10 lines
5.9 KiB
HTML
10 lines
5.9 KiB
HTML
<!DOCTYPE html>
|
||
<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(){
|
||
(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),
|
||
m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
|
||
})(window,document,'script','https://www.google-analytics.com/analytics.js','ga');
|
||
|
||
ga('create', 'UA-36890222-9', 'auto');
|
||
ga('send', 'pageview');
|
||
</script><link href="https://cdnjs.cloudflare.com/ajax/libs/normalize/4.2.0/normalize.min.css" rel="stylesheet" type="text/css"/><link href="https://fonts.googleapis.com/css?family=Lato|Roboto+Mono" rel="stylesheet" type="text/css"/><link href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.6.3/css/font-awesome.min.css" rel="stylesheet" type="text/css"/><link href="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/styles/default.min.css" rel="stylesheet" type="text/css"/><script>documenterBaseURL="."</script><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.2.0/require.min.js" data-main="assets/documenter.js"></script><script src="siteinfo.js"></script><script src="../versions.js"></script><link href="assets/documenter.css" rel="stylesheet" type="text/css"/><link href="assets/flux.css" rel="stylesheet" type="text/css"/></head><body><nav class="toc"><h1>Flux</h1><select id="version-selector" onChange="window.location.href=this.value" style="visibility: hidden"></select><form class="search" id="search-form" action="search/"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li class="current"><a class="toctext" href>Home</a><ul class="internal"><li><a class="toctext" href="#Installation-1">Installation</a></li><li><a class="toctext" href="#Learning-Flux-1">Learning Flux</a></li></ul></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="models/basics/">Basics</a></li><li><a class="toctext" href="models/recurrence/">Recurrence</a></li><li><a class="toctext" href="models/regularisation/">Regularisation</a></li><li><a class="toctext" href="models/layers/">Model Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="training/optimisers/">Optimisers</a></li><li><a class="toctext" href="training/training/">Training</a></li></ul></li><li><a class="toctext" href="data/onehot/">One-Hot Encoding</a></li><li><a class="toctext" href="gpu/">GPU Support</a></li><li><a class="toctext" href="saving/">Saving & Loading</a></li><li><a class="toctext" href="performance/">Performance Tips</a></li><li><span class="toctext">Internals</span><ul><li><a class="toctext" href="internals/tracker/">Backpropagation</a></li></ul></li><li><a class="toctext" href="community/">Community</a></li></ul></nav><article id="docs"><header><nav><ul><li><a href>Home</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/index.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>Home</span><a class="fa fa-bars" href="#"></a></div></header><h1><a class="nav-anchor" id="Flux:-The-Julia-Machine-Learning-Library-1" href="#Flux:-The-Julia-Machine-Learning-Library-1">Flux: The Julia Machine Learning Library</a></h1><p>Flux is a library for machine learning. It comes "batteries-included" 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, it’s 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><a class="nav-anchor" id="Installation-1" href="#Installation-1">Installation</a></h2><p>Download <a href="https://julialang.org/">Julia 1.0</a> or later, if you haven't already. You can add Flux from using Julia'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><a class="nav-anchor" id="Learning-Flux-1" href="#Learning-Flux-1">Learning Flux</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's APIs, as well as a from-scratch introduction to Flux'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's source code</a>, which is intended to be concise, legible and a good reference for more advanced concepts.</p><footer><hr/><a class="next" href="models/basics/"><span class="direction">Next</span><span class="title">Basics</span></a></footer></article></body></html>
|