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.


Reference manual

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0.2.1 by Daniel Falbel, 3 months 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] , RStudio [cph]

Documentation:   PDF Manual  

MIT + file LICENSE license

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

Suggests testthat, covr, knitr, rmarkdown, glue, palmerpenguins

Linking to Rcpp

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

Imported by lambdaTS, tabnet, torchaudio, torchdatasets, torchvision.

Suggested by targets.

See at CRAN