torch_randperm: Randperm

In torch: Tensors and Neural Networks with 'GPU' Acceleration

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)
}

torch documentation built on May 29, 2024, 9:54 a.m.