As_strided

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_tensor
#> -1.0386  0.9525
#> -0.9742 -0.9887
#> [ CPUFloatType{2,2} ]