Randperm

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)
}
#> torch_tensor
#>  1
#>  2
#>  0
#>  3
#> [ CPULongType{4} ]