Thanks for your reply, I already saw the link, but it is not clear to me how should I add that to my model exactly since I am very new to tf keras.
so I have the model as defined above in the post.
now I define this new dense layer for having prediction of two classes:
prediction_layer = tf.keras.layers.Dense(2)

how can I add it to the model so when I print it it shows it in the model.summary()?
For clarification, I dont want to do it like:
inputs = tf.keras.Input(shape=(160, 160, 3))
x = data_augmentation(inputs)
x = preprocess_input(x)
x = base_model(x, training=False)
x = global_average_layer(x)
x = tf.keras.layers.Dropout(0.2)(x)
outputs = prediction_layer(x)
model = tf.keras.Model(inputs, outputs)

but I like to do it so my model.summary() show them all. would that be possible?