
norm (str, optional) --Normalization mode. For the forward transform ("rfft()"),
these correspond to:

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

* ""backward"" - no normalization

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

Calling the backward transform ("irfft()") with the same
normalization mode will apply an overall normalization of
"1/n" between the two transforms. This is required to make
"irfft()" the exact inverse.

Default is ""backward"" (no normalization).



Keyword Arguments:
      out (Tensor, optional) -- the output tensor.
-[ Example ]-



t = torch.arange(4)
t
   tensor([0, 1, 2, 3])
torch.fft.rfft(t)
   tensor([ 6.+0.j, -2.+2.j, -2.+0.j])



Compare against the full output from "fft()":



torch.fft.fft(t)
   tensor([ 6.+0.j, -2.+2.j, -2.+0.j, -2.-2.j])



Notice that the symmetric element "T[-1] == T[1].conj()" is