The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

mlr3torch: Deep Learning with 'mlr3'

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: 0.1.0
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: 2024-07-08
DOI: 10.32614/CRAN.package.mlr3torch
Author: Sebastian Fischer ORCID iD [cre, aut], Bernd Bischl ORCID iD [ctb], Lukas Burk ORCID iD [ctb], Martin Binder [aut], Florian Pfisterer ORCID iD [ctb]
Maintainer: Sebastian Fischer <sebf.fischer at gmail.com>
License: LGPL (≥ 3)
Copyright: see file COPYRIGHTS
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mlr3torch results

Documentation:

Reference manual: mlr3torch.pdf

Downloads:

Package source: mlr3torch_0.1.0.tar.gz
Windows binaries: r-devel: mlr3torch_0.1.0.zip, r-release: mlr3torch_0.1.0.zip, r-oldrel: mlr3torch_0.1.0.zip
macOS binaries: r-release (arm64): mlr3torch_0.1.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): mlr3torch_0.1.0.tgz, r-oldrel (x86_64): not available

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mlr3torch to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.