I’ve spent the last two years building qeep, a deep learning framework written entirely in Go.

Why I built this: While Go has some great math libraries, I wanted a framework that felt more like PyTorch (declarative API) but stayed true to Go’s simplicity. I also wanted to deeply understand how AutoGrad and CUDA kernels interface with Go’s runtime and memory management.

Key Features:

- Multi-Dimensional Tensors with a wide range of linear algebra and statistical operations.

- Automatic differentiation (AutoGrad) for tensors.

- GPU acceleration via CUDA for high-performance large tensor computations.

- A variety of neural network components, such as fully connected (FC) layer.

- A declarative API for defining neural networks using stream package.

Repo: https://github.com/sahandsafizadeh/qeep