"ihfft()" the exact inverse.
    Default is ""backward"" (no normalization).

Keyword Arguments:
      out (Tensor, optional) -- the output tensor.
-[ Example ]-
Taking a real-valued frequency signal and bringing it into the time
   domain gives Hermitian symmetric output:



t = torch.linspace(0, 1, 5)
t
   tensor([0.0000, 0.2500, 0.5000, 0.7500, 1.0000])
T = torch.fft.ifft(t)
T
   tensor([ 0.5000-0.0000j, -0.1250-0.1720j, -0.1250-0.0406j, -0.1250+0.0406j,
           -0.1250+0.1720j])



Note that "T[1] == T[-1].conj()" and "T[2] == T[-2].conj()" is
   redundant. We can thus compute the forward transform without
   considering negative frequencies:



torch.fft.hfft(T[:3], n=5)
   tensor([0.0000, 0.2500, 0.5000, 0.7500, 1.0000])



Like with "irfft()", the output length must be given in order to
   recover an even length output:



torch.fft.hfft(T[:3])
   tensor([0.1250, 0.2809, 0.6250, 0.9691])


