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name: export-and-backends description: "Routes BackgroundMattingV2 TorchScript and ONNX export workflows and backend compatibility checks." disable-model-invocation: true metadata: disco-role: operating license: MIT

export-and-backends

Use this sub-skill when the task is about converting BackgroundMattingV2 models or deciding which runtime/backend path is safe.

Typical triggers

• TorchScript export
• ONNX export
• choosing roi_align, gather, unfold, scatter_nd, or scatter_element
• checking whether a scripted or exported model still loads
• deciding how to validate an export without a real checkpoint
• comparing PyTorch, TorchScript, and ONNX Runtime behavior

Read first

• references/workflows.md for export recipes and compatibility choices.
• references/troubleshooting.md for export and runtime failures.
• scripts/check_export_support.py for the safe dummy-model smoke.
• scripts/run_export_torchscript.py and scripts/run_export_onnx.py for dry-run or execute wrappers around the checkout's exporters.

What this sub-skill owns

• TorchScript export intent and attribute-hoisting behavior
• ONNX export intent, dynamic axes, and patch-method compatibility choices
• conversion validation without checkpoints, including the onnx exporter dependency and ONNX Runtime load step
• exporter-specific failure handling and runtime compatibility notes

What it does not own

• ordinary image/video/webcam inference; use inference-and-demo
• dataset layout or training; use training

Recommended first checks

1. Run scripts/check_export_support.py to verify scripting and optional ONNX runtime loading on a tiny random model.
2. Use the dry-run wrappers if you only need the exact export command shape.
3. Only run the native export CLI with a real checkpoint when you actually need a converted artifact.

Cross-links

• ../inference-and-demo/SKILL.md
• ../training/SKILL.md
• ../../references/backend-compatibility.md