序贯Sequential模型

通过向Sequential模型传递一个layer的list来构造该模型

model = Sequential([Dense(32,input_shape=(784,)),Activation('relu'),Dense(10),Activation('softmax'),])

model.compile(optimizer='rmsprop',
loss='categorical_crossentropy',
metrics=['accuracy'])

print('list',model.summary())

通过add（）方法一个一个的将layer加入模型中

model = Sequential()
model.add(Dense(32,input_shape=(784,)))

model.add(Activation('relu'))
model.add(Dense(10))
model.add(Activation('softmax'))

model.compile(optimizer='rmsprop',
loss='categorical_crossentropy',
metrics=['accuracy'])

print('add',model.summary())