An open source website I built to explain tensor functions in PyTorch: https://whytorch.org
It makes tricky functions like torch.gather and torch.scatter more intuitive by showing element-level relationships between inputs and outputs.
For any function, you can click elements in the result to see where they came from, or elements in the inputs to see how they contribute to the result to see exactly how it contributes to the result. I found that visually tracing tensor operations clarifies indexing, slicing, and broadcasting in ways reading that the docs can't.
You can also jump straight to WhyTorch from the PyTorch docs pages by modifying the base URL directly.
I launched a week or two back and now have the top post of all time on r/pytorch, which has been pretty fun.
This really nice. For `torch.mul(x, y)`, it would be nice if it highlighted the entire row or column in the other matrix and result. Right now it shows only a single multiplication, which gives a misleading impression of how matrix multiply works. I wouldn't mention it, except that matrix multiplication is so important that it's worth showcasing. I've bookmarked the site and will share it at a pytorch training session I'm leading in a couple of weeks.
I have a PhD in robotics. Got my start with Lego Mindstorms and highly recommend them.
Another commenter mentioned FIRST LEGO League, which is a great idea. However, it does require that you have a nearby league, and the experience is probably going to depend a lot on the quality of that league (funding, coaches, etc.) So if you have the funds (but not the time), starting out with the kits just at home could be a great first step.
Indeed. I expect a user guide to have exact instructions on how to use a device. SpaceX's brochure doesn't even go far enough to call it a specification sheet.
Our early testers have found Cherry very useful for preventing interruptions during recording sessions. It works for any size studio, home or pro.
We are trying to remove barriers to creativity. Giving peace of mind during recording is one little way to do that.
Cherry is one of my pandemic side projects. I've learned a lot about SwiftUI and reverse-engineering simple communication protocols, like how digital audio workstations (DAWs) communicate with peripherals.
It was pretty incredible. The "diamond ring" really bursts out over the edge of the moon, and then it's glasses on or look away, because the sun's back.
It makes tricky functions like torch.gather and torch.scatter more intuitive by showing element-level relationships between inputs and outputs.
For any function, you can click elements in the result to see where they came from, or elements in the inputs to see how they contribute to the result to see exactly how it contributes to the result. I found that visually tracing tensor operations clarifies indexing, slicing, and broadcasting in ways reading that the docs can't.
You can also jump straight to WhyTorch from the PyTorch docs pages by modifying the base URL directly.
I launched a week or two back and now have the top post of all time on r/pytorch, which has been pretty fun.