wgpu-py
burn
wgpu-py | burn | |
---|---|---|
5 | 34 | |
371 | 4,845 | |
2.7% | - | |
8.6 | 8.9 | |
4 days ago | 5 months ago | |
Python | Rust | |
BSD 2-clause "Simplified" License | Apache License 2.0 |
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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.
wgpu-py
- Pygfx/wgpu-py: Next generation GPU API for Python
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I'm working on techno audio-visuals using Ableton & Javascript
If you've a Python background, I might suggest checking out something like https://github.com/pygfx/wgpu-py
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Chrome Ships WebGPU
FYI you can already use webgpu directly in python, see https://github.com/pygfx/wgpu-py for webgpu wrappers and https://github.com/pygfx/pygfx for a more high level graphics library
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I've just started mixing shaders with Pygame and got some great results
This reminds me of another Python GPU project, bringing in WebGPU shaders.
https://github.com/pygfx/wgpu-py
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Unifying the CUDA Python Ecosystem
Somewhat related, I’ve built compute shaders using wgpu-py:
https://github.com/pygfx/wgpu-py
You can define any compute shader you like in Python, with the data types, and it compiles it to SPIRV and runs it.
burn
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Burn 0.10.0 Released 🔥 (Deep Learning Framework)
Release Note: https://github.com/burn-rs/burn/releases/tag/v0.10.0
- Deep Learning Framework in Rust: Burn 0.10.0 Released
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Why Rust Is the Optimal Choice for Deep Learning, and How to Start Your Journey with the Burn Deep Learning Framework
The comprehensive, open-source deep learning framework in Rust, Burn, has recently undergone significant advancements in its latest release, highlighted by the addition of The Burn Book 🔥. There has never been a better moment to embark on your deep learning journey with Rust, as this book will guide you through your initial project, providing extensive explanations and links to relevant resources.
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Candle: Torch Replacement in Rust
Burn (deep learning framework in rust) has WGPU backend (WebGPU) already. Check it out https://github.com/burn-rs/burn. It was released recently.
- Burn – A Flexible and Comprehensive Deep Learning Framework in Rust
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Announcing Burn-Wgpu: New Deep Learning Cross-Platform GPU Backend
For more details about the latest release see the release notes: https://github.com/burn-rs/burn/releases/tag/v0.8.0.
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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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Any working wgpu compute example that would run in a browser?
We, the burn team, are working on the wgpu backend (WebGPU) for Burn deep learning framework. You can check out the current state: https://github.com/burn-rs/burn/tree/main/burn-wgpu
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I’ve fallen in love with rust so now what?
Here is the project: https://github.com/burn-rs/burn
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Is anyone doing Machine Learning in Rust?
Disclaimer, I'm the main author of Burn https://burn-rs.github.io.
What are some alternatives?
CudaPy - CudaPy is a runtime library that lets Python programmers access NVIDIA's CUDA parallel computation API.
candle - Minimalist ML framework for Rust
cudf - cuDF - GPU DataFrame Library
dfdx - Deep learning in Rust, with shape checked tensors and neural networks
SHA256-WebGPU - Implementation of sha256 in WGSL
tch-rs - Rust bindings for the C++ api of PyTorch.
grcuda - Polyglot CUDA integration for the GraalVM
Graphite - 2D raster & vector editor that melds traditional layers & tools with a modern node-based, non-destructive, procedural workflow.
web-stable-diffusion - Bringing stable diffusion models to web browsers. Everything runs inside the browser with no server support.
tract - Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference [Moved to: https://github.com/sonos/tract]
copperhead - Data Parallel Python
L2 - l2 is a fast, Pytorch-style Tensor+Autograd library written in Rust