def call(self, y, x):
        """Calculate forward propagation.
        Args:
            y (Tensor): Groundtruth signal (B, T).
            x (Tensor): Predicted signal (B, T).
        Returns:
            Tensor: Multi resolution spectral convergence loss value.
            Tensor: Multi resolution log STFT magnitude loss value.
        """
        B=self.batch
        x=tf.reshape(x,[B,-1])
        y=tf.reshape(y,[B,-1])
        sc_loss = 0.0
        mag_loss = 0.0

        for f in self.stft_losses:
            sc_l, mag_l = f.call([y, x])
            sc_loss += tf.reduce_mean(sc_l)
            mag_loss += tf.reduce_mean(mag_l)
        sc_loss /= len(self.stft_losses)
        mag_loss /= len(self.stft_losses)

        return sc_loss + mag_loss
Calculate forward propagation.
        Args:
            y (Tensor): Groundtruth signal (B, T).
            x (Tensor): Predicted signal (B, T).
        Returns:
            Tensor: Multi resolution spectral convergence loss value.
            Tensor: Multi resolution log STFT magnitude loss value.
        
vad/utils/stft.py