    def predict(self, mix):
        """
        Predict the separated sources from the input mix.

        Args:
            mix (np.ndarray): Input mixture signal.

        Returns:
            tuple: Tuple containing the mixture minus the separated sources and the separated sources.
        """
        if mix.ndim == 1:
            mix = np.asfortranarray([mix, mix])

        tail = mix.shape[1] % (self.args["chunks"] * 44100)
        if mix.shape[1] % (self.args["chunks"] * 44100) != 0:
            mix = np.pad(
                mix,
                (
                    (0, 0),
                    (
                        0,
                        self.args["chunks"] * 44100
                        - mix.shape[1] % (self.args["chunks"] * 44100),
                    ),
                ),
            )

        mix = mix.T
        sources = self.demix(mix.T)
        opt = sources[0].T

        if tail != 0:
            return ((mix - opt)[: -(self.args["chunks"] * 44100 - tail), :], opt)
        else:
            return ((mix - opt), opt)
Predict the separated sources from the input mix.

Args:
mix (np.ndarray): Input mixture signal.

Returns:
tuple: Tuple containing the mixture minus the separated sources and the separated sources.
preprocessors/Emilia/models/separate_fast.py