MiniTorch Module 0

MiniTorch is a teaching library for machine learning engineers who wish to learn about the internal concepts underlying deep learning systems. Specifically, it is a pure Python re-implementation of the Torch API designed to be simple, easy-to-read, tested, and incremental. The final library can run Torch code with minimal changes (at some efficiency cost). The project was developed for the course Machine Learning Engineering at Cornell Tech.

The project is organized into 5 modules. Each module is build upon the precedents.

• Module-0
• Module-1
• Module-2
• Module-3
• Module-4

This is Module-0. It is focused on introducing several core technologies used for testing and debugging future models and also some basic mathematical foundations.

Notes

• Docs: https://minitorch.github.io/

• Overview: https://minitorch.github.io/module0.html

• Tests:

python run_tests.py