Audience

Researchers in need of an open source machine learning solution to accelerate research prototyping and production deployment

About PyTorch

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

Integrations

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Company Information

PyTorch
Founded: 2016
pytorch.org

Videos and Screen Captures

PyTorch Screenshot 1
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Product Details

Platforms Supported
Windows
Mac
Linux
iPhone
iPad
Android
Training
Documentation
Webinars
Videos
Support
Online

PyTorch Frequently Asked Questions

Q: What kinds of users and organization types does PyTorch work with?
Q: What languages does PyTorch support in their product?
Q: What other applications or services does PyTorch integrate with?
Q: Does PyTorch have a mobile app?
Q: What type of training does PyTorch provide?

PyTorch Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Templates
Visualization
Statistical / Mathematical Tools