Theoretical questions about layers in dnn with batchnormalization using keras

[jorgeMariano]

Hi, I'm new here, I'm sorry also for my english.

I have some troubles to understand the models of DNN using batchnormalization, in specifique using keras. Can somebody explaind me the structure and content of each layer in this model that I built?

modelbatch = Sequential()
modelbatch.add(Dense(512, input_dim=1120))
modelbatch.add(BatchNormalization())
modelbatch.add(Activation('relu'))
modelbatch.add(Dropout(0.5))

modelbatch.add(Dense(256))
modelbatch.add(BatchNormalization())
modelbatch.add(Activation('relu'))
modelbatch.add(Dropout(0.5))

modelbatch.add(Dense(num_classes))
modelbatch.add(BatchNormalization())
modelbatch.add(Activation('softmax'))
# Compile model
modelbatch.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
# Train the model
start = time.time()
model_info = modelbatch.fit(X_2, y_2, batch_size=500, \
                         epochs=20, verbose=2, validation_data=(X_test, y_test))
end = time.time()

This is, i think, all the layers of my model:

print(modelbatch.layers[0].get_weights()[0].shape)
(1120, 512)
print(modelbatch.layers[0].get_weights()[1].shape)
(512,)
print(modelbatch.layers[1].get_weights()[0].shape)
(512,)
print(modelbatch.layers[1].get_weights()[1].shape)
(512,)
print(modelbatch.layers[1].get_weights()[2].shape)
(512,)
print(modelbatch.layers[1].get_weights()[3].shape)
(512,)
print(modelbatch.layers[4].get_weights()[0].shape)
(512, 256)
print(modelbatch.layers[4].get_weights()[1].shape)
(256,)
print(modelbatch.layers[5].get_weights()[0].shape)
(256,)
print(modelbatch.layers[5].get_weights()[1].shape)
(256,)
print(modelbatch.layers[5].get_weights()[2].shape)
(256,)
print(modelbatch.layers[5].get_weights()[3].shape)
(256,)
print(modelbatch.layers[8].get_weights()[0].shape)
(256, 38)
print(modelbatch.layers[8].get_weights()[1].shape)
(38,)
print(modelbatch.layers[9].get_weights()[0].shape)
(38,)
print(modelbatch.layers[9].get_weights()[1].shape)
(38,)
print(modelbatch.layers[9].get_weights()[2].shape)
(38,)
print(modelbatch.layers[9].get_weights()[3].shape)
(38,)

I will appreciate your help, thanks in advance.