dfdx
A deep learning library for Rust featuring shape-checked tensors and neural networks with compile-time safety.
What is dfdx?
dfdx is a deep learning library for Rust that provides shape-checked tensors and neural network components. It enables developers to build and train machine learning models with compile-time safety, reducing runtime errors and improving reliability. The library includes GPU acceleration via CUDA and a suite of standard optimizers for efficient model training.
Rust developers and researchers who need a safe, performant deep learning framework with strong compile-time guarantees. It's ideal for those building neural networks in Rust who want to avoid runtime shape errors.
Developers choose dfdx for its unique combination of ergonomics, compile-time shape checking, and performance. Its design minimizes unsafe code and runtime overhead while providing GPU acceleration and a flexible module system.
Overview
Deep learning in Rust, with shape checked tensors and neural networks
Use Cases
Best For
- Building neural networks in Rust with compile-time safety
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