Submitted by Balance- t3_11ksa12 in MachineLearning
tinygrad, a deep learning Frameworks that aims to have a complexity between a pytorch and a karpathy/micrograd, just tagged their 0.5.0 release.
Release notes
An upsetting 2223 lines of code, but so much great stuff!
- 7 backends : CLANG, CPU, CUDA, GPU, LLVM, METAL, and TORCH
- A TinyJit for speed (decorate your GPU function today)
- Support for a lot of onnx, including all the models in the backend tests
- No more MLOP convs, all HLOP (autodiff for convs)
- Improvements to shapetracker and symbolic engine
- 15% faster at running the openpilot model
etesian_dusk t1_jb8yzec wrote
Why would I start using this today?