torch_linspace: Linspace

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

Linspace

Description

Linspace

Usage

torch_linspace(
  start,
  end,
  steps = 100,
  dtype = NULL,
  layout = NULL,
  device = NULL,
  requires_grad = FALSE
)

Arguments

start	(float) the starting value for the set of points
end	(float) the ending value for the set of points
steps	(int) number of points to sample between start and end. Default: 100.
dtype	(torch.dtype, optional) the desired data type of returned tensor. Default: if NULL, uses a global default (see torch_set_default_tensor_type).
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.

linspace(start, end, steps=100, out=NULL, dtype=NULL, layout=torch.strided, device=NULL, requires_grad=False) -> Tensor

Returns a one-dimensional tensor of steps equally spaced points between start and end.

The output tensor is 1-D of size steps.

Examples

if (torch_is_installed()) {

torch_linspace(3, 10, steps=5)
torch_linspace(-10, 10, steps=5)
torch_linspace(start=-10, end=10, steps=5)
torch_linspace(start=-10, end=10, steps=1)
}

torch documentation built on June 7, 2023, 6:19 p.m.