From
             Research
To Production

An open source deep learning platform that provides a seamless path from research prototyping to production deployment.

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Key Features &
Capabilities

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Hybrid Front-End

A new hybrid front-end provides ease-of-use and flexibility in eager mode, while seamlessly transitioning to graph mode for speed, optimization, and functionality in C++ runtime environments.

Distributed Training

Take advantage of native support for asynchronous execution of collective operations and peer-to-peer communication that is accessible from both Python and C++.

Python-First

Deep integration into Python allows popular libraries and packages to be used, while a new pure C++ interface (beta) enables performance-critical research.

Tools & Libraries

Access a rich ecosystem of tools and libraries to extend PyTorch and support development in areas from computer vision to reinforcement learning.

Ecosystem

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Explore a rich ecosystem of libraries, tools, and more to support development.

AllenNLP

AllenNLP is an open-source research library built on PyTorch for designing and evaluating deep learning models for NLP.

ELF

ELF is a platform for game research that allows developers to train and test their algorithms in various game environments.

Glow

Glow is a machine learning compiler that accelerates the performance of deep learning frameworks on different hardware platforms.

Community

Join the PyTorch developer community to contribute, learn, and get your questions answered.

Docs

Access comprehensive developer documentation.

Tutorials

Get in-depth tutorials for beginners and advanced developers.

Github

Report bugs, request features, discuss issues, and more.

Companies & Universities
Using Pytorch

Pushing the state of the art in NLP and Multi-task learning.

Using PyTorch’s flexibility to efficiently research new algorithmic approaches.

Educating the next wave of AI Innovators using PyTorch.

Quick Start
Locally

Select your preferences and run the install command. Please ensure that you are on the latest pip and numpy packages. Anaconda is our recommended package manager. You can also install previous versions of PyTorch.

Your OS
Package
Python
Cuda
Run this Command:
Your OS
Linux
Mac
Windows
Package
Conda
Pip
Source
Python
2.7
3.5
3.6
3.7
Cuda
8.0
9.0
9.2
None
Run this Command:
conda install pytorch torchvision -c pytorch

Quick Start With
Cloud Partners

Get up and running with PyTorch quickly through popular cloud platforms and machine learning services.

AWS
Google Cloud Platform
Microsoft Azure

Docs

Access comprehensive developer documentation for PyTorch

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Tutorials

Get in-depth tutorials for beginners and advanced developers

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Resources

Find development resources and get your questions answered

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