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About

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.

About

Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. The goal of Torch is to have maximum flexibility and speed in building your scientific algorithms while making the process extremely simple. Torch comes with a large ecosystem of community-driven packages in machine learning, computer vision, signal processing, parallel processing, image, video, audio and networking among others, and builds on top of the Lua community. At the heart of Torch are the popular neural network and optimization libraries which are simple to use, while having maximum flexibility in implementing complex neural network topologies. You can build arbitrary graphs of neural networks, and parallelize them over CPUs and GPUs in an efficient manner.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

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

Audience

Developers looking for a scientific computing framework for their neural networks and energy-based models

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

PyTorch
Founded: 2016
pytorch.org

Company Information

Torch
torch.ch/

Alternatives

Alternatives

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Core ML

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Neural Designer

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Create ML

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DeepSpeed

DeepSpeed

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AWS Neuron

AWS Neuron

Amazon Web Services

Categories

Categories

Integrations

Amazon EC2 G5 Instances
Amazon EC2 P4 Instances
Amazon EC2 UltraClusters
Amazon SageMaker Studio Lab
DagsHub
Database Mart
Domino Enterprise MLOps Platform
Exafunction
Fuzzball
Google AI Edge
Groq
Keepsake
Label Studio
LeaderGPU
Lightning AI
Microsoft Azure
PaliGemma 2
SuperDuperDB
io.net

Integrations

Amazon EC2 G5 Instances
Amazon EC2 P4 Instances
Amazon EC2 UltraClusters
Amazon SageMaker Studio Lab
DagsHub
Database Mart
Domino Enterprise MLOps Platform
Exafunction
Fuzzball
Google AI Edge
Groq
Keepsake
Label Studio
LeaderGPU
Lightning AI
Microsoft Azure
PaliGemma 2
SuperDuperDB
io.net
Claim PyTorch and update features and information
Claim PyTorch and update features and information
Claim Torch and update features and information
Claim Torch and update features and information