torch ecosystem

Installation and use

  • Install torch running install.packages("torch").

  • Run library(torch) to use it. Additional software will be downloaded and installed the first time you use torch.

Learn more about the torch package at

The torch ecosystem

There are a few extensions to the core torch package that are useful depending on the kind of data you are working on. See the list below:


torch is the core package in the ecosystem. It provides a GPU accelerated array computation library, a collection of general neural network layers and abstractions for efficiently loading data for deep learning models. 


torchvision is an extension providing image loading, transformations, common architectures for computer vision, pre-trained weights and access to commonly used datasets. 


If you are developing a torch extension, contact us in GitHub to feature it. We welcome all extensions: datasets, transformations, models, pre-trained models and so on! 

Get help

If you’re asking for R help, reporting a bug, or requesting a new feature, you’re more likely to succeed if you include a good reproducible example, which is precisely what the reprex package is meant for.