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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.
