build based on 92f65f9
This commit is contained in:
autodocs
parent
ffb39fb39b
commit
8190cf26bf
@ -1,9 +1,9 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="en"><head><meta charset="UTF-8"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><title>Contributing & Help · Flux</title><script>(function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){
|
||||
<html lang="en"><head><meta charset="UTF-8"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><title>Community · 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="../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="models/basics.html">Basics</a></li><li><a class="toctext" href="models/recurrence.html">Recurrence</a></li><li><a class="toctext" href="models/layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="training/training.html">Training</a></li></ul></li><li><a class="toctext" href="data/onehot.html">One-Hot Encoding</a></li><li><a class="toctext" href="gpu.html">GPU Support</a></li><li class="current"><a class="toctext" href="contributing.html">Contributing & Help</a><ul class="internal"></ul></li></ul></nav><article id="docs"><header><nav><ul><li><a href="contributing.html">Contributing & Help</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/contributing.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>Contributing & Help</span><a class="fa fa-bars" href="#"></a></div></header><h1><a class="nav-anchor" id="Contributing-and-Help-1" href="#Contributing-and-Help-1">Contributing & Help</a></h1><p>If you need help, please ask on the <a href="https://discourse.julialang.org/">Julia forum</a>, the <a href="https://discourse.julialang.org/t/announcing-a-julia-slack/4866">slack</a> (channel #machine-learning), or Flux's <a href="https://gitter.im/FluxML/Lobby">Gitter</a>.</p><p>Right now, the best way to help out is to try out the examples and report any issues or missing features as you find them. The second best way is to help us spread the word, perhaps by <a href="https://github.com/MikeInnes/Flux.jl">starring the repo</a>.</p><p>If you're interested in hacking on Flux, most of the <a href="https://github.com/MikeInnes/Flux.jl/tree/master/src">code</a> is pretty straightforward. Adding new <a href="https://github.com/MikeInnes/Flux.jl/tree/master/src/layers">layer definitions</a> or cost functions is simple using the Flux DSL itself, and things like data utilities and training processes are all plain Julia code.</p><p>If you get stuck or need anything, let us know!</p><footer><hr/><a class="previous" href="gpu.html"><span class="direction">Previous</span><span class="title">GPU Support</span></a></footer></article></body></html>
|
||||
</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="../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="models/basics.html">Basics</a></li><li><a class="toctext" href="models/recurrence.html">Recurrence</a></li><li><a class="toctext" href="models/layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="training/training.html">Training</a></li></ul></li><li><a class="toctext" href="data/onehot.html">One-Hot Encoding</a></li><li><a class="toctext" href="gpu.html">GPU Support</a></li><li class="current"><a class="toctext" href="community.html">Community</a><ul class="internal"></ul></li></ul></nav><article id="docs"><header><nav><ul><li><a href="community.html">Community</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/community.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>Community</span><a class="fa fa-bars" href="#"></a></div></header><h1><a class="nav-anchor" id="Community-1" href="#Community-1">Community</a></h1><p>All Flux users are welcome to join our community on the <a href="https://discourse.julialang.org/">Julia forum</a>, the <a href="https://discourse.julialang.org/t/announcing-a-julia-slack/4866">slack</a> (channel #machine-learning), or Flux's <a href="https://gitter.im/FluxML/Lobby">Gitter</a>. If you have questions or issues we'll try to help you out.</p><p>If you're interested in hacking on Flux, the <a href="https://github.com/FluxML/Flux.jl">source code</a> is open and easy to understand – it's all just the same Julia code you work with normally. You might be interested in our <a href="https://github.com/FluxML/Flux.jl/issues?q=is%3Aopen+is%3Aissue+label%3A%22help+wanted%22">intro issues</a> to get started.</p><footer><hr/><a class="previous" href="gpu.html"><span class="direction">Previous</span><span class="title">GPU Support</span></a></footer></article></body></html>
|
||||
@ -6,7 +6,7 @@ m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
|
||||
|
||||
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="../../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="../index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="../models/basics.html">Basics</a></li><li><a class="toctext" href="../models/recurrence.html">Recurrence</a></li><li><a class="toctext" href="../models/layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="../training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="../training/training.html">Training</a></li></ul></li><li class="current"><a class="toctext" href="onehot.html">One-Hot Encoding</a><ul class="internal"><li><a class="toctext" href="#Batches-1">Batches</a></li></ul></li><li><a class="toctext" href="../gpu.html">GPU Support</a></li><li><a class="toctext" href="../contributing.html">Contributing & Help</a></li></ul></nav><article id="docs"><header><nav><ul><li><a href="onehot.html">One-Hot Encoding</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/data/onehot.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>One-Hot Encoding</span><a class="fa fa-bars" href="#"></a></div></header><h1><a class="nav-anchor" id="One-Hot-Encoding-1" href="#One-Hot-Encoding-1">One-Hot Encoding</a></h1><p>It's common to encode categorical variables (like <code>true</code>, <code>false</code> or <code>cat</code>, <code>dog</code>) in "one-of-k" or <a href="https://en.wikipedia.org/wiki/One-hot">"one-hot"</a> form. Flux provides the <code>onehot</code> function to make this easy.</p><pre><code class="language-none">julia> using Flux: onehot
|
||||
</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="../../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="../index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="../models/basics.html">Basics</a></li><li><a class="toctext" href="../models/recurrence.html">Recurrence</a></li><li><a class="toctext" href="../models/layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="../training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="../training/training.html">Training</a></li></ul></li><li class="current"><a class="toctext" href="onehot.html">One-Hot Encoding</a><ul class="internal"><li><a class="toctext" href="#Batches-1">Batches</a></li></ul></li><li><a class="toctext" href="../gpu.html">GPU Support</a></li><li><a class="toctext" href="../community.html">Community</a></li></ul></nav><article id="docs"><header><nav><ul><li><a href="onehot.html">One-Hot Encoding</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/data/onehot.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>One-Hot Encoding</span><a class="fa fa-bars" href="#"></a></div></header><h1><a class="nav-anchor" id="One-Hot-Encoding-1" href="#One-Hot-Encoding-1">One-Hot Encoding</a></h1><p>It's common to encode categorical variables (like <code>true</code>, <code>false</code> or <code>cat</code>, <code>dog</code>) in "one-of-k" or <a href="https://en.wikipedia.org/wiki/One-hot">"one-hot"</a> form. Flux provides the <code>onehot</code> function to make this easy.</p><pre><code class="language-none">julia> using Flux: onehot
|
||||
|
||||
julia> onehot(:b, [:a, :b, :c])
|
||||
3-element Flux.OneHotVector:
|
||||
|
||||
@ -6,7 +6,7 @@ m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
|
||||
|
||||
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="../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="models/basics.html">Basics</a></li><li><a class="toctext" href="models/recurrence.html">Recurrence</a></li><li><a class="toctext" href="models/layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="training/training.html">Training</a></li></ul></li><li><a class="toctext" href="data/onehot.html">One-Hot Encoding</a></li><li class="current"><a class="toctext" href="gpu.html">GPU Support</a><ul class="internal"></ul></li><li><a class="toctext" href="contributing.html">Contributing & Help</a></li></ul></nav><article id="docs"><header><nav><ul><li><a href="gpu.html">GPU Support</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/gpu.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>GPU Support</span><a class="fa fa-bars" href="#"></a></div></header><h1><a class="nav-anchor" id="GPU-Support-1" href="#GPU-Support-1">GPU Support</a></h1><p>Support for array operations on other hardware backends, like GPUs, is provided by external packages like <a href="https://github.com/JuliaGPU/CuArrays.jl">CuArrays</a> and <a href="https://github.com/JuliaGPU/CLArrays.jl">CLArrays</a>. Flux doesn't care what array type you use, so we can just plug these in without any other changes.</p><p>For example, we can use <code>CuArrays</code> (with the <code>cu</code> converter) to run our <a href="models/basics.html">basic example</a> on an NVIDIA GPU.</p><pre><code class="language-julia">using CuArrays
|
||||
</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="../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="models/basics.html">Basics</a></li><li><a class="toctext" href="models/recurrence.html">Recurrence</a></li><li><a class="toctext" href="models/layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="training/training.html">Training</a></li></ul></li><li><a class="toctext" href="data/onehot.html">One-Hot Encoding</a></li><li class="current"><a class="toctext" href="gpu.html">GPU Support</a><ul class="internal"></ul></li><li><a class="toctext" href="community.html">Community</a></li></ul></nav><article id="docs"><header><nav><ul><li><a href="gpu.html">GPU Support</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/gpu.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>GPU Support</span><a class="fa fa-bars" href="#"></a></div></header><h1><a class="nav-anchor" id="GPU-Support-1" href="#GPU-Support-1">GPU Support</a></h1><p>Support for array operations on other hardware backends, like GPUs, is provided by external packages like <a href="https://github.com/JuliaGPU/CuArrays.jl">CuArrays</a> and <a href="https://github.com/JuliaGPU/CLArrays.jl">CLArrays</a>. Flux doesn't care what array type you use, so we can just plug these in without any other changes.</p><p>For example, we can use <code>CuArrays</code> (with the <code>cu</code> converter) to run our <a href="models/basics.html">basic example</a> on an NVIDIA GPU.</p><pre><code class="language-julia">using CuArrays
|
||||
|
||||
W = cu(rand(2, 5)) # a 2×5 CuArray
|
||||
b = cu(rand(2))
|
||||
@ -22,4 +22,4 @@ d(cu(rand(10))) # CuArray output
|
||||
|
||||
m = Chain(Dense(10, 5, σ), Dense(5, 2), softmax)
|
||||
m = mapleaves(cu, m)
|
||||
d(cu(rand(10)))</code></pre><p>The <a href="https://github.com/FluxML/model-zoo/blob/master/mnist/mnist.jl">mnist example</a> contains the code needed to run the model on the GPU; just uncomment the lines after <code>using CuArrays</code>.</p><footer><hr/><a class="previous" href="data/onehot.html"><span class="direction">Previous</span><span class="title">One-Hot Encoding</span></a><a class="next" href="contributing.html"><span class="direction">Next</span><span class="title">Contributing & Help</span></a></footer></article></body></html>
|
||||
d(cu(rand(10)))</code></pre><p>The <a href="https://github.com/FluxML/model-zoo/blob/master/mnist/mnist.jl">mnist example</a> contains the code needed to run the model on the GPU; just uncomment the lines after <code>using CuArrays</code>.</p><footer><hr/><a class="previous" href="data/onehot.html"><span class="direction">Previous</span><span class="title">One-Hot Encoding</span></a><a class="next" href="community.html"><span class="direction">Next</span><span class="title">Community</span></a></footer></article></body></html>
|
||||
|
||||
@ -6,5 +6,5 @@ m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
|
||||
|
||||
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="../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li class="current"><a class="toctext" href="index.html">Home</a><ul class="internal"><li class="toplevel"><a class="toctext" href="#Installation-1">Installation</a></li></ul></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="models/basics.html">Basics</a></li><li><a class="toctext" href="models/recurrence.html">Recurrence</a></li><li><a class="toctext" href="models/layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="training/training.html">Training</a></li></ul></li><li><a class="toctext" href="data/onehot.html">One-Hot Encoding</a></li><li><a class="toctext" href="gpu.html">GPU Support</a></li><li><a class="toctext" href="contributing.html">Contributing & Help</a></li></ul></nav><article id="docs"><header><nav><ul><li><a href="index.html">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. The whole stack is implemented in clean Julia code (right down to the <a href="https://github.com/FluxML/CuArrays.jl">GPU kernels</a>) and any part can be tweaked to your liking.</p><h1><a class="nav-anchor" id="Installation-1" href="#Installation-1">Installation</a></h1><p>Install <a href="https://julialang.org/downloads/">Julia 0.6.0 or later</a>, if you haven't already.</p><pre><code class="language-julia">Pkg.add("Flux")
|
||||
</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="../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li class="current"><a class="toctext" href="index.html">Home</a><ul class="internal"><li class="toplevel"><a class="toctext" href="#Installation-1">Installation</a></li></ul></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="models/basics.html">Basics</a></li><li><a class="toctext" href="models/recurrence.html">Recurrence</a></li><li><a class="toctext" href="models/layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="training/training.html">Training</a></li></ul></li><li><a class="toctext" href="data/onehot.html">One-Hot Encoding</a></li><li><a class="toctext" href="gpu.html">GPU Support</a></li><li><a class="toctext" href="community.html">Community</a></li></ul></nav><article id="docs"><header><nav><ul><li><a href="index.html">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. The whole stack is implemented in clean Julia code (right down to the <a href="https://github.com/FluxML/CuArrays.jl">GPU kernels</a>) and any part can be tweaked to your liking.</p><h1><a class="nav-anchor" id="Installation-1" href="#Installation-1">Installation</a></h1><p>Install <a href="https://julialang.org/downloads/">Julia 0.6.0 or later</a>, if you haven't already.</p><pre><code class="language-julia">Pkg.add("Flux")
|
||||
Pkg.test("Flux") # Check things installed correctly</code></pre><p>Start with the <a href="models/basics.html">basics</a>. The <a href="https://github.com/FluxML/model-zoo/">model zoo</a> is also a good starting point for many common kinds of models.</p><footer><hr/><a class="next" href="models/basics.html"><span class="direction">Next</span><span class="title">Basics</span></a></footer></article></body></html>
|
||||
|
||||
@ -6,7 +6,7 @@ m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
|
||||
|
||||
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="../../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="../index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li class="current"><a class="toctext" href="basics.html">Basics</a><ul class="internal"><li><a class="toctext" href="#Taking-Gradients-1">Taking Gradients</a></li><li><a class="toctext" href="#Building-Layers-1">Building Layers</a></li><li><a class="toctext" href="#Stacking-It-Up-1">Stacking It Up</a></li></ul></li><li><a class="toctext" href="recurrence.html">Recurrence</a></li><li><a class="toctext" href="layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="../training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="../training/training.html">Training</a></li></ul></li><li><a class="toctext" href="../data/onehot.html">One-Hot Encoding</a></li><li><a class="toctext" href="../gpu.html">GPU Support</a></li><li><a class="toctext" href="../contributing.html">Contributing & Help</a></li></ul></nav><article id="docs"><header><nav><ul><li>Building Models</li><li><a href="basics.html">Basics</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/models/basics.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>Basics</span><a class="fa fa-bars" href="#"></a></div></header><h1><a class="nav-anchor" id="Model-Building-Basics-1" href="#Model-Building-Basics-1">Model-Building Basics</a></h1><h2><a class="nav-anchor" id="Taking-Gradients-1" href="#Taking-Gradients-1">Taking Gradients</a></h2><p>Consider a simple linear regression, which tries to predict an output array <code>y</code> from an input <code>x</code>. (It's a good idea to follow this example in the Julia repl.)</p><pre><code class="language-julia">W = rand(2, 5)
|
||||
</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="../../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="../index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li class="current"><a class="toctext" href="basics.html">Basics</a><ul class="internal"><li><a class="toctext" href="#Taking-Gradients-1">Taking Gradients</a></li><li><a class="toctext" href="#Building-Layers-1">Building Layers</a></li><li><a class="toctext" href="#Stacking-It-Up-1">Stacking It Up</a></li></ul></li><li><a class="toctext" href="recurrence.html">Recurrence</a></li><li><a class="toctext" href="layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="../training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="../training/training.html">Training</a></li></ul></li><li><a class="toctext" href="../data/onehot.html">One-Hot Encoding</a></li><li><a class="toctext" href="../gpu.html">GPU Support</a></li><li><a class="toctext" href="../community.html">Community</a></li></ul></nav><article id="docs"><header><nav><ul><li>Building Models</li><li><a href="basics.html">Basics</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/models/basics.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>Basics</span><a class="fa fa-bars" href="#"></a></div></header><h1><a class="nav-anchor" id="Model-Building-Basics-1" href="#Model-Building-Basics-1">Model-Building Basics</a></h1><h2><a class="nav-anchor" id="Taking-Gradients-1" href="#Taking-Gradients-1">Taking Gradients</a></h2><p>Consider a simple linear regression, which tries to predict an output array <code>y</code> from an input <code>x</code>. (It's a good idea to follow this example in the Julia repl.)</p><pre><code class="language-julia">W = rand(2, 5)
|
||||
b = rand(2)
|
||||
|
||||
predict(x) = W*x .+ b
|
||||
|
||||
@ -6,9 +6,9 @@ m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
|
||||
|
||||
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="../../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="../index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="basics.html">Basics</a></li><li><a class="toctext" href="recurrence.html">Recurrence</a></li><li class="current"><a class="toctext" href="layers.html">Layer Reference</a><ul class="internal"><li><a class="toctext" href="#Model-Layers-1">Model Layers</a></li></ul></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="../training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="../training/training.html">Training</a></li></ul></li><li><a class="toctext" href="../data/onehot.html">One-Hot Encoding</a></li><li><a class="toctext" href="../gpu.html">GPU Support</a></li><li><a class="toctext" href="../contributing.html">Contributing & Help</a></li></ul></nav><article id="docs"><header><nav><ul><li>Building Models</li><li><a href="layers.html">Layer Reference</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/models/layers.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>Layer Reference</span><a class="fa fa-bars" href="#"></a></div></header><h2><a class="nav-anchor" id="Model-Layers-1" href="#Model-Layers-1">Model Layers</a></h2><p>These core layers form the foundation of almost all neural networks.</p><section class="docstring"><div class="docstring-header"><a class="docstring-binding" id="Flux.Chain" href="#Flux.Chain"><code>Flux.Chain</code></a> — <span class="docstring-category">Type</span>.</div><div><pre><code class="language-none">Chain(layers...)</code></pre><p>Chain multiple layers / functions together, so that they are called in sequence on a given input.</p><pre><code class="language-none">m = Chain(x -> x^2, x -> x+1)
|
||||
</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="../../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="../index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="basics.html">Basics</a></li><li><a class="toctext" href="recurrence.html">Recurrence</a></li><li class="current"><a class="toctext" href="layers.html">Layer Reference</a><ul class="internal"><li><a class="toctext" href="#Model-Layers-1">Model Layers</a></li></ul></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="../training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="../training/training.html">Training</a></li></ul></li><li><a class="toctext" href="../data/onehot.html">One-Hot Encoding</a></li><li><a class="toctext" href="../gpu.html">GPU Support</a></li><li><a class="toctext" href="../community.html">Community</a></li></ul></nav><article id="docs"><header><nav><ul><li>Building Models</li><li><a href="layers.html">Layer Reference</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/models/layers.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>Layer Reference</span><a class="fa fa-bars" href="#"></a></div></header><h2><a class="nav-anchor" id="Model-Layers-1" href="#Model-Layers-1">Model Layers</a></h2><p>These core layers form the foundation of almost all neural networks.</p><section class="docstring"><div class="docstring-header"><a class="docstring-binding" id="Flux.Chain" href="#Flux.Chain"><code>Flux.Chain</code></a> — <span class="docstring-category">Type</span>.</div><div><pre><code class="language-none">Chain(layers...)</code></pre><p>Chain multiple layers / functions together, so that they are called in sequence on a given input.</p><pre><code class="language-none">m = Chain(x -> x^2, x -> x+1)
|
||||
m(5) == 26
|
||||
|
||||
m = Chain(Dense(10, 5), Dense(5, 2))
|
||||
x = rand(10)
|
||||
m(x) == m[2](m[1](x))</code></pre><p><code>Chain</code> also supports indexing and slicing, e.g. <code>m[2]</code> or <code>m[1:end-1]</code>. <code>m[1:3](x)</code> will calculate the output of the first three layers.</p></div><a class="source-link" target="_blank" href="https://github.com/FluxML/Flux.jl/blob/55ba236da6ea59230b477a3600e7611a15ccb895/src/layers/basic.jl#L1-L16">source</a></section><section class="docstring"><div class="docstring-header"><a class="docstring-binding" id="Flux.Dense" href="#Flux.Dense"><code>Flux.Dense</code></a> — <span class="docstring-category">Type</span>.</div><div><pre><code class="language-none">Dense(in::Integer, out::Integer, σ = identity)</code></pre><p>Creates a traditional <code>Dense</code> layer with parameters <code>W</code> and <code>b</code>.</p><pre><code class="language-none">y = σ.(W * x .+ b)</code></pre><p>The input <code>x</code> must be a vector of length <code>in</code>, or a batch of vectors represented as an <code>in × N</code> matrix. The out <code>y</code> will be a vector or batch of length <code>in</code>.</p></div><a class="source-link" target="_blank" href="https://github.com/FluxML/Flux.jl/blob/55ba236da6ea59230b477a3600e7611a15ccb895/src/layers/basic.jl#L38-L47">source</a></section><footer><hr/><a class="previous" href="recurrence.html"><span class="direction">Previous</span><span class="title">Recurrence</span></a><a class="next" href="../training/optimisers.html"><span class="direction">Next</span><span class="title">Optimisers</span></a></footer></article></body></html>
|
||||
m(x) == m[2](m[1](x))</code></pre><p><code>Chain</code> also supports indexing and slicing, e.g. <code>m[2]</code> or <code>m[1:end-1]</code>. <code>m[1:3](x)</code> will calculate the output of the first three layers.</p></div><a class="source-link" target="_blank" href="https://github.com/FluxML/Flux.jl/blob/92f65f91c595669fc74e322132df582332cdea65/src/layers/basic.jl#L1-L16">source</a></section><section class="docstring"><div class="docstring-header"><a class="docstring-binding" id="Flux.Dense" href="#Flux.Dense"><code>Flux.Dense</code></a> — <span class="docstring-category">Type</span>.</div><div><pre><code class="language-none">Dense(in::Integer, out::Integer, σ = identity)</code></pre><p>Creates a traditional <code>Dense</code> layer with parameters <code>W</code> and <code>b</code>.</p><pre><code class="language-none">y = σ.(W * x .+ b)</code></pre><p>The input <code>x</code> must be a vector of length <code>in</code>, or a batch of vectors represented as an <code>in × N</code> matrix. The out <code>y</code> will be a vector or batch of length <code>in</code>.</p></div><a class="source-link" target="_blank" href="https://github.com/FluxML/Flux.jl/blob/92f65f91c595669fc74e322132df582332cdea65/src/layers/basic.jl#L38-L47">source</a></section><footer><hr/><a class="previous" href="recurrence.html"><span class="direction">Previous</span><span class="title">Recurrence</span></a><a class="next" href="../training/optimisers.html"><span class="direction">Next</span><span class="title">Optimisers</span></a></footer></article></body></html>
|
||||
|
||||
@ -6,7 +6,7 @@ m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
|
||||
|
||||
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="../../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="../index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="basics.html">Basics</a></li><li class="current"><a class="toctext" href="recurrence.html">Recurrence</a><ul class="internal"><li><a class="toctext" href="#Recurrent-Cells-1">Recurrent Cells</a></li><li><a class="toctext" href="#Stateful-Models-1">Stateful Models</a></li><li><a class="toctext" href="#Sequences-1">Sequences</a></li><li><a class="toctext" href="#Truncating-Gradients-1">Truncating Gradients</a></li></ul></li><li><a class="toctext" href="layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="../training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="../training/training.html">Training</a></li></ul></li><li><a class="toctext" href="../data/onehot.html">One-Hot Encoding</a></li><li><a class="toctext" href="../gpu.html">GPU Support</a></li><li><a class="toctext" href="../contributing.html">Contributing & Help</a></li></ul></nav><article id="docs"><header><nav><ul><li>Building Models</li><li><a href="recurrence.html">Recurrence</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/models/recurrence.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>Recurrence</span><a class="fa fa-bars" href="#"></a></div></header><h1><a class="nav-anchor" id="Recurrent-Models-1" href="#Recurrent-Models-1">Recurrent Models</a></h1><h2><a class="nav-anchor" id="Recurrent-Cells-1" href="#Recurrent-Cells-1">Recurrent Cells</a></h2><p>In the simple feedforward case, our model <code>m</code> is a simple function from various inputs <code>xᵢ</code> to predictions <code>yᵢ</code>. (For example, each <code>x</code> might be an MNIST digit and each <code>y</code> a digit label.) Each prediction is completely independent of any others, and using the same <code>x</code> will always produce the same <code>y</code>.</p><pre><code class="language-julia">y₁ = f(x₁)
|
||||
</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="../../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="../index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="basics.html">Basics</a></li><li class="current"><a class="toctext" href="recurrence.html">Recurrence</a><ul class="internal"><li><a class="toctext" href="#Recurrent-Cells-1">Recurrent Cells</a></li><li><a class="toctext" href="#Stateful-Models-1">Stateful Models</a></li><li><a class="toctext" href="#Sequences-1">Sequences</a></li><li><a class="toctext" href="#Truncating-Gradients-1">Truncating Gradients</a></li></ul></li><li><a class="toctext" href="layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="../training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="../training/training.html">Training</a></li></ul></li><li><a class="toctext" href="../data/onehot.html">One-Hot Encoding</a></li><li><a class="toctext" href="../gpu.html">GPU Support</a></li><li><a class="toctext" href="../community.html">Community</a></li></ul></nav><article id="docs"><header><nav><ul><li>Building Models</li><li><a href="recurrence.html">Recurrence</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/models/recurrence.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>Recurrence</span><a class="fa fa-bars" href="#"></a></div></header><h1><a class="nav-anchor" id="Recurrent-Models-1" href="#Recurrent-Models-1">Recurrent Models</a></h1><h2><a class="nav-anchor" id="Recurrent-Cells-1" href="#Recurrent-Cells-1">Recurrent Cells</a></h2><p>In the simple feedforward case, our model <code>m</code> is a simple function from various inputs <code>xᵢ</code> to predictions <code>yᵢ</code>. (For example, each <code>x</code> might be an MNIST digit and each <code>y</code> a digit label.) Each prediction is completely independent of any others, and using the same <code>x</code> will always produce the same <code>y</code>.</p><pre><code class="language-julia">y₁ = f(x₁)
|
||||
y₂ = f(x₂)
|
||||
y₃ = f(x₃)
|
||||
# ...</code></pre><p>Recurrent networks introduce a <em>hidden state</em> that gets carried over each time we run the model. The model now takes the old <code>h</code> as an input, and produces a new <code>h</code> as output, each time we run it.</p><pre><code class="language-julia">h = # ... initial state ...
|
||||
|
||||
@ -6,4 +6,4 @@ m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
|
||||
|
||||
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="../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="models/basics.html">Basics</a></li><li><a class="toctext" href="models/recurrence.html">Recurrence</a></li><li><a class="toctext" href="models/layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="training/training.html">Training</a></li></ul></li><li><a class="toctext" href="data/onehot.html">One-Hot Encoding</a></li><li><a class="toctext" href="gpu.html">GPU Support</a></li><li><a class="toctext" href="contributing.html">Contributing & Help</a></li></ul></nav><article><header><nav><ul><li>Search</li></ul></nav><hr/><div id="topbar"><span>Search</span><a class="fa fa-bars" href="#"></a></div></header><h1>Search</h1><p id="search-info">Number of results: <span id="search-results-number">loading...</span></p><ul id="search-results"></ul></article></body><script src="search_index.js"></script><script src="assets/search.js"></script></html>
|
||||
</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="../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="models/basics.html">Basics</a></li><li><a class="toctext" href="models/recurrence.html">Recurrence</a></li><li><a class="toctext" href="models/layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="training/optimisers.html">Optimisers</a></li><li><a class="toctext" href="training/training.html">Training</a></li></ul></li><li><a class="toctext" href="data/onehot.html">One-Hot Encoding</a></li><li><a class="toctext" href="gpu.html">GPU Support</a></li><li><a class="toctext" href="community.html">Community</a></li></ul></nav><article><header><nav><ul><li>Search</li></ul></nav><hr/><div id="topbar"><span>Search</span><a class="fa fa-bars" href="#"></a></div></header><h1>Search</h1><p id="search-info">Number of results: <span id="search-results-number">loading...</span></p><ul id="search-results"></ul></article></body><script src="search_index.js"></script><script src="assets/search.js"></script></html>
|
||||
|
||||
@ -305,19 +305,19 @@ var documenterSearchIndex = {"docs": [
|
||||
},
|
||||
|
||||
{
|
||||
"location": "contributing.html#",
|
||||
"page": "Contributing & Help",
|
||||
"title": "Contributing & Help",
|
||||
"location": "community.html#",
|
||||
"page": "Community",
|
||||
"title": "Community",
|
||||
"category": "page",
|
||||
"text": ""
|
||||
},
|
||||
|
||||
{
|
||||
"location": "contributing.html#Contributing-and-Help-1",
|
||||
"page": "Contributing & Help",
|
||||
"title": "Contributing & Help",
|
||||
"location": "community.html#Community-1",
|
||||
"page": "Community",
|
||||
"title": "Community",
|
||||
"category": "section",
|
||||
"text": "If you need help, please ask on the Julia forum, the slack (channel #machine-learning), or Flux's Gitter.Right now, the best way to help out is to try out the examples and report any issues or missing features as you find them. The second best way is to help us spread the word, perhaps by starring the repo.If you're interested in hacking on Flux, most of the code is pretty straightforward. Adding new layer definitions or cost functions is simple using the Flux DSL itself, and things like data utilities and training processes are all plain Julia code.If you get stuck or need anything, let us know!"
|
||||
"text": "All Flux users are welcome to join our community on the Julia forum, the slack (channel #machine-learning), or Flux's Gitter. If you have questions or issues we'll try to help you out.If you're interested in hacking on Flux, the source code is open and easy to understand – it's all just the same Julia code you work with normally. You might be interested in our intro issues to get started."
|
||||
},
|
||||
|
||||
]}
|
||||
|
||||
File diff suppressed because one or more lines are too long
@ -6,7 +6,7 @@ m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
|
||||
|
||||
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="../../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="../index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="../models/basics.html">Basics</a></li><li><a class="toctext" href="../models/recurrence.html">Recurrence</a></li><li><a class="toctext" href="../models/layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="optimisers.html">Optimisers</a></li><li class="current"><a class="toctext" href="training.html">Training</a><ul class="internal"><li><a class="toctext" href="#Loss-Functions-1">Loss Functions</a></li><li><a class="toctext" href="#Datasets-1">Datasets</a></li><li><a class="toctext" href="#Callbacks-1">Callbacks</a></li></ul></li></ul></li><li><a class="toctext" href="../data/onehot.html">One-Hot Encoding</a></li><li><a class="toctext" href="../gpu.html">GPU Support</a></li><li><a class="toctext" href="../contributing.html">Contributing & Help</a></li></ul></nav><article id="docs"><header><nav><ul><li>Training Models</li><li><a href="training.html">Training</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/training/training.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>Training</span><a class="fa fa-bars" href="#"></a></div></header><h1><a class="nav-anchor" id="Training-1" href="#Training-1">Training</a></h1><p>To actually train a model we need three things:</p><ul><li><p>A <em>model loss function</em>, that evaluates how well a model is doing given some input data.</p></li><li><p>A collection of data points that will be provided to the loss function.</p></li><li><p>An <a href="optimisers.html">optimiser</a> that will update the model parameters appropriately.</p></li></ul><p>With these we can call <code>Flux.train!</code>:</p><pre><code class="language-julia">Flux.train!(modelLoss, data, opt)</code></pre><p>There are plenty of examples in the <a href="https://github.com/FluxML/model-zoo">model zoo</a>.</p><h2><a class="nav-anchor" id="Loss-Functions-1" href="#Loss-Functions-1">Loss Functions</a></h2><p>The <code>loss</code> that we defined in <a href="../models/basics.html">basics</a> is completely valid for training. We can also define a loss in terms of some model:</p><pre><code class="language-julia">m = Chain(
|
||||
</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="../../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.html"><input id="search-query" name="q" type="text" placeholder="Search docs"/></form><ul><li><a class="toctext" href="../index.html">Home</a></li><li><span class="toctext">Building Models</span><ul><li><a class="toctext" href="../models/basics.html">Basics</a></li><li><a class="toctext" href="../models/recurrence.html">Recurrence</a></li><li><a class="toctext" href="../models/layers.html">Layer Reference</a></li></ul></li><li><span class="toctext">Training Models</span><ul><li><a class="toctext" href="optimisers.html">Optimisers</a></li><li class="current"><a class="toctext" href="training.html">Training</a><ul class="internal"><li><a class="toctext" href="#Loss-Functions-1">Loss Functions</a></li><li><a class="toctext" href="#Datasets-1">Datasets</a></li><li><a class="toctext" href="#Callbacks-1">Callbacks</a></li></ul></li></ul></li><li><a class="toctext" href="../data/onehot.html">One-Hot Encoding</a></li><li><a class="toctext" href="../gpu.html">GPU Support</a></li><li><a class="toctext" href="../community.html">Community</a></li></ul></nav><article id="docs"><header><nav><ul><li>Training Models</li><li><a href="training.html">Training</a></li></ul><a class="edit-page" href="https://github.com/FluxML/Flux.jl/blob/master/docs/src/training/training.md"><span class="fa"></span> Edit on GitHub</a></nav><hr/><div id="topbar"><span>Training</span><a class="fa fa-bars" href="#"></a></div></header><h1><a class="nav-anchor" id="Training-1" href="#Training-1">Training</a></h1><p>To actually train a model we need three things:</p><ul><li><p>A <em>model loss function</em>, that evaluates how well a model is doing given some input data.</p></li><li><p>A collection of data points that will be provided to the loss function.</p></li><li><p>An <a href="optimisers.html">optimiser</a> that will update the model parameters appropriately.</p></li></ul><p>With these we can call <code>Flux.train!</code>:</p><pre><code class="language-julia">Flux.train!(modelLoss, data, opt)</code></pre><p>There are plenty of examples in the <a href="https://github.com/FluxML/model-zoo">model zoo</a>.</p><h2><a class="nav-anchor" id="Loss-Functions-1" href="#Loss-Functions-1">Loss Functions</a></h2><p>The <code>loss</code> that we defined in <a href="../models/basics.html">basics</a> is completely valid for training. We can also define a loss in terms of some model:</p><pre><code class="language-julia">m = Chain(
|
||||
Dense(784, 32, σ),
|
||||
Dense(32, 10), softmax)
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user