def func(tensor):
     sample_rate = 44100
     n_fft = 400
     ws = 400
     hop = 200
     pad = 0
     window = torch.hann_window(ws, device=tensor.device, dtype=tensor.dtype)
     return F.spectral_centroid(tensor, sample_rate, pad, window, n_fft, hop, ws)
Example #2
0
    def forward(self, waveform: Tensor) -> Tensor:
        r"""
        Args:
            waveform (Tensor): Tensor of audio of dimension (..., time).

        Returns:
            Tensor: Spectral Centroid of size (..., time).
        """

        return F.spectral_centroid(waveform, self.sample_rate, self.pad, self.window, self.n_fft, self.hop_length,
                                   self.win_length)