This project include converters and optimizers in Python3 that are used to generate and optimize ONNX models for Kneron Toolchain.

The current using onnx version is 1.7.0.

Note that the generated onnx is especially optimized for Kneron Toolchain, which may not be the best solution for general purpose ONNX usage, though in most cases, math optimal solutions are good for the toolchain. For example, the ONNX to ONNX optimizer has an option on add a do-nothing BatchNormalization node on the skip branch. This seems not optimal from the math perspective. However, for the Kneron Toolchain, adding such a layer can improve its quantization process.

• 1.7.0
• onnxruntime >= 1.10.0 (if using onnx)
• numpy >= 1.18.5
• keras == 2.2.4 (if using keras-onnx)
• tensorflow == 1.15.3 (if using tflite-onnx)
• tf2onnx == 1.8.4 (if using tflite-onnx)
• caffe == 1.0.0 (if using caffe-onnx. Recommend installing through conda install -c intel caffe=1.0.0)

The Keras to ONNX converter support convert Keras （version 2.2.4) model to onnx. For detail, please check folder keras-onnx.

Note that what we support here is Keras, not tf.Keras. tf.Keras is actually a part of Tensorflow.

The Caffe to ONNX converter support convert Caffe to ONNX. Since Caffe is an old platform which is using C++, our support for the Caffe is based on intel-caffe. We are currently using version 1.1.3. You may need to test other versions yourself. Customized operators may not be supported. Please check folder caffe-onnx.

Pytorch to onnx is achieved through the combination of the torch.onnx and our optimizer under optimizer_scripts folder. Note that you may need to specify opset to 11 while you are exporting the model using torch.onnx. Please check optimizer_scripts folder. We are currently using version 1.7.1. Other version's which has torch.onnx may also works. But versions earlier than 1.1.0 are not recommended.

Tensorflow to onnx is based on the open source project tensorflow-onnx. Our tensorflow2onnx.py use the open source project to generate the ONNX file and optimize the generated ONNX. Currently, the Tensorflow model support is pretty limited. It is still under development. Please check optimizer_scripts folder. We are currently using version 1.6.0. You can use the latest version of tensorflow-onnx. Just remember to set the onnx opset version to 11.

General optimizer optimize ONNX model for the Kneron Toolchain use. Please check optimizer_scripts folder.

Please utilize the Github merge request system.

If you have any question about the project, please contact jiyuan@kneron.us.