Burn provides a flexible, efficient, and portable tensor library for building deep learning applications.
Open source
24 alternativesdfdx
Deep learning in Rust, with shape checked tensors and neural networks.
About dfdx
dfdx is a deep learning library written in Rust. It focuses on tensor shapes and types that are checked at compile time, so that some shape mismatches are caught before the code runs. The library provides tensors with GPU acceleration, a set of tensor operations, neural network building blocks, and optimizers. The project is in a pre-alpha state, and the maintainers have said the next few releases are planned to be breaking releases. The source lists version 0.13.0 as available on crates.io.
Key features
- GPU-accelerated tensor library with shapes up to six dimensions
- Tensor shapes with both compile-time and runtime-sized dimensions
- Tensor operations checked for shape and type at compile time
- Neural network building blocks such as Linear, Conv2D, and Transformer
- Optimizers including Sgd, Adam, AdamW, and RMSprop
- Optional CUDA device support enabled through a cargo feature flag
Best for: Rust developers who want to build neural networks with tensor shapes checked at compile time and who can accept API changes while the project is pre-alpha.
Good for
- States compile-time checking of shapes and types as a design goal
- Lists ergonomics and performance among its stated design goals
- Reports that the only current unsafe calls are for matrix multiplication
Watch out for
- The project is in a pre-alpha state, and the next few releases are planned to be breaking
- CUDA support requires installing NVIDIA's CUDA toolkit
- Contains unsafe code for matrix multiplication
dfdx at a glance
- Website
- github.com/coreylowman/dfdx
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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dfdx FAQ
How do I add dfdx to a Rust project?
Add dfdx = "0.13.0" to your Cargo.toml file. The source says the documentation is at docs.rs/dfdx.
What is required to use GPU acceleration with CUDA?
Enable the cuda feature. The source says this requires the installation of NVIDIA's CUDA toolkit.
Is the API stable?
No. The source says the project is still in a pre-alpha state and the next few releases are planned to be breaking releases.
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