burn
are-we-learning-yet
| burn | are-we-learning-yet | |
|---|---|---|
| 9 | 5 | |
| 7,384 | 426 | |
| 4.2% | - | |
| 9.8 | 4.4 | |
| 5 days ago | 7 days ago | |
| Rust | Rust | |
| Apache License 2.0 | Creative Commons Attribution 4.0 |
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.
burn
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3 years of fulltime Rust game development, and why we're leaving Rust behind
You can use libtorch directly via `tch-rs`, and at present I'm porting over to Burn (see https://burn.dev) which appears incredibly promising. My impression is it's in a good place, if of course not close to the ecosystem of Python/C++. At very least I've gotten my nn models training and running without too much difficulty. (I'm moving to Burn for the thread safety - their `Tensor` impl is `Sync` - libtorch doesn't have such a guarantee.)
Burn has Candle as one of its backends, which I understand is also quite popular.
- Burn: Deep Learning Framework built using Rust
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Transitioning From PyTorch to Burn
[package] name = "resnet_burn" version = "0.1.0" edition = "2021" [dependencies] burn = { git = "https://github.com/tracel-ai/burn.git", rev = "75cb5b6d5633c1c6092cf5046419da75e7f74b11", features = ["ndarray"] } burn-import = { git = "https://github.com/tracel-ai/burn.git", rev = "75cb5b6d5633c1c6092cf5046419da75e7f74b11" } image = { version = "0.24.7", features = ["png", "jpeg"] }
- Burn Deep Learning Framework Release 0.12.0 Improved API and PyTorch Integration
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Supercharge Web AI Model Testing: WebGPU, WebGL, and Headless Chrome
Great!
For Burn project, we have WebGPU example and I was looking into how we could add automated tests in the browser. Now it seems possible.
Here is the image classification example if you'd like to check out:
https://github.com/tracel-ai/burn/tree/main/examples/image-c...
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Burn Deep Learning Framework 0.11.0 Released: Just-in-Time Automatic Kernel Fusion & Founding Announcement
Full Release Note: https://github.com/tracel-ai/burn/releases/tag/v0.11.0
- Burn Deep Learning Framework v0.11.0 Released: Just-in-Time Kernel Fusion
- Burn – comprehensive dynamic Deep Learning Framework built using Rust
- Burn: Deep Learning Framework in Rust
are-we-learning-yet
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This year I tried solving AoC using Rust, here are my impressions coming from Python!
Also http://arewelearningyet.com
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[D] Is Rust stable/mature enough to be used for production ML? Is making Rust-based python wrappers a good choice for performance heavy uses and internal ML dependencies in 2021?
Hey OP, you might want to check this site out: http://arewelearningyet.com
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Is rust good for mathematical computing?
Note that you can update the page (adding packages or updating descriptions) via those github issues: https://github.com/anowell/are-we-learning-yet/issues
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I wanted to share my experience of Rust as a deep learning researcher
Not sure if you’ve encountered it, but you should be aware of http://arewelearningyet.com
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Announcing neuronika 0.1.0, a deep learning framework in Rust
Just make a PR: https://github.com/anowell/are-we-learning-yet
What are some alternatives?
dfdx - Deep learning in Rust, with shape checked tensors and neural networks
rust-gpu - 🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧
candle - Minimalist ML framework for Rust
neuronika - Tensors and dynamic neural networks in pure Rust.
wonnx - A WebGPU-accelerated ONNX inference run-time written 100% in Rust, ready for native and the web
wgpu - A cross-platform, safe, pure-Rust graphics API.
tch-rs - Rust bindings for the C++ api of PyTorch.
book - The Rust Programming Language
rust-mlops-template - A work in progress to build out solutions in Rust for MLOPs
rust-bert - Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)
llama2.rs - A fast llama2 decoder in pure Rust.
Awesome-Rust-MachineLearning - This repository is a list of machine learning libraries written in Rust. It's a compilation of GitHub repositories, blogs, books, movies, discussions, papers, etc. 🦀