卷积层的维度变化

import keras
from keras import Sequential

model = Sequential()
model.add(keras.layers.Conv2D(input_shape=(28, 28, 1), kernel_size=(5,5), filters=20, activation='relu'))
model.add(keras.layers.MaxPool2D(pool_size=(2,2), strides=2, padding='same'))

model.add(keras.layers.Conv2D(kernel_size=(5,5), filters=50, activation='relu', padding='same'))
model.add(keras.layers.MaxPool2D(pool_size=(2,2), strides=2, padding='same'))

model.add(keras.layers.Flatten())
model.add(keras.layers.Dense(500, activation='relu'))
model.add(keras.layers.Dense(10, activation='softmax'))

##>>> model.layers[0].output_shape
##(None, 24, 24, 20)
##>>> model.layers[1].output_shape
##(None, 12, 12, 20)
##>>> model.layers[2].output_shape
##(None, 12, 12, 50)
##>>> model.layers[3].output_shape
##(None, 6, 6, 50)
##>>> model.layers[4].output_shape
##(None, 1800)
##>>> model.layers[5].output_shape
##(None, 500)
##>>> model.layers[6].output_shape
##(None, 10)

//终于弄明白了。