Tensors and Neural Networks with 'GPU' Acceleration

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


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Reference manual

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install.packages("torch")

0.6.0 by Daniel Falbel, 18 days ago


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


Report a bug at https://github.com/mlverse/torch/issues


Browse source code at https://github.com/cran/torch


Authors: Daniel Falbel [aut, cre, cph] , Javier Luraschi [aut] , Dmitriy Selivanov [ctb] , Athos Damiani [ctb] , Christophe Regouby [ctb] , Krzysztof Joachimiak [ctb] , RStudio [cph]


Documentation:   PDF Manual  


Task views: Machine Learning & Statistical Learning


MIT + file LICENSE license


Imports Rcpp, R6, withr, rlang, methods, utils, stats, bit64, magrittr, tools, coro, callr, cli, ellipsis

Suggests testthat, covr, knitr, rmarkdown, glue, palmerpenguins, mvtnorm, numDeriv, katex

Linking to Rcpp

System requirements: C++11, LibTorch (https://pytorch.org/)


Imported by lambdaTS, luz, madgrad, proteus, scDHA, tabnet, torchaudio, torchdatasets, torchvision.

Suggested by targets.


See at CRAN