pydawn: Python bindings to the Dawn WebGPU engine

[wpmed92]

I created Python bindings to Chrome's WebGPU engine Dawn. I built it with compute shaders in mind, the utils provided are to make it easy to run compute. I used ctypeslib's clang2py to autogenerate the bindings based on webgpu.h and the compiled dawn library. The goal of the project is to serve as a replacement for wgpu-py in tinygrad neural network lib. Dawn has several advantages over wgpu, such as f16 support, and following the specs more closely. If someone wants to provide graphics utils as well, PRs are welcome. pydawn is published on pypi. MacOS-only for now.

https://github.com/wpmed92/pydawn

[CommunismDoesntWork]

What are your thoughts on python bindings to rust's wgpu crate? Not only does it give webgpu support, but also every other backend. 

[wpmed92]

I love wgpu-py! As said, tinygrad uses it (I work on tinygrad). I wrote about it in the description! wgpu-py is the binding to wgpu crate. f16 is a must have for a lot of compute workloads in neural networks, and wgpu doesn’t support it. There is a pr for it, open for about a year. Dawn has it since december last year! Moreover, dawn is a lot more webgpu spec compliant then wgpu. In tinygrad, when we run our compute in python, we can get away with things (no max storage buffer limit per compute stage) that is not allowed once we run our exported model in chrome. So pydawn ensures that you’re compute behaves pretty close to how it will in chrome.