tenferro-rs Rust-native differentiable tensor stack for scientific computing

tenferro-rs provides a Rust-native dense tensor stack featuring PyTorch-style eager autodiff, JAX-style traced transforms, and NumPy-style einsum. It includes explicit CPU/CUDA backends and is designed to resolve Julia-specific issues like type instability and slow compile times in large-scale tensor-network codebases.