burn
tch-rs
| burn | tch-rs | |
|---|---|---|
| 9 | 37 | |
| 7,074 | 3,843 | |
| 5.1% | - | |
| 9.8 | 7.5 | |
| 1 day ago | 8 days ago | |
| Rust | Rust | |
| Apache License 2.0 | Apache License 2.0 |
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
tch-rs
- Tch-Rs
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Llama2.rs: One-file Rust implementation of Llama2
I wanted to do something like this but then I would miss on proper CUDA acceleration and lose performance compared to using torchlib.
I wrote a forgettable llama implementation for https://github.com/LaurentMazare/tch-rs (pytorch's torchlib rust binding).
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Playing Atari Games in OCaml
I first encountered OCaml's PyTorch bindings because apparently they generate a C wrapper around PyTorch's C++ API, and Rust's PyTorch bindings use OCaml's C wrapper. See: https://github.com/LaurentMazare/tch-rs
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llm: a Rust crate/CLI for CPU inference of LLMs, including LLaMA, GPT-NeoX, GPT-J and more
You could try looking at the min-GPT example of tch-rs. I'd also strongly suggest watching Karpathy's video to understand what's going on.
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Simply explained: How does GPT work?
If you pefer to see it in code there's a succint gpt implementation here https://github.com/LaurentMazare/tch-rs/blob/main/examples/m...
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Will I ever need python again if I learn rust other than for AI stuff?
Rust is fully compatible w/ C bindings, so even Python libraries written in C can be easily set up to work in Rust (and have been). For example, see PyTorch Rust bindings, which actually works faster than in Python because all of the glue code around the C++ API is in Rust instead of Python.
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A Rust client library for interacting with Microsoft Airsim https://github.com/Sollimann/airsim-client
Pytorch
- [D] HuggingFace in Julia or Rust ?
- This year I tried solving AoC using Rust, here are my impressions coming from Python!
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[Help Needed] Deployment of torchscript using rust
I have looked into this a bit and found some crates which help in loading torchscript models called tch-rs
What are some alternatives?
dfdx - Deep learning in Rust, with shape checked tensors and neural networks
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
candle - Minimalist ML framework for Rust
wonnx - A WebGPU-accelerated ONNX inference run-time written 100% in Rust, ready for native and the web
cbindgen - A project for generating C bindings from Rust code
rust-mlops-template - A work in progress to build out solutions in Rust for MLOPs
wtpsplit - Code for Where's the Point? Self-Supervised Multilingual Punctuation-Agnostic Sentence Segmentation
llama2.rs - A fast llama2 decoder in pure Rust.
veloren - An open world, open source voxel RPG inspired by Dwarf Fortress and Cube World. This repository is a mirror. Please submit all PRs and issues on our GitLab page.
corgi - A neural network, and tensor dynamic automatic differentiation implementation for Rust.
rustlearn - Machine learning crate for Rust