Package: mlr3torch
Title: Deep Learning with 'mlr3'
Version: 0.1.2
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")))
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 (>= 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
Config/testthat/edition: 3
NeedsCompilation: no
ByteCompile: no
Encoding: UTF-8
RoxygenNote: 7.3.2
Collate: 'CallbackSet.R' 'zzz.R' 'TorchCallback.R'
        'CallbackSetCheckpoint.R' 'CallbackSetEarlyStopping.R'
        'CallbackSetHistory.R' 'CallbackSetProgress.R' 'ContextTorch.R'
        'DataBackendLazy.R' 'utils.R' 'DataDescriptor.R'
        'LearnerTorch.R' 'LearnerTorchFeatureless.R'
        'LearnerTorchImage.R' 'LearnerTorchMLP.R' 'task_dataset.R'
        'shape.R' 'PipeOpTorchIngress.R' 'LearnerTorchModel.R'
        'LearnerTorchTabResNet.R' 'LearnerTorchVision.R'
        'ModelDescriptor.R' 'PipeOpModule.R' 'PipeOpTorch.R'
        'PipeOpTaskPreprocTorch.R' 'PipeOpTorchActivation.R'
        'PipeOpTorchAvgPool.R' 'PipeOpTorchBatchNorm.R'
        'PipeOpTorchBlock.R' 'PipeOpTorchCallbacks.R'
        'PipeOpTorchConv.R' 'PipeOpTorchConvTranspose.R'
        'PipeOpTorchDropout.R' 'PipeOpTorchHead.R'
        'PipeOpTorchLayerNorm.R' 'PipeOpTorchLinear.R' 'TorchLoss.R'
        'PipeOpTorchLoss.R' 'PipeOpTorchMaxPool.R' 'PipeOpTorchMerge.R'
        'PipeOpTorchModel.R' 'PipeOpTorchOptimizer.R'
        'PipeOpTorchReshape.R' 'PipeOpTorchSoftmax.R'
        'TaskClassif_lazy_iris.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'
        'nn.R' 'nn_graph.R' 'paramset_torchlearner.R' 'preprocess.R'
        'rd_info.R' 'with_torch_settings.R'
Packaged: 2024-10-15 08:27:30 UTC; sebi
Author: Sebastian Fischer [cre, aut] (<https://orcid.org/0000-0002-9609-3197>),
  Bernd Bischl [ctb] (<https://orcid.org/0000-0001-6002-6980>),
  Lukas Burk [ctb] (<https://orcid.org/0000-0001-7528-3795>),
  Martin Binder [aut],
  Florian Pfisterer [ctb] (<https://orcid.org/0000-0001-8867-762X>)
Maintainer: Sebastian Fischer <sebf.fischer@gmail.com>
Repository: CRAN
Date/Publication: 2024-10-15 10:20:03 UTC
Built: R 4.5.0; ; 2024-11-14 02:41:01 UTC; windows
