这里使用了一个简单的 MNIST convnet。
model = keras.Sequential([
layers.InputLayer(input_shape=input_shape),
layers.Conv2D(16, kernel_size=(3, 3), activation="relu"),
layers.BatchNormalization(),
layers.MaxPooling2D(pool_size=(2, 2)),
layers.Conv2D(32, kernel_size=(3, 3), activation="relu"),
layers.MaxPooling2D(pool_size=(2, 2)),
layers.Flatten(),
layers.Dropout(0.5),
layers.Dense(num_classes),
])