134 lines
11 KiB
JavaScript
134 lines
11 KiB
JavaScript
/* ============================================================================
|
||
* ik-policy-glue.js —— 查看器接入 Transformer 策略（URL 加 ?policy=1 启用）
|
||
* ?policy=1 用 models/traj_policy.onnx
|
||
* ?policy=models/xxx.onnx 指定模型
|
||
* &ep=webgpu 改用 WebGPU 后端（默认 wasm-SIMD 多线程）
|
||
* &threads=N wasm 线程数（默认 min(16, ⌊0.6×逻辑核⌋)；2026-10-18 R4 实测 28 核机 16 最优、24 反而变慢、4 线程 P99 37 ms）
|
||
* &proxy=0 关闭推理代理 Worker（默认开：wasm 推理不占主线程，见下）
|
||
* &probe=1 允许加载 --random 导出的延迟探针模型（默认拒绝，防把随机策略当真模型跑）
|
||
* &autotest=N 自动跑 N 道贴立柱题（与 tests/policy_bench.cjs 同种子同题），结果 POST 到 &report=（默认 /r4/result）；
|
||
* 由 python -m ml.eval.r4_probe --viewer 驱动，测部署形态的整次规划耗时与节拍（方案 R9）
|
||
* 2026-10-18 第五轮：ort.env.wasm.proxy=true 把 wasm 推理挪到 ort 自带的 Worker。此前推理在主线程同步算，
|
||
* R4 实测时 CDP 15 s 拿不到执行槽，50 Hz tick 也被它拖住——丢步不只来自推理时长本身。
|
||
* 目标变化（松手求解 / 实时追踪）都交给 ArmPolicy.Runner：50 Hz 执行时钟放在 Web Worker（不受 rAF 60 Hz 与后台节流影响），
|
||
* 每 3 步推理一次，安全层认证后才执行；ik-glue 的逐帧碰撞守卫不参与（策略执行不走 animTo），由 Runner 安全层保证。
|
||
* onnxruntime-web 默认从 jsDelivr 加载；离线部署把 ort.min.js 与 *.wasm 放到 vendor/ort/ 并加 &ortLocal=1。
|
||
* 多线程 wasm 需要页面跨源隔离（COOP/COEP 头，见 ml/README.md）；没有时自动退回单线程。
|
||
* ==========================================================================*/
|
||
(function () {
|
||
'use strict';
|
||
const qs = new URLSearchParams(location.search);
|
||
if (!qs.has('policy')) return;
|
||
const MODEL = qs.get('policy') && qs.get('policy') !== '1' ? qs.get('policy') : 'models/traj_policy.onnx';
|
||
/* 2026-10-18 第六轮（审查 A-3）：本地路径必须是绝对 URL——ORT 用 import() 加载 .mjs，相对前缀 'vendor/ort/' 会被当成裸模块名而失败 */
|
||
const ORT_BASE = qs.get('ortLocal') === '1' ? new URL('vendor/ort/', location.href).href : 'https://cdn.jsdelivr.net/npm/onnxruntime-web@1.20.1/dist/';
|
||
/* WebGPU 后端只在 ort.webgpu.min.js 里（ort.min.js 只有 wasm，第六轮实测 "[webgpu] backend not found" 即此因） */
|
||
const ORT_JS = qs.get('ep') === 'webgpu' ? 'ort.webgpu.min.js' : 'ort.min.js';
|
||
const badge = () => document.getElementById('ikBadge');
|
||
const say = (t, cls) => { const b = badge(); if (b) { b.textContent = t; b.className = 'badge ' + (cls || 'wait'); } console.log('[policy]', t); };
|
||
let ready = false, runner = null, running = false, worker = null;
|
||
window.__POLICY = { active: () => ready, setGoal: () => false, stats: () => runner && runner.stats };
|
||
|
||
function loadScript(src) { return new Promise((res, rej) => { const s = document.createElement('script'); s.src = src; s.onload = res; s.onerror = () => rej(new Error('load ' + src)); document.head.appendChild(s); }); }
|
||
async function waitIK() { for (let i = 0; i < 200 && !(window.IK && window.IK.solver && window.ArmPolicy); i++) await new Promise(r => setTimeout(r, 50)); if (!window.IK) throw new Error('IK 未就绪'); }
|
||
|
||
async function boot() {
|
||
try {
|
||
await waitIK();
|
||
const S = window.IK.solver;
|
||
const meta = await (await fetch(MODEL.replace('.onnx', '.meta.json'))).json();
|
||
if (meta.fp !== S.modelFingerprint()) throw new Error('模型碰撞指纹 ' + meta.fp + ' ≠ 当前 ' + S.modelFingerprint() + '：collide.json 已变，须重训');
|
||
if (meta.feat_ver !== ArmPolicy.FEAT_VER) throw new Error('特征版本不符：模型 ' + meta.feat_ver + ' / 运行时 ' + ArmPolicy.FEAT_VER);
|
||
if (meta.tcp0 && meta.tcp0.some((v, i) => Math.abs(v - S.TCP0[i]) > 0.01)) throw new Error('TCP 与训练时不同：' + S.TCP0 + ' vs ' + meta.tcp0);
|
||
const probe = !!meta.random_init;
|
||
if (probe && qs.get('probe') !== '1') throw new Error('这是随机初始化的延迟探针模型（meta.random_init），不是训练产物；仅测延迟时加 &probe=1');
|
||
if (!window.ort) await loadScript(ORT_BASE + ORT_JS);
|
||
ort.env.wasm.wasmPaths = ORT_BASE;
|
||
const hc = navigator.hardwareConcurrency || 1;
|
||
ort.env.wasm.numThreads = !self.crossOriginIsolated ? 1 : (+qs.get('threads') || Math.max(1, Math.min(16, Math.floor(hc * 0.6))));
|
||
const ep = qs.get('ep') === 'webgpu' ? ['webgpu', 'wasm'] : ['wasm'];
|
||
let sess = null, proxy = ep[0] === 'wasm' && qs.get('proxy') !== '0'; // proxy 只支持 wasm EP
|
||
if (proxy) {
|
||
ort.env.wasm.proxy = true;
|
||
try { sess = await ort.InferenceSession.create(MODEL, { executionProviders: ep, graphOptimizationLevel: 'all' }); }
|
||
catch (e) { console.warn('[policy] 代理 Worker 不可用，退回主线程推理：', e); proxy = false; ort.env.wasm.proxy = false; sess = null; }
|
||
}
|
||
if (!sess) sess = await ort.InferenceSession.create(MODEL, { executionProviders: ep, graphOptimizationLevel: 'all' });
|
||
const infer = ArmPolicy.ortInfer(ort, sess, { encOnce: !!meta.enc_once, featDyn: !!meta.feat_dyn });
|
||
runner = new ArmPolicy.Runner(S, infer, {});
|
||
/* 预热：首次推理有编译开销 */
|
||
await infer(new Float32Array(8 * ArmPolicy.F_DIM), new Float32Array(8 * ArmPolicy.H * 6), 8);
|
||
const tick = URL.createObjectURL(new Blob(['let h=null;onmessage=e=>{clearInterval(h);if(e.data>0)h=setInterval(()=>postMessage(0),e.data)}'], { type: 'text/javascript' }));
|
||
worker = new Worker(tick);
|
||
worker.onmessage = onTick;
|
||
window.__POLICY = {
|
||
active: () => ready,
|
||
setGoal: (T, R, tool) => {
|
||
if (tool) { say('策略模式暂不支持工具偏移 ≠ 0，已交回规划器', 'badb'); return false; }
|
||
if (!running || !runner.q) runner.reset(window.IK.curQ());
|
||
runner.setGoal(T, R); start(); return true;
|
||
},
|
||
stop, stats: () => runner.stats, runner: () => runner,
|
||
latency: () => { const p = (a, x) => { const s = a.slice().sort((u, v) => u - v); return s.length ? s[Math.min(s.length - 1, Math.floor(s.length * x))] : null; };
|
||
const st = runner.stats;
|
||
return { inferP50: p(st.inferMs, .5), inferP99: p(st.inferMs, .99), safetyP50: p(st.safetyMs, .5), safetyP99: p(st.safetyMs, .99),
|
||
lookaheadP99: p(st.lookaheadMs, .99), planP50: p(st.planMs, .5), planP99: p(st.planMs, .99), planWarmP99: p(st.planWarmMs, .99), planColdP99: p(st.planColdMs, .99), coldPlans: st.planColdMs.length, certQP99: p(st.certQ, .99),
|
||
tickGapP99: p(TICKS.gaps, .99), tickGapMax: TICKS.gaps.length ? Math.max(...TICKS.gaps) : null, starve: TICKS.starve, ticks: TICKS.n,
|
||
threads: ort.env.wasm.numThreads, ep: ep[0], proxy, encOnce: !!meta.enc_once, featDyn: !!meta.feat_dyn, probe }; }
|
||
};
|
||
ready = true;
|
||
const how = ep[0] + '，' + ort.env.wasm.numThreads + ' 线程' + (proxy ? '，推理在 Worker' : '，推理在主线程');
|
||
if (probe) say('随机探针模型（仅测延迟，动作无意义）：' + how, 'badb');
|
||
else say('策略模式就绪（' + how + '）：拖动目标即由策略执行', 'ok');
|
||
if (qs.get('autotest')) autotest(+qs.get('autotest') || 30, meta);
|
||
} catch (e) { say('策略模式不可用：' + e.message, 'badb'); console.error(e); }
|
||
}
|
||
/* 节拍统计（R9）：tick 间隔、饥饿次数（执行时钟到了但队列为空、又没到达 = 实际丢步） */
|
||
const TICKS = { gaps: [], last: 0, starve: 0, n: 0 };
|
||
/* autotest：同一批贴立柱题（PolicyCases.ncCases，与 Node bench 同种子 20261017）逐题跑，每题限时 10 s，结果 POST 回驱动方 */
|
||
async function autotest(N, meta) {
|
||
const S = window.IK.solver;
|
||
if (!window.PolicyCases) await loadScript(new URL('js/policy-cases.js', location.href).href);
|
||
const cases = PolicyCases.ncCases(S, N, 20261017), per = [];
|
||
const t0 = performance.now();
|
||
for (let i = 0; i < cases.length; i++) {
|
||
const c = cases[i]; stop(); await new Promise(r => setTimeout(r, 50));
|
||
window.IK.setJoints(c.q0, false); runner.reset(c.q0); runner.setGoal(c.T, null);
|
||
const s0 = { plans: runner.stats.plans, brakes: runner.stats.brakes }, ts = performance.now(); let col = 0;
|
||
TICKS.last = 0; start();
|
||
while (running && performance.now() - ts < 10000) {
|
||
await new Promise(r => setTimeout(r, 100));
|
||
if (runner.q && !S.collideFree(runner.q)) col++;
|
||
}
|
||
stop();
|
||
const { e } = runner.err(runner.q);
|
||
per.push({ i, reached: runner.done && e < 1, err: +e.toFixed(1), colSamples: col, plans: runner.stats.plans - s0.plans, brakes: runner.stats.brakes - s0.brakes, s: +((performance.now() - ts) / 1000).toFixed(2) });
|
||
}
|
||
const lat = window.__POLICY.latency();
|
||
const res = { kind: 'viewer_autotest', model: MODEL, probe: !!meta.random_init, n: cases.length, reached: per.filter(x => x.reached).length,
|
||
collisionTasks: per.filter(x => x.colSamples).length, brakes: runner.stats.brakes, plans: runner.stats.plans, certMemoHits: runner.stats.certHit,
|
||
certFailWhy: runner.stats.certWhy, wallS: +((performance.now() - t0) / 1000).toFixed(1), coi: self.crossOriginIsolated, ua: navigator.userAgent, ...lat, per };
|
||
say('autotest 完成：到达 ' + res.reached + '/' + res.n + '，整次规划 P99 ' + res.planP99 + ' ms', 'ok');
|
||
try { await fetch(qs.get('report') || '/r4/result', { method: 'POST', body: JSON.stringify(res) }); } catch (e) { console.warn(e); }
|
||
window.__POLICY.autotest = res;
|
||
}
|
||
function start() { if (running) return; running = true; worker.postMessage(ArmPolicy.DT * 1000); }
|
||
function stop() { running = false; if (worker) worker.postMessage(0); }
|
||
function onTick() {
|
||
if (!running) return;
|
||
const tn = performance.now(); if (TICKS.last) TICKS.gaps.push(tn - TICKS.last); TICKS.last = tn; TICKS.n++;
|
||
if (TICKS.gaps.length > 20000) TICKS.gaps.splice(0, 10000);
|
||
/* 第八轮：冷启动（静止起步、首次规划含前瞻）时队列本就为空、机械臂没在动，不算丢步；只统计运动中断粮 */
|
||
if (!runner.queue.length && !runner.done && runner.goal && !runner.cold) TICKS.starve++;
|
||
if (runner.needPlan()) runner.plan().catch(e => { console.error(e); stop(); say('策略推理出错：' + e.message, 'badb'); });
|
||
const q = runner.tick();
|
||
if (q) window.IK.setJoints(q, false);
|
||
if (runner.done && !runner.queue.length) {
|
||
stop();
|
||
const { e, oe } = runner.err(runner.q);
|
||
say('策略到达 · 误差 ' + e.toFixed(2) + ' mm' + (runner.goal.R ? ' / ' + oe.toFixed(2) + '°' : '') + ' · 刹停 ' + runner.stats.brakes + ' 次', 'ok');
|
||
} else if (runner.brakeRun >= 2) say('策略：安全层连续拦截，减速重规划中…', 'wait');
|
||
}
|
||
boot();
|
||
})();
|