6,
        n_hop: int = 1024,
        center: bool = False,
        sample_rate: float = 44100.0,
        window: Optional[nn.Parameter] = None,
    ) -&gt; None:
        super(TorchISTFT, self).__init__()

        self.n_fft = n_fft
        self.n_hop = n_hop
        self.center = center
        self.sample_rate = sample_rate

        if window is not None:
            self.window = nn.Parameter(torch.hann_window(n_fft), requires_grad=False)
        else:
            self.window = window

    def forward(s