armnn | Arm NN ML Software | Machine Learning library

armnn is a C++ library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. armnn has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

Depending on what kind of framework (Tensorflow Lite, ONNX) you've been using to create your model there are multiple software tools available within Arm NN that can serve your needs. Generally, there is a parser available for each supported framework. ArmNN-Parsers are C++ libraries that you can integrate into your application to load, optimize and execute your model. Each parser allows you to run models from one framework. If you would like to run an ONNX model you can make use of the Onnx-Parser. There also is a parser available for TfLite models but the preferred way to execute TfLite models is using our TfLite-Delegate. We also provide python bindings for our parsers and the Arm NN core. We call the result PyArmNN. Therefore your application can be conveniently written in either C++ using the "original" Arm NN library or in Python using PyArmNN. You can find tutorials on how to setup and use our parsers in our doxygen documentation. The latest version can be found in the wiki section of this repository. Arm NN's software toolkit comes with the TfLite Delegate which can be integrated into TfLite. TfLite will then delegate operations, that can be accelerated with Arm NN, to Arm NN. Every other operation will still be executed with the usual TfLite runtime. This is our recommended way to accelerate TfLite models. As with our parsers there are tutorials in our doxygen documentation that can be found in the wiki section. If you would like to use Arm NN on Android you can follow this guide which explains how to build Arm NN using the AndroidNDK. But you might also want to take a look at another repository which implements a hardware abstraction layer (HAL) for Android. The repository is called Android-NN-Driver and when integrated into Android it will automatically run neural networks with Arm NN.