behavior-tree
tract
| behavior-tree | tract | |
|---|---|---|
| 1 | 20 | |
| 25 | 2,072 | |
| - | 2.2% | |
| 1.6 | 9.8 | |
| 11 months ago | 5 days ago | |
| Rust | Rust | |
| - | Apache 2.0/MIT |
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.
behavior-tree
-
BITGUN Demo is now live on Steam - a game made in Rust and Godot by a two person fulltime indie dev team over the past 9 months
After pathfinding was implemented we slowly started converting more of the codebase, wrote a behavior tree crate (don't recommend you use it, but it works and the game uses it), then we converted almost all of the ingame UI to egui (healthbars, inventory, icons, etc., basically everything but the main menu is egui now).
tract
-
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.
-
[Discussion] What crates would you like to see?
tract!!
-
tract VS burn - a user suggested alternative
2 projects | 25 Mar 2023
-
Machine Learning Inference Server in Rust?
we use tract for inference, integrated into our runtime and services.
- onnxruntime
- Rust Native ML Frameworks?
-
Neural networks - what crates to use?
Not for training, but for inference this looks nice: https://github.com/sonos/tract
-
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.
[0] https://github.com/sonos/tract
-
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.
-
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.
What are some alternatives?
bevy - A refreshingly simple data-driven game engine built in Rust
onnxruntime-rs - Rust wrapper for Microsoft's ONNX Runtime (version 1.8)
hecs - A handy ECS
MTuner - MTuner is a C/C++ memory profiler and memory leak finder for Windows, PlayStation 4 and 3, Android and other platforms
emergent - Toolset for producing emergent gameplay for games written in Rust
wonnx - A WebGPU-accelerated ONNX inference run-time written 100% in Rust, ready for native and the web
gdnative - Rust bindings for Godot 3
ncurses-rs - A low-level ncurses wrapper for Rust
linfa - A Rust machine learning framework.
fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
tangram - Tangram makes it easy for programmers to train, deploy, and monitor machine learning models.
bevy_webgl2 - WebGL2 renderer plugin for Bevy game engine