def call(self, y_mag, x_mag):
        """Calculate forward propagation.
        Args:
            y_mag (Tensor): Magnitude spectrogram of groundtruth signal (B, #frames, #freq_bins).
            x_mag (Tensor): Magnitude spectrogram of predicted signal (B, #frames, #freq_bins).
        Returns:
            Tensor: Spectral convergence loss value.
        """
        y_mag = tf.math.log(y_mag)
        x_mag = tf.math.log(x_mag)
        # length = int(tf.shape(y_mag)[-1] //2)
        extra_loss=0.

        return tf.keras.losses.mse(y_mag,x_mag)
        # return tf.norm(y_mag[:,:,:length] - x_mag[:,:,:length], ord="fro", axis=(-2, -1)) / tf.norm(y_mag[:,:,:length], ord="fro", axis=(-2, -1))+tf.norm(y_mag[:,:,length:] - x_mag[:,:,length:], ord="fro", axis=(-2, -1)) / tf.norm(y_mag[:,:,length:], ord="fro", axis=(-2, -1))
        # return tf.norm(y_mag - x_mag, ord="fro", axis=(-2, -1)) / (tf.norm(y_mag, ord="fro", axis=(-2, -1))+1e-6)+ \
        #        tf.norm(y_mag[:,:,length:] - x_mag[:,:,length:], ord="fro", axis=(-2, -1)) / (tf.norm(y_mag[:,:,length:], ord="fro", axis=(-2, -1)) + 1e-6)
Calculate forward propagation.
        Args:
            y_mag (Tensor): Magnitude spectrogram of groundtruth signal (B, #frames, #freq_bins).
            x_mag (Tensor): Magnitude spectrogram of predicted signal (B, #frames, #freq_bins).
        Returns:
            Tensor: Spectral convergence loss value.
        
vad/utils/stft.py