torch.fft.fftn
torch.fft.fftn(input, s=None, dim=None, norm=None, *, out=None) -> Tensor
Computes the N dimensional discrete Fourier transform of "input".
Note:
 The Fourier domain representation of any real signal satisfies
 the Hermitian property: "X[i_1, ..., i_n] = conj(X[-i_1, ...,
 -i_n])". This function always returns all positive and negative
 frequency terms even though, for real inputs, half of these
 values are redundant. "rfftn()" returns the more compact one-
 sided representation where only the positive frequencies of the
 last dimension are returned.

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
