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>
License: LGPL (≥ 3)
Copyright: see file COPYRIGHTS
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mlr3torch results


Reference manual: mlr3torch.pdf


Package source: mlr3torch_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


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