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quark-onnx-autosearch-pro

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업데이트2026년 7월 9일 06:10

End-to-end Quark ONNX AutoSearchPro recipe — drives `quark.onnx.AutoSearchPro` (Optuna-based hyperparameter search) on a `.onnx` model to find the best quantization config (activation/weight spec, calibration method, CLE, AdaRound / AdaQuant, FastFinetune params). Use when the user wants to "auto search", "tune quantization", "find the best quant config", "sweep AdaRound/AdaQuant", "run AutoSearchPro / AutoSearch", "two-stage search", or pick one of the built-in presets (`ADVANCED_SEARCH`, `XINT8_SEARCH`, `A8W8_SEARCH`, `A16W8_SEARCH`) for their `.onnx` model. Not for HuggingFace / safetensors / PyTorch input models — use quark-torch-ptq instead. Not for single-shot ONNX PTQ without search — use quark-onnx-ptq.

설치

Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

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amd

amd/Quark

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소프트웨어 개발자컴퓨터 및 수학직·SOC 15-1252

SKILL.md

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name

quark-onnx-autosearch-pro

description

Read and follow the instructions in .claude/skills-impl/l3-recipes/onnx/quark-onnx-autosearch-pro/SKILL.md.

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Diagnose failed Quark ONNX installation, calibration, quantization, custom-op compilation, or export attempts. Use when the user reports an error, stack trace, invalid artifact, missing dependency, ORT execution-provider mismatch, silent CPU fallback, OOM during calibration, custom-op load failure (BFPQuantizeDequantize / MXQuantizeDequantize / Extended*), or unexpected quantization results from the ONNX flow. Trigger for "Quark ONNX error", "onnxruntime error", "quantize_static failed", "calibration crashed", "CUDAExecutionProvider not available", "ROCMExecutionProvider not available", "custom op library load failed", "model.onnx larger than 2GB", "external data not found", "AdaRound diverged", "GPTQ ONNX failed", "QuaRot failed", "NPU power-of-2 scale", any Python traceback mentioning quark.onnx / onnxruntime / onnx, or when the user pastes an error message related to Quark ONNX workflows.

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Install or verify the correct ONNX Runtime build (and the `onnx` package) for a user's accelerator backend before Quark's ONNX-to-ONNX flow. Use when the user needs ONNX Runtime set up, reports onnxruntime version conflicts, CPU vs GPU variant mix-ups (only one variant of `onnxruntime*` may be installed at a time), missing CUDA/ROCm execution providers, or when `import onnxruntime` / `import onnx` fails. Trigger for "install onnxruntime", "pip install onnxruntime", "set up onnxruntime for ROCm", "set up onnxruntime for CUDA", "onnxruntime-gpu vs onnxruntime", "onnx version mismatch", "CPU-only onnxruntime installed", "ORT providers list missing CUDAExecutionProvider/ROCMExecutionProvider", or any request to get the correct ONNX Runtime build running. Also trigger when `quark-install` reports that ONNX Runtime is missing or mismatched before proceeding with the ONNX flow.

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name

quark-onnx-autosearch-pro

description

Read and follow the instructions in .claude/skills-impl/l3-recipes/onnx/quark-onnx-autosearch-pro/SKILL.md.