Provides functionality to define and train neural networks similar to 'PyTorch' by Paszke et al (2019) <arXiv:1912.01703> but written entirely in R using the 'libtorch' library. Also supports low-level tensor operations and 'GPU' acceleration.
| Version: | 0.1.0 |
| Imports: | Rcpp, R6, withr, rlang, methods, utils, stats, bit64, magrittr |
| LinkingTo: | Rcpp |
| Suggests: | testthat (≥ 2.1.0), covr, knitr, rmarkdown, glue, palmerpenguins |
| Published: | 2020-09-28 |
| Author: | Daniel Falbel [aut, cre, cph], Javier Luraschi [aut, cph], Dmitriy Selivanov [ctb], Athos Damiani [ctb], RStudio [cph] |
| Maintainer: | Daniel Falbel <daniel at rstudio.com> |
| BugReports: | https://github.com/mlverse/torch/issues |
| License: | MIT + file LICENSE |
| URL: | https://torch.mlverse.org/docs, https://github.com/mlverse/torch |
| NeedsCompilation: | yes |
| SystemRequirements: | C++11, LibTorch (https://pytorch.org/) |
| Materials: | README NEWS |
| CRAN checks: | torch results |
| Reference manual: | torch.pdf |
| Vignettes: |
Extending Autograd Indexing tensors Loading data Serialization Creating tensors Using autograd |
| Package source: | torch_0.1.0.tar.gz |
| Windows binaries: | r-devel: torch_0.1.0.zip, r-release: torch_0.1.0.zip, r-oldrel: torch_0.1.0.zip |
| macOS binaries: | r-release: torch_0.1.0.tgz, r-oldrel: torch_0.1.0.tgz |
| Old sources: | torch archive |
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