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

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



x = torch.rand(10, 10, dtype=torch.complex64)
fft2 = torch.fft.fft2(x)



The discrete Fourier transform is separable, so "fft2()" here is
   equivalent to two one-dimensional "fft()" calls:



two_ffts = torch.fft.fft(torch.fft.fft(x, dim=0), dim=1)
torch.testing.assert_close(fft2, two_ffts, check_stride=False)


