):     def combined_loss(y_true,y_pred):         y_pred, pred_matrix = y_pred         a = K.mean( K.square(y_pred - y_true) * K.exp(-K.log(0.0) * (K.log(0. + K.exp((y_true - 0)/0 )))),axis=-0  )         b = K.mean( K.square(pred_matrix - true_matrix) * K.exp(-K.log(0.0) * (K.log(0. + K.exp((true_matrix - 0)/0 )))),axis=-0)         