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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: | 0.1.2 |
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: | 2024-10-15 |
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 |
Reference manual: | mlr3torch.pdf |
Package source: | mlr3torch_0.1.2.tar.gz |
Windows binaries: | r-devel: mlr3torch_0.1.2.zip, r-release: mlr3torch_0.1.2.zip, r-oldrel: mlr3torch_0.1.2.zip |
macOS binaries: | r-release (arm64): mlr3torch_0.1.2.tgz, r-oldrel (arm64): mlr3torch_0.1.2.tgz, r-release (x86_64): mlr3torch_0.1.2.tgz, r-oldrel (x86_64): mlr3torch_0.1.2.tgz |
Old sources: | mlr3torch archive |
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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.
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