torch_repeat_interleave: Repeat_interleave

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

Repeat_interleave

Description

Repeat_interleave

Usage

torch_repeat_interleave(self, repeats, dim = NULL, output_size = NULL)

Arguments

self	(Tensor) the input tensor.
repeats	(Tensor or int) The number of repetitions for each element. repeats is broadcasted to fit the shape of the given axis.
dim	(int, optional) The dimension along which to repeat values. By default, use the flattened input array, and return a flat output array.
output_size	(int, optional) – Total output size for the given axis ( e.g. sum of repeats). If given, it will avoid stream syncronization needed to calculate output shape of the tensor.

repeat_interleave(input, repeats, dim=NULL) -> Tensor

Repeat elements of a tensor.

Warning

This is different from `torch_Tensor.repeat` but similar to `numpy.repeat`.

repeat_interleave(repeats) -> Tensor

If the repeats is ⁠tensor([n1, n2, n3, ...])⁠, then the output will be ⁠tensor([0, 0, ..., 1, 1, ..., 2, 2, ..., ...])⁠ where 0 appears n1 times, 1 appears n2 times, 2 appears n3 times, etc.

Examples

if (torch_is_installed()) {
## Not run: 
x = torch_tensor(c(1, 2, 3))
x$repeat_interleave(2)
y = torch_tensor(matrix(c(1, 2, 3, 4), ncol = 2, byrow=TRUE))
torch_repeat_interleave(y, 2)
torch_repeat_interleave(y, 3, dim=1)
torch_repeat_interleave(y, torch_tensor(c(1, 2)), dim=1)

## End(Not run)
}

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