Package: mlr3torch Title: Deep Learning with 'mlr3' Version: 0.3.3 Authors@R: c(person(given = "Sebastian", family = "Fischer", role = c("cre", "aut"), email = "sebf.fischer@gmail.com", comment = c(ORCID = "0000-0002-9609-3197")), person(given = "Bernd", family = "Bischl", role = "ctb", email = "bernd_bischl@gmx.net", comment = c(ORCID = "0000-0001-6002-6980")), person(given = "Lukas", family = "Burk", role = "ctb", email = "github@quantenbrot.de", comment = c(ORCID = "0000-0001-7528-3795")), person(given = "Martin", family = "Binder", role = "aut", email = "mlr.developer@mb706.com"), person(given = "Florian", family = "Pfisterer", role = "ctb", email = "pfistererf@googlemail.com", comment = c(ORCID = "0000-0001-8867-762X")), person(given = "Carson", family = "Zhang", role = "ctb", email = "carsonzhang4@gmail.com") ) Description: 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'. License: LGPL (>= 3) BugReports: https://github.com/mlr-org/mlr3torch/issues URL: https://mlr3torch.mlr-org.com/, https://github.com/mlr-org/mlr3torch/ Depends: mlr3 (>= 1.0.1), mlr3pipelines (>= 0.6.0), torch (>= 0.16.2), R (>= 3.5.0) Imports: backports, cli, checkmate (>= 2.2.0), data.table, lgr, methods, mlr3misc (>= 0.14.0), paradox (>= 1.0.0), R6, withr Suggests: callr, curl, future, ggplot2, igraph, jsonlite, knitr, mlr3tuning (>= 1.0.0), progress, rmarkdown, rpart, viridis, visNetwork, testthat (>= 3.0.0), tibble, tfevents, torchvision (>= 0.6.0), waldo Config/testthat/edition: 3 NeedsCompilation: no ByteCompile: yes Encoding: UTF-8 Roxygen: list(markdown = TRUE, r6 = TRUE) RoxygenNote: 7.3.3 Collate: 'CallbackSet.R' 'aaa.R' 'TorchCallback.R' 'CallbackSetCheckpoint.R' 'CallbackSetEarlyStopping.R' 'CallbackSetHistory.R' 'CallbackSetLRScheduler.R' 'CallbackSetProgress.R' 'CallbackSetTB.R' 'CallbackSetUnfreeze.R' 'ContextTorch.R' 'DataBackendLazy.R' 'utils.R' 'DataDescriptor.R' 'LearnerFTTransformer.R' 'LearnerTorch.R' 'LearnerTorchFeatureless.R' 'LearnerTorchImage.R' 'LearnerTorchMLP.R' 'task_dataset.R' 'shape.R' 'PipeOpTorchIngress.R' 'LearnerTorchModel.R' 'LearnerTorchModule.R' 'LearnerTorchTabResNet.R' 'LearnerTorchVision.R' 'ModelDescriptor.R' 'PipeOpModule.R' 'PipeOpTorch.R' 'PipeOpTaskPreprocTorch.R' 'PipeOpTorchActivation.R' 'PipeOpTorchAdaptiveAvgPool.R' 'PipeOpTorchAvgPool.R' 'PipeOpTorchBatchNorm.R' 'PipeOpTorchBlock.R' 'PipeOpTorchCallbacks.R' 'PipeOpTorchConv.R' 'PipeOpTorchConvTranspose.R' 'PipeOpTorchDropout.R' 'PipeOpTorchFTCLS.R' 'PipeOpTorchFTTransformerBlock.R' 'PipeOpTorchFn.R' 'PipeOpTorchHead.R' 'PipeOpTorchIdentity.R' 'PipeOpTorchLayerNorm.R' 'PipeOpTorchLinear.R' 'TorchLoss.R' 'PipeOpTorchLoss.R' 'PipeOpTorchMaxPool.R' 'PipeOpTorchMerge.R' 'PipeOpTorchModel.R' 'PipeOpTorchOptimizer.R' 'PipeOpTorchReshape.R' 'PipeOpTorchSoftmax.R' 'PipeOpTorchTokenizer.R' 'Select.R' 'TaskClassif_cifar.R' 'TaskClassif_lazy_iris.R' 'TaskClassif_melanoma.R' 'TaskClassif_mnist.R' 'TaskClassif_tiny_imagenet.R' 'TorchDescriptor.R' 'TorchOptimizer.R' 'bibentries.R' 'cache.R' 'lazy_tensor.R' 'learner_torch_methods.R' 'materialize.R' 'merge_graphs.R' 'multi_tensor_dataset.R' 'nn.R' 'nn_graph.R' 'paramset_torchlearner.R' 'preprocess.R' 'rd_info.R' 'with_torch_settings.R' 'zzz.R' Repository: https://mlr-org.r-universe.dev Date/Publication: 2026-01-31 13:10:42 UTC RemoteUrl: https://github.com/mlr-org/mlr3torch RemoteRef: v0.3.3 RemoteSha: a665daf9049bd59fe78221532cd9cc615e6ec09d Packaged: 2026-07-16 09:02:25 UTC; root Author: Sebastian Fischer [cre, aut] (ORCID: ), Bernd Bischl [ctb] (ORCID: ), Lukas Burk [ctb] (ORCID: ), Martin Binder [aut], Florian Pfisterer [ctb] (ORCID: ), Carson Zhang [ctb] Maintainer: Sebastian Fischer