.float32) if stage == 'zero' else (-float(.25) * base).astype(np.float32) + path = EXP / 'overlays' / (stage + '.npz') + write_npz(path, edge_id=ids, plastic_delta_mv=delta) + save(EXP / 'overlays' / (stage + '.json'), dict(schema='phase4am-overlay-v1', overlay_name=stage, + overlay_sha256=digest(path), mask_path=str(mask_path), mask_sha256=digest(mask_path), + base_candidate_path=str(base_path), base_candidate_sha256=digest(base_path), + aj_model_dir=str(AJ_MODEL), base_rhs_ast_sha256=rhs_sha, + old_f32_expression_source_sha256=digest(ROOT / 'models/male-cns-lif/phase4c.py'), + training=False, fixed_for_whole_trial=True)) + meta = pd.read_parquet(META).sort_values('neuron_idx').reset_index(drop=True) + assert np.array_equal(meta.neuron_idx.to_numpy(), graph['nodes']) + kc = np.flatnonzero(meta.annotation_class.eq('Kenyon_Cell')).astype(np.int32) + mbon = np.flatnonzero(meta.annotation_class.eq('MBON')).astype(np.int32) + assert len(kc) == 4064 and len(mbon) == 97 + assert np.isin(candidate.source_neuron_idx, kc).all() and np.isin(candidate.target_neuron_idx, mbon).all() + down = pd.read_parquet(H / 'mappings/mbon-to-downstream-actual-edges.parquet') + assert np.array_equal(graph['src'][down.edge_id.to_numpy()], down.source_neuron_idx.to_numpy()) + assert np.array_equal(graph['dst'][down.edge_id.to_numpy()], down.target_neuron_idx.to_numpy()) + populations = dict(KC=kc, MBON=mbon, + mask_recipient_MBON=np.unique(candidate.target_neuron_idx.to_numpy(dtype=np.int32)), + DAN=np.flatnonzero(meta.annotation_class.eq('DAN')).astype(np.int32), + MBON_downstream=np.unique(down.target_neuron_idx.to_numpy(dtype=np.int32))) + # Exact observed superclass strings are checked; no inferred body identity. + role_labels = {'descending': ['descending_neuron', 'descending_neuron_tbc'], + 'motor': ['vnc_motor', 'cb_motor']} + for name, labels in role_labels.items(): + assert set(labels).issubset(set(meta.annotation_superclass.dropna().astype(str))), labels + populations[name] = np.flatnonzero(meta.annotation_superclass.isin(labels)).astype(np.int32) + write_npz(EXP / 'protocol/populations.npz', **populations) + save(EXP / 'protocol/static-audit.json', dict(candidate_edges=len(ids), mask_fixed=True, + old_base_rhs_ast_sha256=rhs_sha, populations={k: len(v) for k, v in populations.items()}, + exact_descending_motor_superclass_labels=role_labels, + compartments={str(k): len(g) for k, g in candidate.groupby('target_compartment_verbatim')}, + old_selected_odors=read(ROOT / 'experiments/phase4l-olfactory-grounding/odor-encoder/selection.json'), + source_mapping='Exact annotation_class/superclass and frozen actual-edge table; no inferred type/body IDs', + old_base_signed_positive=True, training=False)) + save(EXP / 'protocol/prepared-hashes.json', [dict(path=p.relative_to(EXP).as_posix(), sha256=digest(p)) + for folder in ('protocol', 'overlays') for p in sorted((EXP / folder).rglob('*')) + if p.is_file() and p.name != 'prepared-hashes.json']) + print('PREREGISTERED zero 144 then static25 144; no brain trajectories or training', flush=True) + + +if __name__ == '__main__': + main() diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/run_suite.py b/models/male-cns-lif/wholebrain-plastic-interface-v1/run_suite.py new file mode 100644 index 0000000..c1b5cd9 --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/run_suite.py @@ -0,0 +1,132 @@ +"""Finite fixed inventory; no overwrites, no automatic scientific retries.""" +import argparse +import json +import os +import time +import traceback +import urllib.request +from context import ROOT, MODEL, EXP, AK, CFG, read, save, digest, check, budget + + +def preflight(): + os.environ['CUDA_VISIBLE_DEVICES'] = CFG['gpu_uuid'] + 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: + q = json.load(response) + assert not q['queue_running'] and not q['queue_pending'], 'ComfyUI busy: defer, never evict' + + +def output_inventory(folder): + return [dict(path=p.relative_to(folder).as_posix(), bytes=p.stat().st_size, sha256=digest(p)) + for p in sorted(folder.rglob('*')) if p.is_file() and p.name != 'output-hashes.json'] + + +def compare_expected(stage, row, folder): + from comparison import compare_runs, validate_run + case = AK / 'cases' / row['cohort'] / row['name'] + if stage == 'zero': + reference = AK / 'gpu' / row['cohort'] / (row['name'] + '-r' + str(row['repeat'])) + return compare_runs(case, reference, folder, mode='zero') + if row['repeat'] == 1: + reference = EXP / 'gpu' / stage / (row['name'] + '-r0') + return compare_runs(case, reference, folder, mode='repeat') + return validate_run(case, folder) + + +def verify_identity(folder, stage, row): + assert stage in CFG['stages'] and row['repeat'] in (0, 1) + assert folder == EXP / 'gpu' / stage / (row['name'] + '-r' + str(row['repeat'])) + case = AK / 'cases' / row['cohort'] / row['name'] + summary = read(folder / 'summary.json') + assert summary['case'] == row['name'] and summary['complete'] and summary['pass_all'] + assert summary['input_sha256']['spec.json'] == digest(case / 'spec.json') + assert summary['input_sha256']['requests.npz'] == digest(case / 'requests.npz') + overlay = read(folder / 'overlay-audit.json') + assert overlay['complete'] and overlay['overlay_name'] == stage + assert overlay['input']['overlay_sha256'] == digest(EXP / 'overlays' / (stage + '.npz')) + assert overlay['input']['manifest_sha256'] == digest(EXP / 'overlays' / (stage + '.json')) + report = read(folder / 'comparison.json') + assert report['pass_all'] and report['overlay_name'] == stage + assert report['case_dir'] == str(case) and report['right'] == str(folder) + if stage == 'zero': + assert report['mode'] == 'zero' + assert report['left'] == str(AK / 'gpu' / row['cohort'] / (row['name'] + '-r' + str(row['repeat']))) + elif row['repeat'] == 1: + assert report['mode'] == 'repeat' and report['left'] == str(EXP / 'gpu' / stage / (row['name'] + '-r0')) + else: + assert report['mode'] == 'self' and report['left'] == str(folder) + + +def verify_completed(folder, stage=None, row=None, recompute=False): + rows = read(folder / 'output-hashes.json') + assert rows == output_inventory(folder), 'Completed output bytes changed: ' + str(folder) + assert read(folder / 'comparison.json')['pass_all'] + assert read(folder / 'summary.json')['complete'] + if stage is not None: + verify_identity(folder, stage, row) + if recompute: + report = compare_expected(stage, row, folder) + assert report['pass_all'] and report == read(folder / 'comparison.json'), 'Recomputed comparison differs' + + +def run(stage): + assert stage in CFG['stages'] + reg = check(full=True); budget() + assert not list((EXP / 'audit').glob('stopped-*.json')), 'Previous failure: preserve and inspect, never silently retry' + receipt = EXP / 'audit' / (stage + '-complete.json') + assert not receipt.exists(), 'Stage already completed' + if stage == 'static25': + prior = read(EXP / 'audit/zero-complete.json') + assert prior['pass_all'] and prior['trials'] == 144 + for row in reg['planned']: + verify_completed(EXP / 'gpu/zero' / (row['name'] + '-r' + str(row['repeat'])), 'zero', row) + preflight() + from adapter import run_gpu_overlay + began = time.perf_counter() + completed = [] + try: + for ordinal, row in enumerate(reg['planned'], 1): + key = row['name'] + '-r' + str(row['repeat']) + folder = EXP / 'gpu' / stage / key + case = AK / 'cases' / row['cohort'] / row['name'] + if folder.exists(): + verify_completed(folder, stage, row, recompute=True) + print('VERIFIED-COMPLETED', stage, ordinal, key, flush=True) + else: + preflight(); check(); budget() + print('START', stage, ordinal, key, flush=True) + summary = run_gpu_overlay(case, folder, EXP / 'extension-build', + EXP / 'overlays' / (stage + '.npz'), EXP / 'overlays' / (stage + '.json')) + assert summary['pass_all'] and summary['complete'] + report = compare_expected(stage, row, folder) + save(folder / 'comparison.json', report) + assert report['pass_all'], 'Independent recording/equivalence gate failed: ' + key + save(folder / 'output-hashes.json', output_inventory(folder)) + verify_completed(folder, stage, row) + print('COMPLETE', stage, ordinal, key, 'simulation_seconds', summary['diagnostic_simulation_seconds'], flush=True) + completed.append(dict(name=row['name'], repeat=row['repeat'], + output_hashes_sha256=digest(folder / 'output-hashes.json'), + comparison_sha256=digest(folder / 'comparison.json'))) + assert len(completed) == 144 + check(full=True) + result = dict(stage=stage, pass_all=True, trials=144, primary_trials=120, technical_repeats=24, + completed=completed, wall_seconds=time.perf_counter() - began, training=False, + scope='All zero-delta runs exactly match sealed AK' if stage == 'zero' else + 'Full closed-loop fixed overlay, internal event/queue accounting and 24 exact technical repeats; not learning') + save(receipt, result); budget() + return result + except Exception as error: + save(EXP / 'audit' / ('stopped-' + stage + '.json'), dict(stage=stage, + completed_before_error=completed, type=type(error).__name__, message=str(error), + traceback=traceback.format_exc(), partial_outputs_preserved=True, no_parameter_rescue=True)) + raise + + +if __name__ == '__main__': + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument('stage', choices=CFG['stages']) + run(parser.parse_args().stage) diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/summarize.py b/models/male-cns-lif/wholebrain-plastic-interface-v1/summarize.py new file mode 100644 index 0000000..e8c0d2e --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/summarize.py @@ -0,0 +1,106 @@ +"""Complete paired static-overlay effects; no learned-memory inference.""" +import numpy as np +import pandas as pd +from context import EXP, CFG, read, save, digest, bit_equal +from run_suite import verify_completed + + +def load(path): + with np.load(path, allow_pickle=False) as data: + return {k: data[k].copy() for k in data.files} + + +def first_ticks(state, n=166700): + out = np.full(n, np.iinfo(np.int32).max, np.int32) + np.minimum.at(out, state['neuron_idx'], state['step']) + out[out == np.iinfo(np.int32).max] = -1 + return out + + +def metrics(base, changed, population): + a, b = base['counts'][population], changed['counts'][population] + af, bf = first_ticks(base)[population], first_ticks(changed)[population] + ae = np.isin(base['neuron_idx'], population); be = np.isin(changed['neuron_idx'], population) + same = bit_equal(base['step'][ae], changed['step'][be]) and bit_equal(base['neuron_idx'][ae], changed['neuron_idx'][be]) + ax = base['step'][ae].astype(np.int64) * 166700 + base['neuron_idx'][ae] + bx = changed['step'][be].astype(np.int64) * 166700 + changed['neuron_idx'][be] + different = np.setxor1d(ax, bx, assume_unique=True) + return dict(cells=len(population), base_active=int(np.count_nonzero(a)), changed_active=int(np.count_nonzero(b)), + base_spikes=int(a.sum()), changed_spikes=int(b.sum()), + recruited_cells=int(np.count_nonzero((a == 0) & (b > 0))), lost_cells=int(np.count_nonzero((a > 0) & (b == 0))), + count_changed_cells=int(np.count_nonzero(a != b)), first_spike_changed_cells=int(np.count_nonzero(af != bf)), + count_l1=int(np.abs(a.astype(np.int64) - b.astype(np.int64)).sum()), event_sequence_changed=not same, + first_event_divergence_ms=None if not len(different) else float(different.min() // 166700 * .1), + final_v_max_abs_SI=float(np.max(np.abs(base['v'][population] - changed['v'][population]))) if len(population) else None, + final_g_max_abs_SI=float(np.max(np.abs(base['g'][population] - changed['g'][population]))) if len(population) else None) + + +def run(verify_only=False): + def emit(path, value): + if verify_only: + assert read(path) == value, str(path) + else: + save(path, value) + reg = read(EXP / 'protocol/preregistered.json') + for stage in CFG['stages']: + receipt = read(EXP / 'audit' / (stage + '-complete.json')) + assert receipt['pass_all'] and receipt['trials'] == 144 + assert len(receipt['completed']) == 144 + for row, entry in zip(reg['planned'], receipt['completed']): + assert entry['name'] == row['name'] and entry['repeat'] == row['repeat'] + folder = EXP / 'gpu' / stage / (row['name'] + '-r' + str(row['repeat'])) + verify_completed(folder, stage, row, recompute=True) + assert digest(folder / 'output-hashes.json') == entry['output_hashes_sha256'] + assert digest(folder / 'comparison.json') == entry['comparison_sha256'] + pops = load(EXP / 'protocol/populations.npz') + rows, cellrows, times, peaks = [], [], [], [] + for row in reg['planned']: + if row['repeat']: + continue + key = row['name'] + '-r0' + base, changed = [load(EXP / 'gpu' / stage / key / 'state.npz') for stage in CFG['stages']] + effects = {name: metrics(base, changed, nodes) for name, nodes in pops.items()} + result = dict(**row, effects=effects, whole_brain=metrics(base, changed, np.arange(166700, dtype=np.int32))) + emit(EXP / 'summaries' / (row['name'] + '.json'), result); rows.append(result) + af, bf = first_ticks(base), first_ticks(changed) + for neuron in pops['MBON']: + n = int(neuron) + cellrows.append(dict(case=row['name'], cohort=row['cohort'], mode=row['mode'], seed=row['seed'], + neuron_idx=n, base_count=int(base['counts'][n]), static25_count=int(changed['counts'][n]), + base_first_tick=int(af[n]), static25_first_tick=int(bf[n]), + base_final_v_SI=float(base['v'][n]), static25_final_v_SI=float(changed['v'][n]), + base_final_g_SI=float(base['g'][n]), static25_final_g_SI=float(changed['g'][n]))) + for stage in CFG['stages']: + s = read(EXP / 'gpu' / stage / key / 'summary.json') + times.append(dict(stage=stage, case=row['name'], wall_seconds=s['wall_seconds'], + simulation_seconds=s['diagnostic_simulation_seconds'])) + peaks.append(s['peak_allocated_vram_bytes']) + table = pd.DataFrame(cellrows) + table_path = EXP / 'summaries/per-MBON-static-effects.parquet' + if verify_only: + pd.testing.assert_frame_equal(table, pd.read_parquet(table_path), check_exact=True) + else: + assert not table_path.exists(); table.to_parquet(table_path, index=False) + blocks = {} + for cohort in sorted({r['cohort'] for r in rows}): + for mode in sorted({r['mode'] for r in rows}): + block = [r for r in rows if r['cohort'] == cohort and r['mode'] == mode] + assert len(block) == 30 + blocks[cohort + '/' + mode] = dict(trials=30, populations={name: dict( + trials_event_change=sum(r['effects'][name]['event_sequence_changed'] for r in block), + trials_count_change=sum(r['effects'][name]['count_changed_cells'] > 0 for r in block), + mean_count_l1=float(np.mean([r['effects'][name]['count_l1'] for r in block])), + mean_recruited_cells=float(np.mean([r['effects'][name]['recruited_cells'] for r in block])), + mean_lost_cells=float(np.mean([r['effects'][name]['lost_cells'] for r in block]))) for name in pops}) + summary = dict(status='PASS-EXACT-WHOLEBRAIN-PLASTIC-INTERFACE-NOT-LEARNING', + primary_trials_per_stage=120, technical_repeats_per_stage=24, zero_overlay_exact=True, + static25_repeat_exact=True, blocks=blocks, peak_allocated_vram_bytes=max(peaks), + timing=times, per_MBON_sha256=digest(table_path), training=False, learned_candidate=False, + conditional_AL_not_a_nonzero_arithmetic_oracle=True, + scope='Valid interface and recording; reported static response is not an associative learning PASS') + emit(EXP / 'audit/scientific-summary.json', summary) + return summary + + +if __name__ == '__main__': + print(run()['status'], flush=True) diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/test_comparison.py b/models/male-cns-lif/wholebrain-plastic-interface-v1/test_comparison.py new file mode 100644 index 0000000..e1652cf --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/test_comparison.py @@ -0,0 +1,363 @@ +"""Pure temporary-file synthetic tests; never a brain run or old-file write. + +Public integration tests mock only the full-case loader to use a tiny graph. +The sealed output parser, timing/queue reconstructor, overlay bridge, source AST +and receipt checks remain real. Production rejects these tiny cases unchanged. +""" +import copy +import hashlib +import json +from pathlib import Path +import shutil +import tempfile +import unittest +from unittest.mock import patch + +import numpy as np + +import comparison as c + + +def write_json(path, data): + Path(path).write_text(json.dumps(data, sort_keys=True, allow_nan=False), encoding='utf-8') + + +class ComparisonTests(unittest.TestCase): + def setUp(self): + self.temp = tempfile.TemporaryDirectory(prefix='phase4am-comparison-synthetic-') + self.addCleanup(self.temp.cleanup) + self.root = Path(self.temp.name).resolve() + self.case_dir = self.root / 'case' + self.graph_dir = self.root / 'graph' + self.bundle_dir = self.root / 'bundle' + for p in (self.case_dir, self.graph_dir, self.bundle_dir): + p.mkdir() + self.helper = c._helper(set()) + self.steps = 30 + self.graph = dict(nodes=np.arange(4, dtype=np.int32), edge_id=np.arange(6, dtype=np.int64), + ptr=np.array([0, 2, 3, 5, 6], np.int64), src=np.array([0, 0, 1, 2, 2, 3], np.int32), + dst=np.array([3, 2, 2, 0, 3, 1], np.int32), signed_raw=np.array([1, 0, 2, -2, 3, 1], np.int64)) + self.graph['weights'] = self.graph['signed_raw'] * (.275 * .001) + for key, value in self.graph.items(): + np.save(self.graph_dir / (key + '.npy'), value) + self.bundle = {'kc_globals.npy': np.r_[np.array([0, 1], np.int32), np.arange(4, 4066, dtype=np.int32)], + 'apl_globals.npy': np.array([2, 3], np.int32), 'input_matrix.npy': np.zeros((2, c.N), np.float32), + 'output_matrix.npy': np.zeros((2, c.K), np.float32)} + for key, value in self.bundle.items(): + np.save(self.bundle_dir / key, value) + self.requests = [(0, 0), (1, 1), (2, 0), (22, 0), (23, 3)] + np.savez(self.case_dir / 'requests.npz', tick=np.array([x[0] for x in self.requests], np.int32), + neuron_idx=np.array([x[1] for x in self.requests], np.int32)) + write_json(self.case_dir / 'spec.json', {'name': 'synthetic', 'steps': self.steps, + 'dt_ms': .1, 'duration_ms': 3., 'record_history': False, 'apl_delay_steps': 18}) + write_json(self.root / 'coeff.json', {'synthetic': True}) + self.case = dict(spec=json.loads((self.case_dir / 'spec.json').read_text()), graph=self.graph, + bundle=self.bundle, token=('synthetic', str(self.root)), graph_dir=self.graph_dir, bundle_dir=self.bundle_dir, + requested=self.requests, input_hashes={'spec.json': c.file_hash(self.case_dir / 'spec.json'), + 'requests.npz': c.file_hash(self.case_dir / 'requests.npz'), 'base_weights.npy': c.file_hash(self.graph_dir / 'weights.npy'), + 'coefficients.json': c.file_hash(self.root / 'coeff.json')}) + self.ids = np.array([0, 2], np.int64) + self.base = np.array([.275, .55], np.float32) + np.save(self.root / 'mask.npy', self.ids) + np.save(self.root / 'base.npy', self.base) + self.delta = np.zeros(2, np.float32) + self.overlay_name = 'zero' + self._overlay_inputs() + + def _overlay_inputs(self): + np.savez(self.root / 'overlay.npz', edge_id=self.ids, plastic_delta_mv=self.delta) + write_json(self.root / 'overlay-manifest.json', dict(schema='phase4am-overlay-v1', overlay_name=self.overlay_name, + overlay_sha256=c.file_hash(self.root / 'overlay.npz'), mask_path=str(self.root / 'mask.npy'), + mask_sha256=c.file_hash(self.root / 'mask.npy'), base_candidate_path=str(self.root / 'base.npy'), + base_candidate_sha256=c.file_hash(self.root / 'base.npy'), + aj_model_dir=str(Path(c.__file__).resolve().parent.parent / 'apl-timing-lab-v1'))) + + def run_files(self, name, wrapped): + directory = self.root / name + directory.mkdir() + ticks = np.array([0, 1, 18, 22, 23], np.int32) + nodes = np.array([0, 1, 2, 0, 3], np.int32) + state = dict(step=ticks, neuron_idx=nodes, counts=np.bincount(nodes, minlength=4).astype(np.int32), + v=np.full(4, -.052, np.float64), g=np.zeros(4, np.float64)) + hashes, queues, requests = [], [], [] + last = np.full(4, -1000000000, np.int64) + for tick in range(self.steps): + fired = nodes[ticks == tick] + for request_tick, target in self.requests: + if request_tick == tick: + ok = tick - last[target] >= 22 + requests.append(dict(tick=tick, neuron_idx=target, attempted=1, accepted=int(ok), rejected=int(not ok))) + last[fired] = tick + ref = np.maximum(22 - (tick - last), 0).astype(np.int32) + hashes.append(dict(tick=tick, v_sha256=c.raw_hash(state['v']), g_sha256=c.raw_hash(state['g']), ref_sha256=c.raw_hash(ref))) + sources = nodes[ticks == tick - 18] if tick >= 18 else [] + rows = np.array([eid for source in sources for eid in range(self.graph['ptr'][source], self.graph['ptr'][source + 1])], np.int64) + accepted = (ref[self.graph['dst'][rows]] == 0).astype(np.uint8) + queues.append(self.helper._queue_digest(tick, rows, accepted)) + state['ref'] = ref + np.savez(directory / 'state.npz', **state) + for filename, rows in (('tick-state-hashes.jsonl', hashes), ('queue.jsonl', queues)): + (directory / filename).write_text(''.join(json.dumps(row) + '\n' for row in rows), encoding='utf-8') + (directory / 'requests.csv').write_text('tick,neuron_idx,attempted,accepted,rejected\n' + + ''.join(','.join(str(row[key]) for key in c._helper(set()).REQUEST_FIELDS) + '\n' for row in requests), encoding='utf-8') + for field, width in (('drive', 2), ('state', 2), ('inhibition', c.K), ('applied', c.K)): + np.save(directory / ('apl-' + field + '.float32.npy'), np.zeros((self.steps, width), np.float32)) + pending = np.zeros((18, c.K), np.float32) + np.save(directory / 'apl-pending-tail.float32.npy', pending) + timing = dict(apl_delay_steps=18, steps=self.steps, pending_generated_count=18, generated_rows=self.steps, + applied_generated_rows=self.steps - 18, pending_shape=[18, c.K], pending_initial_zero_prefix=0, + pending_application_tick_start=self.steps, pending_application_tick_stop_exclusive=self.steps + 18, + pending_generated_tick_start=self.steps - 18, pending_generated_tick_stop_exclusive=self.steps, + pending_raw_sha256=c.raw_hash(pending), final_apl_state_float32=[0., 0.], final_apl_state_u32_bits=[0, 0], + final_apl_state_nonzero=False, brain_tail_advanced=False, future_apl_decay_or_feedback_generated=False, + finite_generated_sequence_only=True, closed_loop_branch_integrals_claimed_equal=False, + biological_delay_measurement_claimed=False) + write_json(directory / 'apl-timing-audit.json', timing) + component = dict(ok=True, protocol='phase4ag-apl-v1', n_neurons=c.N, n_apl=2, n_kc=c.K, dt_ms=.1, + files_sha256={key: c.file_hash(self.bundle_dir / key) for key in self.bundle}, + array_sha256={key: c.raw_hash(value) for key, value in self.bundle.items()}, + decay_f32_bits=f'{int(np.float32(np.exp(-.1 / 20.)).view(np.uint32)):08x}', + gain_f32_bits=f'{int(np.float32(.01).view(np.uint32)):08x}', + environment=dict(device_name='NVIDIA GeForce RTX 4090', cuda_matmul_allow_tf32=False, + float32_matmul_precision='highest', precision_configuration_changed_by_component=False)) + write_json(directory / 'apl-component.json', component) + (directory / 'sealed-gpu-source.diff').write_text('synthetic diff, not executed\n', encoding='utf-8') + provenance = dict(sealed_source_sha256=c.SEALED, candidate_sha256=c.AJ_SHA, + source_diff_sha256=c.file_hash(directory / 'sealed-gpu-source.diff'), module_globals_patched=False) + write_json(directory / 'source-audit.json', provenance) + _, effective_sha, apl_count = c._effective_hash(self.case, self.ids if wrapped else None, self.delta if wrapped else None) + summary = dict(case='synthetic', complete=True, pass_all=True, steps=self.steps, completed_ticks=self.steps, + nodes=4, edges=6, precision='float64', apl_precision='float32', state_units='SI volts', total_spikes=len(ticks), + requested=len(requests), accepted_requests=sum(row['accepted'] for row in requests), + rejected_requests=sum(row['rejected'] for row in requests), arriving_edges=sum(row['count'] for row in queues), + accepted_arriving_edges=sum(row['accepted_count'] for row in queues), counts_match_sparse_events=True, + all_finite=True, record_history=False, apl_fast_edges_zeroed=apl_count, kc_targets_present=c.K, + effective_weights_raw_sha256=effective_sha, apl_component=component, + apl_schedule='end, after threshold/reset and guarded arrivals, unconditional all KC', + apl_si_conversion='applied h32 -> float64 -> multiply float64 0.001 -> separate float64 subtraction', + apl_delay_steps=18, apl_timing=timing, source_provenance=provenance, pending_generated_count=18, + pending_initial_zero_prefix=0, pending_tail_shape=[18, c.K], future_generated_decay_tail_included=False, + build=dict(sources={'author_ext.cpp': c.CPP_SHA, 'author_ext.cu': c.CUDA_SHA}, arch_list='8.9', + cuda_flags=['-O2', '--fmad=false', '--ftz=false', '--prec-div=true', '--prec-sqrt=true']), + sealed_ae_backend_sha256=c.SEALED['ae_backend'], learning=False, input_sha256=self.case['input_hashes'], + **{key: 1.0 for key in c.PERFORMANCE}) + write_json(directory / 'summary.json', summary) + if wrapped: + self._write_overlay(directory, summary) + return directory + + def _write_overlay(self, directory, summary): + for source, target in (('overlay.npz', 'overlay-input.npz'), ('overlay-manifest.json', 'overlay-manifest.json')): + shutil.copyfile(self.root / source, directory / target) + input_rows = {} + for label, filename in (('overlay', 'overlay.npz'), ('manifest', 'overlay-manifest.json'), ('mask', 'mask.npy'), ('base_candidate', 'base.npy')): + input_rows[label + '_file'] = str(self.root / filename) + input_rows[label + '_sha256'] = c.file_hash(self.root / filename) + audit = dict(schema='phase4am-overlay-audit-v1', complete=True, overlay_name=self.overlay_name, input=input_rows, + arrays={key: dict(dtype=str(value.dtype), shape=list(value.shape), raw_sha256=c.raw_hash(value)) for key, value in + dict(edge_id=self.ids, plastic_delta_mv=self.delta, base_candidate_mv=self.base).items()}, + candidate_count=2, nonzero_delta_count=int(np.count_nonzero(self.delta)), mapped_candidate_count=2, + missing_candidate_count=0, installed_nonzero_count=int(np.count_nonzero(self.delta)), delta_dtype='float32', + delta_units='mV', state_dtype='float64', bridge=c.BRIDGE, installation_schedule=c.SCHEDULE, + weights_updated_during_run=False, learning=False, zero_delta_no_write=True, frozen_mask_exact=True, + bounds_pass=True, apl_overlap_count=0, apl_fast_edges_zeroed=summary['apl_fast_edges_zeroed'], + base_graph_files_modified=False, untouched_weights_bitwise_preserved=True, + base_weights_file_sha256=c.file_hash(self.graph_dir / 'weights.npy'), base_weights_raw_sha256=c._base_raw_hash(self.case), + effective_weights_raw_sha256=summary['effective_weights_raw_sha256'], + expected_effective_weights_raw_sha256=summary['effective_weights_raw_sha256'], + copied_overlay_file='overlay-input.npz', copied_manifest_file='overlay-manifest.json', + inherited_aj_source_provenance=summary['source_provenance'], + inherited_source_audit_scope='AJ source provenance only; AM overlay semantics are recorded separately', + static25_is_exact_fraction_of_float64_base_claimed=False, arrival_weight_sampling='arrival time; delta fixed for entire trial') + write_json(directory / 'overlay-audit.json', audit) + model = Path(c.__file__).resolve().parent + receipt = dict(schema='phase4am-adapter-provenance-v1', complete=True, + scope='constant sparse overlay installation only; no within-trial plasticity or learning', + adapter_file=str(model / 'adapter.py'), adapter_sha256=c.file_hash(model / 'adapter.py'), + overlay_module_file=str(model / 'overlay.py'), overlay_module_sha256=c.file_hash(model / 'overlay.py'), + sealed_sources={relative: dict(path=str(model.parent / relative), sha256=sha) for relative, sha in c.ADAPTER_PINS.items()}, + ast=c._expected_ast(model.parent / 'apl-timing-lab-v1/gpu_timing.py', model / 'adapter.py'), + installation_calls=1, weights_updated_during_run=False, learning=False, apl_delay_steps=18, + original_module_globals_patched=False, delta_constant_for_entire_trial=True, + inherited_source_audit_describes_AM_semantics=False, overlay_audit_sha256=c.file_hash(directory / 'overlay-audit.json'), + inherited_summary_sha256=c.file_hash(directory / 'summary.json'), effective_weights_raw_sha256=summary['effective_weights_raw_sha256']) + write_json(directory / 'adapter-provenance.json', receipt) + + def compare(self, left, right, mode='zero', output=None): + with patch.object(c, '_load_case', return_value=self.case), patch.object(c, 'CANDIDATES', 2): + return c.compare_runs(self.case_dir, left, right, output, mode) + + def assert_pass(self, report): + self.assertTrue(report['pass_all'], json.dumps({key: report.get(key) for key in ('error', 'failed_checks', 'differences')})) + self.assertFalse(report['learning_achieved']) + self.assertFalse(report['candidate_generated']) + self.assertTrue(report['read_manifest']) + + def test_zero_complete_real_parsers(self): + left, right = self.run_files('left', False), self.run_files('right', True) + self.assert_pass(self.compare(left, right)) + + def test_static25_repeat_and_single_validation(self): + self.overlay_name = 'static25' + self.delta = np.multiply(self.base, np.float32(-.25)) + self._overlay_inputs() + left, right = self.run_files('left', True), self.run_files('right', True) + self.assert_pass(self.compare(left, right, 'repeat')) + self.assert_pass(self.compare(left, left, 'self')) + + def test_production_rejects_toy_dimensions(self): + with self.assertRaises(ValueError): + c._load_case(self.case_dir, set()) + + def test_missing_adapter_receipt_fails_despite_complete_summary(self): + left, right = self.run_files('left', False), self.run_files('right', True) + (right / 'adapter-provenance.json').unlink() + self.assertFalse(self.compare(left, right)['pass_all']) + + def test_corrupt_adapter_receipt_ast_and_summary_binding_fail(self): + left, right = self.run_files('left', False), self.run_files('right', True) + path = right / 'adapter-provenance.json' + original = json.loads(path.read_text()) + for change in ('ast', 'binding', 'complete'): + data = copy.deepcopy(original) + if change == 'ast': + data['ast']['entire_tick_loop_ast_identical'] = False + elif change == 'binding': + data['inherited_summary_sha256'] = '0' * 64 + else: + data['complete'] = False + write_json(path, data) + self.assertFalse(self.compare(left, right)['pass_all'], change) + + def test_per_neuron_count_corruption_not_hidden_by_equal_total(self): + left, right = self.run_files('left', False), self.run_files('right', True) + for folder in (left, right): + with np.load(folder / 'state.npz') as f: + state = {key: f[key].copy() for key in f.files} + state['counts'][0] -= 1 + state['counts'][1] += 1 + np.savez(folder / 'state.npz', **state) + self.assertFalse(self.compare(left, right)['pass_all']) + + def test_both_equal_wrong_queues_fail_independent_reconstruction(self): + left, right = self.run_files('left', False), self.run_files('right', True) + for folder in (left, right): + path = folder / 'queue.jsonl' + rows = [json.loads(row) for row in path.read_text().splitlines()] + rows[18]['ordered_edge_sha256'] = '0' * 64 + path.write_text(''.join(json.dumps(row) + '\n' for row in rows), encoding='utf-8') + report = self.compare(left, right) + self.assertFalse(report['pass_all']) + self.assertIn('left_gpu.full_event_queue_request_accounting', report['failed_checks']) + + def test_both_equal_wrong_requests_fail(self): + left, right = self.run_files('left', False), self.run_files('right', True) + for folder in (left, right): + path = folder / 'requests.csv' + path.write_text(path.read_text().replace('2,0,1,0,1', '2,0,1,1,0'), encoding='utf-8') + self.assertFalse(self.compare(left, right)['pass_all']) + + def test_both_equal_wrong_ref_hash_fails(self): + left, right = self.run_files('left', False), self.run_files('right', True) + for folder in (left, right): + path = folder / 'tick-state-hashes.jsonl' + rows = [json.loads(row) for row in path.read_text().splitlines()] + rows[1]['ref_sha256'] = '0' * 64 + path.write_text(''.join(json.dumps(row) + '\n' for row in rows), encoding='utf-8') + self.assertFalse(self.compare(left, right)['pass_all']) + + def test_state_signed_zero_detected(self): + left, right = self.run_files('left', False), self.run_files('right', True) + with np.load(right / 'state.npz') as f: + state = {key: f[key].copy() for key in f.files} + state['g'][0] = -0. + np.savez(right / 'state.npz', **state) + self.assertFalse(self.compare(left, right)['pass_all']) + + def test_same_nonfinite_states_fail(self): + left, right = self.run_files('left', False), self.run_files('right', True) + for folder in (left, right): + with np.load(folder / 'state.npz') as f: + state = {key: f[key].copy() for key in f.files} + state['v'][0] = np.inf + np.savez(folder / 'state.npz', **state) + self.assertFalse(self.compare(left, right)['pass_all']) + + def test_apl_pending_signed_zero_fails(self): + left, right = self.run_files('left', False), self.run_files('right', True) + path = right / 'apl-pending-tail.float32.npy' + value = np.load(path) + value[0, 0] = np.float32(-0.) + np.save(path, value) + self.assertFalse(self.compare(left, right)['pass_all']) + + def test_missing_tick_or_extra_request_fails(self): + left, right = self.run_files('left', False), self.run_files('right', True) + path = right / 'queue.jsonl' + path.write_text('\n'.join(path.read_text().splitlines()[:-1]) + '\n', encoding='utf-8') + self.assertFalse(self.compare(left, right)['pass_all']) + + def test_summary_only_whitelisted_performance_may_differ(self): + a = dict(dynamics='same', build={'source': 'same'}, wall_seconds=1) + b = dict(a, wall_seconds=5) + checks, differences = {}, {} + c._summary_pair(a, b, checks, differences) + self.assertTrue(all(checks.values())) + b['build'] = {'source': 'different'} + c._summary_pair(a, b, checks, differences) + self.assertFalse(all(checks.values())) + + def test_overlay_bad_units_and_fake_complete_receipt_fail(self): + left, right = self.run_files('left', False), self.run_files('right', True) + path = right / 'overlay-audit.json' + data = json.loads(path.read_text()); data['delta_units'] = 'V'; write_json(path, data) + self.assertFalse(self.compare(left, right)['pass_all']) + + def test_source_or_build_mutation_fails(self): + left, right = self.run_files('left', False), self.run_files('right', True) + path = right / 'summary.json' + data = json.loads(path.read_text()); data['build']['cuda_flags'].append('--use_fast_math'); write_json(path, data) + self.assertFalse(self.compare(left, right)['pass_all']) + + def test_no_existing_output_overwrite_and_no_input_directory_write(self): + left, right = self.run_files('left', False), self.run_files('right', True) + output = self.root / 'report.json' + self.assert_pass(self.compare(left, right, output=output)) + with self.assertRaises(ValueError): + self.compare(left, right, output=output) + with self.assertRaises(ValueError): + self.compare(left, right, output=right / 'report.json') + + def test_fake_repeat_self_disallowed(self): + left = self.run_files('left', True) + self.assertFalse(self.compare(left, left, 'repeat')['pass_all']) + + def test_static25_cannot_be_zero_reference(self): + self.overlay_name = 'static25'; self.delta = np.multiply(self.base, np.float32(-.25)); self._overlay_inputs() + left, right = self.run_files('left', False), self.run_files('right', True) + self.assertFalse(self.compare(left, right)['pass_all']) + + def test_helper_source_pin_and_adapter_ast_contract(self): + model = Path(c.__file__).resolve().parent + self.assertEqual(c.file_hash(model.parent / 'apl-timing-lab-v1/compare_timing.py'), c.HELPER_SHA) + import adapter + _, owner = adapter.derive_ast((model.parent / 'apl-timing-lab-v1/gpu_timing.py').read_bytes()) + independent = c._expected_ast(model.parent / 'apl-timing-lab-v1/gpu_timing.py', model / 'adapter.py') + for key, value in owner.items(): + self.assertEqual(independent[key], value) + + def test_fresh_sha_detects_same_size_write_even_with_identical_stat(self): + path = self.root / 'same-stat.bin' + path.write_bytes(b'first!') + identity = c._fingerprint(path) + with patch.object(c, '_fingerprint', return_value=identity): + before = c.file_hash(path) + path.write_bytes(b'other!') + after = c.file_hash(path) + self.assertEqual(before, hashlib.sha256(b'first!').hexdigest()) + self.assertEqual(after, hashlib.sha256(b'other!').hexdigest()) + self.assertNotEqual(before, after) + + +if __name__ == '__main__': + unittest.main() diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/test_eligibility_bridge.py b/models/male-cns-lif/wholebrain-plastic-interface-v1/test_eligibility_bridge.py new file mode 100644 index 0000000..6c076bc --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/test_eligibility_bridge.py @@ -0,0 +1,259 @@ +"""Synthetic eligibility tests only; never load recorded brain trajectories.""" +import ast +import importlib.util +import json +import math +import os +from pathlib import Path +from types import SimpleNamespace +import tempfile +import unittest +from typing import Any + +import numpy as np + +import eligibility_bridge as bridge + + +def source_path(): + explicit = os.environ.get("PHASE4J_SOURCE") + if explicit: + return Path(explicit) + parent = Path(__file__).resolve().parents[1] + paths = (parent / "models/male-cns-lif/phase4j.py", parent / "mb-physiology-v1/phase4j.py") + for path in paths: + if path.is_file(): + return path + raise FileNotFoundError("Set PHASE4J_SOURCE to the SHA-pinned original phase4j.py") + + +SOURCE = source_path() +KC = np.array([1, 3, 7], np.int32) + + +def run_trace(rows=(), steps=8, commands=(0, 3, 7), backend="numpy"): + events = np.asarray(rows, np.int32).reshape(-1, 2) + return bridge.trace_from_events(events[:, 0], events[:, 1], KC, steps, commands, + phase4j_source=SOURCE, backend=backend, n_neurons=10) + + +def update_args(): + return dict(trace=np.array([1, .25, 0], np.float32), kc=KC.copy(), + candidate_sources=np.array([1, 1, 3, 7, 3], np.int32), + candidate_compartments=np.array(["y5B'2a", "a1", "y5B'2a", "y5B'2a", "y2a'1"]), + compartment="y5B'2a", delta=np.zeros(5, np.float32), + base_candidate=np.array([.275, .55, .0001, .275, 2.75], np.float32), + d=1., phase4j_source=SOURCE, n_neurons=10) + + +class FrozenTraceTests(unittest.TestCase): + def test_no_input_positive_zero_and_no_command(self): + result = run_trace(commands=()) + self.assertEqual(result.snapshots.shape, (0, 3)) + self.assertTrue(bridge.bit_equal(result.final, np.zeros(3, np.float32))) + self.assertTrue(bridge.bit_equal(result.last_command_trace, result.final)) + self.assertFalse(result.audit["training_executed"]) + self.assertFalse(result.audit["torch_numpy_bitwise_comparison_performed"]) + json.dumps(result.audit, allow_nan=False) + + def test_simultaneous_spike_is_seen_and_cap_is_one(self): + result = run_trace([(0, 1), (1, 1), (3, 3), (3, 7)]) + self.assertEqual(result.snapshots[0, 0], np.float32(1)) + self.assertEqual(result.snapshots[1, 1:].tolist(), [1., 1.]) + self.assertLessEqual(float(result.final.max()), 1.) + + def test_interval_decay_is_each_tick_not_power_jump(self): + result = run_trace([(0, 1)], steps=1001, commands=(0, 1, 1000)) + expected = np.float32(1) + decay = np.float32(math.exp(-.1 / 100.)) + for _ in range(1000): + expected = np.float32(expected * decay) + self.assertEqual(result.snapshots[-1, 0].view(np.uint32), expected.view(np.uint32)) + self.assertEqual(result.snapshots[1, 0].view(np.uint32), decay.view(np.uint32)) + + def test_us_before_future_cs_has_zero_delta(self): + result = run_trace([(2, 1)], commands=(1,)) + args = update_args() + args["trace"] = result.last_command_trace + delta, _ = bridge.apply_eligibility(**args) + self.assertTrue(bridge.bit_equal(delta, args["delta"])) + + def test_plus_1000_ms_ratio_strict_below_point01(self): + result = run_trace([(0, 1)], steps=10001, commands=(0, 10000)) + args = update_args() + args["base_candidate"][:] = 100 # no saturation in this temporal check + args["trace"] = result.snapshots[0] + zero, _ = bridge.apply_eligibility(**args) + args["trace"] = result.snapshots[1] + late, _ = bridge.apply_eligibility(**args) + self.assertLess(float(np.abs(late).sum() / np.abs(zero).sum()), .01) + self.assertGreater(float(result.snapshots[-1, 0]), 0.) + + def test_non_kc_events_do_not_enter_trace(self): + a = run_trace([(0, 1), (3, 3)]) + b = run_trace([(0, 0), (0, 1), (2, 9), (3, 3)]) + self.assertTrue(bridge.bit_equal(a.snapshots, b.snapshots)) + self.assertEqual(b.audit["actual_kc_events"], 2) + + def test_inputs_and_outputs_are_not_mutated(self): + step, node, kc = np.array([0, 7], np.int32), np.array([1, 3], np.int32), KC.copy() + before = [a.copy() for a in (step, node, kc)] + result = bridge.trace_from_events(step, node, kc, 8, [7], phase4j_source=SOURCE, n_neurons=10) + for a, b in zip((step, node, kc), before): + self.assertTrue(bridge.bit_equal(a, b)) + for a in (result.final, result.snapshots, result.command_steps, result.last_command_trace): + self.assertFalse(a.flags.writeable) + + def test_bad_event_and_command_schema_is_rejected(self): + for rows in ([(0, 1), (0, 1)], [(1, 1), (0, 1)], [(-1, 1)], [(8, 1)], [(0, 10)]): + with self.subTest(rows=rows), self.assertRaises(ValueError): + run_trace(rows) + for commands in ((1, 1), (3, 1), (-1,), (8,), (.5,), (True,), np.empty((0, 2), np.int32)): + with self.subTest(commands=commands), self.assertRaises(ValueError): + run_trace(commands=commands) + with self.assertRaises(ValueError): + bridge.trace_from_events(np.array([], np.int64), np.array([], np.int32), KC, 8, [], phase4j_source=SOURCE) + + def test_bad_kc_and_backend_are_rejected(self): + for kc in (np.array([3, 1], np.int32), np.array([1, 1], np.int32), np.array([], np.int32)): + with self.assertRaises(ValueError): + bridge.trace_from_events(np.array([], np.int32), np.array([], np.int32), kc, 1, [], phase4j_source=SOURCE) + with self.assertRaises(ValueError): + run_trace(backend="auto") + + @unittest.skipUnless(importlib.util.find_spec("torch") is not None, "Torch absent: CPU bitwise compatibility NOT established locally") + def test_torch_original_expression_bitwise_against_numpy(self): + rng = np.random.default_rng(719) + mask = rng.random((1001, 10)) < .07 + tick, node = np.nonzero(mask) + rows = np.stack((tick, node), axis=1).tolist() + numpy_result = run_trace(rows, steps=1001, commands=(0, 1, 7, 999, 1000)) + torch_result = run_trace(rows, steps=1001, commands=(0, 1, 7, 999, 1000), backend="torch") + self.assertTrue(bridge.bit_equal(numpy_result.snapshots, torch_result.snapshots)) + self.assertTrue(bridge.bit_equal(numpy_result.final, torch_result.final)) + empty_np = run_trace([(0, 1)], steps=10001, commands=(0, 10000)) + empty_torch = run_trace([(0, 1)], steps=10001, commands=(0, 10000), backend="torch") + self.assertTrue(bridge.bit_equal(empty_np.snapshots, empty_torch.snapshots)) + + +class FrozenUpdateTests(unittest.TestCase): + def test_actual_source_sha_and_ast_only_extraction(self): + _, report = bridge.apply_eligibility(**update_args()) + self.assertEqual(report["source_sha256"], bridge.PHASE4J_SHA256) + self.assertFalse(report["actual_dan_activity_used_to_gate"]) + self.assertFalse(report["learning_pass_claimed"]) + json.dumps(report, allow_nan=False) + + def test_source_drift_is_rejected_before_execution(self): + with tempfile.TemporaryDirectory() as directory: + path = Path(directory) / "phase4j.py" + path.write_bytes(SOURCE.read_bytes() + b"\nraise RuntimeError('must not execute')\n") + args = update_args() + args["phase4j_source"] = path + with self.assertRaisesRegex(ValueError, "SHA256 mismatch"): + bridge.apply_eligibility(**args) + + def test_bitwise_against_independently_extracted_original_apply_v2(self): + tree = ast.parse(SOURCE.read_text(encoding="utf-8")) + function = next(x for x in tree.body if isinstance(x, ast.FunctionDef) and x.name == "apply_v2") + namespace = {"np": np, "Validator": object, "Any": Any} + exec(compile(ast.Module(body=[function], type_ignores=[]), "independent-old-apply-v2", "exec"), namespace) + + class Column: + def __init__(self, values): + self.values = values + + def to_numpy(self, dtype=None): + return np.array(self.values, dtype=dtype) + + def astype(self, dtype): + return Column(np.asarray(self.values).astype(dtype)) + + args = update_args() + validator = SimpleNamespace(n=10, kc=KC, base_candidate=args["base_candidate"], + cand={"source_neuron_idx": Column(args["candidate_sources"]), + "target_compartment_verbatim": Column(args["candidate_compartments"])}) + cfg = {"eligibility_v2": {"eta_effective_mv": .00275, "max_fractional_depression": .25}} + for _ in range(50): + actual, report = bridge.apply_eligibility(**args) + expected, old_report = namespace["apply_v2"](validator, args["trace"], args["compartment"], 1., args["delta"], cfg) + self.assertTrue(bridge.bit_equal(actual, expected)) + self.assertEqual(report["original_report"], old_report) + args["delta"] = actual + + def test_zero_d_and_frozen_preserve_existing_overlay(self): + args = update_args() + args["delta"][:] = -.25 * args["base_candidate"] + for d, frozen in ((0., False), (1., True), (0., True)): + args.update(d=d, frozen=frozen) + result, report = bridge.apply_eligibility(**args) + self.assertTrue(bridge.bit_equal(result, args["delta"])) + self.assertEqual(report["actual_changed_edges"], 0) + + def test_off_compartment_and_inactive_source_exact_unchanged(self): + args = update_args() + args["delta"][1] = -.01 + result, _ = bridge.apply_eligibility(**args) + self.assertTrue(bridge.bit_equal(result[[1, 3, 4]], args["delta"][[1, 3, 4]])) + self.assertEqual(result[0], np.float32(-.00275)) + + def test_original_floor_clamps_and_does_not_reverse_sign(self): + args = update_args() + result, report = bridge.apply_eligibility(**args) + self.assertEqual(result[2], (-.25 * args["base_candidate"])[2]) + args["delta"] = result + again, _ = bridge.apply_eligibility(**args) + self.assertEqual(again[2].view(np.uint32), result[2].view(np.uint32)) + self.assertTrue(np.all(again <= 0)) + # Original updated_edges counts attempted updates, including saturation. + self.assertEqual(report["original_report"]["updated_edges"], 2) + + def test_all_original_compartments_are_literal_not_inferred(self): + args = update_args() + args["candidate_sources"] = np.full(4, 1, np.int32) + args["candidate_compartments"] = np.array(bridge.COMPARTMENTS) + args["delta"] = np.zeros(4, np.float32) + args["base_candidate"] = np.ones(4, np.float32) + for comp in bridge.COMPARTMENTS: + args["compartment"] = comp + result, _ = bridge.apply_eligibility(**args) + self.assertEqual(int(np.count_nonzero(result)), 1) + self.assertNotEqual(result[list(bridge.COMPARTMENTS).index(comp)], 0) + + def test_update_does_not_mutate_inputs_and_returns_readonly(self): + args = update_args() + before = {k: v.copy() for k, v in args.items() if isinstance(v, np.ndarray)} + result, _ = bridge.apply_eligibility(**args) + for k, value in before.items(): + self.assertTrue(bridge.bit_equal(args[k], value)) + self.assertFalse(result.flags.writeable) + + def test_invalid_units_dtypes_values_and_compartment_fail_closed(self): + bad = [("trace", np.array([1, .25, 0], np.float64)), + ("trace", np.array([1, np.nan, 0], np.float32)), + ("trace", np.array([1.1, 0, 0], np.float32)), + ("candidate_sources", np.array([1, 1, 3, 8, 3], np.int32)), + ("compartment", "PAM15"), ("d", -.1), ("d", .5), ("d", float("nan")), + ("d", True), ("frozen", 1), + ("base_candidate", np.zeros(5, np.float32)), + ("delta", np.ones(5, np.float32)), + ("delta", np.full(5, -.5, np.float32)), + ("delta", np.full(5, -0., np.float32))] + for key, value in bad: + with self.subTest(key=key, value=value): + args = update_args() + args[key] = value + with self.assertRaises(ValueError): + bridge.apply_eligibility(**args) + + def test_empty_candidate_subset_is_safe_but_not_claimed_full_mask(self): + args = update_args() + for key in ("candidate_sources", "candidate_compartments", "delta", "base_candidate"): + args[key] = args[key][:0] + result, report = bridge.apply_eligibility(**args) + self.assertEqual(result.shape, (0,)) + self.assertFalse(report["complete_mask_identity_verified_by_this_function"]) + + +if __name__ == "__main__": + unittest.main() diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/test_overlay_adapter.py b/models/male-cns-lif/wholebrain-plastic-interface-v1/test_overlay_adapter.py new file mode 100644 index 0000000..e1d5091 --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/test_overlay_adapter.py @@ -0,0 +1,275 @@ +"""Pure synthetic inputs/AST tests; no Torch import, GPU, or brain execution.""" +import ast +import hashlib +import json +from pathlib import Path +import tempfile +import types +import unittest +import time + +import numpy as np + +import adapter +import overlay + + +HERE = Path(__file__).absolute().parent +AJ = HERE.parent / 'apl-timing-lab-v1/gpu_timing.py' + + +class ArrayTests(unittest.TestCase): + def setUp(self): + self.ids = np.array([2, 7, 15], np.int64) + self.base32 = np.array([.275, 1.1, 2.75], np.float32) + + def plan(self, delta=None): + if delta is None: + delta = np.zeros(3, np.float32) + return overlay.validate_arrays(self.ids, delta, self.ids, self.base32) + + def test_zero_preserves_unrelated_signed_zero_and_original_bytes(self): + ids = np.array([0, 2, 7, 15, 17], np.int64) + base = np.array([-0., .000275, .0011, .00275, -1.], np.float64) + original = base.tobytes() + result, mapping = overlay.materialize_numpy(base, ids, np.zeros(5, bool), self.plan()) + self.assertEqual(result.tobytes(), original) + self.assertEqual(base.tobytes(), original) + self.assertEqual(mapping['installed_nonzero_count'], 0) + self.assertEqual(len(mapping['rows']), 0) + self.assertFalse(np.shares_memory(result, base)) + + def test_negative_zero_delta_does_not_write(self): + plan = self.plan(np.full(3, -0., np.float32)) + result, mapping = overlay.materialize_numpy(self.base32.astype(np.float64) * .001, + self.ids, np.zeros(3, bool), plan) + self.assertEqual(len(mapping['rows']), 0) + self.assertTrue(np.signbit(plan['plastic_delta_mv']).all()) + + def test_original_float32_floor_then_widen_and_multiply(self): + delta = np.float32(-.25) * self.base32 + plan = self.plan(delta) + base_si = np.array([.000275, .0011, .00275], np.float64) + result, mapping = overlay.materialize_numpy(base_si, self.ids, np.zeros(3, bool), plan) + reference = np.add(base_si, np.multiply(delta.astype(np.float64), np.float64(.001))) + self.assertTrue(overlay.bit_equal(result, reference)) + self.assertTrue(np.any(result.view(np.uint64) != (base_si * .75).view(np.uint64))) + self.assertEqual(mapping['installed_nonzero_count'], 3) + + def test_global_id_mapping_fixture_intersection_and_missing_nonzero_reject(self): + plan = self.plan(np.array([0., -.1, 0.], np.float32)) + ids = np.array([1, 7, 20], np.int64) + result, mapping = overlay.materialize_numpy(np.array([1., .002, -0.], np.float64), ids, + np.array([True, False, False]), plan) + np.testing.assert_array_equal(mapping['rows'], np.array([1], np.int64)) + self.assertEqual(mapping['missing_candidate_count'], 2) + self.assertEqual(result[0].view(np.uint64), 0) + self.assertTrue(np.signbit(result[2])) + with self.assertRaises(ValueError): + overlay.materialize_numpy(np.array([1.], np.float64), np.array([1], np.int64), np.zeros(1, bool), plan) + + def test_apl_overlap_sign_nonfinite_bad_mapping_fail_closed(self): + base = self.base32.astype(np.float64) * .001 + for ids, values, apl in ((self.ids, base, np.array([1, 0, 0], bool)), + (self.ids[::-1], base, np.zeros(3, bool)), + (self.ids, -base, np.zeros(3, bool)), + (self.ids, np.array([np.nan, 1., 2.]), np.zeros(3, bool))): + with self.subTest(ids=ids), self.assertRaises(ValueError): + overlay.map_installation(values, ids, apl, self.plan()) + + def test_validation_bad_dtype_shape_sign_finite_bound_and_mask(self): + bad_deltas = [np.zeros(3, np.float64), np.zeros((3, 1), np.float32), np.zeros(2, np.float32), + np.array([.1, 0, 0], np.float32), np.array([np.nan, 0, 0], np.float32), + np.array([-np.inf, 0, 0], np.float32), np.array([-1., 0, 0], np.float32)] + for delta in bad_deltas: + with self.subTest(delta=delta), self.assertRaises(ValueError): + self.plan(delta) + for ids in (self.ids.astype(np.int32), self.ids[::-1], np.array([2, 2, 15], np.int64), + np.array([-1, 7, 15], np.int64), np.array([2, 7, overlay.EDGE_COUNT], np.int64)): + with self.subTest(ids=ids), self.assertRaises(ValueError): + overlay.validate_arrays(ids, np.zeros(3, np.float32), self.ids, self.base32) + with self.assertRaises(ValueError): + overlay.validate_arrays(self.ids, np.array([-.01, 0, 0], np.float32), self.ids) + + def test_positive_original_base_and_bound_bits_readonly(self): + for base in (np.zeros(3, np.float32), -self.base32, self.base32.astype(np.float64), + np.array([np.inf, 1., 1.], np.float32)): + with self.assertRaises(ValueError): + overlay.validate_arrays(self.ids, np.zeros(3, np.float32), self.ids, base) + self.ids.flags.writeable = False + self.base32.flags.writeable = False + plan = self.plan() + self.assertFalse(plan['edge_id'].flags.writeable) + self.assertFalse(plan['plastic_delta_mv'].flags.writeable) + self.assertFalse(np.shares_memory(plan['base_candidate_mv'], self.base32)) + lower = np.float32(-.25) * self.base32 + too_low = lower.copy(); too_low[0] = np.nextafter(lower[0], np.float32(-np.inf)) + with self.assertRaises(ValueError): + self.plan(too_low) + + def test_chunked_expected_hash_matches_materialization(self): + ids = np.array([0, 2, 7, 15, 20], np.int64) + base = np.array([-0., .001, .002, .003, -1.], np.float64) + apl = np.array([False, False, False, False, True]) + plan = self.plan(np.array([-.01, 0, -.2], np.float32)) + result, mapping = overlay.materialize_numpy(base, ids, apl, plan) + for chunk in (1, 2, 3, 100): + self.assertEqual(overlay.expected_hashes(base, apl, mapping, chunk), + (overlay.raw_hash(base), overlay.raw_hash(result))) + + +class FileTests(unittest.TestCase): + def setUp(self): + self.temp = tempfile.TemporaryDirectory() + self.addCleanup(self.temp.cleanup) + self.root = Path(self.temp.name) + self.ids = np.arange(overlay.CANDIDATE_COUNT, dtype=np.int64) + self.base = np.full(overlay.CANDIDATE_COUNT, .275, np.float32) + np.save(self.root / 'mask.npy', self.ids) + np.save(self.root / 'base.npy', self.base) + + def files(self, name='zero', embedded=False, base=True): + delta = np.zeros_like(self.base) if name == 'zero' else np.float32(-.25) * self.base + values = dict(edge_id=self.ids, plastic_delta_mv=delta) + if embedded: + values['base_candidate_mv'] = self.base + np.savez(self.root / 'overlay.npz', **values) + manifest = dict(schema=overlay.SCHEMA, overlay_name=name, + overlay_sha256=overlay.file_hash(self.root / 'overlay.npz'), + mask_path=str(self.root / 'mask.npy'), mask_sha256=overlay.file_hash(self.root / 'mask.npy'), + base_candidate_path=str(self.root / 'base.npy') if base else None, + base_candidate_sha256=overlay.file_hash(self.root / 'base.npy') if base else None, + aj_model_dir=str(self.root)) + (self.root / 'manifest.json').write_text(json.dumps(manifest), encoding='utf-8') + return self.root / 'overlay.npz', self.root / 'manifest.json' + + def test_full_mask_zero_optional_base_and_static_floor(self): + for name, embedded, base in (('zero', False, False), ('zero', True, True), ('static25', True, True)): + plan = overlay.load_overlay(*self.files(name, embedded, base)) + self.assertEqual(len(plan['edge_id']), overlay.CANDIDATE_COUNT) + overlay.verify_inputs(plan) + + def test_hash_tamper_and_wrong_count_reject(self): + paths = self.files() + (self.root / 'base.npy').write_bytes(b'not the anchored source') + with self.assertRaises(ValueError): + overlay.load_overlay(*paths) + np.save(self.root / 'base.npy', self.base) + np.save(self.root / 'mask.npy', self.ids[:-1]) + paths = self.files() + with self.assertRaises(ValueError): + overlay.load_overlay(*paths) + + def test_static25_needs_original_base_and_postload_tampering_is_detected(self): + with self.assertRaises(ValueError): + overlay.load_overlay(*self.files('static25', base=False)) + paths = self.files() + plan = overlay.load_overlay(*paths) + (self.root / 'manifest.json').write_text('{}', encoding='utf-8') + with self.assertRaises(ValueError): + overlay.verify_inputs(plan) + + +class AstTests(unittest.TestCase): + def source(self): + if not AJ.is_file(): + self.skipTest('Pinned AJ static source is not installed at its declared sibling path') + return AJ.read_bytes() + + def test_exact_whole_tick_loop_and_only_one_preloop_insertion(self): + source = self.source() + transformed, audit = adapter.derive_ast(source) + original = next(node for node in ast.parse(source).body if isinstance(node, ast.FunctionDef) and node.name == 'run_gpu') + getloop = lambda function: next(node for node in ast.walk(function) if isinstance(node, ast.For) and + isinstance(node.target, ast.Name) and node.target.id == 'tick') + self.assertEqual(ast.dump(getloop(original), include_attributes=False), ast.dump(getloop(transformed), include_attributes=False)) + hooks = [node for node in ast.walk(transformed) if isinstance(node, ast.Call) and + isinstance(node.func, ast.Name) and node.func.id == adapter.HOOK_NAME] + self.assertEqual(len(hooks), 1) + self.assertFalse(any(node is hooks[0] for node in ast.walk(getloop(transformed)))) + self.assertTrue(audit['entire_tick_loop_ast_identical']) + self.assertEqual(audit['inserted_ast_statements'], 1) + + def test_mutated_source_fails_even_if_loop_looks_plausible(self): + with self.assertRaises(ValueError): + adapter.derive_ast(self.source() + b'\n# unregistered change\n') + + def test_compilation_new_namespace_no_fake_file_no_old_global_patch(self): + self.source() + # Compile only; the function is never called, so no Torch or GPU needed. + sealed = types.ModuleType('synthetic_sealed_namespace') + sealed.__file__ = str(AJ) + sealed.marker = object() + before = dict(sealed.__dict__) + hook = lambda *args: None + function, audit = adapter.compile_derived(sealed, hook) + self.assertEqual(sealed.__dict__, before) + self.assertNotIn(adapter.HOOK_NAME, sealed.__dict__) + self.assertIs(function.__globals__[adapter.HOOK_NAME], hook) + self.assertIs(function.__globals__['marker'], sealed.marker) + self.assertEqual(function.__globals__['__file__'], str(Path(adapter.__file__).absolute())) + self.assertNotEqual(function.__globals__['__file__'], sealed.__file__) + self.assertFalse(audit['fake_original_file_used']) + self.assertFalse(audit['original_module_globals_patched']) + + def test_real_source_dependency_hashes_without_importing_gpu(self): + self.source() + proof = adapter.verify_sources(AJ.parent) + self.assertEqual({key: row['sha256'] for key, row in proof.items()}, adapter.PINS) + self.assertEqual(hashlib.sha256(AJ.read_bytes()).hexdigest(), adapter.AJ_SHA256) + + def test_derived_hook_runs_after_apl_zero_and_before_any_state_tick(self): + self.source() + + class StopBeforeBrain(BaseException): + pass + + class Tensor: + def __init__(self, array): + self.array = np.array(array, copy=True) + + def to(self, *, device, dtype): + return Tensor(self.array.astype(dtype)) + + def contiguous(self): + return self + + def clone(self): + return Tensor(self.array) + + def __setitem__(self, item, value): + self.array[item.array if isinstance(item, Tensor) else item] = value + + torch_stub = types.SimpleNamespace(from_numpy=Tensor, float64=np.float64, int64=np.int64, + int32=np.int32, bool=bool, cuda=types.SimpleNamespace(is_available=lambda: True, + device_count=lambda: 1, get_device_name=lambda: 'synthetic RTX4090', reset_peak_memory_stats=lambda _: None)) + graph = {'weights': np.array([.1, -.2], np.float64), 'nodes': np.array([3, 9], np.int32), + 'edge_id': np.array([4, 12], np.int64), 'ptr': np.array([0, 1, 2], np.int64), + 'dst': np.array([1, 0], np.int32), 'src': np.array([0, 1], np.int32)} + apl = types.SimpleNamespace(device='no-device', apl_globals=np.array([9], np.int32), metadata={}) + sealed = types.ModuleType('synthetic_before_loop') + sealed.__file__ = str(AJ) + sealed.__dict__.update(Path=Path, time=time, np=np, torch=torch_stub, require=overlay.require, + source_audit=lambda _: {'scope': 'synthetic inherited AJ source'}, write_json=lambda *_: None, + load_inputs=lambda _: ({'apl_bundle_dir': 'unused', 'dt_ms': .1, 'steps': 2}, graph, {}, + np.empty(0, np.int32), np.empty(0, np.int32), np.empty(0, np.int32), {}), + sealed_backend=lambda: types.SimpleNamespace(build_extension=lambda _: (None, {})), + sealed_apl=lambda: types.SimpleNamespace(LegacyAPL=lambda *_: apl)) + observed = [] + + def hook(weights, actual_graph, mask, upload, out_dir, provenance): + self.assertTrue(overlay.bit_equal(weights.array, np.array([.1, 0.], np.float64))) + self.assertTrue(overlay.bit_equal(graph['weights'], np.array([.1, -.2], np.float64))) + np.testing.assert_array_equal(mask, [False, True]) + observed.append(provenance) + raise StopBeforeBrain() + + derived, _ = adapter.compile_derived(sealed, hook) + with tempfile.TemporaryDirectory() as directory: + with self.assertRaises(StopBeforeBrain): + derived(Path(directory), Path(directory) / 'new-output', Path(directory) / 'new-build') + self.assertEqual(len(observed), 1) + + +if __name__ == '__main__': + unittest.main() diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/test_workflow.py b/models/male-cns-lif/wholebrain-plastic-interface-v1/test_workflow.py new file mode 100644 index 0000000..76f946f --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/test_workflow.py @@ -0,0 +1,55 @@ +"""Small independent checks of provenance/summary mechanics.""" +import ast +from pathlib import Path +import tempfile +import unittest +import numpy as np +from prepare import old_base_candidate +from summarize import first_ticks, metrics +from run_suite import output_inventory, verify_completed +from context import save + + +class WorkflowTests(unittest.TestCase): + def test_old_expression_float32(self): + candidates = [Path(__file__).resolve().parent.parent / 'phase4c.py', + Path(__file__).resolve().parent.parent / 'models/male-cns-lif/phase4c.py'] + source = next(p for p in candidates if p.is_file()) + x = np.array([1, 2, 9, 19, 1234, 1048577], np.int64) + value, sha = old_base_candidate(x, source) + expected = x.astype(np.float32) * np.int8(1) * float(.275) + self.assertEqual(value.tobytes(), expected.tobytes()) + self.assertEqual(len(sha), 64) + + def test_first_tick_and_missing(self): + state = dict(step=np.array([0, 2, 3, 4], np.int32), neuron_idx=np.array([1, 2, 1, 2], np.int32)) + np.testing.assert_array_equal(first_ticks(state, 4), [-1, 0, 2, -1]) + + def test_same_counts_event_change_not_hidden(self): + a = dict(step=np.array([0], np.int32), neuron_idx=np.array([1], np.int32), + counts=np.array([0, 1, 0], np.int32), v=np.zeros(3), g=np.zeros(3)) + b = {k: v.copy() for k, v in a.items()}; b['step'][0] = 2 + m = metrics(a, b, np.array([1], np.int32)) + self.assertTrue(m['event_sequence_changed']); self.assertEqual(m['count_changed_cells'], 0) + self.assertEqual(m['first_spike_changed_cells'], 1); self.assertEqual(m['first_event_divergence_ms'], 0) + + def test_extra_or_changed_output_rejected(self): + with tempfile.TemporaryDirectory() as temp: + folder = Path(temp) + save(folder / 'comparison.json', {'pass_all': True}) + save(folder / 'summary.json', {'complete': True}) + save(folder / 'output-hashes.json', output_inventory(folder)) + verify_completed(folder) + save(folder / 'unexpected.json', {}) + with self.assertRaises(AssertionError): + verify_completed(folder) + + def test_exclusive_json(self): + with tempfile.TemporaryDirectory() as temp: + path = Path(temp) / 'value.json'; save(path, {}) + with self.assertRaises(FileExistsError): + save(path, {}) + + +if __name__ == '__main__': + unittest.main() diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/test_workflow_identity.py b/models/male-cns-lif/wholebrain-plastic-interface-v1/test_workflow_identity.py new file mode 100644 index 0000000..96975ba --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/test_workflow_identity.py @@ -0,0 +1,220 @@ +"""Synthetic AM workflow identity/dispatch tests; no old evidence or network.""" +import builtins +import copy +import io +import json +import os +from pathlib import Path +import sys +import tempfile +from types import ModuleType +import unittest +from unittest.mock import Mock, patch + +import run_suite as runner + + +class WorkflowIdentityTests(unittest.TestCase): + def setUp(self): + self.temp = tempfile.TemporaryDirectory() + self.addCleanup(self.temp.cleanup) + self.root = Path(self.temp.name).resolve() + self.exp = self.root / "experiments/new-am" + self.ak = self.root / "experiments/fake-ak" + self.patches = patch.multiple(runner, ROOT=self.root, EXP=self.exp, AK=self.ak) + self.patches.start() + self.addCleanup(self.patches.stop) + + def fixture(self, stage="zero", repeat=0, name="synthetic-odor"): + row = dict(name=name, repeat=repeat, cohort="seed_validation") + case = self.ak / "cases" / row["cohort"] / name + case.mkdir(parents=True, exist_ok=True) + (case / "spec.json").write_bytes(b'{"synthetic":true}\n') + # This is a hash-only mock input, never parsed as scientific NPZ data. + (case / "requests.npz").write_bytes(b"synthetic-request-bytes") + overlays = self.exp / "overlays" + overlays.mkdir(parents=True, exist_ok=True) + (overlays / (stage + ".npz")).write_bytes((stage + "-synthetic-overlay").encode()) + (overlays / (stage + ".json")).write_bytes((stage + "-synthetic-manifest").encode()) + folder = self.exp / "gpu" / stage / (name + "-r" + str(repeat)) + folder.mkdir(parents=True, exist_ok=False) + summary = dict(case=name, complete=True, pass_all=True, input_sha256={ + key: runner.digest(case / key) for key in ("spec.json", "requests.npz")}) + overlay = dict(complete=True, overlay_name=stage, input={ + "overlay_sha256": runner.digest(overlays / (stage + ".npz")), + "manifest_sha256": runner.digest(overlays / (stage + ".json"))}) + if stage == "zero": + mode = "zero" + left = self.ak / "gpu" / row["cohort"] / (name + "-r" + str(repeat)) + elif repeat == 1: + mode = "repeat" + left = self.exp / "gpu" / stage / (name + "-r0") + else: + mode, left = "self", folder + report = dict(pass_all=True, overlay_name=stage, case_dir=str(case), + right=str(folder), left=str(left), mode=mode) + for key, value in (("summary.json", summary), ("overlay-audit.json", overlay), + ("comparison.json", report)): + runner.save(folder / key, value) + runner.save(folder / "output-hashes.json", runner.output_inventory(folder)) + return row, case, folder, report + + @staticmethod + def replace_json(path, value): + # Mutations are deliberate corruptions of NEW temporary test fixtures. + path.write_text(json.dumps(value), encoding="utf-8") + + def corrupt(self, folder, filename, field, value): + original = runner.read(folder / filename) + changed = copy.deepcopy(original) + target = changed + for key in field[:-1]: + target = target[key] + target[field[-1]] = value + self.replace_json(folder / filename, changed) + return original + + def test_three_legitimate_identities_and_zero_repeat(self): + for stage, repeat in (("zero", 0), ("zero", 1), ("static25", 0), ("static25", 1)): + with self.subTest(stage=stage, repeat=repeat): + row, _, folder, _ = self.fixture(stage, repeat) + runner.verify_identity(folder, stage, row) + runner.verify_completed(folder, stage, row) + + def test_wrong_case_and_cohort_fail_even_with_valid_hash_inventory(self): + row, _, folder, _ = self.fixture() + for altered in (dict(row, name="other-odor"), dict(row, cohort="novel_to_aj")): + with self.subTest(altered=altered), self.assertRaises((AssertionError, FileNotFoundError)): + runner.verify_identity(folder, "zero", altered) + self.corrupt(folder, "summary.json", ("case",), "other-odor") + self.replace_json(folder / "output-hashes.json", runner.output_inventory(folder)) + with self.assertRaises(AssertionError): + runner.verify_completed(folder, "zero", row) + + def test_wrong_stage_and_repeat_path_are_rejected(self): + row, _, folder, _ = self.fixture() + for stage, wrong_row in (("static25", row), ("zero", dict(row, repeat=1)), + ("unknown", row), ("zero", dict(row, repeat=2))): + with self.subTest(stage=stage, row=wrong_row), self.assertRaises(AssertionError): + runner.verify_identity(folder, stage, wrong_row) + + def test_overlay_stage_identity_and_two_input_hashes_are_required(self): + row, _, folder, _ = self.fixture("static25") + for field, value in ((("overlay_name",), "zero"), (("complete",), False), + (("input", "overlay_sha256"), "0" * 64), + (("input", "manifest_sha256"), "0" * 64)): + original = self.corrupt(folder, "overlay-audit.json", field, value) + with self.subTest(field=field), self.assertRaises(AssertionError): + runner.verify_identity(folder, "static25", row) + self.replace_json(folder / "overlay-audit.json", original) + + def test_summary_completion_and_actual_case_hashes_are_required(self): + row, _, folder, _ = self.fixture() + for field, value in ((("complete",), False), (("pass_all",), False), + (("input_sha256", "spec.json"), "0" * 64), + (("input_sha256", "requests.npz"), "0" * 64)): + original = self.corrupt(folder, "summary.json", field, value) + with self.subTest(field=field), self.assertRaises(AssertionError): + runner.verify_identity(folder, "zero", row) + self.replace_json(folder / "summary.json", original) + + def test_comparison_case_paths_mode_and_stage_are_required(self): + for stage, repeat in (("zero", 0), ("static25", 0), ("static25", 1)): + row, _, folder, _ = self.fixture(stage, repeat) + for field, value in ((("case_dir",), str(self.root / "wrong-case")), + (("right",), str(self.root / "wrong-output")), + (("left",), str(self.root / "wrong-reference")), + (("overlay_name",), "not-the-stage"), + (("mode",), "invalid-mode"), (("pass_all",), False)): + original = self.corrupt(folder, "comparison.json", field, value) + with self.subTest(stage=stage, repeat=repeat, field=field), self.assertRaises(AssertionError): + runner.verify_identity(folder, stage, row) + self.replace_json(folder / "comparison.json", original) + + def test_self_report_cannot_substitute_for_repeat(self): + row, _, folder, _ = self.fixture("static25", 1) + report = runner.read(folder / "comparison.json") + report.update(mode="self", left=str(folder)) + self.replace_json(folder / "comparison.json", report) + self.replace_json(folder / "output-hashes.json", runner.output_inventory(folder)) + with self.assertRaises(AssertionError): + runner.verify_completed(folder, "static25", row) + + def test_recompute_must_match_full_stored_report(self): + row, _, folder, report = self.fixture("static25", 1) + with patch.object(runner, "compare_expected", return_value=copy.deepcopy(report)) as compare: + runner.verify_completed(folder, "static25", row, recompute=True) + compare.assert_called_once_with("static25", row, folder) + for result in (dict(report, pass_all=False), dict(report, newly_detected_difference=True)): + with patch.object(runner, "compare_expected", return_value=result), self.assertRaises(AssertionError): + runner.verify_completed(folder, "static25", row, recompute=True) + + def test_partial_folder_is_preserved_without_attempted_comparison(self): + row, _, folder, _ = self.fixture() + (folder / "output-hashes.json").unlink() # Deliberately incomplete NEW fixture. + before = {p.name: p.read_bytes() for p in folder.iterdir()} + with patch.object(runner, "compare_expected") as compare, self.assertRaises(FileNotFoundError): + runner.verify_completed(folder, "zero", row, recompute=True) + compare.assert_not_called() + self.assertEqual(before, {p.name: p.read_bytes() for p in folder.iterdir()}) + + def test_compare_expected_zero_dispatches_to_corresponding_ak_repeat(self): + self.assert_dispatch("zero", 0) + self.assert_dispatch("zero", 1) + + def test_compare_expected_static_repeat_dispatches_to_r0(self): + self.assert_dispatch("static25", 1) + + def test_compare_expected_static_primary_uses_self_validation(self): + self.assert_dispatch("static25", 0) + + def assert_dispatch(self, stage, repeat): + fake = ModuleType("comparison") + fake.compare_runs = Mock(return_value={"marker": "pair"}) + fake.validate_run = Mock(return_value={"marker": "single"}) + row = dict(name="synthetic", cohort="novel_to_aj", repeat=repeat) + folder = self.exp / "gpu" / stage / (row["name"] + "-r" + str(repeat)) + case = self.ak / "cases" / row["cohort"] / row["name"] + with patch.dict(sys.modules, {"comparison": fake}): + result = runner.compare_expected(stage, row, folder) + if stage == "zero": + reference = self.ak / "gpu" / row["cohort"] / (row["name"] + "-r" + str(repeat)) + fake.compare_runs.assert_called_once_with(case, reference, folder, mode="zero") + fake.validate_run.assert_not_called() + self.assertEqual(result, {"marker": "pair"}) + elif repeat: + reference = self.exp / "gpu" / stage / (row["name"] + "-r0") + fake.compare_runs.assert_called_once_with(case, reference, folder, mode="repeat") + fake.validate_run.assert_not_called() + self.assertEqual(result, {"marker": "pair"}) + else: + fake.validate_run.assert_called_once_with(case, folder) + fake.compare_runs.assert_not_called() + self.assertEqual(result, {"marker": "single"}) + # No output_path was passed: the comparator cannot write into evidence. + + def test_preflight_sets_cuda_environment_without_torch_or_network(self): + imported = builtins.__import__ + + def guarded_import(name, *args, **kwargs): + if name == "torch" or name.startswith("torch."): + self.fail("preflight imported Torch") + return imported(name, *args, **kwargs) + + def response(url, timeout): + self.assertEqual(os.environ["CUDA_VISIBLE_DEVICES"], runner.CFG["gpu_uuid"]) + self.assertEqual(os.environ["CUDA_HOME"], "/usr/local/cuda") + self.assertEqual(os.environ["TORCH_CUDA_ARCH_LIST"], "8.9") + self.assertEqual(timeout, 5) + return io.BytesIO(b'{"queue_running":[],"queue_pending":[]}') + + with patch.dict(os.environ, {"PATH": "synthetic-original-path"}), \ + patch("builtins.__import__", side_effect=guarded_import), \ + patch.object(runner.urllib.request, "urlopen", side_effect=response) as urlopen: + runner.preflight() + self.assertEqual(urlopen.call_count, 3) + self.assertTrue(os.environ["PATH"].endswith("synthetic-original-path")) + + +if __name__ == "__main__": + unittest.main() diff --git a/models/male-cns-lif/wholebrain-plastic-interface-v1/verify_frozen.py b/models/male-cns-lif/wholebrain-plastic-interface-v1/verify_frozen.py new file mode 100644 index 0000000..8a35ca0 --- /dev/null +++ b/models/male-cns-lif/wholebrain-plastic-interface-v1/verify_frozen.py @@ -0,0 +1,47 @@ +"""Old deterministic-v2 references, into new output paths only.""" +import sys +import time +import numpy as np +import pandas as pd +import yaml +from context import ROOT, EXP, check, save, bit_equal +from run_suite import preflight + + +def main(): + check(full=True) + assert not (EXP / 'regression/frozen-five.json').exists() + preflight() + runtime_path = ROOT / 'models/male-cns-lif/deterministic-runtime-v2' + pc = 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(pc, runtime_path, EXP) + rows = [] + for spec in pc['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={key: bool(bit_equal(value, result[key])) for key, value in reference.items()}, + dtype_shape={key: dict(reference_dtype=str(value.dtype), actual_dtype=str(result[key].dtype), + reference_shape=list(value.shape), actual_shape=list(result[key].shape)) for key, value 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) + save(EXP / 'regression/frozen-five.json', dict(pass_all=passed, trials=rows, + wall_seconds=time.perf_counter() - started, peak_allocated_vram=int(torch.cuda.max_memory_allocated()), + scope='Old frozen deterministic-v2 references; not a claim D18 equals old runtime')) + assert passed + + +if __name__ == '__main__': + main() diff --git a/registry/phase4am-wholebrain-plastic-interface/evidence-index.json b/registry/phase4am-wholebrain-plastic-interface/evidence-index.json new file mode 100644 index 0000000..9e6ffda --- /dev/null +++ b/registry/phase4am-wholebrain-plastic-interface/evidence-index.json @@ -0,0 +1,18122 @@ +[ + { + "source": "experiments/phase4am-wholebrain-plastic-interface/REPORT.md", + 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b/registry/phase4am-wholebrain-plastic-interface/evidence/REPORT.md new file mode 100644 index 0000000..d240984 --- /dev/null +++ b/registry/phase4am-wholebrain-plastic-interface/evidence/REPORT.md @@ -0,0 +1,13 @@ +# Phase 4AM — whole-brain plastic interface + +Status: `PASS-EXACT-WHOLEBRAIN-PLASTIC-INTERFACE-NOT-LEARNING`. + +All 144 zero-overlay runs reproduce sealed AK D18 exactly. All 120 fixed-overlay primary runs and 24 repeats are retained. +The fixed overlay is the original float32 25% floor, added through the declared float64 SI bridge. No training occurred. + +- novel_to_aj/matched_energy: KC event changes 30/30; MBON event changes 30/30; mask_recipient_MBON event changes 30/30; DAN event changes 30/30; MBON_downstream event changes 30/30; descending event changes 30/30; motor event changes 30/30. +- novel_to_aj/physiological: KC event changes 30/30; MBON event changes 30/30; mask_recipient_MBON event changes 30/30; DAN event changes 30/30; MBON_downstream event changes 30/30; descending event changes 30/30; motor event changes 30/30. +- seed_validation/matched_energy: KC event changes 30/30; MBON event changes 30/30; mask_recipient_MBON event changes 30/30; DAN event changes 30/30; MBON_downstream event changes 30/30; descending event changes 30/30; motor event changes 30/30. +- seed_validation/physiological: KC event changes 30/30; MBON event changes 30/30; mask_recipient_MBON event changes 30/30; DAN event changes 30/30; MBON_downstream event changes 30/30; descending event changes 30/30; motor event changes 30/30. + +Old artifacts and five deterministic-v2 references pass integrity/regression. This does not complete the learning goal. diff --git a/registry/phase4am-wholebrain-plastic-interface/evidence/audit/final-status.json b/registry/phase4am-wholebrain-plastic-interface/evidence/audit/final-status.json new file mode 100644 index 0000000..9725fff --- /dev/null +++ b/registry/phase4am-wholebrain-plastic-interface/evidence/audit/final-status.json @@ -0,0 +1,16 @@ +{ + "status": "PASS-EXACT-WHOLEBRAIN-PLASTIC-INTERFACE-NOT-LEARNING", + "zero_overlay_exact": true, + "static25_repeat_exact": true, + "primary_trials_per_stage": 120, + "repeats_per_stage": 24, + "old_integrity_pass": true, + "frozen_five_reference_pass": true, + "frozen_eligibility_and_mask_unchanged": true, + "base_weights_unchanged": true, + "training": false, + "learned_candidate": false, + "scientific_summary_sha256": "03f229fc0768d38bb7c2a3c558dbd68c2c3a622cbf96b1b16aef2819b6b67b77", + "payload_bytes_before_manifest": 10251867790, + "next_required": "Separately preregister finite olfactory paired/control conditioning; no automatic learning PASS" +} diff --git a/registry/phase4am-wholebrain-plastic-interface/evidence/audit/scientific-summary.json b/registry/phase4am-wholebrain-plastic-interface/evidence/audit/scientific-summary.json new file mode 100644 index 0000000..c510657 --- /dev/null +++ b/registry/phase4am-wholebrain-plastic-interface/evidence/audit/scientific-summary.json @@ -0,0 +1,1673 @@ +{ + "status": "PASS-EXACT-WHOLEBRAIN-PLASTIC-INTERFACE-NOT-LEARNING", + "primary_trials_per_stage": 120, + "technical_repeats_per_stage": 24, + "zero_overlay_exact": true, + "static25_repeat_exact": true, + "blocks": { + "novel_to_aj/matched_energy": { + "trials": 30, + "populations": { + "KC": { + "trials_event_change": 30, + "trials_count_change": 6, + "mean_count_l1": 0.23333333333333334, + "mean_recruited_cells": 0.03333333333333333, + "mean_lost_cells": 0.03333333333333333 + }, + "MBON": { + "trials_event_change": 30, + "trials_count_change": 30, + "mean_count_l1": 29.933333333333334, + 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"pass_all": true, + "exit_code": 0, + "log_sha256": "856fc56d9d12b576e3dd0f6cacd6aa017ad093ce2b9d2e04311eb2b167aa34ea" +} diff --git a/registry/phase4am-wholebrain-plastic-interface/evidence/regression/unit-tests.log b/registry/phase4am-wholebrain-plastic-interface/evidence/regression/unit-tests.log new file mode 100644 index 0000000..4822bde --- /dev/null +++ b/registry/phase4am-wholebrain-plastic-interface/evidence/regression/unit-tests.log @@ -0,0 +1,80 @@ +test_apl_pending_signed_zero_fails (test_comparison.ComparisonTests) ... ok +test_both_equal_wrong_queues_fail_independent_reconstruction (test_comparison.ComparisonTests) ... ok +test_both_equal_wrong_ref_hash_fails (test_comparison.ComparisonTests) ... ok +test_both_equal_wrong_requests_fail (test_comparison.ComparisonTests) ... ok +test_corrupt_adapter_receipt_ast_and_summary_binding_fail (test_comparison.ComparisonTests) ... ok +test_fake_repeat_self_disallowed (test_comparison.ComparisonTests) ... ok +test_fresh_sha_detects_same_size_write_even_with_identical_stat (test_comparison.ComparisonTests) ... ok +test_helper_source_pin_and_adapter_ast_contract (test_comparison.ComparisonTests) ... ok +test_missing_adapter_receipt_fails_despite_complete_summary (test_comparison.ComparisonTests) ... ok +test_missing_tick_or_extra_request_fails (test_comparison.ComparisonTests) ... ok +test_no_existing_output_overwrite_and_no_input_directory_write (test_comparison.ComparisonTests) ... ok +test_overlay_bad_units_and_fake_complete_receipt_fail (test_comparison.ComparisonTests) ... ok +test_per_neuron_count_corruption_not_hidden_by_equal_total (test_comparison.ComparisonTests) ... ok +test_production_rejects_toy_dimensions (test_comparison.ComparisonTests) ... ok +test_same_nonfinite_states_fail (test_comparison.ComparisonTests) ... ok +test_source_or_build_mutation_fails (test_comparison.ComparisonTests) ... ok +test_state_signed_zero_detected (test_comparison.ComparisonTests) ... ok +test_static25_cannot_be_zero_reference (test_comparison.ComparisonTests) ... ok +test_static25_repeat_and_single_validation (test_comparison.ComparisonTests) ... ok +test_summary_only_whitelisted_performance_may_differ (test_comparison.ComparisonTests) ... ok +test_zero_complete_real_parsers (test_comparison.ComparisonTests) ... ok +test_bad_event_and_command_schema_is_rejected (test_eligibility_bridge.FrozenTraceTests) ... ok +test_bad_kc_and_backend_are_rejected (test_eligibility_bridge.FrozenTraceTests) ... ok +test_inputs_and_outputs_are_not_mutated (test_eligibility_bridge.FrozenTraceTests) ... ok +test_interval_decay_is_each_tick_not_power_jump (test_eligibility_bridge.FrozenTraceTests) ... ok +test_no_input_positive_zero_and_no_command (test_eligibility_bridge.FrozenTraceTests) ... ok +test_non_kc_events_do_not_enter_trace (test_eligibility_bridge.FrozenTraceTests) ... ok +test_plus_1000_ms_ratio_strict_below_point01 (test_eligibility_bridge.FrozenTraceTests) ... ok +test_simultaneous_spike_is_seen_and_cap_is_one (test_eligibility_bridge.FrozenTraceTests) ... ok +test_torch_original_expression_bitwise_against_numpy (test_eligibility_bridge.FrozenTraceTests) ... ok +test_us_before_future_cs_has_zero_delta (test_eligibility_bridge.FrozenTraceTests) ... ok +test_actual_source_sha_and_ast_only_extraction (test_eligibility_bridge.FrozenUpdateTests) ... ok +test_all_original_compartments_are_literal_not_inferred (test_eligibility_bridge.FrozenUpdateTests) ... ok +test_bitwise_against_independently_extracted_original_apply_v2 (test_eligibility_bridge.FrozenUpdateTests) ... ok +test_empty_candidate_subset_is_safe_but_not_claimed_full_mask (test_eligibility_bridge.FrozenUpdateTests) ... ok +test_invalid_units_dtypes_values_and_compartment_fail_closed (test_eligibility_bridge.FrozenUpdateTests) ... ok +test_off_compartment_and_inactive_source_exact_unchanged (test_eligibility_bridge.FrozenUpdateTests) ... ok +test_original_floor_clamps_and_does_not_reverse_sign (test_eligibility_bridge.FrozenUpdateTests) ... ok +test_source_drift_is_rejected_before_execution (test_eligibility_bridge.FrozenUpdateTests) ... ok +test_update_does_not_mutate_inputs_and_returns_readonly (test_eligibility_bridge.FrozenUpdateTests) ... ok +test_zero_d_and_frozen_preserve_existing_overlay (test_eligibility_bridge.FrozenUpdateTests) ... ok +test_apl_overlap_sign_nonfinite_bad_mapping_fail_closed (test_overlay_adapter.ArrayTests) ... ok +test_chunked_expected_hash_matches_materialization (test_overlay_adapter.ArrayTests) ... ok +test_global_id_mapping_fixture_intersection_and_missing_nonzero_reject (test_overlay_adapter.ArrayTests) ... ok +test_negative_zero_delta_does_not_write (test_overlay_adapter.ArrayTests) ... ok +test_original_float32_floor_then_widen_and_multiply (test_overlay_adapter.ArrayTests) ... ok +test_positive_original_base_and_bound_bits_readonly (test_overlay_adapter.ArrayTests) ... ok +test_validation_bad_dtype_shape_sign_finite_bound_and_mask (test_overlay_adapter.ArrayTests) ... ok +test_zero_preserves_unrelated_signed_zero_and_original_bytes (test_overlay_adapter.ArrayTests) ... ok +test_compilation_new_namespace_no_fake_file_no_old_global_patch (test_overlay_adapter.AstTests) ... ok +test_derived_hook_runs_after_apl_zero_and_before_any_state_tick (test_overlay_adapter.AstTests) ... ok +test_exact_whole_tick_loop_and_only_one_preloop_insertion (test_overlay_adapter.AstTests) ... ok +test_mutated_source_fails_even_if_loop_looks_plausible (test_overlay_adapter.AstTests) ... ok +test_real_source_dependency_hashes_without_importing_gpu (test_overlay_adapter.AstTests) ... ok +test_full_mask_zero_optional_base_and_static_floor (test_overlay_adapter.FileTests) ... ok +test_hash_tamper_and_wrong_count_reject (test_overlay_adapter.FileTests) ... ok +test_static25_needs_original_base_and_postload_tampering_is_detected (test_overlay_adapter.FileTests) ... ok +test_exclusive_json (test_workflow.WorkflowTests) ... ok +test_extra_or_changed_output_rejected (test_workflow.WorkflowTests) ... ok +test_first_tick_and_missing (test_workflow.WorkflowTests) ... ok +test_old_expression_float32 (test_workflow.WorkflowTests) ... ok +test_same_counts_event_change_not_hidden (test_workflow.WorkflowTests) ... ok +test_compare_expected_static_primary_uses_self_validation (test_workflow_identity.WorkflowIdentityTests) ... ok +test_compare_expected_static_repeat_dispatches_to_r0 (test_workflow_identity.WorkflowIdentityTests) ... ok +test_compare_expected_zero_dispatches_to_corresponding_ak_repeat (test_workflow_identity.WorkflowIdentityTests) ... ok +test_comparison_case_paths_mode_and_stage_are_required (test_workflow_identity.WorkflowIdentityTests) ... ok +test_overlay_stage_identity_and_two_input_hashes_are_required (test_workflow_identity.WorkflowIdentityTests) ... ok +test_partial_folder_is_preserved_without_attempted_comparison (test_workflow_identity.WorkflowIdentityTests) ... ok +test_preflight_sets_cuda_environment_without_torch_or_network (test_workflow_identity.WorkflowIdentityTests) ... ok +test_recompute_must_match_full_stored_report (test_workflow_identity.WorkflowIdentityTests) ... ok +test_self_report_cannot_substitute_for_repeat (test_workflow_identity.WorkflowIdentityTests) ... ok +test_summary_completion_and_actual_case_hashes_are_required (test_workflow_identity.WorkflowIdentityTests) ... ok +test_three_legitimate_identities_and_zero_repeat (test_workflow_identity.WorkflowIdentityTests) ... ok +test_wrong_case_and_cohort_fail_even_with_valid_hash_inventory (test_workflow_identity.WorkflowIdentityTests) ... ok +test_wrong_stage_and_repeat_path_are_rejected (test_workflow_identity.WorkflowIdentityTests) ... ok + +---------------------------------------------------------------------- +Ran 75 tests in 7.213s + +OK diff --git a/registry/phase4am-wholebrain-plastic-interface/evidence/summaries/novel_to_aj-matched_energy-00-s1073741825.json b/registry/phase4am-wholebrain-plastic-interface/evidence/summaries/novel_to_aj-matched_energy-00-s1073741825.json new file mode 100644 index 0000000..716281c --- /dev/null +++ b/registry/phase4am-wholebrain-plastic-interface/evidence/summaries/novel_to_aj-matched_energy-00-s1073741825.json @@ -0,0 +1,145 @@ +{ + "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, + "effects": { + "KC": { + "cells": 4064, + "base_active": 160, + "changed_active": 160, + "base_spikes": 163, + "changed_spikes": 163, + "recruited_cells": 0, + "lost_cells": 0, + 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a/registry/phase4am-wholebrain-plastic-interface/evidence/summaries/novel_to_aj-matched_energy-02-s1073741829.json b/registry/phase4am-wholebrain-plastic-interface/evidence/summaries/novel_to_aj-matched_energy-02-s1073741829.json new file mode 100644 index 0000000..7b9a5c4 --- /dev/null +++ b/registry/phase4am-wholebrain-plastic-interface/evidence/summaries/novel_to_aj-matched_energy-02-s1073741829.json @@ -0,0 +1,145 @@ +{ + "name": "novel_to_aj-matched_energy-02-s1073741829", + "cohort": "novel_to_aj", + "source_panel_split": "heldout", + "source_panel_row": 8, + "mode": "matched_energy", + "odor_id": "CETWDUZRCINIHU-ZETCQYMHSA-N", + "odor_index": 2, + "seed": 1073741829, + "targets": 39, + "requests": 97, + "expected_external_events": 102.24430541992187, + "rates_sum": 1022.4430541992188, + "repeat": 0, + "effects": { + "KC": { + "cells": 4064, + "base_active": 137, + "changed_active": 137, + "base_spikes": 140, + "changed_spikes": 140, + "recruited_cells": 0, + "lost_cells": 0, + 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index 0000000..9acda8e --- /dev/null +++ b/tools/phase4am-publication/fetch_phase4am.py @@ -0,0 +1,340 @@ +"""Fetch only externally anchored Phase 4AM 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/wholebrain-plastic-interface-v1' +EXPERIMENT_RELATIVE = 'experiments/phase4am-wholebrain-plastic-interface' +REGISTRY_RELATIVE = 'registry/phase4am-wholebrain-plastic-interface' +MODEL_ROOT = REMOTE_ROOT + '/' + MODEL_RELATIVE +REGISTRY_ROOT = REMOTE_ROOT + '/' + REGISTRY_RELATIVE +DEFAULT_DESTINATION = Path(__file__).resolve().parents[2] / 'reports/phase4am-wholebrain-plastic-interface' +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 AM 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 AM 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', 'evidence/audit/scientific-summary.json', + 'evidence/protocol/preregistered.json', 'evidence/audit/zero-complete.json', + 'evidence/audit/static25-complete.json', 'evidence/regression/frozen-five.json', *GENERATED} + require(required.issubset(rows), 'Receipt omits required AM 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 AM 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/phase4am-publication/publish_phase4am.py b/tools/phase4am-publication/publish_phase4am.py new file mode 100644 index 0000000..4e72536 --- /dev/null +++ b/tools/phase4am-publication/publish_phase4am.py @@ -0,0 +1,354 @@ +"""Exclusive small-evidence publication after both Phase 4AM 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 +import math +from pathlib import Path, PurePosixPath + + +ROOT = Path('/data/digital-drosophila') +MODEL_RELATIVE = Path('models/male-cns-lif/wholebrain-plastic-interface-v1') +EXPERIMENT_RELATIVE = Path('experiments/phase4am-wholebrain-plastic-interface') +REGISTRY_RELATIVE = Path('registry/phase4am-wholebrain-plastic-interface') +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-EXACT-WHOLEBRAIN-PLASTIC-INTERFACE-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', 'protocol/preregistered.json', + 'audit/zero-complete.json', 'audit/static25-complete.json') +REFERENCE_EVIDENCE = 'regression/frozen-five.json' +GATE_FIELDS = ('zero_overlay_exact', 'static25_repeat_exact', 'old_integrity_pass', + 'frozen_five_reference_pass', 'frozen_eligibility_and_mask_unchanged', 'base_weights_unchanged') +COUNT_FIELDS = ('primary_trials_per_stage', 'repeats_per_stage') +COHORTS = ('seed_validation', 'novel_to_aj') +MODES = ('physiological', 'matched_energy') +STAGES = ('zero', 'static25') +POPULATIONS = ('KC', 'MBON', 'mask_recipient_MBON', 'DAN', 'MBON_downstream', 'descending', 'motor') +REFERENCE_NAMES = ('auditory-10hz', 'auditory-100hz', 'olfactory-50hz', + 'mechanosensory-50hz', 'gustatory-50hz') +EXPECTED_CONFIG = dict(phase='4AM', + purpose='Exact D18 trial-boundary plastic-overlay interface and closed-loop transfer gate', + neurons=166700, edges=25582938, candidate_edges=14232, primary_trials=120, technical_repeats=24, + steps=1000, dt_ms=.1, apl_delay_steps=18, stages=list(STAGES), max_fractional_depression=.25, + virtual_gate_tick=900, gpu_uuid='GPU-79f3a85d-adce-7833-7003-6488140ca596', output_budget_bytes=17179869184, + training=False, candidate_generation=False, static_test_is_learning=False, + precision_bridge='base float64 SI plus separate float64(delta float32 mV) times 0.001; zero rows untouched', + future_learning='Original frozen eligibility-v2 and additive trial-boundary update; artificial scalar D remains separate from actual DAN events') +SCIENCE_SCOPE = 'Valid interface and recording; reported static response is not an associative learning PASS' + + +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('phase4am_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 _small_json(helper, experiment, rows, relative): + require(relative in rows, 'Required finalized evidence absent from seal: ' + relative) + require(rows[relative]['bytes'] <= MAX_EVIDENCE_BYTES, 'Required finalized evidence exceeds 4 MiB') + return helper._json_bytes((experiment / relative).read_bytes()) + + +def _planned_inventory(registration, config): + require(registration.get('config') == config and registration.get('training') is False and + registration.get('candidate_generated') is False and registration.get('before_new_brain_trajectories') is True, + 'Preregistration configuration/scope mismatch') + planned = registration.get('planned') + require(isinstance(planned, list) and len(planned) == 144, 'Planned inventory must contain 144 records') + primary, repeated = {}, {} + for row in planned: + require(isinstance(row, dict) and isinstance(row.get('name'), str) and row['name'] and + PurePosixPath(row['name']).name == row['name'] and row['name'] not in ('.', '..') and + not any(c in row['name'] for c in ('\\', ':', '\0', '\r', '\n')), 'Invalid planned case name') + require(row.get('cohort') in COHORTS and row.get('mode') in MODES and type(row.get('seed')) is int and + isinstance(row.get('odor_id'), str) and row['odor_id'] and type(row.get('repeat')) is int and + row['repeat'] in (0, 1), 'Invalid planned cohort/mode/seed/repeat') + target = primary if row['repeat'] == 0 else repeated + require(row['name'] not in target, 'Duplicate planned case/repeat') + target[row['name']] = row + require(len(primary) == 120 and len(repeated) == 24, 'Planned primary/repeat coverage mismatch') + seeds = {row['seed'] for row in primary.values()} + require(len(seeds) == 5, 'Planned inventory requires five seeds') + identities = {(r['cohort'], r['mode'], r['odor_id'], r['seed']) for r in primary.values()} + require(len(identities) == 120, 'Duplicate planned scientific identity') + for cohort in COHORTS: + odors_by_mode = [] + for mode in MODES: + block = [r for r in primary.values() if r['cohort'] == cohort and r['mode'] == mode] + odors = {r['odor_id'] for r in block} + require(len(block) == 30 and len(odors) == 6 and + {(r['odor_id'], r['seed']) for r in block} == {(o, s) for o in odors for s in seeds}, + 'Incomplete planned cohort-mode inventory') + odors_by_mode.append(odors) + require(odors_by_mode[0] == odors_by_mode[1], 'Modes use different odor identities') + require(len({r['odor_id'] for r in primary.values()}) == 12, 'Cohorts must retain twelve distinct frozen odors') + expected_repeats = {name for name, r in primary.items() if r['seed'] == min(seeds)} + require(set(repeated) == expected_repeats and all(repeated[name] == dict(primary[name], repeat=1) + for name in repeated), 'Repeats do not match the complete first-seed inventory') + return planned, primary + + +def _stage_coverage(helper, experiment, rows, stage, planned): + receipt = _small_json(helper, experiment, rows, 'audit/' + stage + '-complete.json') + require(receipt.get('stage') == stage and receipt.get('pass_all') is True and receipt.get('training') is False and + all(type(receipt.get(k)) is int and receipt[k] == v for k, v in + (('trials', 144), ('primary_trials', 120), ('technical_repeats', 24))), 'Incomplete stage gate receipt: ' + stage) + completed = receipt.get('completed') + require(isinstance(completed, list) and len(completed) == 144, 'Stage receipt lacks 144 completed records') + project = experiment.parents[1] + for plan, entry in zip(planned, completed): + require(isinstance(entry, dict) and set(entry) == {'name', 'repeat', 'output_hashes_sha256', 'comparison_sha256'} + and entry['name'] == plan['name'] and type(entry['repeat']) is int and entry['repeat'] == plan['repeat'], + 'Stage receipt inventory order/identity mismatch') + prefix = 'gpu/' + stage + '/' + plan['name'] + '-r' + str(plan['repeat']) + '/' + for filename, key in (('output-hashes.json', 'output_hashes_sha256'), ('comparison.json', 'comparison_sha256')): + require(prefix + filename in rows and rows[prefix + filename]['sha256'] == entry[key], + 'Stage receipt does not bind sealed output evidence: ' + prefix + filename) + report = _small_json(helper, experiment, rows, prefix + 'comparison.json') + mode = 'zero' if stage == 'zero' else ('repeat' if plan['repeat'] else 'self') + folder = experiment / prefix.rstrip('/') + case = project / 'experiments/phase4ak-apl-timing-validation/cases' / plan['cohort'] / plan['name'] + left = (project / 'experiments/phase4ak-apl-timing-validation/gpu' / plan['cohort'] / + (plan['name'] + '-r' + str(plan['repeat'])) if stage == 'zero' else + (experiment / 'gpu' / stage / (plan['name'] + '-r0') if plan['repeat'] else folder)) + require(report.get('pass_all') is True and report.get('overlay_name') == stage and report.get('mode') == mode and + report.get('case_dir') == str(case) and report.get('left') == str(left) and report.get('right') == str(folder), + 'Stage comparison evidence has wrong case/stage/repeat identity') + inventory = _small_json(helper, experiment, rows, prefix + 'output-hashes.json') + require(isinstance(inventory, list) and inventory, 'Empty trial output inventory') + expected = {name[len(prefix):]: {**r, 'path': name[len(prefix):]} for name, r in rows.items() + if name.startswith(prefix) and name != prefix + 'output-hashes.json'} + actual = {} + for item in inventory: + require(isinstance(item, dict) and set(item) == {'path', 'bytes', 'sha256'} and + item['path'] not in actual, 'Invalid/duplicate trial output inventory') + actual[item['path']] = item + require(actual == expected, 'Trial output inventory contradicts complete experiment seal') + return dict(pass_all=True, trials=144, primary_trials=120, technical_repeats=24, + receipt_sha256=rows['audit/' + stage + '-complete.json']['sha256']) + + +def _status_evidence(helper, experiment, rows, model): + """Verify declarations and their sealed coverage, never recompute science.""" + evidence = {name: _small_json(helper, experiment, rows, name) for name in REQUIRED_EVIDENCE} + status = evidence['audit/final-status.json'] + science = evidence['audit/scientific-summary.json'] + integrity = evidence['regression/old-integrity-after.json'] + config = helper._json_bytes((model / 'config.json').read_bytes()) + require(isinstance(config, dict) and set(config) == set(EXPECTED_CONFIG) and all( + type(config[k]) is type(v) and config[k] == v for k, v in EXPECTED_CONFIG.items()), + 'Changed Phase 4AM configuration/design contract') + require(isinstance(status, dict) and status.get('status') in FINAL_STATUSES, 'Unrecognized Phase 4AM final status') + require(all(status.get(key) is True for key in GATE_FIELDS), 'Declared PASS contradicts finalized gate flags') + require(type(status.get('primary_trials_per_stage')) is int and status['primary_trials_per_stage'] == 120 and + type(status.get('repeats_per_stage')) is int and status['repeats_per_stage'] == 24, 'Invalid finalized coverage') + require(status.get('training') is False and status.get('learned_candidate') is False, 'Unexpected finalized scope claim') + for record in (status, science): + require(isinstance(record, dict) and all(record.get(k, False) is False for k in + ('learning_achieved', 'candidate_generated', 'conditioning_executed', 'full_scientific_goal_achieved')), + 'Unexpected learning/candidate scope claim') + require(status.get('scientific_summary_sha256') == rows['audit/scientific-summary.json']['sha256'], + 'Final status scientific-summary SHA mismatch') + require(isinstance(science, dict) and science.get('status') == status['status'] and + science.get('zero_overlay_exact') is True and science.get('static25_repeat_exact') is True and + science.get('training') is False and science.get('learned_candidate') is False and + science.get('conditional_AL_not_a_nonzero_arithmetic_oracle') is True and science.get('scope') == SCIENCE_SCOPE, + 'Scientific summary scope/status contradiction') + require(type(science.get('primary_trials_per_stage')) is int and science['primary_trials_per_stage'] == 120 and + type(science.get('technical_repeats_per_stage')) is int and science['technical_repeats_per_stage'] == 24, + 'Scientific summary coverage mismatch') + require('summaries/per-MBON-static-effects.parquet' in rows and science.get('per_MBON_sha256') == + rows['summaries/per-MBON-static-effects.parquet']['sha256'], 'Scientific per-MBON payload SHA mismatch') + require(isinstance(integrity, dict) and integrity and all(isinstance(r, dict) and r.get('pass') is True + for r in integrity.values()), 'Final status contradicts its frozen-integrity report') + reference = _small_json(helper, experiment, rows, REFERENCE_EVIDENCE) + require(isinstance(reference, dict), 'Invalid frozen reference report') + trials = reference.get('trials') + require(reference.get('pass_all') is True and isinstance(trials, list) and + [r.get('trial') for r in trials if isinstance(r, dict)] == list(REFERENCE_NAMES) and len(trials) == 5 and + all(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 trials), + 'Declared frozen-five PASS requires five exact trial records with the original ordered names') + blocks = science.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 + isinstance(block.get('populations'), dict) and set(block['populations']) == set(POPULATIONS), + 'Incomplete cohort-mode population block') + for metrics in block['populations'].values(): + require(isinstance(metrics, dict) and set(metrics) == {'trials_event_change', 'trials_count_change', + 'mean_count_l1', 'mean_recruited_cells', 'mean_lost_cells'}, 'Invalid population metric fields') + for key in ('trials_event_change', 'trials_count_change'): + require(type(metrics[key]) is int and 0 <= metrics[key] <= 30, 'Invalid diagnostic count') + for key in ('mean_count_l1', 'mean_recruited_cells', 'mean_lost_cells'): + require(type(metrics[key]) in (int, float) and math.isfinite(metrics[key]) and metrics[key] >= 0, + 'Nonfinite/negative population metric') + require(metrics['trials_count_change'] <= metrics['trials_event_change'], 'Count change without event change') + # Zero effects remain publishable: this is not an effect-size gate. + planned, primary = _planned_inventory(evidence['protocol/preregistered.json'], config) + timing = science.get('timing') + require(isinstance(timing, list) and len(timing) == 240 and all(isinstance(r, dict) for r in timing) and + {(r.get('stage'), r.get('case')) for r in timing} == {(s, n) for s in STAGES for n in primary}, + 'Scientific timing inventory lacks all 240 primary runs') + for item in timing: + require(all(type(item.get(k)) in (int, float) and math.isfinite(item[k]) and item[k] >= 0 + for k in ('wall_seconds', 'simulation_seconds')), 'Invalid diagnostic timing value') + stages = {stage: _stage_coverage(helper, experiment, rows, stage, planned) for stage in STAGES} + return status, reference, integrity, stages + + +def publish(root=ROOT, helper_path=None): + """Publish the fixed AM 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, stages = _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='Exact zero-overlay D18 identity and fixed whole-brain static25 interface; no training or associative learning', + declared_stage_coverage=stages, declared_scientific_summary_scope=SCIENCE_SCOPE, + static_effect_size_gate_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/phase4am-publication/test_fetch_phase4am.py b/tools/phase4am-publication/test_fetch_phase4am.py new file mode 100644 index 0000000..120ee4b --- /dev/null +++ b/tools/phase4am-publication/test_fetch_phase4am.py @@ -0,0 +1,245 @@ +"""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_phase4am 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-AM-EVIDENCE', zero_overlay_exact=False, + primary_trials_per_stage=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}}), + 'audit/scientific-summary.json': data({'synthetic_scope': 'not scientific output'}), + 'protocol/preregistered.json': data({'synthetic_only': True}), + 'audit/zero-complete.json': data({'pass_all': False, 'synthetic_only': True}), + 'audit/static25-complete.json': data({'pass_all': False, 'synthetic_only': True}), + 'regression/frozen-five.json': data({'pass_all': False, 'trials': []}), + '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={'zero_overlay_exact': False}, + declared_audit_counts={'primary_trials_per_stage': 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='phase4am-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-AM-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/phase4am-publication/test_publish_phase4am.py b/tools/phase4am-publication/test_publish_phase4am.py new file mode 100644 index 0000000..81eda97 --- /dev/null +++ b/tools/phase4am-publication/test_publish_phase4am.py @@ -0,0 +1,411 @@ +"""Temporary synthetic seals only; never publish/register any real evidence.""" +import hashlib +import copy +import json +from pathlib import Path +import tempfile +import unittest +from unittest import mock + +import publish_phase4am 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='phase4am-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 = copy.deepcopy(publication.EXPECTED_CONFIG) + write(self.model / 'config.json', self.config) + self.planned = [] + for cohort in publication.COHORTS: + for mode in publication.MODES: + for odor in range(6): + for seed in range(11, 16): + name = f'{cohort}-{mode}-odor{odor}-seed{seed}' + for repeat in ((0, 1) if seed == 11 else (0,)): + self.planned.append(dict(name=name, cohort=cohort, mode=mode, + odor_id=f'{cohort}-odor{odor}', seed=seed, repeat=repeat)) + self.registration = dict(config=self.config, planned=self.planned, training=False, + candidate_generated=False, before_new_brain_trajectories=True) + write(self.experiment / 'protocol/preregistered.json', self.registration) + for stage in publication.STAGES: + completed = [] + for row in self.planned: + key = row['name'] + '-r' + str(row['repeat']) + folder = self.experiment / 'gpu' / stage / key + case = self.root / 'experiments/phase4ak-apl-timing-validation/cases' / row['cohort'] / row['name'] + mode = 'zero' if stage == 'zero' else ('repeat' if row['repeat'] else 'self') + left = (self.root / 'experiments/phase4ak-apl-timing-validation/gpu' / row['cohort'] / key + if stage == 'zero' else (self.experiment / 'gpu' / stage / (row['name'] + '-r0') + if row['repeat'] else folder)) + write(folder / 'comparison.json', dict(pass_all=True, overlay_name=stage, mode=mode, + case_dir=str(case), left=str(left), right=str(folder))) + item = folder / 'comparison.json' + write(folder / 'output-hashes.json', [dict(path=item.name, bytes=item.stat().st_size, sha256=sha(item))]) + completed.append(dict(name=row['name'], repeat=row['repeat'], + output_hashes_sha256=sha(folder / 'output-hashes.json'), comparison_sha256=sha(item))) + write(self.experiment / 'audit' / (stage + '-complete.json'), dict(stage=stage, pass_all=True, + trials=144, primary_trials=120, technical_repeats=24, completed=completed, training=False)) + table = self.experiment / 'summaries/per-MBON-static-effects.parquet' + table.parent.mkdir(parents=True) + table.write_bytes(b'synthetic table placeholder, never parsed as science') + self.science = dict(status=publication.FINAL_STATUS, primary_trials_per_stage=120, + technical_repeats_per_stage=24, zero_overlay_exact=True, static25_repeat_exact=True, + training=False, learned_candidate=False, conditional_AL_not_a_nonzero_arithmetic_oracle=True, + scope=publication.SCIENCE_SCOPE, per_MBON_sha256=sha(table), + timing=[dict(stage=s, case=r['name'], wall_seconds=.01, simulation_seconds=.005) + for s in publication.STAGES for r in self.planned if r['repeat'] == 0], + blocks={c + '/' + m: dict(trials=30, populations={p: dict(trials_event_change=0, + trials_count_change=0, mean_count_l1=0., mean_recruited_cells=0., mean_lost_cells=0.) + for p in publication.POPULATIONS}) 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, primary_trials_per_stage=120, repeats_per_stage=24, + zero_overlay_exact=True, static25_repeat_exact=True, old_integrity_pass=True, + frozen_five_reference_pass=True, frozen_eligibility_and_mask_unchanged=True, base_weights_unchanged=True, + training=False, learned_candidate=False, + 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=name, exact={k: True for k in ('step', 'neuron_idx', 'counts', 'v', 'g')}) + for name in publication.REFERENCE_NAMES])) + 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 check_declarations(self): + seal(self.experiment) + rows = {r['path']: r for r in json.loads((self.experiment / 'manifest.json').read_text())['files']} + return publication._status_evidence(publication.load_helpers(HELPER), self.experiment, rows, self.model) + + def write_science(self, science): + write(self.experiment / 'audit/scientific-summary.json', science) + write(self.experiment / 'audit/final-status.json', dict(self.status, + scientific_summary_sha256=sha(self.experiment / 'audit/scientific-summary.json'))) + + def test_stage_receipts_require_both_full_144_inventories(self): + for stage in publication.STAGES: + path = self.experiment / 'audit' / (stage + '-complete.json') + original = json.loads(path.read_text()) + for change in ({'trials': 143}, {'primary_trials': 119}, {'technical_repeats': 23}, + {'completed': original['completed'][:-1]}, {'pass_all': False}, {'stage': 'other'}): + with self.subTest(stage=stage, change=list(change)): + write(path, dict(original, **change)) + with self.assertRaises(ValueError): + self.check_declarations() + write(path, original) + + def test_stage_receipt_hash_and_order_cannot_hide_wrong_case(self): + path = self.experiment / 'audit/static25-complete.json' + original = json.loads(path.read_text()) + for bad in ('hash', 'duplicate', 'reorder'): + receipt = copy.deepcopy(original) + if bad == 'hash': + receipt['completed'][0]['comparison_sha256'] = '0' * 64 + elif bad == 'duplicate': + receipt['completed'][1] = copy.deepcopy(receipt['completed'][0]) + else: + receipt['completed'][0], receipt['completed'][1] = receipt['completed'][1], receipt['completed'][0] + with self.subTest(bad=bad): + write(path, receipt) + with self.assertRaises(ValueError): + self.check_declarations() + + def test_reanchored_comparison_cannot_change_stage_case_or_repeat_mode(self): + stage_path = self.experiment / 'audit/static25-complete.json' + original_stage = json.loads(stage_path.read_text()) + plan = self.planned[0] + folder = self.experiment / 'gpu/static25' / (plan['name'] + '-r0') + comparison = folder / 'comparison.json' + inventory = folder / 'output-hashes.json' + original_report = json.loads(comparison.read_text()) + for key, value in (('mode', 'repeat'), ('overlay_name', 'zero'), ('case_dir', '/wrong-case'), + ('left', '/wrong-reference'), ('right', '/wrong-output')): + with self.subTest(key=key): + write(comparison, dict(original_report, **{key: value})) + write(inventory, [dict(path=comparison.name, bytes=comparison.stat().st_size, sha256=sha(comparison))]) + receipt = copy.deepcopy(original_stage) + receipt['completed'][0].update(comparison_sha256=sha(comparison), output_hashes_sha256=sha(inventory)) + write(stage_path, receipt) + with self.assertRaisesRegex(ValueError, 'wrong case/stage/repeat identity'): + self.check_declarations() + + def test_preregistered_scientific_coverage_and_first_seed_repeats_required(self): + for mode in ('missing', 'duplicate', 'wrong_repeat_seed', 'training'): + reg = copy.deepcopy(self.registration) + if mode == 'missing': + reg['planned'].pop() + elif mode == 'duplicate': + reg['planned'][-1] = copy.deepcopy(reg['planned'][0]) + elif mode == 'wrong_repeat_seed': + next(r for r in reg['planned'] if r['repeat'] == 1)['seed'] += 1 + else: + reg['training'] = True + with self.subTest(mode=mode): + write(self.experiment / 'protocol/preregistered.json', reg) + with self.assertRaises(ValueError): + self.check_declarations() + + def test_scientific_population_metrics_and_explicit_scopes_required(self): + for defect in ('missing_population', 'nonfinite', 'negative', 'bool_count', 'more_than30', + 'count_without_event', 'AL_oracle_claim', 'learning', 'timing_missing', 'table_hash'): + science = copy.deepcopy(self.science) + pops = science['blocks'][next(iter(science['blocks']))]['populations'] + if defect == 'missing_population': + pops.pop('motor') + elif defect in ('nonfinite', 'negative'): + pops['KC']['mean_count_l1'] = float('nan') if defect == 'nonfinite' else -1. + elif defect in ('bool_count', 'more_than30'): + pops['KC']['trials_event_change'] = True if defect == 'bool_count' else 31 + elif defect == 'count_without_event': + pops['KC']['trials_count_change'] = 1 + elif defect == 'AL_oracle_claim': + science['conditional_AL_not_a_nonzero_arithmetic_oracle'] = False + elif defect == 'learning': + science['learning_achieved'] = True + elif defect == 'timing_missing': + science['timing'].pop() + else: + science['per_MBON_sha256'] = '0' * 64 + with self.subTest(defect=defect): + self.write_science(science) + with self.assertRaises(ValueError): + self.check_declarations() + + def test_five_refs_require_original_names_and_nonempty_exact_keys(self): + path = self.experiment / 'regression/frozen-five.json' + original = json.loads(path.read_text()) + for defect in ('duplicate_name', 'unknown_name', 'empty_exact', 'missing_exact', 'non_bool'): + refs = copy.deepcopy(original) + if defect == 'duplicate_name': + refs['trials'][1]['trial'] = refs['trials'][0]['trial'] + elif defect == 'unknown_name': + refs['trials'][0]['trial'] = 'invented-reference' + elif defect == 'empty_exact': + refs['trials'][0]['exact'] = {} + elif defect == 'missing_exact': + refs['trials'][0]['exact'].pop('g') + else: + refs['trials'][0]['exact']['g'] = 1 + with self.subTest(defect=defect): + write(path, refs) + with self.assertRaises(ValueError): + self.check_declarations() + + 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['static_effect_size_gate_defined']) + self.assertEqual(set(receipt['declared_stage_coverage']), {'zero', 'static25'}) + self.assertEqual(receipt['declared_audit_counts'], {'primary_trials_per_stage': 120, 'repeats_per_stage': 24}) + 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), + ('max_fractional_depression', .5), ('training', True), ('virtual_gate_tick', 901), + ('apl_delay_steps', 0)): + 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_per_stage': 119}, + {'repeats_per_stage': 23}, {'learned_candidate': True}, {'zero_overlay_exact': '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, + 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 4AM'): + 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, 'Required finalized evidence absent'): + 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/phase4am-publication/test_verify_git_payload.py b/tools/phase4am-publication/test_verify_git_payload.py new file mode 100644 index 0000000..eafe883 --- /dev/null +++ b/tools/phase4am-publication/test_verify_git_payload.py @@ -0,0 +1,270 @@ +"""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='phase4am-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-SYNTHETIC-AM-INTERFACE')), + '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-SYNTHETIC-AM-INTERFACE') + 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-SYNTHETIC-AM-INTERFACE') + 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-SYNTHETIC-AM-EXECUTION' + self.receipt_write(); self.git('add', '--', verifier.REGISTRY) + result = self.verify() + self.assertEqual(result['declared_audit_status'], 'INCOMPLETE-SYNTHETIC-AM-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/phase4am-publication/verify_git_payload.py b/tools/phase4am-publication/verify_git_payload.py new file mode 100644 index 0000000..84c039d --- /dev/null +++ b/tools/phase4am-publication/verify_git_payload.py @@ -0,0 +1,325 @@ +"""Verify fixed Phase 4AM 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/wholebrain-plastic-interface-v1' +EXPERIMENT = 'experiments/phase4am-wholebrain-plastic-interface' +REGISTRY = 'registry/phase4am-wholebrain-plastic-interface' +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 AM 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 AM 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 4AM 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 4AM 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()) +