TensorFlow 2.0 implementation of mini VGG-based Autoencoder.

mini_vgg_ae.py

class Autoencoder(tf.keras.Model):
    def __init__(self, **kwargs):
        super(Autoencoder, self).__init__()
        self.encoder = Encoder(
                input_shape=kwargs['input_shape'],
                latent_dim=kwargs['latent_dim']
                )
        self.decoder = Decoder(latent_dim=kwargs['latent_dim'])

    def call(self, features):
        code = self.encoder(features)
        reconstructed = self.decoder(code)
        return reconstructed