Package: torch
Type: Package
Title: Tensors and Neural Networks with 'GPU' Acceleration
Version: 0.3.0
Authors@R: c(
    person("Daniel", "Falbel", email = "daniel@rstudio.com", role = c("aut", "cre", "cph")),
    person("Javier", "Luraschi", email = "jluraschi@gmail.com", role = c("aut")),
    person("Dmitriy", "Selivanov", role = c("ctb")),
    person("Athos", "Damiani", role = c("ctb")),
    person("Christophe", "Regouby", role = c("ctb")),
    person("Krzysztof", "Joachimiak", role = c("ctb")),
    person(family = "RStudio", role = c("cph"))
    )
Description: Provides functionality to define and train neural networks similar to 
    'PyTorch' by Paszke et al (2019) <arXiv:1912.01703> but written entirely in R 
    using the 'libtorch' library. Also supports low-level tensor operations and 
    'GPU' acceleration.
License: MIT + file LICENSE
URL: https://torch.mlverse.org/docs, https://github.com/mlverse/torch
BugReports: https://github.com/mlverse/torch/issues
Encoding: UTF-8
SystemRequirements: C++11, LibTorch (https://pytorch.org/)
LinkingTo: Rcpp
Imports: Rcpp, R6, withr, rlang, methods, utils, stats, bit64,
        magrittr, tools, coro, callr, cli
RoxygenNote: 7.1.1
Suggests: testthat (>= 3.0.0), covr, knitr, rmarkdown, glue,
        palmerpenguins
VignetteBuilder: knitr
Collate: 'R7.R' 'RcppExports.R' 'tensor.R' 'autograd.R' 'backends.R'
        'codegen-utils.R' 'conditions.R' 'creation-ops.R' 'cuda.R'
        'device.R' 'dimname_list.R' 'utils.R'
        'distributions-constraints.R' 'distributions-utils.R'
        'distributions-exp-family.R' 'distributions.R'
        'distributions-bernoulli.R' 'distributions-gamma.R'
        'distributions-chi2.R' 'distributions-normal.R'
        'distributions-poisson.R' 'dtype.R' 'gen-method.R'
        'gen-namespace-docs.R' 'gen-namespace-examples.R'
        'gen-namespace.R' 'generator.R' 'help.R' 'indexing.R'
        'install.R' 'lantern_load.R' 'lantern_sync.R' 'layout.R'
        'memory_format.R' 'utils-data.R' 'nn.R' 'nn-activation.R'
        'nn-batchnorm.R' 'nn-conv.R' 'nn-distance.R' 'nn-dropout.R'
        'nn-init.R' 'nn-linear.R' 'nn-loss.R' 'nn-normalization.R'
        'nn-pooling.R' 'nn-rnn.R' 'nn-sparse.R' 'nn-utils-clip-grad.R'
        'nn-utils-rnn.R' 'nn-utils.R' 'nn_adaptive.R'
        'nnf-activation.R' 'nnf-batchnorm.R' 'nnf-conv.R'
        'nnf-distance.R' 'nnf-dropout.R' 'nnf-embedding.R' 'nnf-fold.R'
        'nnf-instancenorm.R' 'nnf-linear.R' 'nnf-loss.R'
        'nnf-normalization.R' 'nnf-padding.R' 'nnf-pixelshuffle.R'
        'nnf-pooling.R' 'nnf-upsampling.R' 'nnf-vision.R' 'operators.R'
        'optim.R' 'optim-adadelta.R' 'optim-adagrad.R' 'optim-adam.R'
        'optim-asgd.R' 'optim-lbfgs.R' 'optim-lr_scheduler.R'
        'optim-rmsprop.R' 'optim-rprop.R' 'optim-sgd.R' 'package.R'
        'qscheme.R' 'quantization.R' 'reduction.R' 'save.R' 'scalar.R'
        'stack.R' 'storage.R' 'tensor_options.R' 'threads.R' 'trace.R'
        'type-info.R' 'utils-data-collate.R' 'utils-data-dataloader.R'
        'utils-data-enum.R' 'utils-data-fetcher.R'
        'utils-data-sampler.R' 'utils-pipe.R' 'variable_list.R'
        'with-indices.R' 'wrapers.R'
NeedsCompilation: yes
Packaged: 2021-04-28 11:41:08 UTC; dfalbel
Author: Daniel Falbel [aut, cre, cph],
  Javier Luraschi [aut],
  Dmitriy Selivanov [ctb],
  Athos Damiani [ctb],
  Christophe Regouby [ctb],
  Krzysztof Joachimiak [ctb],
  RStudio [cph]
Maintainer: Daniel Falbel <daniel@rstudio.com>
Repository: CRAN
Date/Publication: 2021-04-28 13:10:03 UTC
Built: R 3.6.3; x86_64-w64-mingw32; 2021-05-12 19:33:45 UTC; windows
Archs: i386, x64
