// Investigate and fix model conversion issues in OpenVINO Frontends (ONNX, PyTorch) — triage, debugging, accuracy comparison, and pre-submission verification.
Adds a core operator to the OpenVINO toolkit. Use when asked to implement a new operation into OpenVINO.
Add a new operation to the OpenVINO CPU plugin — node registration, JIT/oneDNN executors (AVX2/AVX-512/AMX), and functional tests.
Adds a new operation to OpenVINO Frontend pipelines with translator updates, registration, and tests.
Adds a new OpenVINO fusion transformation (subgraph to one or several operations) and corresponding tests.
Add a new operation to the OpenVINO GPU plugin — OpenCL kernel design, oneDNN-backed paths, sub-group/LWS tuning, and functional tests.
Analyze a HuggingFace model and attempt OpenVINO conversion — probe properties, run strategy matrix, classify failures, and produce a structured routing report.
| 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 |