torch.istft
torch.istft(input, n_fft, hop_length=None, win_length=None, window=None, center=True, normalized=False, onesided=None, length=None, return_complex=False) -> Tensor:
Inverse short time Fourier Transform. This is expected to be the
   inverse of "stft()".
It has the same parameters (+ additional optional parameter of
   "length") and it should return the least squares estimation of the
   original signal. The algorithm will check using the NOLA condition
   ( nonzero overlap).
Important consideration in the parameters "window" and "center" so
   that the envelop created by the summation of all the windows is
   never zero at certain point in time. Specifically,
   \sum_{t=-\infty}^{\infty} |w|^2[n-t\times hop_length] \cancel{=}
   0.
Since "stft()" discards elements at the end of the signal if they
   do not fit in a frame, "istft" may return a shorter signal than the
   original signal (can occur if "center" is False since the signal