Minimal Deep Learning Framework
A PyTorch-like framework with define-by-run autograd and CuPy-based GPU support.
I built this framework to understand the mechanics of deep learning systems from first principles.
Highlights
- Implemented a dynamic computation graph and automatic differentiation engine from scratch.
- Followed a define-by-run execution model to mirror modern deep learning frameworks.
- Added GPU support through CuPy to keep the framework lightweight but practical.