Rust neural-networks

Open-source Rust projects categorized as neural-networks | Edit details

Top 5 Rust neural-network Projects

  • GitHub repo tract

    Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference

    Project mention: [N] PyTorch 1.10 Release, including CUDA Graphs APIs, Frontend and compiler improvements | reddit.com/r/MachineLearning | 2021-10-21

    I like to use the setup pytorch -> onnx -> tract Tract runs efficiently on ARM single board computers.

  • GitHub repo neuronika

    Tensors and dynamic neural networks in pure Rust.

    Project mention: Enzyme: Towards state-of-the-art AutoDiff in Rust | reddit.com/r/rust | 2021-12-12

    I have a question: as the maintainer of [neuronika](https://github.com/neuronika/neuronika), a crate that offers dynamic neural network and auto-differentiation with dynamic graphs, I'm looking at a future possible feature for such framework consisting in the possibility of compiling models, getting thus rid of the "dynamic" part, which is not always needed. This would speed the inference and training times quite a bit.

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  • GitHub repo autograph

    Machine Learning Library for Rust

    Project mention: Where to Learn Vulkan for parallel computation (with references to porting from CUDA) | reddit.com/r/vulkan | 2022-01-04

    I'm working on a machine learning library https://github.com/charles-r-earp/autograph implemented in Rust that uses rust-gpu to compile Rust compute shaders to spirv, and then gfx_hal to target metal and dx12. Training performance is currently about 2x slower than pytorch (cuda) on my laptop but I've made significant progress recently and I am targeting 1.5x. While rust-gpu itself has it's own restrictions, it does support inline spirv assembly, which provides direct access to operations not provided in its std lib, thus it's lower level than GLSL. For example, it should be possible to target cuda tensor cores via cooperative matrix operations (I believe Metal supports these as well but this may not be implemented in spirv-cross and certainly isn't in naga). Once I have things a bit more stabilized I'd like to provide more examples, like porting from cuda / opencl, but I'm still figuring out patterns like how to work with 16 and 8 bit types in a nice and portable way.

  • GitHub repo tractjs

    Run ONNX and TensorFlow inference in the browser.

    Project mention: Run WASM, a client side Python runtime | news.ycombinator.com | 2021-09-26

    Tensorflow (and by extension Keras) offload most of the actual work to C++ or C, so having those compile to WebAssembly would (I imagine) be a herculean effort.

    Instead, The TF team maintains TFJS, which can run on WebAssembly[0].

    There are also tractjs[1], and onnyxjs[2], both of which allow you to run (most) ONNX models (which is an open standard for specifying ML models) using WebAssembly and WebGL(only onnyxjs supports WebGL). A bunch of frameworks (caffe, pytorch, TF) support exporting to/importing from ONNX.

    [0] https://blog.tensorflow.org/2020/03/introducing-webassembly-...

    [1] https://github.com/bminixhofer/tractjs

    [2] https://github.com/microsoft/onnxjs

  • GitHub repo dpar

    Neural network transition-based dependency parser (in Rust)

NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020). The latest post mention was on 2022-01-04.

Rust neural-networks related posts

Index

What are some of the best open-source neural-network projects in Rust? This list will help you:

Project Stars
1 tract 1,175
2 neuronika 614
3 autograph 182
4 tractjs 64
5 dpar 42
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