tract
gpu.js
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| tract | gpu.js | |
|---|---|---|
| 20 | 9 | |
| 2,046 | 14,951 | |
| 2.7% | 0.4% | |
| 9.8 | 0.0 | |
| 7 days ago | about 2 months ago | |
| Rust | JavaScript | |
| Apache 2.0/MIT | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tract
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Are there any ML crates that would compile to WASM?
Tract is the most well known ML crate in Rust, which I believe can compile to WASM - https://github.com/sonos/tract/. Burn may also be useful - https://github.com/burn-rs/burn.
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[Discussion] What crates would you like to see?
tract!!
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tract VS burn - a user suggested alternative
2 projects | 25 Mar 2023
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Machine Learning Inference Server in Rust?
we use tract for inference, integrated into our runtime and services.
- onnxruntime
- Rust Native ML Frameworks?
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Neural networks - what crates to use?
Not for training, but for inference this looks nice: https://github.com/sonos/tract
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Brain.js: GPU Accelerated Neural Networks in JavaScript
There's also tract, from sonos[0]. 100% rust.
I'm currently trying to use it to do speech recognition with a variant of the Conformer architecture (exported to ONNX).
The final goal is to do it in WASM client-side.
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Serving ML at the Speed of Rust
As the article notes, there isn't any official Rust-native support for any common frameworks.
tract (https://github.com/sonos/tract) seems like the most mature for ONNX (for which TF/PT export is good nowadays), and recently it successfully implemented BERT.
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Run deep neural network models from scratch
There are some DL libraries written in Rust: https://github.com/sonos/tract , https://docs.rs/neuronika/latest/neuronika/index.html . The second one could be used for training, I think.
gpu.js
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Deep Learning in JavaScript
You might already be familiar, but a GPU.js backend can provide some speedups via good old WebGL -- no need for WebGPU just yet!
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Show HN: Shadeup – A language that makes WebGPU easier
Very cool project.
I learned WebGL three years ago but before I dove into the underlying concepts I used GPU.js [1] to quickly prototype my project. Eventually, the abstraction prevented necessary performance optimizations so I switched to vanilla GLSL and these vanilla GLSL "shaders" were initially ejected from GPU.js.
Writing JS code then looking at the generated WebGPU output is a great way to get familiar with WebGPU. Thanks for this.
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Gpu.js: GPU Accelerated JavaScript
I used this library on my project but I think it's no longer maintained. I PRed a fix for buggy atan2 over a year ago and no movement [1]. I do highly recommend it if you're a web developer interested in harnessing parallel processing.
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Brain.js: GPU Accelerated Neural Networks in JavaScript
Thanks for pointing this out. I've submitted a PR to resolve this: https://github.com/gpujs/gpu.js/issues/757
That being said, if you're not building from source (you're running an LTS version of node on a supported platform), you don't need to worry about python or many of the build deps.
- GPU.js
- For what projects, Nodejs is an absolute No No?
What are some alternatives?
onnxruntime-rs - Rust wrapper for Microsoft's ONNX Runtime (version 1.8)
numjs - Like NumPy, in JavaScript
MTuner - MTuner is a C/C++ memory profiler and memory leak finder for Windows, PlayStation 4 and 3, Android and other platforms
headless-gl - 🎃 Windowless WebGL for node.js
wonnx - A WebGPU-accelerated ONNX inference run-time written 100% in Rust, ready for native and the web
aladino - 🧞♂️ Your magic WebGL carpet
ncurses-rs - A low-level ncurses wrapper for Rust
math-clamp - Clamp a number
linfa - A Rust machine learning framework.
math-sum - Sum numbers
fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Brain.js - 🤖 GPU accelerated Neural networks in JavaScript for Browsers and Node.js