C2W3 Assignment. Layer numbers are different. Does this matter?

Course Q&A TensorFlow Developer Professional Convolutional Neural Networks in TensorFlow
1

My output for model summary (last few lines):

batch_normalization_93 (BatchN  (None, 3, 3, 192)   576         ['conv2d_93[0][0]']              
 ormalization)                                                                                    
                                                                                                  
 activation_85 (Activation)     (None, 3, 3, 320)    0           ['batch_normalization_85[0][0]'] 
                                                                                                  
 mixed9_1 (Concatenate)         (None, 3, 3, 768)    0           ['activation_87[0][0]',          
                                                                  'activation_88[0][0]']          
                                                                                                  
 concatenate_1 (Concatenate)    (None, 3, 3, 768)    0           ['activation_91[0][0]',          
                                                                  'activation_92[0][0]']          
                                                                                                  
 activation_93 (Activation)     (None, 3, 3, 192)    0           ['batch_normalization_93[0][0]'] 
                                                                                                  
 mixed10 (Concatenate)          (None, 3, 3, 2048)   0           ['activation_85[0][0]',          
                                                                  'mixed9_1[0][0]',               
                                                                  'concatenate_1[0][0]',          
                                                                  'activation_93[0][0]']          
                                                                                                  
==================================================================================================
Total params: 21,802,784
Trainable params: 0
Non-trainable params: 21,802,784

Expected output:

batch_normalization_v1_281 (Bat (None, 3, 3, 192)    576         conv2d_281[0][0]                 
__________________________________________________________________________________________________
activation_273 (Activation)     (None, 3, 3, 320)    0           batch_normalization_v1_273[0][0] 
__________________________________________________________________________________________________
mixed9_1 (Concatenate)          (None, 3, 3, 768)    0           activation_275[0][0]             
                                                                activation_276[0][0]             
__________________________________________________________________________________________________
concatenate_5 (Concatenate)     (None, 3, 3, 768)    0           activation_279[0][0]             
                                                                activation_280[0][0]             
__________________________________________________________________________________________________
activation_281 (Activation)     (None, 3, 3, 192)    0           batch_normalization_v1_281[0][0] 
__________________________________________________________________________________________________
mixed10 (Concatenate)           (None, 3, 3, 2048)   0           activation_273[0][0]             
                                                                mixed9_1[0][0]                   
                                                                concatenate_5[0][0]              
                                                                activation_281[0][0]             
==================================================================================================
Total params: 21,802,784
Trainable params: 0
Non-trainable params: 21,802,784

Does this difference matter? (e.g “batch_normalization_93” and “batch_normalization_v1_281” seem to be the same layer but have different names) What causes this difference?

2

Layer names don’t matter as long as you don’t look for a particular layer by name.