ONNX tutorials
| Framework / tool | Installation | Exporting to ONNX (frontend) | Importing ONNX models (backend) |
|---|---|---|---|
| Caffe2 | onnx/onnx-caffe2 | Exporting | Importing |
| PyTorch | part of pytorch package | Exporting, Extending support | coming soon |
| CNTK | part of CNTK | Exporting | Importing |
| Apache MXNet | onnx/onnx-mxnet | coming soon | Importing [experimental] |
| TensorFlow | onnx/onnx-tensorflow | coming soon | Importing [experimental] |
| Apple CoreML | onnx/onnx-coreml | coming soon | Importing |
- Converting SuperResolution model from PyTorch to Caffe2 and deploying on mobile device
- Transferring SqueezeNet from PyTorch to Caffe2 and to Android app
- Verifying correctness and comparing performance
- Visualizing an ONNX model (useful for debugging)
- Example of operating on ONNX protobuf
We welcome improvements to the convertor tools and contributions of new ONNX bindings. Check out contributor guide to get started.
Use ONNX for something cool? Send the tutorial to this repo by submitting a PR.