tf_2_intro_model.py

IMG_SIZE = (28, 28, 1)
input_img = layers.Input(shape=IMG_SIZE)

model = layers.Conv2D(32, (3, 3), padding='same')(input_img)
model = layers.Activation('relu')(model)
model = layers.Conv2D(32, (3, 3), padding='same', strides=(2, 2))(model)
model = layers.Activation('relu')(model)

model = layers.Conv2D(64, (3, 3), padding='same')(model)
model = layers.Activation('relu')(model)
model = layers.Conv2D(64, (3, 3), padding='same', strides=(2, 2))(model)
model = layers.Activation('relu')(model)

model = layers.Conv2D(64, (3, 3), padding='same')(model)
model = layers.Activation('relu')(model)
model = layers.Conv2D(64, (3, 3), padding='same')(model)
model = layers.Activation('relu')(model)

model = layers.GlobalAveragePooling2D()(model)
model = layers.Dense(32)(model)
model = layers.Activation('relu')(model)
model = layers.Dense(10)(model)
output_img = layers.Activation('softmax')(model)

model = models.Model(input_img, output_img)

model.summary()