Autograd.c – A tiny ML framework built from scratch

In plain words

Autograd.c is a minimal machine learning framework written in C that replicates core PyTorch functionality. Built as a learning resource following Professor Vijay Janapa Reddi's ML systems textbook, it is designed for developers and students who want to understand how ML frameworks operate internally. The project exposes the fundamental components and mechanisms underlying modern deep learning systems in a stripped-down, accessible codebase.

written from the facts on this page · September 2026

From the sources

tiny torch, but close to metal. Contribute to sueszli/autograd.c development by creating an account on GitHub.

$ toilet -f mono9 -w 100 "autograd.c" ▄ █ ▄▄▄ ▄ ▄ ▄▄█▄▄ ▄▄▄ ▄▄▄▄ ▄ ▄▄ ▄▄▄ ▄▄▄█ ▄▄▄ ▀ █ █ █ █ █▀ ▀█ █▀ ▀█ █▀ ▀ ▀ █ █▀ ▀█ █▀ ▀ ▄▀▀▀█ █ █ █ █ █ █ █ █ ▄▀▀▀█ █ █ █ ▀▄▄▀█ ▀▄▄▀█ ▀▄▄ ▀█▄█▀ ▀█▄▀█ █ ▀▄▄▀█ ▀█▄██ █ ▀█▄▄▀ ▄ █ ▀▀ $ cat about.txt | fold -w 75 a minimal reverse mode autograd engine in c with reference counted tensors, arena allocated function nodes, explicit dependency counting, centralized gradient accumulation, scalar loss backpropagation and a small set of core tensor ops implemented with tightly coupled forward and backward code. discussion on hackernews: https://news.ycombinator.com/item?id=46285424 $ make download data/cifar-10-binary 40%[====> ] 33.10M 2.55MB/s eta 47s $ make…from github.com

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