two transforms. This is required to make "ihfft2()" the exact
        inverse.
    Default is ""backward"" (no normalization).

Keyword Arguments:
      out (Tensor, optional) -- the output tensor.
-[ Example ]-
Starting from a real frequency-space signal, we can generate a
   Hermitian-symmetric time-domain signal: >>> T = torch.rand(10, 9)



t = torch.fft.ihfft2(T)



Without specifying the output length to "hfftn()", the output will
   not round-trip properly because the input is odd-length in the last
   dimension:



torch.fft.hfft2(t).size()
   torch.Size([10, 10])



So, it is recommended to always pass the signal shape "s".



roundtrip = torch.fft.hfft2(t, T.size())
roundtrip.size()
   torch.Size([10, 9])
torch.allclose(roundtrip, T)
   True


