mirror of
https://github.com/wassname/pytorch-lightning.git
synced 2026-09-18 12:50:58 +08:00
1343 lines
34 KiB
HTML
1343 lines
34 KiB
HTML
|
|
|
|
|
|
|
|
<!doctype html>
|
|
<html lang="en" class="no-js">
|
|
<head>
|
|
|
|
<meta charset="utf-8">
|
|
<meta name="viewport" content="width=device-width,initial-scale=1">
|
|
<meta http-equiv="x-ua-compatible" content="ie=edge">
|
|
|
|
<meta name="description" content="Documentation for Pytorch LightningModule, the researcher version of keras.">
|
|
|
|
|
|
|
|
|
|
<meta name="lang:clipboard.copy" content="Copy to clipboard">
|
|
|
|
<meta name="lang:clipboard.copied" content="Copied to clipboard">
|
|
|
|
<meta name="lang:search.language" content="en">
|
|
|
|
<meta name="lang:search.pipeline.stopwords" content="True">
|
|
|
|
<meta name="lang:search.pipeline.trimmer" content="True">
|
|
|
|
<meta name="lang:search.result.none" content="No matching documents">
|
|
|
|
<meta name="lang:search.result.one" content="1 matching document">
|
|
|
|
<meta name="lang:search.result.other" content="# matching documents">
|
|
|
|
<meta name="lang:search.tokenizer" content="[\s\-]+">
|
|
|
|
<link rel="shortcut icon" href="../../assets/images/favicon.png">
|
|
<meta name="generator" content="mkdocs-1.0.4, mkdocs-material-4.4.0">
|
|
|
|
|
|
|
|
<title>Lightning Module interface - Pytorch lightning Documentation</title>
|
|
|
|
|
|
|
|
<link rel="stylesheet" href="../../assets/stylesheets/application.0284f74d.css">
|
|
|
|
|
|
|
|
|
|
<script src="../../assets/javascripts/modernizr.74668098.js"></script>
|
|
|
|
|
|
|
|
<link href="https://fonts.gstatic.com" rel="preconnect" crossorigin>
|
|
<link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Roboto:300,400,400i,700|Roboto+Mono&display=fallback">
|
|
<style>body,input{font-family:"Roboto","Helvetica Neue",Helvetica,Arial,sans-serif}code,kbd,pre{font-family:"Roboto Mono","Courier New",Courier,monospace}</style>
|
|
|
|
|
|
<link rel="stylesheet" href="../../assets/fonts/material-icons.css">
|
|
|
|
|
|
|
|
|
|
|
|
|
|
</head>
|
|
|
|
<body dir="ltr">
|
|
|
|
<svg class="md-svg">
|
|
<defs>
|
|
|
|
|
|
<svg xmlns="http://www.w3.org/2000/svg" width="416" height="448" viewBox="0 0 416 448" id="__github"><path fill="currentColor" d="M160 304q0 10-3.125 20.5t-10.75 19T128 352t-18.125-8.5-10.75-19T96 304t3.125-20.5 10.75-19T128 256t18.125 8.5 10.75 19T160 304zm160 0q0 10-3.125 20.5t-10.75 19T288 352t-18.125-8.5-10.75-19T256 304t3.125-20.5 10.75-19T288 256t18.125 8.5 10.75 19T320 304zm40 0q0-30-17.25-51T296 232q-10.25 0-48.75 5.25Q229.5 240 208 240t-39.25-2.75Q130.75 232 120 232q-29.5 0-46.75 21T56 304q0 22 8 38.375t20.25 25.75 30.5 15 35 7.375 37.25 1.75h42q20.5 0 37.25-1.75t35-7.375 30.5-15 20.25-25.75T360 304zm56-44q0 51.75-15.25 82.75-9.5 19.25-26.375 33.25t-35.25 21.5-42.5 11.875-42.875 5.5T212 416q-19.5 0-35.5-.75t-36.875-3.125-38.125-7.5-34.25-12.875T37 371.5t-21.5-28.75Q0 312 0 260q0-59.25 34-99-6.75-20.5-6.75-42.5 0-29 12.75-54.5 27 0 47.5 9.875t47.25 30.875Q171.5 96 212 96q37 0 70 8 26.25-20.5 46.75-30.25T376 64q12.75 25.5 12.75 54.5 0 21.75-6.75 42 34 40 34 99.5z"/></svg>
|
|
|
|
</defs>
|
|
</svg>
|
|
<input class="md-toggle" data-md-toggle="drawer" type="checkbox" id="__drawer" autocomplete="off">
|
|
<input class="md-toggle" data-md-toggle="search" type="checkbox" id="__search" autocomplete="off">
|
|
<label class="md-overlay" data-md-component="overlay" for="__drawer"></label>
|
|
|
|
<a href="#lightning-module-interface" tabindex="1" class="md-skip">
|
|
Skip to content
|
|
</a>
|
|
|
|
|
|
<header class="md-header" data-md-component="header">
|
|
<nav class="md-header-nav md-grid">
|
|
<div class="md-flex">
|
|
<div class="md-flex__cell md-flex__cell--shrink">
|
|
<a href="../.." title="Pytorch lightning Documentation" class="md-header-nav__button md-logo">
|
|
|
|
<i class="md-icon"></i>
|
|
|
|
</a>
|
|
</div>
|
|
<div class="md-flex__cell md-flex__cell--shrink">
|
|
<label class="md-icon md-icon--menu md-header-nav__button" for="__drawer"></label>
|
|
</div>
|
|
<div class="md-flex__cell md-flex__cell--stretch">
|
|
<div class="md-flex__ellipsis md-header-nav__title" data-md-component="title">
|
|
|
|
<span class="md-header-nav__topic">
|
|
Pytorch lightning Documentation
|
|
</span>
|
|
<span class="md-header-nav__topic">
|
|
|
|
Lightning Module interface
|
|
|
|
</span>
|
|
|
|
</div>
|
|
</div>
|
|
<div class="md-flex__cell md-flex__cell--shrink">
|
|
|
|
<label class="md-icon md-icon--search md-header-nav__button" for="__search"></label>
|
|
|
|
<div class="md-search" data-md-component="search" role="dialog">
|
|
<label class="md-search__overlay" for="__search"></label>
|
|
<div class="md-search__inner" role="search">
|
|
<form class="md-search__form" name="search">
|
|
<input type="text" class="md-search__input" name="query" placeholder="Search" autocapitalize="off" autocorrect="off" autocomplete="off" spellcheck="false" data-md-component="query" data-md-state="active">
|
|
<label class="md-icon md-search__icon" for="__search"></label>
|
|
<button type="reset" class="md-icon md-search__icon" data-md-component="reset" tabindex="-1">
|
|

|
|
</button>
|
|
</form>
|
|
<div class="md-search__output">
|
|
<div class="md-search__scrollwrap" data-md-scrollfix>
|
|
<div class="md-search-result" data-md-component="result">
|
|
<div class="md-search-result__meta">
|
|
Type to start searching
|
|
</div>
|
|
<ol class="md-search-result__list"></ol>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
</div>
|
|
|
|
<div class="md-flex__cell md-flex__cell--shrink">
|
|
<div class="md-header-nav__source">
|
|
|
|
|
|
|
|
|
|
|
|
<a href="https://github.com/williamFalcon/pytorch-lightning/" title="Go to repository" class="md-source" data-md-source="github">
|
|
|
|
<div class="md-source__icon">
|
|
<svg viewBox="0 0 24 24" width="24" height="24">
|
|
<use xlink:href="#__github" width="24" height="24"></use>
|
|
</svg>
|
|
</div>
|
|
|
|
<div class="md-source__repository">
|
|
GitHub
|
|
</div>
|
|
</a>
|
|
</div>
|
|
</div>
|
|
|
|
</div>
|
|
</nav>
|
|
</header>
|
|
|
|
<div class="md-container">
|
|
|
|
|
|
|
|
|
|
<main class="md-main">
|
|
<div class="md-main__inner md-grid" data-md-component="container">
|
|
|
|
|
|
<div class="md-sidebar md-sidebar--primary" data-md-component="navigation">
|
|
<div class="md-sidebar__scrollwrap">
|
|
<div class="md-sidebar__inner">
|
|
<nav class="md-nav md-nav--primary" data-md-level="0">
|
|
<label class="md-nav__title md-nav__title--site" for="__drawer">
|
|
<a href="../.." title="Pytorch lightning Documentation" class="md-nav__button md-logo">
|
|
|
|
<i class="md-icon"></i>
|
|
|
|
</a>
|
|
Pytorch lightning Documentation
|
|
</label>
|
|
|
|
<div class="md-nav__source">
|
|
|
|
|
|
|
|
|
|
|
|
<a href="https://github.com/williamFalcon/pytorch-lightning/" title="Go to repository" class="md-source" data-md-source="github">
|
|
|
|
<div class="md-source__icon">
|
|
<svg viewBox="0 0 24 24" width="24" height="24">
|
|
<use xlink:href="#__github" width="24" height="24"></use>
|
|
</svg>
|
|
</div>
|
|
|
|
<div class="md-source__repository">
|
|
GitHub
|
|
</div>
|
|
</a>
|
|
</div>
|
|
|
|
<ul class="md-nav__list" data-md-scrollfix>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item">
|
|
<a href="../.." title="PYTORCH-LIGHTNING DOCUMENTATION" class="md-nav__link">
|
|
PYTORCH-LIGHTNING DOCUMENTATION
|
|
</a>
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item">
|
|
<a href="../../Examples/" title="Examples" class="md-nav__link">
|
|
Examples
|
|
</a>
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item md-nav__item--active md-nav__item--nested">
|
|
|
|
<input class="md-toggle md-nav__toggle" data-md-toggle="nav-3" type="checkbox" id="nav-3" checked>
|
|
|
|
<label class="md-nav__link" for="nav-3">
|
|
LightningModule
|
|
</label>
|
|
<nav class="md-nav" data-md-component="collapsible" data-md-level="1">
|
|
<label class="md-nav__title" for="nav-3">
|
|
LightningModule
|
|
</label>
|
|
<ul class="md-nav__list" data-md-scrollfix>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item md-nav__item--active">
|
|
|
|
<input class="md-toggle md-nav__toggle" data-md-toggle="toc" type="checkbox" id="__toc">
|
|
|
|
|
|
|
|
|
|
<label class="md-nav__link md-nav__link--active" for="__toc">
|
|
Lightning Module interface
|
|
</label>
|
|
|
|
<a href="./" title="Lightning Module interface" class="md-nav__link md-nav__link--active">
|
|
Lightning Module interface
|
|
</a>
|
|
|
|
|
|
<nav class="md-nav md-nav--secondary">
|
|
|
|
|
|
|
|
|
|
|
|
<label class="md-nav__title" for="__toc">Table of contents</label>
|
|
<ul class="md-nav__list" data-md-scrollfix>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#training_step" title="training_step" class="md-nav__link">
|
|
training_step
|
|
</a>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#validation_step" title="validation_step" class="md-nav__link">
|
|
validation_step
|
|
</a>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#validation_end" title="validation_end" class="md-nav__link">
|
|
validation_end
|
|
</a>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#configure_optimizers" title="configure_optimizers" class="md-nav__link">
|
|
configure_optimizers
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#get_save_dict" title="get_save_dict" class="md-nav__link">
|
|
get_save_dict
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return_1" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#load_model_specific" title="load_model_specific" class="md-nav__link">
|
|
load_model_specific
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return_2" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#tng_dataloader" title="tng_dataloader" class="md-nav__link">
|
|
tng_dataloader
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return_3" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#val_dataloader" title="val_dataloader" class="md-nav__link">
|
|
val_dataloader
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return_4" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#test_dataloader" title="test_dataloader" class="md-nav__link">
|
|
test_dataloader
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return_5" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#update_tng_log_metrics" title="update_tng_log_metrics" class="md-nav__link">
|
|
update_tng_log_metrics
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return_6" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#add_model_specific_args" title="add_model_specific_args" class="md-nav__link">
|
|
add_model_specific_args
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return_7" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
</ul>
|
|
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item">
|
|
<a href="../methods/" title="Methods" class="md-nav__link">
|
|
Methods
|
|
</a>
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item">
|
|
<a href="../properties/" title="Properties" class="md-nav__link">
|
|
Properties
|
|
</a>
|
|
</li>
|
|
|
|
|
|
</ul>
|
|
</nav>
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item md-nav__item--nested">
|
|
|
|
<input class="md-toggle md-nav__toggle" data-md-toggle="nav-4" type="checkbox" id="nav-4">
|
|
|
|
<label class="md-nav__link" for="nav-4">
|
|
Trainer
|
|
</label>
|
|
<nav class="md-nav" data-md-component="collapsible" data-md-level="1">
|
|
<label class="md-nav__title" for="nav-4">
|
|
Trainer
|
|
</label>
|
|
<ul class="md-nav__list" data-md-scrollfix>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item">
|
|
<a href="../../Trainer/" title="Trainer" class="md-nav__link">
|
|
Trainer
|
|
</a>
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item">
|
|
<a href="../../Trainer/Checkpointing/" title="Checkpointing" class="md-nav__link">
|
|
Checkpointing
|
|
</a>
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item">
|
|
<a href="../../Trainer/Distributed training/" title="Distributed training" class="md-nav__link">
|
|
Distributed training
|
|
</a>
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item">
|
|
<a href="../../Trainer/Logging/" title="Logging" class="md-nav__link">
|
|
Logging
|
|
</a>
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item">
|
|
<a href="../../Trainer/SLURM Managed Cluster/" title="SLURM Managed Cluster" class="md-nav__link">
|
|
SLURM Managed Cluster
|
|
</a>
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item">
|
|
<a href="../../Trainer/Training Loop/" title="Training Loop" class="md-nav__link">
|
|
Training Loop
|
|
</a>
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item">
|
|
<a href="../../Trainer/Validation loop/" title="Validation loop" class="md-nav__link">
|
|
Validation loop
|
|
</a>
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item">
|
|
<a href="../../Trainer/debugging/" title="Debugging" class="md-nav__link">
|
|
Debugging
|
|
</a>
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<li class="md-nav__item">
|
|
<a href="../../Trainer/hooks/" title="Hooks" class="md-nav__link">
|
|
Hooks
|
|
</a>
|
|
</li>
|
|
|
|
|
|
</ul>
|
|
</nav>
|
|
</li>
|
|
|
|
|
|
</ul>
|
|
</nav>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
|
|
<div class="md-sidebar md-sidebar--secondary" data-md-component="toc">
|
|
<div class="md-sidebar__scrollwrap">
|
|
<div class="md-sidebar__inner">
|
|
|
|
<nav class="md-nav md-nav--secondary">
|
|
|
|
|
|
|
|
|
|
|
|
<label class="md-nav__title" for="__toc">Table of contents</label>
|
|
<ul class="md-nav__list" data-md-scrollfix>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#training_step" title="training_step" class="md-nav__link">
|
|
training_step
|
|
</a>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#validation_step" title="validation_step" class="md-nav__link">
|
|
validation_step
|
|
</a>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#validation_end" title="validation_end" class="md-nav__link">
|
|
validation_end
|
|
</a>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#configure_optimizers" title="configure_optimizers" class="md-nav__link">
|
|
configure_optimizers
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#get_save_dict" title="get_save_dict" class="md-nav__link">
|
|
get_save_dict
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return_1" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#load_model_specific" title="load_model_specific" class="md-nav__link">
|
|
load_model_specific
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return_2" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#tng_dataloader" title="tng_dataloader" class="md-nav__link">
|
|
tng_dataloader
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return_3" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#val_dataloader" title="val_dataloader" class="md-nav__link">
|
|
val_dataloader
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return_4" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#test_dataloader" title="test_dataloader" class="md-nav__link">
|
|
test_dataloader
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return_5" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#update_tng_log_metrics" title="update_tng_log_metrics" class="md-nav__link">
|
|
update_tng_log_metrics
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return_6" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#add_model_specific_args" title="add_model_specific_args" class="md-nav__link">
|
|
add_model_specific_args
|
|
</a>
|
|
|
|
<nav class="md-nav">
|
|
<ul class="md-nav__list">
|
|
|
|
<li class="md-nav__item">
|
|
<a href="#return_7" title="Return" class="md-nav__link">
|
|
Return
|
|
</a>
|
|
|
|
</li>
|
|
|
|
</ul>
|
|
</nav>
|
|
|
|
</li>
|
|
|
|
|
|
|
|
|
|
|
|
</ul>
|
|
|
|
</nav>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
|
|
<div class="md-content">
|
|
<article class="md-content__inner md-typeset">
|
|
|
|
|
|
<a href="https://github.com/williamFalcon/pytorch-lightning/edit/master/docs/LightningModule/RequiredTrainerInterface.md" title="Edit this page" class="md-icon md-content__icon"></a>
|
|
|
|
|
|
<h1 id="lightning-module-interface">Lightning Module interface</h1>
|
|
<p>[<a href="https://github.com/williamFalcon/pytorch-lightning/blob/master/pytorch_lightning/root_module/root_module.py">Github Code</a>]</p>
|
|
<p>A lightning module is a strict superclass of nn.Module, it provides a standard interface for the trainer to interact with the model.</p>
|
|
<p>The easiest thing to do is copy <a href="../../examples/new_project_templates/lightning_module_template.py">this template</a> and modify accordingly. </p>
|
|
<p>Otherwise, to Define a Lightning Module, implement the following methods:</p>
|
|
<p><strong>Required</strong>: </p>
|
|
<ul>
|
|
<li><a href="./#training_step">training_step</a> </li>
|
|
<li><a href="./#validation_step">validation_step</a></li>
|
|
<li>
|
|
<p><a href="./#validation_end">validation_end</a></p>
|
|
</li>
|
|
<li>
|
|
<p><a href="./#configure_optimizers">configure_optimizers</a></p>
|
|
</li>
|
|
<li><a href="./#get_save_dict">get_save_dict</a></li>
|
|
<li>
|
|
<p><a href="./#load_model_specific">load_model_specific</a></p>
|
|
</li>
|
|
<li>
|
|
<p><a href="./#tng_dataloader">tng_dataloader</a></p>
|
|
</li>
|
|
<li><a href="./#tng_dataloader">tng_dataloader</a></li>
|
|
<li><a href="./#test_dataloader">test_dataloader</a></li>
|
|
</ul>
|
|
<p><strong>Optional</strong>: </p>
|
|
<ul>
|
|
<li><a href="./#update_tng_log_metrics">update_tng_log_metrics</a></li>
|
|
<li><a href="./#add_model_specific_args">add_model_specific_args</a></li>
|
|
</ul>
|
|
<hr />
|
|
<h3 id="training_step">training_step</h3>
|
|
<pre><code class="python">def training_step(self, data_batch, batch_nb)
|
|
</code></pre>
|
|
|
|
<p>In this step you'd normally do the forward pass and calculate the loss for a batch. You can also do fancier things like multiple forward passes or something specific to your model.</p>
|
|
<p><strong>Params</strong> </p>
|
|
<table>
|
|
<thead>
|
|
<tr>
|
|
<th>Param</th>
|
|
<th>description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td>data_batch</td>
|
|
<td>The output of your dataloader. A tensor, tuple or list</td>
|
|
</tr>
|
|
<tr>
|
|
<td>batch_nb</td>
|
|
<td>Integer displaying which batch this is</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<p><strong>Return</strong> </p>
|
|
<p>Dictionary or OrderedDict </p>
|
|
<table>
|
|
<thead>
|
|
<tr>
|
|
<th>key</th>
|
|
<th>value</th>
|
|
<th>is required</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td>loss</td>
|
|
<td>tensor scalar</td>
|
|
<td>Y</td>
|
|
</tr>
|
|
<tr>
|
|
<td>prog</td>
|
|
<td>Dict for progress bar display. Must have only tensors</td>
|
|
<td>N</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<p><strong>Example</strong></p>
|
|
<pre><code class="python">def training_step(self, data_batch, batch_nb):
|
|
x, y, z = data_batch
|
|
|
|
# implement your own
|
|
out = self.forward(x)
|
|
loss = self.loss(out, x)
|
|
|
|
output = {
|
|
'loss': loss, # required
|
|
'prog': {'tng_loss': loss, 'batch_nb': batch_nb} # optional
|
|
}
|
|
|
|
# return a dict
|
|
return output
|
|
</code></pre>
|
|
|
|
<hr />
|
|
<h3 id="validation_step">validation_step</h3>
|
|
<pre><code class="python">def validation_step(self, data_batch, batch_nb)
|
|
</code></pre>
|
|
|
|
<p>In this step you'd normally do the forward pass and calculate the loss for a batch. You can also do fancier things like multiple forward passes or something specific to your model.
|
|
This is most likely the same as your training_step. But unlike training step, the outputs from here will go to validation_end for collation.</p>
|
|
<p><strong>Params</strong> </p>
|
|
<table>
|
|
<thead>
|
|
<tr>
|
|
<th>Param</th>
|
|
<th>description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td>data_batch</td>
|
|
<td>The output of your dataloader. A tensor, tuple or list</td>
|
|
</tr>
|
|
<tr>
|
|
<td>batch_nb</td>
|
|
<td>Integer displaying which batch this is</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<p><strong>Return</strong> </p>
|
|
<table>
|
|
<thead>
|
|
<tr>
|
|
<th>Return</th>
|
|
<th>description</th>
|
|
<th>optional</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td>dict</td>
|
|
<td>Dict of OrderedDict with metrics to display in progress bar. All keys must be tensors.</td>
|
|
<td>Y</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<p><strong>Example</strong></p>
|
|
<pre><code class="python">def validation_step(self, data_batch, batch_nb):
|
|
x, y, z = data_batch
|
|
|
|
# implement your own
|
|
out = self.forward(x)
|
|
loss = self.loss(out, x)
|
|
|
|
# calculate acc
|
|
labels_hat = torch.argmax(out, dim=1)
|
|
val_acc = torch.sum(y == labels_hat).item() / (len(y) * 1.0)
|
|
|
|
# all optional...
|
|
# return whatever you need for the collation function validation_end
|
|
output = OrderedDict({
|
|
'val_loss': loss_val,
|
|
'val_acc': torch.tensor(val_acc), # everything must be a tensor
|
|
})
|
|
|
|
# return an optional dict
|
|
return output
|
|
</code></pre>
|
|
|
|
<hr />
|
|
<h3 id="validation_end">validation_end</h3>
|
|
<pre><code class="python">def validation_end(self, outputs)
|
|
</code></pre>
|
|
|
|
<p>Called at the end of the validation loop with the output of each validation_step.</p>
|
|
<p><strong>Params</strong> </p>
|
|
<table>
|
|
<thead>
|
|
<tr>
|
|
<th>Param</th>
|
|
<th>description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td>outputs</td>
|
|
<td>List of outputs you defined in validation_step</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<p><strong>Return</strong> </p>
|
|
<table>
|
|
<thead>
|
|
<tr>
|
|
<th>Return</th>
|
|
<th>description</th>
|
|
<th>optional</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td>dict</td>
|
|
<td>Dict of OrderedDict with metrics to display in progress bar</td>
|
|
<td>Y</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
<p><strong>Example</strong></p>
|
|
<pre><code class="python">def validation_end(self, outputs):
|
|
"""
|
|
Called at the end of validation to aggregate outputs
|
|
:param outputs: list of individual outputs of each validation step
|
|
:return:
|
|
"""
|
|
val_loss_mean = 0
|
|
val_acc_mean = 0
|
|
for output in outputs:
|
|
val_loss_mean += output['val_loss']
|
|
val_acc_mean += output['val_acc']
|
|
|
|
val_loss_mean /= len(outputs)
|
|
val_acc_mean /= len(outputs)
|
|
tqdm_dic = {'val_loss': val_loss_mean.item(), 'val_acc': val_acc_mean.item()}
|
|
return tqdm_dic
|
|
</code></pre>
|
|
|
|
<hr />
|
|
<h3 id="configure_optimizers">configure_optimizers</h3>
|
|
<pre><code class="python">def configure_optimizers(self)
|
|
</code></pre>
|
|
|
|
<p>Set up as many optimizers as you need. Normally you'd need one. But in the case of GANs or something more esoteric you might have multiple.
|
|
Lightning will call .backward() and .step() on each one. If you use 16 bit precision it will also handle that.</p>
|
|
<h5 id="return">Return</h5>
|
|
<p>List - List of optimizers</p>
|
|
<p><strong>Example</strong></p>
|
|
<pre><code class="python"># most cases
|
|
def configure_optimizers(self):
|
|
opt = Adam(lr=0.01)
|
|
return [opt]
|
|
|
|
# gan example
|
|
def configure_optimizers(self):
|
|
generator_opt = Adam(lr=0.01)
|
|
disriminator_opt = Adam(lr=0.02)
|
|
return [generator_opt, disriminator_opt]
|
|
</code></pre>
|
|
|
|
<hr />
|
|
<h3 id="get_save_dict">get_save_dict</h3>
|
|
<pre><code class="python">def get_save_dict(self)
|
|
</code></pre>
|
|
|
|
<p>Called by lightning to checkpoint your model. Lightning saves current epoch, current batch nb, etc...
|
|
All you have to return is what specifically about your lightning model you want to checkpoint.</p>
|
|
<h5 id="return_1">Return</h5>
|
|
<p>Dictionary - No required keys. Most of the time as described in this example. </p>
|
|
<p><strong>Example</strong></p>
|
|
<pre><code class="python">def get_save_dict(self):
|
|
# 99% of use cases this is all you need to return
|
|
checkpoint = {'state_dict': self.state_dict()}
|
|
return checkpoint
|
|
</code></pre>
|
|
|
|
<hr />
|
|
<h3 id="load_model_specific">load_model_specific</h3>
|
|
<pre><code class="python">def load_model_specific(self, checkpoint)
|
|
</code></pre>
|
|
|
|
<p>Called by lightning to restore your model. This is your chance to restore your model using the keys you added in get_save_dict.
|
|
Lightning will automatically restore current epoch, batch nb, etc. </p>
|
|
<h5 id="return_2">Return</h5>
|
|
<p>Nothing </p>
|
|
<p><strong>Example</strong></p>
|
|
<pre><code class="python">def load_model_specific(self, checkpoint):
|
|
# you defined 'state_dict' in get_save_dict()
|
|
self.load_state_dict(checkpoint['state_dict'])
|
|
</code></pre>
|
|
|
|
<hr />
|
|
<h3 id="tng_dataloader">tng_dataloader</h3>
|
|
<pre><code class="python">@property
|
|
def tng_dataloader(self)
|
|
</code></pre>
|
|
|
|
<p>Called by lightning during training loop. Define it as a property.</p>
|
|
<h5 id="return_3">Return</h5>
|
|
<p>Pytorch DataLoader</p>
|
|
<p><strong>Example</strong></p>
|
|
<pre><code class="python">@property
|
|
def tng_dataloader(self):
|
|
if self._tng_dataloader is None:
|
|
try:
|
|
transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (1.0,))])
|
|
dataset = MNIST(root='/path/to/mnist/', train=True, transform=transform, download=True)
|
|
loader = torch.utils.data.DataLoader(
|
|
dataset=dataset,
|
|
batch_size=self.hparams.batch_size,
|
|
shuffle=True
|
|
)
|
|
self._tng_dataloader = loader
|
|
except Exception as e:
|
|
raise e
|
|
|
|
return self._tng_dataloader
|
|
</code></pre>
|
|
|
|
<hr />
|
|
<h3 id="val_dataloader">val_dataloader</h3>
|
|
<pre><code class="python">@property
|
|
def tng_dataloader(self)
|
|
</code></pre>
|
|
|
|
<p>Called by lightning during validation loop. Define it as a property.</p>
|
|
<h5 id="return_4">Return</h5>
|
|
<p>Pytorch DataLoader</p>
|
|
<p><strong>Example</strong></p>
|
|
<pre><code class="python">@property
|
|
def val_dataloader(self):
|
|
if self._val_dataloader is None:
|
|
try:
|
|
transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (1.0,))])
|
|
dataset = MNIST(root='/path/to/mnist/', train=False, transform=transform, download=True)
|
|
loader = torch.utils.data.DataLoader(
|
|
dataset=dataset,
|
|
batch_size=self.hparams.batch_size,
|
|
shuffle=True
|
|
)
|
|
self._val_dataloader = loader
|
|
except Exception as e:
|
|
raise e
|
|
|
|
return self._val_dataloader
|
|
</code></pre>
|
|
|
|
<hr />
|
|
<h3 id="test_dataloader">test_dataloader</h3>
|
|
<pre><code class="python">@property
|
|
def test_dataloader(self)
|
|
</code></pre>
|
|
|
|
<p>Called by lightning during test loop. Define it as a property.</p>
|
|
<h5 id="return_5">Return</h5>
|
|
<p>Pytorch DataLoader</p>
|
|
<p><strong>Example</strong></p>
|
|
<pre><code class="python">@property
|
|
def test_dataloader(self):
|
|
if self._test_dataloader is None:
|
|
try:
|
|
transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (1.0,))])
|
|
dataset = MNIST(root='/path/to/mnist/', train=False, transform=transform, download=True)
|
|
loader = torch.utils.data.DataLoader(
|
|
dataset=dataset,
|
|
batch_size=self.hparams.batch_size,
|
|
shuffle=True
|
|
)
|
|
self._test_dataloader = loader
|
|
except Exception as e:
|
|
raise e
|
|
|
|
return self._test_dataloader
|
|
</code></pre>
|
|
|
|
<hr />
|
|
<h3 id="update_tng_log_metrics">update_tng_log_metrics</h3>
|
|
<pre><code class="python">def update_tng_log_metrics(self, logs)
|
|
</code></pre>
|
|
|
|
<p>Called by lightning right before it logs metrics for this batch.
|
|
This is a chance to ammend or add to the metrics about to be logged.</p>
|
|
<h5 id="return_6">Return</h5>
|
|
<p>Dict </p>
|
|
<p><strong>Example</strong></p>
|
|
<pre><code class="python">def update_tng_log_metrics(self, logs):
|
|
# modify or add to logs
|
|
return logs
|
|
</code></pre>
|
|
|
|
<hr />
|
|
<h3 id="add_model_specific_args">add_model_specific_args</h3>
|
|
<pre><code class="python">@staticmethod
|
|
def add_model_specific_args(parent_parser, root_dir)
|
|
</code></pre>
|
|
|
|
<p>Lightning has a list of default argparse commands.
|
|
This method is your chance to add or modify commands specific to your model.
|
|
The <a href="https://williamfalcon.github.io/test-tube/hyperparameter_optimization/HyperOptArgumentParser/">hyperparameter argument parser</a> is available anywhere in your model by calling self.hparams.</p>
|
|
<h5 id="return_7">Return</h5>
|
|
<p>An argument parser</p>
|
|
<p><strong>Example</strong></p>
|
|
<pre><code class="python">@staticmethod
|
|
def add_model_specific_args(parent_parser, root_dir):
|
|
parser = HyperOptArgumentParser(strategy=parent_parser.strategy, parents=[parent_parser])
|
|
|
|
# param overwrites
|
|
# parser.set_defaults(gradient_clip=5.0)
|
|
|
|
# network params
|
|
parser.opt_list('--drop_prob', default=0.2, options=[0.2, 0.5], type=float, tunable=False)
|
|
parser.add_argument('--in_features', default=28*28)
|
|
parser.add_argument('--out_features', default=10)
|
|
parser.add_argument('--hidden_dim', default=50000) # use 500 for CPU, 50000 for GPU to see speed difference
|
|
|
|
# data
|
|
parser.add_argument('--data_root', default=os.path.join(root_dir, 'mnist'), type=str)
|
|
|
|
# training params (opt)
|
|
parser.opt_list('--learning_rate', default=0.001, type=float, options=[0.0001, 0.0005, 0.001, 0.005],
|
|
tunable=False)
|
|
parser.opt_list('--batch_size', default=256, type=int, options=[32, 64, 128, 256], tunable=False)
|
|
parser.opt_list('--optimizer_name', default='adam', type=str, options=['adam'], tunable=False)
|
|
return parser
|
|
</code></pre>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
</article>
|
|
</div>
|
|
</div>
|
|
</main>
|
|
|
|
|
|
<footer class="md-footer">
|
|
|
|
<div class="md-footer-nav">
|
|
<nav class="md-footer-nav__inner md-grid">
|
|
|
|
<a href="../../Examples/" title="Examples" class="md-flex md-footer-nav__link md-footer-nav__link--prev" rel="prev">
|
|
<div class="md-flex__cell md-flex__cell--shrink">
|
|
<i class="md-icon md-icon--arrow-back md-footer-nav__button"></i>
|
|
</div>
|
|
<div class="md-flex__cell md-flex__cell--stretch md-footer-nav__title">
|
|
<span class="md-flex__ellipsis">
|
|
<span class="md-footer-nav__direction">
|
|
Previous
|
|
</span>
|
|
Examples
|
|
</span>
|
|
</div>
|
|
</a>
|
|
|
|
|
|
<a href="../methods/" title="Methods" class="md-flex md-footer-nav__link md-footer-nav__link--next" rel="next">
|
|
<div class="md-flex__cell md-flex__cell--stretch md-footer-nav__title">
|
|
<span class="md-flex__ellipsis">
|
|
<span class="md-footer-nav__direction">
|
|
Next
|
|
</span>
|
|
Methods
|
|
</span>
|
|
</div>
|
|
<div class="md-flex__cell md-flex__cell--shrink">
|
|
<i class="md-icon md-icon--arrow-forward md-footer-nav__button"></i>
|
|
</div>
|
|
</a>
|
|
|
|
</nav>
|
|
</div>
|
|
|
|
<div class="md-footer-meta md-typeset">
|
|
<div class="md-footer-meta__inner md-grid">
|
|
<div class="md-footer-copyright">
|
|
|
|
powered by
|
|
<a href="https://www.mkdocs.org">MkDocs</a>
|
|
and
|
|
<a href="https://squidfunk.github.io/mkdocs-material/">
|
|
Material for MkDocs</a>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
</footer>
|
|
|
|
</div>
|
|
|
|
<script src="../../assets/javascripts/application.245445c6.js"></script>
|
|
|
|
<script>app.initialize({version:"1.0.4",url:{base:"../.."}})</script>
|
|
|
|
|
|
</body>
|
|
</html> |