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 https://torch.mlverse.org.

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

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

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

More

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.