torch_empty_strided: Empty_strided

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

Empty_strided

Description

Empty_strided

Usage

torch_empty_strided(
  size,
  stride,
  dtype = NULL,
  layout = NULL,
  device = NULL,
  requires_grad = FALSE,
  pin_memory = FALSE
)

Arguments

size	(tuple of ints) the shape of the output tensor
stride	(tuple of ints) the strides of the output tensor
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.
pin_memory	(bool, optional) If set, returned tensor would be allocated in the pinned memory. Works only for CPU tensors. Default: FALSE.

empty_strided(size, stride, dtype=NULL, layout=NULL, device=NULL, requires_grad=False, pin_memory=False) -> Tensor

Returns a tensor filled with uninitialized data. The shape and strides of the tensor is defined by the variable argument size and stride respectively. torch_empty_strided(size, stride) is equivalent to ⁠torch_empty(size).as_strided(size, stride)⁠.

Warning

More than one element of the created tensor may refer to a single memory location. As a result, in-place operations (especially ones that are vectorized) may result in incorrect behavior. If you need to write to the tensors, please clone them first.

Examples

if (torch_is_installed()) {

a = torch_empty_strided(list(2, 3), list(1, 2))
a
a$stride(1)
a$size(1)
}

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