torch_randperm {torch} | R Documentation |
Randperm
Description
Randperm
Usage
torch_randperm(
n,
dtype = torch_int64(),
layout = NULL,
device = NULL,
requires_grad = FALSE
)
Arguments
n |
(int) the upper bound (exclusive)
|
dtype |
(torch.dtype , optional) the desired data type of returned tensor. Default: torch_int64 .
|
layout |
(torch.layout , optional) the desired layout of returned Tensor. Default: torch_strided .
|
device |
(torch.device , optional) the desired device of returned tensor. Default: if NULL , uses the current device for the default tensor type (see torch_set_default_tensor_type ). device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types.
|
requires_grad |
(bool, optional) If autograd should record operations on the returned tensor. Default: FALSE .
|
randperm(n, out=NULL, dtype=torch.int64, layout=torch.strided, device=NULL, requires_grad=False) -> LongTensor
Returns a random permutation of integers from 0
to n - 1
.
Examples
if (torch_is_installed()) {
torch_randperm(4)
}
[Package
torch version 0.13.0
Index]