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document.addEventListener("DOMContentLoaded", function() { | ||
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var toctreeItems = document.querySelectorAll('li.toctree-l1'); | ||
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toctreeItems.forEach(function(item) { | ||
// Find the link within the item | ||
var link = item.querySelector('a'); | ||
var nestedList = item.querySelector('ul'); | ||
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if (link && nestedList) { | ||
// Create a span element for the "[+]" or "[-]" sign | ||
var expandSign = document.createElement('span'); | ||
expandSign.style.cursor = 'pointer'; // Make it look clickable | ||
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// Use the link text as a unique key for localStorage | ||
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// Retrieve the saved state from localStorage | ||
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// If no state is saved, default to expanded for "Learn the Basics" and collapsed for others | ||
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`Introduction <introyt/introyt1_tutorial.html>`_ || | ||
`Tensors <introyt/tensors_deeper_tutorial.html>`_ || | ||
`Autograd <introyt/autogradyt_tutorial.html>`_ || | ||
`Building Models <introyt/modelsyt_tutorial.html>`_ || | ||
`TensorBoard Support <introyt/tensorboardyt_tutorial.html>`_ || | ||
`Training Models <introyt/trainingyt.html>`_ || | ||
`Model Understanding <introyt/captumyt.html>`_ | ||
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Introduction to PyTorch - YouTube Series | ||
======================================== | ||
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Authors: | ||
`Brad Heintz <https://github.com/fbbradheintz>`_ | ||
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This tutorial follows along with the `PyTorch Beginner Series <https://www.youtube.com/playlist?list=PL_lsbAsL_o2CTlGHgMxNrKhzP97BaG9ZN>`_ on YouTube. | ||
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`This tutorial assumes a basic familiarity with Python and Deep Learning concepts.` | ||
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Running the Tutorial Code | ||
------------------------- | ||
You can run this tutorial in a couple of ways: | ||
This page has been moved. | ||
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- **In the cloud**: This is the easiest way to get started! Each section has a Colab link at the top, which opens a notebook with the code in a fully-hosted environment. Pro tip: Use Colab with a GPU runtime to speed up operations *Runtime > Change runtime type > GPU* | ||
- **Locally**: This option requires you to setup PyTorch and torchvision first on your local machine (`installation instructions <https://pytorch.org/get-started/locally/>`_). Download the notebook or copy the code into your favorite IDE. | ||
Redirecting now... | ||
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.. include:: /beginner_source/introyt/tocyt.txt | ||
.. raw:: html | ||
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.. toctree:: | ||
:hidden: | ||
<meta http-equiv="Refresh" content="0; url='https://pytorch.org/tutorials/beginner/introyt/introyt_index.html'" /> |
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""" | ||
`Introduction <introyt/introyt1_tutorial.html>`_ || | ||
`Tensors <introyt/tensors_deeper_tutorial.html>`_ || | ||
`Autograd <introyt/autogradyt_tutorial.html>`_ || | ||
`Building Models <introyt/modelsyt_tutorial.html>`_ || | ||
`TensorBoard Support <introyt/tensorboardyt_tutorial.html>`_ || | ||
`Training Models <introyt/trainingyt.html>`_ || | ||
`Model Understanding <introyt/captumyt.html>`_ | ||
Introduction to PyTorch - YouTube Series | ||
======================================== | ||
Authors: | ||
`Brad Heintz <https://github.com/fbbradheintz>`_ | ||
This tutorial follows along with the `PyTorch Beginner Series <https://www.youtube.com/playlist?list=PL_lsbAsL_o2CTlGHgMxNrKhzP97BaG9ZN>`_ on YouTube. | ||
`This tutorial assumes a basic familiarity with Python and Deep Learning concepts.` | ||
Running the Tutorial Code | ||
------------------------- | ||
You can run this tutorial in a couple of ways: | ||
- **On the cloud**: This is the easiest way to get started! Each section has a Colab link at the top, which opens a notebook with the code in a fully-hosted environment. Pro tip: Use Colab with a GPU runtime to speed up operations *Runtime > Change runtime type > GPU* | ||
- **Locally**: This option requires you to set up PyTorch and torchvision on your local machine (`installation instructions <https://pytorch.org/get-started/locally/>`_). Download the notebook or copy the code into your favorite IDE. | ||
.. toctree:: | ||
:maxdepth: 2 | ||
:hidden: | ||
introyt1_tutorial | ||
tensors_deeper_tutorial | ||
autogradyt_tutorial | ||
modelsyt_tutorial | ||
tensorboardyt_tutorial | ||
trainingyt | ||
captumyt | ||
""" |
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Distributed Pipeline Parallelism Using RPC | ||
========================================== | ||
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This tutorial has been deprecated. | ||
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Redirecting to a newer tutorial in 3 seconds... | ||
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.. raw:: html | ||
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<meta http-equiv="Refresh" content="3; url='https://pytorch.org/tutorials/intermediate/pipelining_tutorial.html'" /> |
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Training Transformer models using Pipeline Parallelism | ||
====================================================== | ||
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This tutorial has been deprecated. | ||
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Redirecting to the latest parallelism APIs in 3 seconds... | ||
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.. raw:: html | ||
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<meta http-equiv="Refresh" content="3; url='https://pytorch.org/tutorials/intermediate/pipelining_tutorial.html'" /> | ||
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