LuxDL Docs

Elegant & Performant Deep Learning in JuliaLang

A Pure Julia Deep Learning Framework putting Correctness and Performance First

Tutorials

Ecosystem

API Reference 📚

View on GitHub

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Fast & Extendible

Lux.jl is written in Julia itself, making it extremely extendible. CUDA and AMDGPU are supported first-class, with experimental support for Metal Hardware.

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SciML ❤️ Lux

Lux is the default choice for many SciML packages, including DiffEqFlux.jl, NeuralPDE.jl, and more.

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Uniquely Composable

Lux.jl natively supports Arbitrary Parameter Types, making it uniquely composable with other Julia packages (and even Non-Julia packages).

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Well Tested

Lux.jl tests every supported Automatic Differentiation Framework with every supported hardware backend against Finite Differences to prevent sneaky 🐛 in your code.