Welcome to PyTorch Tutorials
============================

To get started with learning PyTorch, start with our Beginner Tutorials.
The :doc:`60-minute blitz </beginner/deep_learning_60min_blitz>` is the most common
starting point, and gives you a quick introduction to PyTorch.
If you like learning by examples, you will like the tutorial
:doc:`/beginner/pytorch_with_examples`

If you would like to do the tutorials interactively via IPython / Jupyter,
each tutorial has a download link for a Jupyter Notebook and Python source code.

We also provide a lot of high-quality examples covering image classification,
unsupervised learning, reinforcement learning, machine translation and
many other applications at https://github.com/pytorch/examples/

You can find reference documentation for PyTorch's API and layers at
http://docs.pytorch.org or via inline help.
If you would like the tutorials section improved, please open a github issue
here with your feedback: https://github.com/pytorch/tutorials

Beginner Tutorials
------------------

.. customgalleryitem::
   :figure: /_static/img/thumbnails/pytorch-logo-flat.png
   :tooltip: Understand PyTorch’s Tensor library and neural networks at a high level.
   :description: :doc:`/beginner/deep_learning_60min_blitz`

.. customgalleryitem::
   :tooltip: Understand similarities and differences between torch and pytorch.
   :figure: /_static/img/thumbnails/torch-logo.png
   :description: :doc:`/beginner/former_torchies_tutorial`

.. customgalleryitem::
   :tooltip: This tutorial introduces the fundamental concepts of PyTorch through self-contained examples.
   :figure: /_static/img/thumbnails/examples.png
   :description: :doc:`/beginner/pytorch_with_examples`

.. galleryitem:: beginner/transfer_learning_tutorial.py

.. galleryitem:: beginner/data_loading_tutorial.py

.. customgalleryitem::
    :tooltip: I am writing this tutorial to focus specifically on NLP for people who have never written code in any deep learning framework
    :figure: /_static/img/thumbnails/babel.jpg
    :description: :doc:`/beginner/deep_learning_nlp_tutorial`

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.. toctree::
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   :caption: Beginner Tutorials

   beginner/deep_learning_60min_blitz
   beginner/former_torchies_tutorial
   beginner/pytorch_with_examples
   beginner/transfer_learning_tutorial
   beginner/data_loading_tutorial
   beginner/deep_learning_nlp_tutorial

Intermediate Tutorials
----------------------

RNNs for NLP
^^^^^^^^^^^^

Applying recurrent neural networks to natural language tasks, from
classification to generation.


.. galleryitem:: intermediate/char_rnn_classification_tutorial.py
.. galleryitem:: intermediate/char_rnn_generation_tutorial.py
  :figure: _static/img/char_rnn_generation.png
.. galleryitem:: intermediate/seq2seq_translation_tutorial.py
  :figure: _static/img/seq2seq_flat.png

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Reinforcement Learning
^^^^^^^^^^^^^^^^^^^^^^

.. galleryitem:: intermediate/reinforcement_q_learning.py
    :figure: _static/img/cartpole.gif

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Distributed Learning
^^^^^^^^^^^^^^^^^^^^^^

.. customgalleryitem::
   :tooltip: Writing Distributed Applications with PyTorch.
   :description: :doc:`/intermediate/dist_tuto`
   :figure: _static/img/distributed/DistPyTorch.jpg

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.. toctree::
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   :caption: Intermediate Tutorials

   intermediate/char_rnn_classification_tutorial
   intermediate/char_rnn_generation_tutorial
   intermediate/seq2seq_translation_tutorial
   intermediate/reinforcement_q_learning
   intermediate/dist_tuto


Advanced Tutorials
------------------

.. galleryitem:: advanced/neural_style_tutorial.py
    :intro: This tutorial explains how to implement the Neural-Style algorithm developed by Leon A. Gatys, Alexander S. Ecker and Matthias Bethge.

.. galleryitem:: advanced/numpy_extensions_tutorial.py

.. galleryitem:: advanced/super_resolution_with_caffe2.py

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   :tooltip: Implement custom extensions in C.
   :description: :doc:`/advanced/c_extension`


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.. toctree::
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   :caption: Advanced Tutorials

   advanced/neural_style_tutorial
   advanced/numpy_extensions_tutorial
   advanced/super_resolution_with_caffe2
   advanced/c_extension