def call(self, y, x):
        """Calculate forward propagation.
        Args:
            y (Tensor): Groundtruth signal (B, T).
            x (Tensor): Predicted signal (B, T).
        Returns:
            Tensor: Mean absolute Error Spectrogram Loss.
        """
        y_mag = self._calculate_log_mels_spectrogram(y)
        x_mag = self._calculate_log_mels_spectrogram(x)
        # return tf.norm(y_mels - x_mels, ord="fro", axis=(-2, -1)) / tf.norm(y_mels, ord="fro", axis=(-2, -1))
        # return tf.norm(y_mels - x_mels, ord="fro", axis=(-2, -1)) / tf.norm(y_mels, ord="fro", axis=(-2, -1))
        length = 176
        return tf.reduce_mean(tf.square(y_mag - x_mag)) + tf.reduce_mean(
            tf.square(y_mag[:, :, length:] - x_mag[:, :, length:]))
        # return tf.norm(y_mels - x_mels, ord="fro", axis=(-2, -1)) / (tf.norm(y_mels, ord="fro", axis=(-2, -1))+1e-6)+ \
        #        tf.norm(y_mels[:,:,length:] - x_mels[:,:,length:], ord="fro", axis=(-2, -1)) / (tf.norm(y_mels[:,:,length:], ord="fro", axis=(-2, -1)) + 1e-6)
Calculate forward propagation.
        Args:
            y (Tensor): Groundtruth signal (B, T).
            x (Tensor): Predicted signal (B, T).
        Returns:
            Tensor: Mean absolute Error Spectrogram Loss.
        
vad/utils/stft.py