rTorch0.4.2 package

R Bindings to 'PyTorch'

grapes-.-times-grapes

#' @export "round.torch.Tensor" <- function(input) # round: Returns a ...

grapes-grapes-.torch.Tensor

Remainder

grapes-times-times-grapes

Matrix/Tensor multiplication of two tensors

greater-than-.torch.Tensor

A tensor greater than another tensor

greater-than-equals-.torch.Tensor

Is a tensor greater or equal than another tensor

logical_or

Logical OR of two tensors

make_copy

Make copy of tensor, numpy array or R array

modules

Main PyTorch module

not_equal_to

Compare two tensors if not equal

one_tensor_op

One tensor operation

plus-.torch.Tensor

Add two tensors

reexports

Objects exported from other packages

rTorch

PyTorch for R

shape

Tensor shape

slash-.torch.Tensor

Divide two tensors

install_pytorch

Install PyTorch and its dependencies

install_torch_extras

Install additional Python packages alongside PyTorch

is_tensor

Is the object a tensor

length.torch.Tensor

Length of a tensor.

less-than-.torch.Tensor

Is a tensor less than another tensor

less-than-equals-.torch.Tensor

Is a tensor less or equal than another tensor

log.torch.Tensor

Logarithm of a tensor given the tensor and the base

log10.torch.Tensor

Logarithm of a tensor in base 10

log2.torch.Tensor

Logarithm of a tensor in base 2

logical_and

Logical AND of two tensors

logical_not

Logical NOT of a tensor

all.torch.Tensor

all

all_dims

All dims

any.torch.Tensor

any

as_boolean

Convert tensor to boolean type

dataset_mnist_digits

MNIST database of handwritten digits

dim.torch.Tensor

Dimensions of a tensor

dot-torch.Tensor

Subtract two tensors

equals-.torch.Tensor

Compares two tensors if equal

sub-.torch.Tensor

Subset tensors with [

tensor_ops

Two tensor operations

times-.torch.Tensor

Tensor multiplication

torch_config

Torch configuration information

torch_extract_opts

Tensor extract options

torch_size

Size of a torch tensor object

'R' implementation and interface of the Machine Learning platform 'PyTorch' <https://pytorch.org/> developed in 'Python'. It requires a 'conda' environment with 'torch' and 'torchvision' Python packages to provide 'PyTorch' functions, methods and classes. The key object in 'PyTorch' is the tensor which is in essence a multidimensional array. These tensors are fairly flexible in performing calculations in CPUs as well as 'GPUs' to accelerate tensor operations.

  • Maintainer: Alfonso R. Reyes
  • License: MIT + file LICENSE
  • Last published: 2020-10-12