Lokad.Onnx

About

Lokad.Onnx is a 100% managed code ONNX backend implementation.

Getting started

• Clone the repo and submodules: git clone https://github.com/Lokad/Onnx.git --recurse-submodules.
• Run build.cmd from the repo root directory
• Run lonnx --help to show the available CLI commands. The basic command syntax for running an ONNX model is: lonnx run (modelpathorurl) (input) --<options> e.g lonnx run .\tests\Lokad.Onnx.Backend.Tests\models\mnist-8.onnx .\tests\Lokad.Onnx.Backend.Tests\images\mnist4.png::mnist --softmax will run the MNIST model at the path indicated using the image file indicated as input converted to the MNIST tensor shape 1x1x28x28. For language models you can say lonnx run https://huggingface.co/intfloat/multilingual-e5-small/resolve/main/onnx/model.onnx?download=true --text "me5s" "Hello world this is some text" --op-times 200 --print-input To download and run the language model from the URL indicated using the text input converted to input tensors 1x[tokennum] using the multilingual-e5-small tokenizer, printing op times and the model input.
• See the unit tests for example on how to use the library in your own .NET apps.
• The modules for using the backend from Python are here and can be imported into Python apps in the usual way.

Implementation notes

• The tensors library is pure managed C# adapted from here.
• Current NuGet dependencies for the Backend library are:
  • System.Memory
  • OnnxSharp - For parsing ONNX ProtoBuf model files and getting the computational graph structure