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A minimal, self-contained manual autograd implementation for a transformer-based classifier in PyTorch, designed to build intuition for how autograd works under the hood and how gradients flow through attention blocks.
The tweet discusses the approach of writing model code without using autograd and torch.nn module abstractions, emphasizing manual backward propagation and direct matrix computations.
I built a deep learning library in C from scratch that supports tensor operations, autograd, and neural network modules, and used it to train a tiny language model on Shakespeare data.
The PyTorch team discusses the concept of PyTorch serving as both a reference language and an implementation language for deep learning, emphasizing its role in verifying optimized kernel implementations and the potential for LLMs to generate explicit forward-backward code.
Talos-XII is a CLI simulator for Arknights: Endfield's gacha system, built entirely in Rust with a custom autograd engine and small RL/MLP stack (no external ML frameworks). It uses neural networks for environment modeling and pull-decision policy, and includes sophisticated SIMD dispatch and an open experiment called ACHF for adaptive caching.
A developer built a transformer model entirely from scratch in TypeScript, including a custom autograd engine, and released it as an open-source educational tool on GitHub.
PyTorch is an open-source deep learning framework providing GPU-accelerated tensor computation and dynamic neural networks via tape-based autograd. The GitHub README offers installation instructions, component overviews, and links to documentation.