torch.fft.ifftn
torch.fft.ifftn(input, s=None, dim=None, norm=None, *, out=None) -> Tensor
Computes the N 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 dimensions.

Parameters:
      * input (Tensor) -- the input tensor
  * **s** (*Tuple**[**int**]**, **optional*) -- Signal size in the
    transformed dimensions. If given, each dimension "dim[i]" will
    either be zero-padded or trimmed to the length "s[i]" before
    computing the IFFT. If a length "-1" is specified, no padding
    is done in that dimension. Default: "s = [input.size(d) for d
    in dim]"

  * **dim** (*Tuple**[**int**]**, **optional*) -- Dimensions to be
    transformed. Default: all dimensions, or the last "len(s)"
    dimensions if "s" is given.
