take the one dimensional Hermitian IFFT.
  * **norm** (*str**, **optional*) --

    Normalization mode. For the backward transform ("ihfft()"),
    these correspond to:

    * ""forward"" - no normalization

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

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

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

    Default is ""backward"" (normalize by "1/n").

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



t = torch.arange(5)
t
   tensor([0, 1, 2, 3, 4])
torch.fft.ihfft(t)
   tensor([ 2.0000-0.0000j, -0.5000-0.6882j, -0.5000-0.1625j])



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



torch.fft.ifft(t)


