aae_build_encoder_model.py

def _build_encoder_model(self):
    print("Building Encoder...")

    encoder_input = Input(shape=self.img_shape)

    encoder_sequence = Flatten()(encoder_input)
    encoder_sequence = Dense(512)(encoder_sequence)
    encoder_sequence = LeakyReLU(alpha=0.2)(encoder_sequence)
    encoder_sequence = Dense(512)(encoder_sequence)
    encoder_sequence = LeakyReLU(alpha=0.2)(encoder_sequence)
    mean = Dense(self.latent_dimension)(encoder_sequence)
    deviation = Dense(self.latent_dimension)(encoder_sequence)

    latent_vector = merge([mean, deviation],
            mode=lambda p: p[0] + K.random_normal(K.shape(p[0])) * K.exp(p[1] / 2),
            output_shape=lambda p: p[0])

    self.encoder_model = Model(encoder_input, latent_vector, name = 'encoder')
    self.encoder_model.summary()