build based on e27ae25

LuxDL · Sep 21, 2024 · 0fa9512 · 0fa9512
1 parent b9bc383
commit 0fa9512
Show file tree

Hide file tree

Showing 165 changed files with 13,937 additions and 0 deletions.
diff --git a/previews/PR949/404.html b/previews/PR949/404.html
@@ -0,0 +1,31 @@
+<!DOCTYPE html>
+<html lang="en-US" dir="ltr">
+  <head>
+    <meta charset="utf-8">
+    <meta name="viewport" content="width=device-width,initial-scale=1">
+    <title>404 | Lux.jl Docs</title>
+    <meta name="description" content="Not Found">
+    <meta name="generator" content="VitePress v1.3.4">
+    <link rel="preload stylesheet" href="/previews/PR949/assets/style.CYFZZFrM.css" as="style">
+
+    <script type="module" src="/previews/PR949/assets/app.Dw-Z_I16.js"></script>
+    <link rel="preload" href="/previews/PR949/assets/inter-roman-latin.Di8DUHzh.woff2" as="font" type="font/woff2" crossorigin="">
+    <script async src="https://www.googletagmanager.com/gtag/js?id=G-Q8GYTEVTZ2"></script>
+    <script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}gtag("js",new Date),gtag("config","G-Q8GYTEVTZ2");</script>
+    <link rel="apple-touch-icon" sizes="180x180" href="/apple-touch-icon.png">
+    <link rel="icon" type="image/png" sizes="32x32" href="/favicon-32x32.png">
+    <link rel="icon" type="image/png" sizes="16x16" href="/favicon-16x16.png">
+    <link rel="icon" href="/favicon.ico">
+    <link rel="manifest" href="/site.webmanifest">
+    <link rel="icon" href="REPLACE_ME_DOCUMENTER_VITEPRESS_FAVICON">
+    <script src="/previews/versions.js"></script>
+    <script src="/previews/PR949/siteinfo.js"></script>
+    <script id="check-dark-mode">(()=>{const e=localStorage.getItem("vitepress-theme-appearance")||"auto",a=window.matchMedia("(prefers-color-scheme: dark)").matches;(!e||e==="auto"?a:e==="dark")&&document.documentElement.classList.add("dark")})();</script>
+    <script id="check-mac-os">document.documentElement.classList.toggle("mac",/Mac|iPhone|iPod|iPad/i.test(navigator.platform));</script>
+  </head>
+  <body>
+    <div id="app"></div>
+    <script>window.__VP_HASH_MAP__=JSON.parse("{\"api_accelerator_support_mldatadevices.md\":\"BMDHIxdP\",\"api_building_blocks_luxcore.md\":\"BKYx5MWw\",\"api_building_blocks_luxlib.md\":\"109zBEo6\",\"api_building_blocks_weightinitializers.md\":\"BcZLrQJK\",\"api_lux_autodiff.md\":\"PejxQjxl\",\"api_lux_contrib.md\":\"BlnRN77U\",\"api_lux_distributed_utils.md\":\"BPAgzTJM\",\"api_lux_interop.md\":\"CIzlrMtw\",\"api_lux_layers.md\":\"VaZqS53q\",\"api_lux_utilities.md\":\"KzJYd7pR\",\"api_testing_functionality_luxtestutils.md\":\"BsNMyfB8\",\"ecosystem.md\":\"B7DbvBCj\",\"index.md\":\"BEQG_MYP\",\"introduction_citation.md\":\"pY1DdJrQ\",\"introduction_index.md\":\"BIVeyKby\",\"introduction_overview.md\":\"Dw3plv2j\",\"introduction_resources.md\":\"DFa4bscZ\",\"introduction_updating_to_v1.md\":\"DMGnMpb2\",\"manual_autodiff.md\":\"-GlQlAmA\",\"manual_debugging.md\":\"BUPXphTf\",\"manual_dispatch_custom_input.md\":\"mb9xrke9\",\"manual_distributed_utils.md\":\"CccZjOEO\",\"manual_freezing_model_parameters.md\":\"BrmdBm6e\",\"manual_gpu_management.md\":\"Asa4cp5K\",\"manual_interface.md\":\"xgLle2sz\",\"manual_migrate_from_flux.md\":\"DRQx5DhR\",\"manual_nested_autodiff.md\":\"Ctn1TrIB\",\"manual_nn_inside_gpu_kernels.md\":\"B5J_qXz0\",\"manual_performance_pitfalls.md\":\"CPgeXY1s\",\"manual_preferences.md\":\"C8hQm02W\",\"manual_weight_initializers.md\":\"BczvGcJK\",\"tutorials_advanced_1_gravitationalwaveform.md\":\"iMbGcWNv\",\"tutorials_beginner_1_basics.md\":\"DJThZHBo\",\"tutorials_beginner_2_polynomialfitting.md\":\"D3DtXpt3\",\"tutorials_beginner_3_simplernn.md\":\"BbcesOQR\",\"tutorials_beginner_4_simplechains.md\":\"C0ehagYj\",\"tutorials_beginner_5_optimizationintegration.md\":\"CkIYlZBw\",\"tutorials_index.md\":\"BycmLOBs\",\"tutorials_intermediate_1_neuralode.md\":\"BZ4W7puu\",\"tutorials_intermediate_2_bayesiannn.md\":\"FDfgI5Be\",\"tutorials_intermediate_3_hypernet.md\":\"sK_4ps88\",\"tutorials_intermediate_4_pinn2dpde.md\":\"dWD_L60i\"}");window.__VP_SITE_DATA__=JSON.parse("{\"lang\":\"en-US\",\"dir\":\"ltr\",\"title\":\"Lux.jl Docs\",\"description\":\"Documentation for LuxDL Repositories\",\"base\":\"/previews/PR949/\",\"head\":[],\"router\":{\"prefetchLinks\":true},\"appearance\":true,\"themeConfig\":{\"outline\":\"deep\",\"logo\":{\"light\":\"/lux-logo.svg\",\"dark\":\"/lux-logo-dark.svg\"},\"search\":{\"provider\":\"local\",\"options\":{\"detailedView\":true}},\"nav\":[{\"text\":\"Home\",\"link\":\"/\"},{\"text\":\"Getting Started\",\"link\":\"/introduction\"},{\"text\":\"Benchmarks\",\"link\":\"https://lux.csail.mit.edu/benchmarks/\"},{\"text\":\"Tutorials\",\"link\":\"/tutorials/\"},{\"text\":\"Manual\",\"link\":\"/manual/interface\"},{\"text\":\"API\",\"items\":[{\"text\":\"Lux\",\"items\":[{\"text\":\"Built-In Layers\",\"link\":\"/api/Lux/layers\"},{\"text\":\"Automatic Differentiation\",\"link\":\"/api/Lux/autodiff\"},{\"text\":\"Utilities\",\"link\":\"/api/Lux/utilities\"},{\"text\":\"Experimental\",\"link\":\"/api/Lux/contrib\"},{\"text\":\"InterOp\",\"link\":\"/api/Lux/interop\"},{\"text\":\"DistributedUtils\",\"link\":\"/api/Lux/distributed_utils\"}]},{\"text\":\"Accelerator Support\",\"items\":[{\"text\":\"MLDataDevices\",\"link\":\"/api/Accelerator_Support/MLDataDevices\"}]},{\"text\":\"Building Blocks\",\"items\":[{\"text\":\"LuxCore\",\"link\":\"/api/Building_Blocks/LuxCore\"},{\"text\":\"LuxLib\",\"link\":\"/api/Building_Blocks/LuxLib\"},{\"text\":\"WeightInitializers\",\"link\":\"/api/Building_Blocks/WeightInitializers\"},{\"text\":\"NNlib\",\"link\":\"https://fluxml.ai/NNlib.jl/dev/\"},{\"text\":\"Activation Functions\",\"link\":\"https://fluxml.ai/NNlib.jl/dev/reference/#Activation-Functions\"}]},{\"text\":\"Testing Functionality\",\"items\":[{\"text\":\"LuxTestUtils\",\"link\":\"/api/Testing_Functionality/LuxTestUtils\"}]}]},{\"component\":\"VersionPicker\"}],\"sidebar\":{\"/introduction/\":{\"text\":\"Getting Started\",\"collapsed\":false,\"items\":[{\"text\":\"Introduction\",\"link\":\"/introduction\"},{\"text\":\"Overview\",\"link\":\"/introduction/overview\"},{\"text\":\"Resources\",\"link\":\"/introduction/resources\"},{\"text\":\"Updating to v1\",\"link\":\"/introduction/updating_to_v1\"},{\"text\":\"Citation\",\"link\":\"/introduction/citation\"}]},\"/tutorials/\":{\"text\":\"Tutorials\",\"collapsed\":false,\"items\":[{\"text\":\"Overview\",\"link\":\"/tutorials/\"},{\"text\":\"Beginner\",\"collapsed\":false,\"items\":[{\"text\":\"Julia & Lux for the Uninitiated\",\"link\":\"/tutorials/beginner/1_Basics\"},{\"text\":\"Fitting a Polynomial using MLP\",\"link\":\"/tutorials/beginner/2_PolynomialFitting\"},{\"text\":\"Training a Simple LSTM\",\"link\":\"/tutorials/beginner/3_SimpleRNN\"},{\"text\":\"MNIST Classification with SimpleChains\",\"link\":\"/tutorials/beginner/4_SimpleChains\"},{\"text\":\"Fitting with Optimization.jl\",\"link\":\"/tutorials/beginner/5_OptimizationIntegration\"}]},{\"text\":\"Intermediate\",\"collapsed\":false,\"items\":[{\"text\":\"MNIST Classification using Neural ODEs\",\"link\":\"/tutorials/intermediate/1_NeuralODE\"},{\"text\":\"Bayesian Neural Network\",\"link\":\"/tutorials/intermediate/2_BayesianNN\"},{\"text\":\"Training a HyperNetwork on MNIST and FashionMNIST\",\"link\":\"/tutorials/intermediate/3_HyperNet\"},{\"text\":\"Training a PINN on 2D PDE\",\"link\":\"/tutorials/intermediate/4_PINN2DPDE\"}]},{\"text\":\"Advanced\",\"collapsed\":false,\"items\":[{\"text\":\"Training a Neural ODE to Model Gravitational Waveforms\",\"link\":\"/tutorials/advanced/1_GravitationalWaveForm\"}]},{\"text\":\"Large Models\",\"collapsed\":true,\"items\":[{\"text\":\"Training Image Classification Models on ImageNet with Distributed Data Parallel Training\",\"link\":\"https://github.com/LuxDL/Lux.jl/tree/main/examples/ImageNet\"},{\"text\":\"Training a DDIM (Diffusion Model) for Image Generation\",\"link\":\"https://github.com/LuxDL/Lux.jl/tree/main/examples/DDIM\"},{\"text\":\"ConvMixer on CIFAR-10\",\"link\":\"https://github.com/LuxDL/Lux.jl/tree/main/examples/ConvMixer\"}]},{\"text\":\"3rd Party Tutorials\",\"collapsed\":true,\"items\":[{\"text\":\"PINNs (NeuralPDE.jl)\",\"link\":\"https://docs.sciml.ai/NeuralPDE/stable/tutorials/pdesystem/\"},{\"text\":\"UDEs (SciMLSensitivity.jl)\",\"link\":\"https://docs.sciml.ai/SciMLSensitivity/stable/tutorials/data_parallel/\"},{\"text\":\"Neural DEs (DiffEqFlux.jl)\",\"link\":\"https://docs.sciml.ai/DiffEqFlux/stable/examples/neural_ode/\"},{\"text\":\"DEQs (DeepEquilibriumNetworks.jl)\",\"link\":\"https://docs.sciml.ai/DeepEquilibriumNetworks/stable/tutorials/basic_mnist_deq/\"},{\"text\":\"Medical Image Segmentation\",\"link\":\"https://github.com/Dale-Black/ComputerVisionTutorials.jl/\"},{\"text\":\"Neural closure models\",\"link\":\"https://github.com/agdestein/NeuralClosureTutorials/\"}]}]},\"/manual/\":{\"text\":\"Manual\",\"collapsed\":false,\"items\":[{\"text\":\"Basics\",\"items\":[{\"text\":\"Lux Interface\",\"link\":\"/manual/interface\"},{\"text\":\"Freezing Parameters\",\"link\":\"/manual/freezing_model_parameters\"},{\"text\":\"GPU Management\",\"link\":\"/manual/gpu_management\"},{\"text\":\"Initializing Weights\",\"link\":\"/manual/weight_initializers\"}]},{\"text\":\"Automatic Differentiation\",\"items\":[{\"text\":\"Automatic Differentiation\",\"link\":\"/manual/autodiff\"},{\"text\":\"Nested AutoDiff\",\"link\":\"/manual/nested_autodiff\"}]},{\"text\":\"Debugging / Performance Enhancement Tools\",\"items\":[{\"text\":\"Debugging Lux Models\",\"link\":\"/manual/debugging\"},{\"text\":\"Performance Pitfalls\",\"link\":\"/manual/performance_pitfalls\"}]},{\"text\":\"Migration Guides\",\"items\":[{\"text\":\"Migrating from Flux\",\"link\":\"/manual/migrate_from_flux\"}]},{\"text\":\"Advanced Usage\",\"items\":[{\"text\":\"Custom Input Types\",\"link\":\"/manual/dispatch_custom_input\"},{\"text\":\"Configuration via Preferences\",\"link\":\"/manual/preferences\"},{\"text\":\"Distributed Training\",\"link\":\"/manual/distributed_utils\"},{\"text\":\"Lux In GPU Kernels\",\"link\":\"/manual/nn_inside_gpu_kernels\"}]}]},\"/api/\":{\"text\":\"API Reference\",\"collapsed\":false,\"items\":[{\"text\":\"Lux\",\"collapsed\":false,\"items\":[{\"text\":\"Built-In Layers\",\"link\":\"/api/Lux/layers\"},{\"text\":\"Automatic Differentiation\",\"link\":\"/api/Lux/autodiff\"},{\"text\":\"Utilities\",\"link\":\"/api/Lux/utilities\"},{\"text\":\"Experimental Features\",\"link\":\"/api/Lux/contrib\"},{\"text\":\"Interoperability\",\"link\":\"/api/Lux/interop\"},{\"text\":\"DistributedUtils\",\"link\":\"/api/Lux/distributed_utils\"}]},{\"text\":\"Accelerator Support\",\"collapsed\":false,\"items\":[{\"text\":\"MLDataDevices\",\"link\":\"/api/Accelerator_Support/MLDataDevices\"}]},{\"text\":\"Building Blocks\",\"collapsed\":false,\"items\":[{\"text\":\"LuxCore\",\"link\":\"/api/Building_Blocks/LuxCore\"},{\"text\":\"LuxLib\",\"link\":\"/api/Building_Blocks/LuxLib\"},{\"text\":\"WeightInitializers\",\"link\":\"/api/Building_Blocks/WeightInitializers\"},{\"text\":\"NNlib\",\"link\":\"https://fluxml.ai/NNlib.jl/dev/\"},{\"text\":\"Activation Functions\",\"link\":\"https://fluxml.ai/NNlib.jl/dev/reference/#Activation-Functions\"}]},{\"text\":\"Testing Functionality\",\"collapsed\":false,\"items\":[{\"text\":\"LuxTestUtils\",\"link\":\"/api/Testing_Functionality/LuxTestUtils\"}]}]}},\"editLink\":{\"pattern\":\"https://github.com/LuxDL/Lux.jl/edit/main/docs/src/:path\",\"text\":\"Edit this page on GitHub\"},\"socialLinks\":[{\"icon\":\"github\",\"link\":\"https://github.com/LuxDL/Lux.jl\"},{\"icon\":\"twitter\",\"link\":\"https://twitter.com/avikpal1410\"},{\"icon\":\"slack\",\"link\":\"https://julialang.org/slack/\"}],\"footer\":{\"message\":\"Made with <a href=\\\"https://documenter.juliadocs.org/stable/\\\" target=\\\"_blank\\\"><strong>Documenter.jl</strong></a>, <a href=\\\"https://vitepress.dev\\\" target=\\\"_blank\\\"><strong>VitePress</strong></a> and <a href=\\\"https://luxdl.github.io/DocumenterVitepress.jl/stable\\\" target=\\\"_blank\\\"><strong>DocumenterVitepress.jl</strong></a><br>Released under the MIT License. Powered by the <a href=\\\"https://www.julialang.org\\\">Julia Programming Language</a>.<br>\",\"copyright\":\"© Copyright 2024 Avik Pal.\"},\"lastUpdated\":{\"text\":\"Updated at\",\"formatOptions\":{\"dateStyle\":\"full\",\"timeStyle\":\"medium\"}}},\"locales\":{},\"scrollOffset\":134,\"cleanUrls\":true}");</script>
+
+  </body>
+</html>
diff --git a/previews/PR949/api/Accelerator_Support/MLDataDevices.html b/previews/PR949/api/Accelerator_Support/MLDataDevices.html
diff --git a/previews/PR949/api/Building_Blocks/LuxCore.html b/previews/PR949/api/Building_Blocks/LuxCore.html
diff --git a/previews/PR949/api/Building_Blocks/LuxLib.html b/previews/PR949/api/Building_Blocks/LuxLib.html
diff --git a/previews/PR949/api/Building_Blocks/WeightInitializers.html b/previews/PR949/api/Building_Blocks/WeightInitializers.html
diff --git a/previews/PR949/api/Lux/autodiff.html b/previews/PR949/api/Lux/autodiff.html
diff --git a/previews/PR949/api/Lux/contrib.html b/previews/PR949/api/Lux/contrib.html
diff --git a/previews/PR949/api/Lux/distributed_utils.html b/previews/PR949/api/Lux/distributed_utils.html
diff --git a/previews/PR949/api/Lux/interop.html b/previews/PR949/api/Lux/interop.html
diff --git a/previews/PR949/api/Lux/layers.html b/previews/PR949/api/Lux/layers.html
diff --git a/previews/PR949/api/Lux/utilities.html b/previews/PR949/api/Lux/utilities.html
diff --git a/previews/PR949/api/Testing_Functionality/LuxTestUtils.html b/previews/PR949/api/Testing_Functionality/LuxTestUtils.html
diff --git a/previews/PR949/assets/api_Accelerator_Support_MLDataDevices.md.BMDHIxdP.js b/previews/PR949/assets/api_Accelerator_Support_MLDataDevices.md.BMDHIxdP.js
diff --git a/previews/PR949/assets/api_Accelerator_Support_MLDataDevices.md.BMDHIxdP.lean.js b/previews/PR949/assets/api_Accelerator_Support_MLDataDevices.md.BMDHIxdP.lean.js
diff --git a/previews/PR949/assets/api_Building_Blocks_LuxCore.md.BKYx5MWw.js b/previews/PR949/assets/api_Building_Blocks_LuxCore.md.BKYx5MWw.js
diff --git a/previews/PR949/assets/api_Building_Blocks_LuxCore.md.BKYx5MWw.lean.js b/previews/PR949/assets/api_Building_Blocks_LuxCore.md.BKYx5MWw.lean.js