How I Re-implemented PyTorch for WebGPU

TL;DR I’ve been working on a WebGPU optimized inference and autograd library called webgpu-torch with an API that matches PyTorch. The goal is to run neural networks in the browser at speeds comparable to a Linux workstation. Many kernels have been implemented and its design is easily extensible. It’s available on NPM now and works in both the browser and Node.js!