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Use after cpu-model-wiring to prove the CPU-enabled model is numerically correct. ORDERING (critical): on UNOPTIMIZED code do NOT gate correctness on full-model generation or a task harness (too slow — watchdog); the feasible correctness gate is the per-layer fingerprint parity vs the GPU/HF baseline on ONE short prefill. CONFIG LADDER (do not mistake the proxy for the gate): a TINY arch-faithful config is the BRING-UP proxy (op-TYPE coverage) ONLY — the AUTHORITATIVE correctness gate is FULL-MODEL DUMMY parity (ALL layers at REAL shapes, deterministic-dummy weights so NO real-weight load, MULTI-GPU reference when the full model exceeds one GPU), established BEFORE optimizing and reused to regression-guard EACH optimization; REAL weights only for the dtype-bridge + task finale. Optimize AFTER correctness; regression-guard with the SAME fast parity; full generation + task accuracy come LAST once fast. LAYERED checks so a failure localizes: (0) a cheap real-prompt COHERENCE smoke test first ('it ran' on random/dummy inputs is NOT 'it's correct'; catches gross zeroed/no-op/routing/layout bugs and silently-stubbed forward paths), (0.5) a per-kernel LOW-BIT PARITY gate for every dtype bridge (fp4/mxfp4/fp8/int4 weights on a bf16/fp8 kernel) — kernel output vs an independent torch dequant oracle from the same packed bytes, because 'a bf16/fp8 kernel exists' is coverage, not correctness, (1) per-layer / logits parity vs a trusted reference (HF or the GPU SGLang path) under tolerance, and (2) end-to-end task accuracy via the in-repo harnesses (gsm8k, mmlu, hellaswag) within N points. Includes a correct-by-construction ISOLATION technique to bisect MoE vs shared-path bugs. Blocks enablement on any regression; a per-layer diff pinpoints the offending op for the wiring step to fix.
accuracy-oracle 是 ChatHome Skills 收录的 技能 条目,来源为 GitHub Skill Search,质量分 58/100。 # Accuracy Oracle Correctness is the non-negotiable gate. A plausible-but-wrong model is worse than an unenabled one, so prove parity numerically AND on task, a. 作为 agent 技能,它把一组可复用的任务指令打包成 Codex 和 Claude Code 等 AI 编程 agent 可直接加载的格式,无需为该任务手写胶水代码。 该条目由 ChatHome Skills 的每日抓取从官方 registry 和 GitHub 发现查询中收录,每次运行都会重新核验仓库事实、新鲜度信号和安装元数据。 质量分综合了官方 registry 收录情况、可用安装命令、许可证完整性、仓库活跃度和 GitHub star 趋势,完整算法说明见来源页。安装命令已列于上方,可直接复制使用。 在将 accuracy-oracle 加入生产 agent 工作流前,请核对上方的最近更新日期和仓库状态——下方事实快照是最近一次抓取的时点值。
codex skill install bharat-kaul/sglang-cpu-opt运行此命令前,请先核对上游源码。
扫描范围: 安装元数据与已收录的文档正文。
基于安装元数据和有界技能正文的自动风险信号,不是完整代码安全审计,也不会递归审查源码或依赖。
# Accuracy Oracle Correctness is the non-negotiable gate. A plausible-but-wrong model is worse than an unenabled one, so prove parity numerically AND on task, and make failures loc