However, unlike the traditional conditional GAN methods (Mirza and Osindero, 2014;Hu et al., 2017), we do not concatenate the sentiment label directly into latent codes; considering the relatively high dimensions of latent embeddings, concatenating the sentiment scalar into the input might not be powerful enough to force the generator to update itself to match with the designated sentiment.
we condition the sentiment labels on the discriminator to artificially change the rules that the discriminator works, and force it backpropagate loss functions that update generator policy correspondingly.