/tutorials

Tutorials for using ONNX

Primary LanguageJupyter NotebookMIT LicenseMIT

ONNX Tutorials

Open Neural Network Exchange (ONNX) is an open standard format for representing machine learning models. ONNX is supported by a community of partners who have implemented it in many frameworks and tools.

Getting ONNX models

  • Choose a pre-trained ONNX model from the ONNX Model Zoo. A lot of pre-trained ONNX models are provided for common scenarios.
  • Convert models from mainstream frameworks. More tutorials are below.
Framework / tool Installation Exporting to ONNX (frontend) Importing ONNX models (backend)
Caffe apple/coremltools and onnx/onnxmltools Exporting n/a
Caffe2 part of caffe2 package Exporting Importing
Chainer chainer/onnx-chainer Exporting coming soon
Cognitive Toolkit (CNTK) built-in Exporting Importing
Apple CoreML onnx/onnx-coreml and onnx/onnxmltools Exporting Importing
Keras onnx/keras-onnx Exporting n/a
LibSVM onnx/onnxmltools Exporting n/a
LightGBM onnx/onnxmltools Exporting n/a
MATLAB onnx converter on matlab central file exchange Exporting Importing
Menoh pfnet-research/menoh n/a Importing
ML.NET built-in Exporting Importing
Apache MXNet part of mxnet package docs github Exporting Importing
PyTorch part of pytorch package Exporting, Exporting - Different ONNX Opsets, Extending support coming soon
SciKit-Learn onnx/sklearn-onnx Exporting n/a
TensorFlow onnx/onnx-tensorflow and onnx/tensorflow-onnx Exporting - ONNX-Tensorflow
Exporting - Tensorflow-ONNX
Importing [experimental]
TensorRT onnx/onnx-tensorrt n/a Importing

End-to-end tutorials

ONNX tools

Contributing

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.