5 posts
TenfloweRS 0.1.2 adds PyTorch-style implicit autograd for Python, real ONNX protobuf import/export, a pure-Rust Blosc codec for Zarr, and a wide honesty-hardening sweep that replaces fabricated results with real computation or honest errors across the framework.
phop 0.1.0 — a pure-Rust differentiable symbolic-discovery engine that learns the topology and constants of closed-form laws by gradient descent over trees of a single operator, eml(x,y)=exp(x)−ln(y), then certifies and SMT/Lean-proves them. Runs the whole pipeline in the browser via WASM.
SciRS2 0.5.1 is a correctness and Pure-Rust hardening release: exact autograd gradients for matrix functions (Sylvester / Daleckii–Krein / reduced-SVD VJP), a restored CoreError #[non_exhaustive] contract, honest GPU/CUDA reporting, public Zarr v2/v3, and the removal of the C/MPFR rug, C rusqlite, and tokenizers dependencies. 36,606 tests, zero warnings — the sovereign scientific-computing layer of the COOLJAPAN ecosystem.
TenfloweRS is a pure-Rust alternative to TensorFlow, and this is its first stable release. It ships dual eager + graph execution, reverse-mode autodiff, 150+ research domains, and WGPU GPU acceleration — built on the SciRS2 and NumRS2 ecosystem, with no C++, CUDA-C, or Python runtime.
ToRSh is a PyTorch-compatible deep-learning framework in pure Rust with native tensor sharding. The 0.1.1 release hardens the 33-crate workspace onto consistent, published crates.io dependencies and adds the new torsh-convert model-converter CLI.