before computing the FFT.
  * **dim** (*int**, **optional*) -- The dimension along which to
    take the one dimensional FFT.

  * **norm** (*str**, **optional*) --

    Normalization mode. For the forward transform ("fft()"), 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 ("ifft()") with the same
    normalization mode will apply an overall normalization of
    "1/n" between the two transforms. This is required to make
    "ifft()" 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.fft(t)
   tensor([ 6.+0.j, -2.+2.j, -2.+0.j, -2.-2.j])


