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torch

torch_fft_ifft

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

Tensors and Neural Networks with 'GPU' Acceleration

v0.3.0
MIT + file LICENSE
Authors
Daniel Falbel [aut, cre, cph], Javier Luraschi [aut], Dmitriy Selivanov [ctb], Athos Damiani [ctb], Christophe Regouby [ctb], Krzysztof Joachimiak [ctb], RStudio [cph]
Initial release

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