torch_fft_ifft: Ifft

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

Ifft

Description

Computes the one dimensional inverse discrete Fourier transform of input.

Usage

torch_fft_ifft(self, n = NULL, dim = -1L, norm = NULL)

Arguments

self	(Tensor) the input tensor
n	(int, optional) – Signal length. If given, the input will either be zero-padded or trimmed to this length before computing the IFFT.
dim	(int, optional) – The dimension along which to take the one dimensional IFFT.
norm	(str, optional) – Normalization mode. For the backward transform, these correspond to: "forward" - no normalization "backward" - normalize by 1/n "ortho" - normalize by 1/sqrt(n) (making the IFFT orthonormal) Calling the forward transform with the same normalization mode will apply an overall normalization of 1/n between the two transforms. This is required to make ifft() the exact inverse. Default is "backward" (normalize by 1/n).

Examples

if (torch_is_installed()) {
t <- torch_arange(start = 0, end = 3)
t
x <- torch_fft_fft(t, norm = "backward")
torch_fft_ifft(x)


}

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