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.
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PyTorch
Founded: 2016
pytorch.org
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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?
PyTorch works with these users and organization types: Mid Size Business, Small Business, Enterprise, Freelance, Nonprofit, Government, and Startup.
Q: What languages does PyTorch support in their product?
PyTorch supports these languages: English.
Q: What kind of support options does PyTorch offer?
PyTorch offers support via online.
Q: What other applications or services does PyTorch integrate with?
PyTorch integrates with: AI Squared, Alibaba Cloud, Amazon Web Services (AWS), Microsoft Azure, BentoML, Coiled, Comet, Exafunction, Fabric for Deep Learning (FfDL), Flyte, Google Cloud Deep Learning VM Image, Gemini Enterprise Agent Platform Notebooks, Giskard, Google Cloud Platform, Gradient, Collimator, neptune.ai, NVIDIA NGC, NVIDIA Triton Inference Server, JFrog ML, Ray, Superwise, TrueFoundry, Vectice, and Zepl and more.
Q: Does PyTorch have a mobile app?
Yes, PyTorch has a mobile app for iPad, iPhone, and Android.
Q: What type of training does PyTorch provide?
PyTorch provides training in the form of documentation, webinars, and videos.
