Machine Learning, Data Science, Deep Learning, Artificial Intelligence, Towards Data Science.
loss='binary_crossentropy') d.trainable = False # GAN gan = Sequential([g, d]) gan.compile(optimizer=Adam(lr=0.0001, beta_1=0.5), loss='binary_crossentropy') return gan, g, d The above code is just for the architecture of the generator and discriminator network. Comparing this method of coding the