如何从两个顺序网络创建自动编码器?
How to create an autoencoder from two sequential networks?
我有两个顺序网络(编码器网络和解码器网络)。如何使用顺序 API 创建自动编码器模型?
请不要推荐使用函数 API 或解释函数优于顺序的好处,因为这不是这里的问题。
encoder_network = tf.keras.Sequential([
Conv2D(64, 3, padding='same', activation="swish"),
DownscaleBlock(1),
DownscaleBlock(2),
Conv2D(128, 3, padding='same', activation="swish"),
Conv2D(32, 3, padding='same', activation="swish"),
Conv2D(10, 3, padding='same'),
])
decoder_network = tf.keras.Sequential([
Conv2D(4, 3, padding='same', activation="swish"),
Conv2D(16, 3, padding='same', activation="swish"),
Conv2D(64, 3, padding='same', activation="swish"),
UpscaleBlock(1),
UpscaleBlock(2),
Conv2D(4, 3, padding='same', activation="swish"),
Conv2D(1, 3, padding='same'),
])
您可以像使用图层一样使用您的模型:
model = tf.keras.Sequential([
encoder_network,
decoder_network
])
我有两个顺序网络(编码器网络和解码器网络)。如何使用顺序 API 创建自动编码器模型?
请不要推荐使用函数 API 或解释函数优于顺序的好处,因为这不是这里的问题。
encoder_network = tf.keras.Sequential([
Conv2D(64, 3, padding='same', activation="swish"),
DownscaleBlock(1),
DownscaleBlock(2),
Conv2D(128, 3, padding='same', activation="swish"),
Conv2D(32, 3, padding='same', activation="swish"),
Conv2D(10, 3, padding='same'),
])
decoder_network = tf.keras.Sequential([
Conv2D(4, 3, padding='same', activation="swish"),
Conv2D(16, 3, padding='same', activation="swish"),
Conv2D(64, 3, padding='same', activation="swish"),
UpscaleBlock(1),
UpscaleBlock(2),
Conv2D(4, 3, padding='same', activation="swish"),
Conv2D(1, 3, padding='same'),
])
您可以像使用图层一样使用您的模型:
model = tf.keras.Sequential([
encoder_network,
decoder_network
])