torch_diff: Computes the n-th forward difference along the given...

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

Computes the n-th forward difference along the given dimension.

Description

The first-order differences are given by out[i] = input[i + 1] - input[i]. Higher-order differences are calculated by using torch_diff() recursively.

Usage

torch_diff(self, n = 1L, dim = -1L, prepend = list(), append = list())

Arguments

self	the tensor to compute the differences on
n	the number of times to recursively compute the difference
dim	the dimension to compute the difference along. Default is the last dimension.
prepend	values to prepend to input along dim before computing the difference. Their dimensions must be equivalent to that of input, and their shapes must match input’s shape except on dim.
append	values to append to input along dim before computing the difference. Their dimensions must be equivalent to that of input, and their shapes must match input’s shape except on dim.

Note

Only n = 1 is currently supported

Examples

if (torch_is_installed()) {
a <- torch_tensor(c(1,2,3))
torch_diff(a)

b <- torch_tensor(c(4, 5))
torch_diff(a, append = b)

c <- torch_tensor(rbind(c(1,2,3), c(3,4,5)))
torch_diff(c, dim = 1)
torch_diff(c, dim = 2) 

}

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