keras中summary()打印上一篇的网络函数

>>>print(model.summary())
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_anchor (InputLayer)       (None, 299, 299, 3)  0                                            
__________________________________________________________________________________________________
input_pos (InputLayer)          (None, 299, 299, 3)  0                                            
__________________________________________________________________________________________________
input_neg (InputLayer)          (None, 299, 299, 3)  0                                            
__________________________________________________________________________________________________
resnet_model (Model)            (None, 128)          23883008    input_anchor[0][0]               
                                                                 input_pos[0][0]                  
                                                                 input_neg[0][0]                  
__________________________________________________________________________________________________
pos_dist (Lambda)               (None, 1)            0           resnet_model[1][0]               
                                                                 resnet_model[2][0]               
__________________________________________________________________________________________________
neg_dist (Lambda)               (None, 1)            0           resnet_model[1][0]               
                                                                 resnet_model[3][0]               
__________________________________________________________________________________________________
stacked_dists (Lambda)          (None, 2, 1)         0           pos_dist[0][0]                   
                                                                 neg_dist[0][0]                   
==================================================================================================
Total params: 23,883,008
Trainable params: 295,296
Non-trainable params: 23,587,712
__________________________________________________________________________________________________
None