+ <script>window.__VP_HASH_MAP__=JSON.parse("{\"api_accelerator_support_mldatadevices.md\":\"CRjGmKN0\",\"api_building_blocks_luxcore.md\":\"CkEIp4Ry\",\"api_building_blocks_weightinitializers.md\":\"CPqzPnq-\",\"api_lux_autodiff.md\":\"APcbkq4T\",\"api_lux_contrib.md\":\"D_ysa58o\",\"api_lux_distributed_utils.md\":\"BC1OXFsJ\",\"api_lux_interop.md\":\"CXbXPeIC\",\"api_lux_layers.md\":\"CxcldwjE\",\"api_lux_utilities.md\":\"CciUggj8\",\"api_nn_primitives_activationfunctions.md\":\"Dx5_A4nF\",\"api_nn_primitives_luxlib.md\":\"BM55S5DB\",\"api_nn_primitives_nnlib.md\":\"Mwa5_QVM\",\"api_testing_functionality_luxtestutils.md\":\"vKv0INtp\",\"index.md\":\"CR3XfkY2\",\"introduction_citation.md\":\"pdLfmoIw\",\"introduction_index.md\":\"BgDeTMW-\",\"introduction_overview.md\":\"C5N1K3uD\",\"introduction_resources.md\":\"DIObvahC\",\"introduction_updating_to_v1.md\":\"BPCwbKoO\",\"manual_autodiff.md\":\"BYeisKku\",\"manual_compiling_lux_models.md\":\"BMUvgh2o\",\"manual_debugging.md\":\"C5i0ns_a\",\"manual_dispatch_custom_input.md\":\"CVwXZOdP\",\"manual_distributed_utils.md\":\"DqOKl18B\",\"manual_exporting_to_jax.md\":\"C1JwUE6e\",\"manual_freezing_model_parameters.md\":\"CuSd8OFZ\",\"manual_gpu_management.md\":\"DVnNFZo3\",\"manual_interface.md\":\"BLZMDv5I\",\"manual_migrate_from_flux.md\":\"iLCCcJ6k\",\"manual_nested_autodiff.md\":\"LjjH0L40\",\"manual_performance_pitfalls.md\":\"B5vwXFfO\",\"manual_preferences.md\":\"BrMLVD9_\",\"manual_visualize_lux_models.md\":\"BYKItRux\",\"manual_weight_initializers.md\":\"2vgFFFy6\",\"references.md\":\"hwdIlfkE\",\"tutorials_advanced_1_gravitationalwaveform.md\":\"bYLJ1k-1\",\"tutorials_beginner_1_basics.md\":\"Co8qFGGl\",\"tutorials_beginner_2_polynomialfitting.md\":\"CDAxMJLA\",\"tutorials_beginner_3_simplernn.md\":\"D3WdzAH1\",\"tutorials_beginner_4_simplechains.md\":\"nHH0aAvG\",\"tutorials_beginner_5_optimizationintegration.md\":\"CKtRDlf5\",\"tutorials_index.md\":\"CVcXamgP\",\"tutorials_intermediate_1_neuralode.md\":\"DKF_4TwR\",\"tutorials_intermediate_2_bayesiannn.md\":\"DJ3Iv65T\",\"tutorials_intermediate_3_hypernet.md\":\"BAw-VyoZ\",\"tutorials_intermediate_4_pinn2dpde.md\":\"BmucbYiV\",\"tutorials_intermediate_5_convolutionalvae.md\":\"3W8aUz5F\",\"tutorials_intermediate_6_gcn_cora.md\":\"BKsFdq41\",\"tutorials_intermediate_7_realnvp.md\":\"Cc6yjfSm\"}");window.__VP_SITE_DATA__=JSON.parse("{\"lang\":\"en-US\",\"dir\":\"ltr\",\"title\":\"Lux.jl Docs\",\"description\":\"Documentation for LuxDL Repositories\",\"base\":\"/v1.11.2/\",\"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\":\"NN Primitives\",\"items\":[{\"text\":\"LuxLib\",\"link\":\"/api/NN_Primitives/LuxLib\"},{\"text\":\"NNlib\",\"link\":\"/api/NN_Primitives/NNlib\"},{\"text\":\"Activation Functions\",\"link\":\"/api/NN_Primitives/ActivationFunctions\"}]},{\"text\":\"Building Blocks\",\"items\":[{\"text\":\"LuxCore\",\"link\":\"/api/Building_Blocks/LuxCore\"},{\"text\":\"WeightInitializers\",\"link\":\"/api/Building_Blocks/WeightInitializers\"}]},{\"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\":\"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\":\"Convolutional VAE for MNIST using Reactant\",\"link\":\"/tutorials/intermediate/5_ConvolutionalVAE\"},{\"text\":\"Graph Convolutional Network on Cora\",\"link\":\"/tutorials/intermediate/6_GCN_Cora\"},{\"text\":\"Normalizing Flows for Density Estimation\",\"link\":\"/tutorials/intermediate/7_RealNVP\"}]},{\"text\":\"Advanced\",\"collapsed\":false,\"items\":[{\"text\":\"Training a Neural ODE to Model Gravitational Waveforms\",\"link\":\"/tutorials/advanced/1_GravitationalWaveForm\"}]},{\"text\":\"Larger 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\":\"Different Vision Models on CIFAR-10\",\"link\":\"https://github.com/LuxDL/Lux.jl/tree/main/examples/CIFAR10\"}]},{\"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\":\"Visualizing Lux Models\",\"link\":\"/manual/visualize_lux_models\"}]},{\"text\":\"Reactant Compilation\",\"items\":[{\"text\":\"Compiling Lux Models\",\"link\":\"/manual/compiling_lux_models\"},{\"text\":\"Exporting Lux Models to Jax\",\"link\":\"/manual/exporting_to_jax\"}]},{\"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\"}]}]},\"/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\":\"NN Primitives\",\"collapsed\":false,\"items\":[{\"text\":\"LuxLib\",\"link\":\"/api/NN_Primitives/LuxLib\"},{\"text\":\"NNlib\",\"link\":\"/api/NN_Primitives/NNlib\"},{\"text\":\"Activation Functions\",\"link\":\"/api/NN_Primitives/ActivationFunctions\"}]},{\"text\":\"Building Blocks\",\"collapsed\":false,\"items\":[{\"text\":\"LuxCore\",\"link\":\"/api/Building_Blocks/LuxCore\"},{\"text\":\"WeightInitializers\",\"link\":\"/api/Building_Blocks/WeightInitializers\"}]},{\"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 2025 Avik Pal.\"},\"lastUpdated\":{\"text\":\"Updated at\",\"formatOptions\":{\"dateStyle\":\"full\",\"timeStyle\":\"medium\"}}},\"locales\":{},\"scrollOffset\":134,\"cleanUrls\":true}");</script>
0 commit comments