菜单
Investigate and fix model conversion issues in OpenVINO Frontends (ONNX, PyTorch) — triage, debugging, accuracy comparison, and pre-submission verification.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/openvinotoolkit/openvino --skill conversion-issues命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Upgrade the PyTorch version used by OpenVINO tests (torch / torchvision / torchaudio) and resolve fallout — missing operator translators, new functionalized `*_copy` aten ops, decomposition changes, FX-only tests failing in TorchScript mode, and accuracy regressions caused by stricter typing. Use when the user asks to "bump torch", "update pytorch to X.Y", "upgrade torch tests", or when pytorch_tests / model_hub pytorch tests fail after a torch version change. Do not use for: enabling a single new PyTorch operator unrelated to a version bump, GenAI / Optimum upgrades, or plugin-level numerical bugs unrelated to the frontend.
Author, edit, compile, validate, and debug any OpenVINO gh-aw agentic workflow (e.g. ci-doctor, ci-doctor-mq, and any future ones) and their shared safe-output jobs under .github/workflows/shared/agentic-workflows. Use when a user wants to create a new agentic workflow; change an existing one's prompt, triggers, tools, permissions, or safe-outputs; add or edit a shared job/step; recompile a .lock.yml; update a workflow's persisted-state JSON schemas; or test a workflow via workflow_dispatch. Do NOT use for regular (non-agentic) GitHub Actions workflows, plugin/runtime code, or diagnosing a specific live CI failure.
Write unit tests for OpenVINO ov::Model graph transformations (passes). Use when the user asks to write, add, or refactor tests for a transformation pass (MatcherPass, ModelPass), or to modernize legacy transformation tests.
基于 SOC 职业分类
正在显示 SKILL.md
| name | conversion-issues |
| description | Investigate and fix model conversion issues in OpenVINO Frontends (ONNX, PyTorch) — triage, debugging, accuracy comparison, and pre-submission verification. |
Diagnose and fix issues where models fail to convert to OpenVINO IR or produce incorrect inference results through an OpenVINO frontend.
Each frontend has its own detailed investigation workflow. Read the one matching the target framework:
| Frontend | Skill file | What it covers |
|---|---|---|
| ONNX | onnx.md | Triage (unsupported op / conversion bug / shape-type / opset gap), ORT baseline comparison, translator debugging, .prototxt test models, C++ GTest, pre-submission checklist |
| PyTorch | pytorch.md | Triage (unsupported op / tracing mode / inplace / normalize-step), TorchScript vs torch.export identification, layer test debugging, pre-submission checklist |
| Frontend | Skill file | When to use |
|---|---|---|
| ONNX | add-fe-op/onnx.md | Implementing a new ONNX op translator from scratch |
| PyTorch | add-fe-op/pytorch.md | Implementing a new PyTorch op translator from scratch |
