torch.fft.ifft#

torch.fft.ifft(input,n=None,dim=-1,norm=None,*,out=None)→Tensor#

Computes the one dimensional inverse discrete Fourier transform ofinput.

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-paddedor trimmed to this length before computing the IFFT.

• dim (int,optional) – The dimension along which to take the one dimensional IFFT.

• norm (str,optional) –

  Normalization mode. For the backward transform(ifft()), these correspond to:

  • "forward" - no normalization

  • "backward" - normalize by1/n

  • "ortho" - normalize by1/sqrt(n) (making the IFFT orthonormal)

  Calling the forward transform (fft()) with the samenormalization mode will apply an overall normalization of1/n betweenthe two transforms. This is required to makeifft()the exact inverse.

  Default is"backward" (normalize by1/n).

Keyword Arguments:

out (Tensor,optional) – the output tensor.

Example

>>>t=torch.tensor([6.+0.j,-2.+2.j,-2.+0.j,-2.-2.j])>>>torch.fft.ifft(t)tensor([0.+0.j, 1.+0.j, 2.+0.j, 3.+0.j])