tinygrad VS flameshot

Not sure if I completely understand what "Ryzen AI" does, but Tinygrad for example has some limited support for RDNA3[0]. It isn't quite there yet in matters of performance though, as you can read in the comments of that file.

There's also a small tutorial by AMD on how to use the WMMA intrinsic[1] using AMD's hipcc[2] compiler. Documentation is sparse kinda sparse, but the instruction set is not huge. The RDNA3 ISA guide[3] might also be helpful (and only a fraction of the pages are relevant.)

0. https://github.com/tinygrad/tinygrad/blob/master/extra/gemm/...

1. https://gpuopen.com/learn/wmma_on_rdna3/

2. https://github.com/ROCm/HIPCC

3. https://www.amd.com/content/dam/amd/en/documents/radeon-tech...

This post describes how I added automatic differentiation to Tensorken. Tensorken is my attempt to build a fully featured yet easy-to-understand and hackable implementation of a deep learning library in Rust. It takes inspiration from the likes of PyTorch, Tinygrad, and JAX.

what do you think about tinygrad? I think its a good example of growing and well written, (partially) well documented library with many close to reference implementations

The idea of model architecture making fast hardware design easier is what makes https://github.com/tinygrad/tinygrad so interesting.

🌟 Support on GitHub Website: https://tinygrad.org/

Before we begin, make sure you have TinyGrad and the required dependencies installed. You can find the installation instructions here.

Try to get something like tinygrad[1] running locally, that way you can tweak things a bit run it again and see how it performs. While doing this you'll pick up most of the concepts and get a feeling of how things work. Also, take a look at projects like llama.cpp[2], you don't have to fully understand what's going on here, tho.

You may need some intermediate knowledge of linear algebra and this thing called "data science" nowadays, which is pretty much knowing how to mangle data and visualize it.

Try creating a small model on your own, it doesn't have to be super fancy just make sure it does something you want it to do. And then ... you'll probably could go on your own then.

1: https://github.com/tinygrad/tinygrad

2: https://github.com/ggerganov/llama.cpp

For your screenshots simply use Flameshot: https://flameshot.org

First, conceptually this is what I mean: think about when using a good screen-capture/annotation tool like flameshot: you select a region of the screen, and "magic" you can "edit" it, "in situ". No, what I'm talking about wouldn't share any of the same technical underpinnings with the way flameshot works, it would be the live monitor output, not a raster dump of the screen made to look like it's live. And the annotating would be done on a different screen. But as a user, this is pretty similar.

Flameshot is a free and open-source screenshot tool for Linux that allows users to take screenshots of an area, a window or the full screen. It then provides an editor where users can modify the screenshots by drawing on them, adding text, highlighting areas, blurring parts and more. Users can save the screenshots in common image formats like PNG and JPEG, and upload them directly to image hosting sites like Imgur.

I would recommend Flameshot, available on Linux, Windows and Mac.

This https://github.com/flameshot-org/flameshot/issues/1529 mat or may not be an issue for you with Flameshot, but it may be for others. It's solvable if it is an issue by using mandatory access control such as AppArmor or conditional build. Just FYI.

Flameshot viene con todo eso.

[3] https://github.com/flameshot-org/flameshot/issues/2848