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Svetlana Karslioglu
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Add Distributed tutorials landing page
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‎_static/css/custom.css

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/* sphinx-design styles for cards/tabs
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*/
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:root {
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--sd-color-primary: #6c6c6d;
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--sd-color-primary-highlight: #f3f4f7;
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--sd-color-card-border-hover: #ee4c2c;
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--sd-color-card-border: #f3f4f7;
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--sd-color-card-background: #f3f4f7;
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--sd-color-card-text: inherit;
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--sd-color-card-header: transparent;
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--sd-color-card-footer: transparent;
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--sd-color-tabs-label-active: hsla(231, 99%, 66%, 1);
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--sd-color-tabs-label-hover: hsla(231, 99%, 66%, 1);
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--sd-color-tabs-label-inactive: hsl(0, 0%, 66%);
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--sd-color-tabs-underline-active: hsla(231, 99%, 66%, 1);
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--sd-color-tabs-underline-hover: rgba(178, 206, 245, 0.62);
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--sd-color-tabs-underline-inactive: transparent;
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--sd-color-tabs-overline: rgb(222, 222, 222);
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--sd-color-tabs-underline: rgb(222, 222, 222);
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}
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.sd-card {
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position: relative;
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background-color: #f3f4f7;
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opacity: 0.5;
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border-radius: 0px;
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width: 30%;
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}
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.sd-card-img {
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opacity: 0.5;
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width: 200px;
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padding: 0px;
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}
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.sd-card-img:hover {
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opacity: 1.0;
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background-color: #f3f4f7;
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}
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.sd-card:after {
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display:block;
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opacity: 1;
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content: '';
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background-color: #fff;
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border: none;
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border-bottom: solid 1px #ee4c2c;
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transform: scaleX(0);
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transition: transform .250s ease-in-out;
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}
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.sd-card:hover {
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background-color: #fff;
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opacity: 1;
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border: none;
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border-bottom: solid 1px #ee4c2c;
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transition: transform .250s ease-in-out;
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}
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.sd-card:hover:after {
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border: none;
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transform: scaleX(1);
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}
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.sd-card:after {
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transform-origin: 0% 50%;
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}

‎conf.py

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'sphinx.ext.intersphinx',
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'sphinx_copybutton',
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'sphinx_gallery.gen_gallery',
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'sphinx_design'
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]
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intersphinx_mapping = {
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'Miscellaneous'),
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]
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html_css_files = [
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'https://cdn.jsdelivr.net/npm/[email protected]/dist/katex.min.css',
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'css/custom.css'
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]
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def setup(app):
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# NOTE: in Sphinx 1.8+ `html_css_files` is an official configuration value
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# and can be moved outside of this function (and the setup(app) function
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# can be deleted).
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html_css_files = [
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'https://cdn.jsdelivr.net/npm/[email protected]/dist/katex.min.css'
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]
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#html_css_files = [
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# 'https://cdn.jsdelivr.net/npm/[email protected]/dist/katex.min.css',
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# 'css/custom.css'
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#]
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# In Sphinx 1.8 it was renamed to `add_css_file`, 1.7 and prior it is
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# `add_stylesheet` (deprecated in 1.8).
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add_css = getattr(app, 'add_css_file', app.add_stylesheet)
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for css_file in html_css_files:
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add_css(css_file)
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#add_css = getattr(app, 'add_css_file', app.add_stylesheet)
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#for css_file in html_css_files:
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# add_css(css_file)
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# Custom CSS
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# app.add_stylesheet('css/pytorch_theme.css')
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#app.add_stylesheet('css/pytorch_theme.css')
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# app.add_stylesheet('https://fonts.googleapis.com/css?family=Lato')
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# Custom directives
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app.add_directive('includenodoc', IncludeDirective)

‎distributed/home.rst

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Distributed and Parallel Training Tutorials
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===========================================
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This page includes all distributed and parallel trainings available
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at pytorch.org website.
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Getting Started with Distributed Data-Parallel Training (DDP)
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-------------------------------------------------------------
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.. grid:: 3
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.. grid-item-card:: Getting Started with PyTorch Distributed
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:shadow: none
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:link: https://example.com
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:link-type: url
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This tutorial provides a gentle intro to the PyTorch
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DistributedData Parallel.
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.. grid-item-card:: Single Machine Model Parallel Best Practices
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:shadow: none
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:link: https://example.com
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:link-type: url
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In this tutorial you will learn about best practices in
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using model parallel.
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.. grid-item-card:: Writing Distributed Applications with PyTorch
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:shadow: none
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:link: https://example.com
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:link-type: url
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This tutorial demonstrates how to write a distributed application
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with PyTorch.
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Learn FSDP
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----------
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Fully-Sharded Data Parallel (FSDP) is a tool that distributes model
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parameters across multiple workers, therefore enabling you to train larger
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models.
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.. grid:: 3
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.. grid-item-card:: Getting Started with FSDP
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:shadow: none
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:img-top: ../_static/img/thumbnails/cropped/pytorch-logo.png
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:link: https://example.com
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:link-type: url
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This tutorial provides a gentle intro to the PyTorch
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DistributedData Parallel.
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.. grid-item-card:: Single Machine Model Parallel Best Practices
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:shadow: none
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:img-top: ../_static/img/thumbnails/cropped/pytorch-logo.png
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:link: https://example.com
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:link-type: url
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In this tutorial you will learn about best practices in
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using model parallel.
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.. grid-item-card:: Writing Distributed Applications with PyTorch
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:shadow: none
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:img-top: ../_static/img/thumbnails/cropped/pytorch-logo.png
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:link: https://example.com
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:link-type: url
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This tutorial demonstrates how to write a distributed application
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with PyTorch.
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Learn RPC
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---------
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Distributed Remote Procedure Call (RPC) framework provides
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mechanisms for multi-machine model training

‎index.rst

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:hidden:
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:caption: Parallel and Distributed Training
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distributed/home
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beginner/dist_overview
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intermediate/model_parallel_tutorial
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intermediate/ddp_tutorial

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