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<html lang="en"><head><meta charset="UTF-8"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><title>Home · Flux</title><script>(function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){
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It comes &quot;batteries-included&quot; with many useful tools built in, but also lets you use the full power of the Julia language where you need it. We follow a few key principles:</p><ul><li><strong>Doing the obvious thing</strong>. Flux has relatively few explicit APIs for features like regularisation or embeddings. Instead, writing down the mathematical form will work and be fast.</li><li><strong>You could have written Flux</strong>. All of it, from <a href="https://github.com/FluxML/Flux.jl/blob/ec16a2c77dbf6ab8b92b0eecd11661be7a62feef/src/layers/recurrent.jl#L131">LSTMs</a> to <a href="https://github.com/JuliaGPU/CuArrays.jl">GPU kernels</a>, is straightforward Julia code. When in doubt, its well worth looking at <a href="https://github.com/FluxML/Flux.jl/">the source</a>. If you need something different, you can easily roll your own.</li><li><strong>Play nicely with others</strong>. Flux works well with Julia libraries from <a href="https://github.com/JuliaComputing/JuliaDB.jl">data frames</a> and <a href="https://github.com/JuliaImages/Images.jl">images</a> to <a href="https://github.com/JuliaDiffEq/DifferentialEquations.jl">differential equation solvers</a>, so you can easily build complex data processing pipelines that integrate Flux models.</li></ul><h2 id="Installation-1"><a class="docs-heading-anchor" href="#Installation-1">Installation</a><a class="docs-heading-anchor-permalink" href="#Installation-1" title="Permalink"></a></h2><p>Download <a href="https://julialang.org/">Julia 1.0</a> or later, if you haven&#39;t already. You can add Flux from using Julia&#39;s package manager, by typing <code>] add Flux</code> in the Julia prompt.</p><p>If you have CUDA you can also run <code>] add CuArrays</code> to get GPU support; see <a href="gpu/">here</a> for more details.</p><h2 id="Learning-Flux-1"><a class="docs-heading-anchor" href="#Learning-Flux-1">Learning Flux</a><a class="docs-heading-anchor-permalink" href="#Learning-Flux-1" title="Permalink"></a></h2><p>There are several different ways to learn Flux. If you just want to get started writing models, the <a href="https://github.com/FluxML/model-zoo/">model zoo</a> gives good starting points for many common ones. This documentation provides a reference to all of Flux&#39;s APIs, as well as a from-scratch introduction to Flux&#39;s take on models and how they work. Once you understand these docs, congratulations, you also understand <a href="https://github.com/FluxML/Flux.jl">Flux&#39;s source code</a>, which is intended to be concise, legible and a good reference for more advanced concepts.</p></article><nav class="docs-footer"><a class="docs-footer-nextpage" href="models/basics/">Basics »</a></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> on <span class="colophon-date" title="Wednesday 27 May 2020 11:52">Wednesday 27 May 2020</span>. Using Julia version 1.3.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>