torch.fft.ifft
torch.fft.ifft(input, n=None, dim=- 1, norm=None, *, out=None) -> Tensor
Computes the one dimensional inverse discrete Fourier transform of
   "input".
Note:
 Supports torch.half and torch.chalf on CUDA with GPU Architecture
 SM53 or greater. However it only supports powers of 2 signal
 length in every transformed dimension.

Parameters:
      * input (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 ("ifft()"),
    these correspond to:

    * ""forward"" - no normalization

    * ""backward"" - normalize by "1/n"

    * ""ortho"" - normalize by "1/sqrt(n)" (making the IFFT
