Package: torch
Type: Package
Title: Tensors and Neural Networks with 'GPU' Acceleration
Version: 0.10.0
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("Hamada S.", "Badr", 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: LibTorch (https://pytorch.org/); Only x86_64
        platforms are currently supported except for ARM system running
        macOS.
Config/build/copy-method: copy
LinkingTo: Rcpp
Imports: Rcpp, R6, withr, rlang, methods, utils, stats, bit64,
        magrittr, tools, coro (>= 1.0.2), callr, cli (>= 3.0.0), glue,
        ellipsis, desc
RoxygenNote: 7.2.3
Suggests: testthat (>= 3.0.0), covr, knitr (>= 1.36), rmarkdown,
        palmerpenguins, mvtnorm, numDeriv, katex
VignetteBuilder: knitr
Collate: 'R7.R' 'RcppExports.R' 'autocast.R' 'tensor.R' 'autograd.R'
        'backends.R' 'call_torch_function.R' 'codegen-utils.R'
        'compat-purrr.R' 'compilation_unit.R' 'conditions.R'
        'contrib.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-categorical.R' 'distributions-gamma.R'
        'distributions-chi2.R' 'distributions-mixture_same_family.R'
        'distributions-multivariate_normal.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' 'ivalue.R' 'jit-compile.R' 'lantern_load.R'
        'lantern_sync.R' 'layout.R' 'linalg.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-flatten.R'
        'nn-init.R' 'nn-linear.R' 'nn-loss.R' 'nn-normalization.R'
        'nn-pooling.R' 'nn-rnn.R' 'nn-sparse.R' 'nn-upsampling.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-adamw.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' 'script_module.R' 'stack.R'
        'storage.R' 'tensor_options.R' 'threads.R' 'trace.R'
        'translate.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: 2023-04-13 06:12:56 UTC; dfalbel
Author: Daniel Falbel [aut, cre, cph],
  Javier Luraschi [aut],
  Dmitriy Selivanov [ctb],
  Athos Damiani [ctb],
  Christophe Regouby [ctb],
  Krzysztof Joachimiak [ctb],
  Hamada S. Badr [ctb],
  RStudio [cph]
Maintainer: Daniel Falbel <daniel@rstudio.com>
Repository: CRAN
Date/Publication: 2023-04-13 22:30:03 UTC
Built: R 4.1.3; x86_64-w64-mingw32; 2023-04-20 16:57:54 UTC; windows
Archs: x64
