torch.fft.rfft2
torch.fft.rfft2(input, s=None, dim=(- 2, - 1), norm=None, *, out=None) -> Tensor
Computes the 2-dimensional discrete Fourier transform of real
   "input". Equivalent to "rfftn()" but FFTs only the last two
   dimensions by default.
The FFT of a real signal is Hermitian-symmetric, "X[i, j] =
   conj(X[-i, -j])", so the full "fft2()" output contains redundant
   information. "rfft2()" instead omits the negative frequencies in
   the last dimension.
Note:
 Supports torch.half 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 real FFT. If a length "-1" is specified, no
