torch_as_strided: As_strided

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

As_strided

Description

As_strided

Usage

torch_as_strided(self, size, stride, storage_offset = NULL)

Arguments

self	(Tensor) the input tensor.
size	(tuple or ints) the shape of the output tensor
stride	(tuple or ints) the stride of the output tensor
storage_offset	(int, optional) the offset in the underlying storage of the output tensor

as_strided(input, size, stride, storage_offset=0) -> Tensor

Create a view of an existing torch_Tensor input with specified size, stride and storage_offset.

Warning

More than one element of a 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.

Many PyTorch functions, which return a view of a tensor, are internally
implemented with this function. Those functions, like
`torch_Tensor.expand`, are easier to read and are therefore more
advisable to use.

Examples

if (torch_is_installed()) {

x = torch_randn(c(3, 3))
x
t = torch_as_strided(x, list(2, 2), list(1, 2))
t
t = torch_as_strided(x, list(2, 2), list(1, 2), 1)
t
}

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