doi:10.48550/arXiv.1912.01703> but written entirely in R using the 'libtorch' library. Also supports low-level tensor operations and 'GPU' acceleration.">

torch: Tensors and Neural Networks with 'GPU' Acceleration (original) (raw)

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

BugReports:

https://github.com/mlverse/torch/issues

License:

MIT + file

URL:

https://torch.mlverse.org/docs, https://github.com/mlverse/torch

NeedsCompilation:

yes

SystemRequirements:

LibTorch (https://pytorch.org/); Only x86_64 platforms are currently supported except for ARM system running macOS.

Materials:

README NEWS

In views:

MachineLearning

CRAN checks:

torch results