torch_full: Full

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

Full

Description

Full

Usage

torch_full(
  size,
  fill_value,
  names = NULL,
  dtype = NULL,
  layout = NULL,
  device = NULL,
  requires_grad = FALSE
)

Arguments

size	(int...) a list, tuple, or torch_Size of integers defining the shape of the output tensor.
fill_value	NA the number to fill the output tensor with.
names	optional names of the dimensions
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.

full(size, fill_value, out=NULL, dtype=NULL, layout=torch.strided, device=NULL, requires_grad=False) -> Tensor

Returns a tensor of size size filled with fill_value.

Warning

In PyTorch 1.5 a bool or integral fill_value will produce a warning if dtype or out are not set. In a future PyTorch release, when dtype and out are not set a bool fill_value will return a tensor of torch.bool dtype, and an integral fill_value will return a tensor of torch.long dtype.

Examples

if (torch_is_installed()) {

torch_full(list(2, 3), 3.141592)
}

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