Deep Learning library that extends the mlr3 framework by building
upon the 'torch' package. It allows to conveniently build, train,
and evaluate deep learning models without having to worry about low level
details. Custom architectures can be created using the graph language
defined in 'mlr3pipelines'.
| Version: |
0.1.1 |
| Depends: |
mlr3 (≥ 0.20.0), mlr3pipelines (≥ 0.6.0), torch (≥ 0.13.0), R (≥ 3.5.0) |
| Imports: |
backports, checkmate (≥ 2.2.0), data.table, lgr, methods, mlr3misc (≥ 0.14.0), paradox (≥ 1.0.0), R6, withr |
| Suggests: |
callr, future, ggplot2, igraph, jsonlite, knitr, magick, mlr3tuning (≥ 1.0.0), progress, rmarkdown, rpart, viridis, visNetwork, testthat (≥ 3.0.0), torchvision (≥ 0.6.0), waldo |
| Published: |
2024-09-12 |
| DOI: |
10.32614/CRAN.package.mlr3torch |
| Author: |
Sebastian Fischer 
[cre, aut],
Bernd Bischl
[ctb],
Lukas Burk [ctb],
Martin Binder [aut],
Florian Pfisterer
[ctb] |
| Maintainer: |
Sebastian Fischer <sebf.fischer at gmail.com> |
| BugReports: |
https://github.com/mlr-org/mlr3torch/issues |
| License: |
LGPL (≥ 3) |
| Copyright: |
see file COPYRIGHTS |
| URL: |
https://mlr3torch.mlr-org.com/,
https://github.com/mlr-org/mlr3torch/ |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
mlr3torch results |