torch.fft.fft
torch.fft.fft(input, n=None, dim=- 1, norm=None, *, out=None) -> Tensor
Computes the one dimensional discrete Fourier transform of "input".
Note:
 The Fourier domain representation of any real signal satisfies
 the Hermitian property: *X[i] = conj(X[-i])*. This function
 always returns both the positive and negative frequency terms
 even though, for real inputs, the negative frequencies are
 redundant. "rfft()" returns the more compact one-sided
 representation where only the positive frequencies are returned.

Note:
 Supports torch.half and torch.chalf on CUDA with GPU Architecture
 SM53 or greater. However it only supports powers of 2 signal
 length in every transformed dimension.

Parameters:
      * input (Tensor) -- the input tensor
  * **n** (*int**, **optional*) -- Signal length. If given, the
    input will either be zero-padded or trimmed to this length
    before computing the FFT.
