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name: export description: "Routes Chainer model export workflows for ONNX-Chainer and Caffe." metadata: disco-role: operating disable-model-invocation: true license: MIT

Export

Use this sub-skill when the user wants to export a Chainer model to ONNX or Caffe, generate export testcases, or debug conversion failures.

Typical requests

• "Export this model to ONNX."
• "How do I generate ONNX testcases?"
• "Why does onnx_chainer.export fail on my model?"
• "How do I export a Chainer model to Caffe?"
• "Why is chainer_model.prototxt or chainer_model.caffemodel missing?"

Read these first

• references/workflows.md for the export flow.
• references/api-reference.md for the exact export signatures and limits.
• references/troubleshooting.md for exporter-specific failure modes.

Use this script

• ../../scripts/export_smoke.py for a tiny ONNX and Caffe export check.

Include here

• onnx_chainer.export(...) and onnx_chainer.export_testcase(...)
• ONNX opset version limits and named inputs / outputs
• Caffe export via chainer.exporters.caffe.export(...)
• Export validation, file layout, and unsupported-layer debugging

Route elsewhere

• Ordinary model training or serialization -> ../training/
• MPI / distributed / multi-node export scenarios -> ../distributed/
• ChainerX-specific model behavior -> ../chainerx/

Quick mental model

A normal export workflow is:

1. Build a tiny model or load a trained model.
2. Feed a representative input.
3. Export the model to ONNX or Caffe.
4. Validate that the target files exist and the exported graph is structurally valid.

When you only need a fast check, use the bundled smoke script.