To learn how to use PyTorch, begin with our Getting Started Tutorials. The :doc:`60-minute blitz </beginner/deep_learning_60min_blitz>` is the most common starting point, and provides a broad view into how to use PyTorch from the basics all the way into constructing deep neural networks.
Some considerations:
- We’ve added a new feature to tutorials that allows users to open the notebook associated with a tutorial in Google Colab. Visit this page for more information.
- 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.
- Additional high-quality examples are available, including image classification, unsupervised learning, reinforcement learning, machine translation, and many other applications, in PyTorch Examples.
- You can find reference documentation for the PyTorch API and layers in PyTorch Docs or via inline help.
- If you would like the tutorials section improved, please open a github issue here with your feedback.
- Check out our PyTorch Cheat Sheet for additional useful information.
- Finally, here's a link to the PyTorch Release Notes
.. 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:: :figure: /_static/img/thumbnails/landmarked_face2.png :tooltip: Learn how to load and preprocess/augment data from a non trivial dataset :description: :doc:`/beginner/data_loading_tutorial`
.. customgalleryitem:: :figure: /_static/img/thumbnails/pytorch_tensorboard.png :tooltip: Learn to use TensorBoard to visualize data and model training :description: :doc:`intermediate/tensorboard_tutorial`
.. customgalleryitem:: :figure: /_static/img/thumbnails/tv-img.png :tooltip: Finetuning a pre-trained Mask R-CNN model :description: :doc:`intermediate/torchvision_tutorial`
.. customgalleryitem:: :figure: /_static/img/thumbnails/sphx_glr_transfer_learning_tutorial_001.png :tooltip: In transfer learning, a model created from one task is used in another :description: :doc:`beginner/transfer_learning_tutorial`
.. customgalleryitem:: :figure: /_static/img/stn/Five.gif :tooltip: Learn how to augment your network using a visual attention mechanism called spatial transformer networks :description: :doc:`intermediate/spatial_transformer_tutorial`
.. customgalleryitem:: :figure: /_static/img/neural-style/sphx_glr_neural_style_tutorial_004.png :tooltip: How to implement the Neural-Style algorithm developed by Gatys, Ecker, and Bethge :description: :doc:`advanced/neural_style_tutorial`
.. customgalleryitem:: :figure: /_static/img/panda.png :tooltip: Raise your awareness to the security vulnerabilities of ML models, and get insight into the hot topic of adversarial machine learning :description: :doc:`beginner/fgsm_tutorial`
.. customgalleryitem::
:tooltip: Train a generative adversarial network (GAN) to generate new celebrities
:figure: /_static/img/dcgan_generator.png
:description: :doc:`beginner/dcgan_faces_tutorial`
.. customgalleryitem:: :figure: /_static/img/named_tensor.png :tooltip: Named Tensor :description: :doc:`intermediate/named_tensor_tutorial`
.. customgalleryitem:: :figure: /_static/img/audio_preprocessing_tutorial_waveform.png :tooltip: Preprocessing with torchaudio Tutorial :description: :doc:`beginner/audio_preprocessing_tutorial`
.. customgalleryitem:: :figure: /_static/img/rnnclass.png :tooltip: Build and train a basic character-level RNN to classify words :description: :doc:`intermediate/char_rnn_classification_tutorial`
.. customgalleryitem:: :figure: /_static/img/char_rnn_generation.png :tooltip: Generate names from languages :description: :doc:`intermediate/char_rnn_generation_tutorial`
.. galleryitem:: intermediate/seq2seq_translation_tutorial.py :figure: _static/img/seq2seq_flat.png
.. customgalleryitem::
:tooltip: Sentiment Ngrams with Torchtext
:figure: /_static/img/text_sentiment_ngrams_model.png
:description: :doc:`/beginner/text_sentiment_ngrams_tutorial`
.. customgalleryitem::
:tooltip: Language Translation with Torchtext
:figure: /_static/img/thumbnails/german_to_english_translation.png
:description: :doc:`/beginner/torchtext_translation_tutorial`
.. customgalleryitem::
:tooltip: Transformer Tutorial
:figure: /_static/img/transformer_architecture.jpg
:description: :doc:`/beginner/transformer_tutorial`
.. customgalleryitem::
:tooltip: Use PyTorch to train a Deep Q Learning (DQN) agent
:figure: /_static/img/cartpole.gif
:description: :doc:`intermediate/reinforcement_q_learning`
.. customgalleryitem:: :tooltip: Deploying PyTorch and Building a REST API using Flask :description: :doc:`/intermediate/flask_rest_api_tutorial` :figure: _static/img/flask.png
.. customgalleryitem:: :tooltip: Introduction to TorchScript :description: :doc:`beginner/Intro_to_TorchScript_tutorial` :figure: _static/img/torchscript.png
.. customgalleryitem:: :tooltip: Loading a PyTorch model in C++ :description: :doc:`advanced/cpp_export` :figure: _static/img/torchscript_to_cpp.png
.. customgalleryitem:: :figure: /_static/img/cat.jpg :tooltip: Exporting a Model from PyTorch to ONNX and Running it using ONNXRuntime :description: :doc:`advanced/super_resolution_with_onnxruntime`
.. customgalleryitem:: :tooltip: Model parallel training on multiple GPUs :description: :doc:`/intermediate/model_parallel_tutorial` :figure: _static/img/distributed/DistPyTorch.jpg
.. customgalleryitem:: :tooltip: Getting started with DistributedDataParallel :description: :doc:`/intermediate/ddp_tutorial` :figure: _static/img/distributed/DistPyTorch.jpg
.. customgalleryitem:: :tooltip: Parallelize computations across processes and clusters of machines :description: :doc:`/intermediate/dist_tuto` :figure: _static/img/distributed/DistPyTorch.jpg
.. customgalleryitem:: :tooltip: PyTorch distributed trainer with Amazon AWS :description: :doc:`/beginner/aws_distributed_training_tutorial` :figure: _static/img/distributed/DistPyTorch.jpg
.. customgalleryitem:: :tooltip: Implement custom operators in C++ or CUDA for TorchScript :description: :doc:`/advanced/torch_script_custom_ops` :figure: _static/img/cpp_logo.png
.. customgalleryitem::
:tooltip: Create extensions using numpy and scipy
:figure: /_static/img/scipynumpy.png
:description: :doc:`advanced/numpy_extensions_tutorial`
.. customgalleryitem:: :tooltip: Implement custom extensions in C++ or CUDA for eager PyTorch :description: :doc:`/advanced/cpp_extension` :figure: _static/img/cpp_logo.png
.. customgalleryitem:: :tooltip: Perform dynamic quantization on a pre-trained PyTorch model :description: :doc:`/advanced/dynamic_quantization_tutorial` :figure: _static/img/quant_asym.png
.. customgalleryitem::
:tooltip: (experimental) Static Quantization with Eager Mode in PyTorch
:figure: /_static/img/qat.png
:description: :doc:`advanced/static_quantization_tutorial`
.. customgalleryitem::
:tooltip: Perform quantized transfer learning with feature extractor
:description: :doc:`/intermediate/quantized_transfer_learning_tutorial`
:figure: /_static/img/quantized_transfer_learning.png
.. customgalleryitem:: :tooltip: Convert a well-known state-of-the-art model like BERT into dynamic quantized model :description: :doc:`/intermediate/dynamic_quantization_bert_tutorial` :figure: /_static/img/bert.png
.. customgalleryitem::
:tooltip: Using the PyTorch C++ Frontend
:figure: /_static/img/cpp-pytorch.png
:description: :doc:`advanced/cpp_frontend`
.. 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`
.. customgalleryitem:: :figure: /_static/img/torch.nn.png :tooltip: Use torch.nn to create and train a neural network :description: :doc:`beginner/nn_tutorial`
.. toctree:: :maxdepth: 2 :hidden: :includehidden: :caption: Getting Started beginner/deep_learning_60min_blitz beginner/data_loading_tutorial intermediate/tensorboard_tutorial
.. toctree:: :maxdepth: 2 :includehidden: :hidden: :caption: Image intermediate/torchvision_tutorial beginner/transfer_learning_tutorial intermediate/spatial_transformer_tutorial advanced/neural_style_tutorial beginner/fgsm_tutorial beginner/dcgan_faces_tutorial
.. toctree:: :maxdepth: 2 :includehidden: :hidden: :caption: Audio beginner/audio_preprocessing_tutorial
.. toctree:: :maxdepth: 2 :includehidden: :hidden: :caption: Text intermediate/char_rnn_classification_tutorial intermediate/char_rnn_generation_tutorial intermediate/seq2seq_translation_tutorial beginner/text_sentiment_ngrams_tutorial beginner/torchtext_translation_tutorial beginner/transformer_tutorial
.. toctree:: :maxdepth: 2 :includehidden: :hidden: :caption: Named Tensor (experimental) intermediate/named_tensor_tutorial
.. toctree:: :maxdepth: 2 :includehidden: :hidden: :caption: Reinforcement Learning intermediate/reinforcement_q_learning
.. toctree:: :maxdepth: 2 :includehidden: :hidden: :caption: Deploying PyTorch Models in Production intermediate/flask_rest_api_tutorial beginner/Intro_to_TorchScript_tutorial advanced/cpp_export advanced/super_resolution_with_onnxruntime
.. toctree:: :maxdepth: 2 :includehidden: :hidden: :caption: Parallel and Distributed Training intermediate/model_parallel_tutorial intermediate/ddp_tutorial intermediate/dist_tuto beginner/aws_distributed_training_tutorial
.. toctree:: :maxdepth: 2 :includehidden: :hidden: :caption: Extending PyTorch advanced/torch_script_custom_ops advanced/numpy_extensions_tutorial advanced/cpp_extension
.. toctree:: :maxdepth: 2 :includehidden: :hidden: :caption: Quantization (experimental) advanced/dynamic_quantization_tutorial advanced/static_quantization_tutorial intermediate/quantized_transfer_learning_tutorial intermediate/dynamic_quantization_bert_tutorial
.. toctree:: :maxdepth: 2 :includehidden: :hidden: :caption: PyTorch in Other Languages advanced/cpp_frontend
.. toctree:: :maxdepth: 2 :includehidden: :hidden: :caption: PyTorch Fundamentals In-Depth beginner/pytorch_with_examples beginner/nn_tutorial