torch: Tensors and Neural Networks with 'GPU' Acceleration

Provides functionality to define and train neural networks similar to 'PyTorch' by Paszke et al (2019) <doi:10.48550/arXiv.1912.01703> but written entirely in R using the 'libtorch' library. Also supports low-level tensor operations and 'GPU' acceleration.

Version: 0.13.0
Imports: Rcpp, R6, withr, rlang, methods, utils, stats, bit64, magrittr, tools, coro (≥ 1.0.2), callr, cli (≥ 3.0.0), glue, ellipsis, desc, safetensors (≥ 0.1.1), jsonlite
LinkingTo: Rcpp
Suggests: testthat (≥ 3.0.0), covr, knitr (≥ 1.36), rmarkdown, palmerpenguins, mvtnorm, numDeriv, katex
Published: 2024-05-21
DOI: 10.32614/CRAN.package.torch
Author: Daniel Falbel [aut, cre, cph], Javier Luraschi [aut], Dmitriy Selivanov [ctb], Athos Damiani [ctb], Christophe Regouby [ctb], Krzysztof Joachimiak [ctb], Hamada S. Badr [ctb], Sebastian Fischer [ctb], RStudio [cph]
Maintainer: Daniel Falbel <daniel at>
License: MIT + file LICENSE
NeedsCompilation: yes
SystemRequirements: LibTorch (; Only x86_64 platforms are currently supported except for ARM system running macOS.
Materials: README NEWS
In views: MachineLearning
CRAN checks: torch results


Reference manual: torch.pdf
Vignettes: Distributions
Extending Autograd
Indexing tensors
Loading data
Python to R
Creating tensors
Using autograd


Package source: torch_0.13.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): torch_0.13.0.tgz, r-oldrel (arm64): torch_0.13.0.tgz, r-release (x86_64): torch_0.13.0.tgz, r-oldrel (x86_64): torch_0.13.0.tgz
Old sources: torch archive

Reverse dependencies:

Reverse depends: mlr3torch
Reverse imports: BKTR, brulee, causalOT, cito, engression, glmnetr, innsight, lambdaTS, luz, madgrad, nFunNN, PLNmodels, proteus, RGAN, scDHA, SCFA, sits, spinner, tabnet, topicmodels.etm, torchaudio, torchdatasets, torchopt, torchvision, torchvisionlib
Reverse linking to: causalOT, torchvisionlib
Reverse suggests: bundle, COTAN, GPUmatrix, nn2poly, safetensors, targets, vetiver


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