Trickle – See PyTorch tensor shapes inline in VSCode as you code
AST rewriting for runtime types without code changes — why didn't this exist before.
A lightweight autograd engine inspired by PyTorch and micrograd
Takes micrograd's toy autodiff idea and scales it to real tensor operations with NumPy and optional CuPy GPU support. The repo exposes an nn-like module, common activations (ReLU/Softmax), self-attention and an MNIST MLP example, so it's excellent as a learning resource. It's explicitly flagged as WIP — expect performance and OOM rough edges, so treat it as a study tool rather than a training backbone.
Students, ML learners, hobbyist researchers and engineers who want to understand or prototype autograd and simple neural nets
AST rewriting for runtime types without code changes — why didn't this exist before.
56 ns cross-language IPC beats iceoryx and Aeron on their own turf.
Local tensor visualization beats Jupyter notebooks for quick diffusion latent inspection.
Deep dive into why silent shape bugs happen when tensor axes lack names.
Three-concept scheduling model targeting FlashAttention, but generated code isn't performant yet.
Compile-time tensor shape checking beats PyTorch's runtime dimension errors.