However, its input is not the meaning vector but the form vector:f The motivator has the same architecture as the discriminator, and the same loss function.
while the adversarial loss forces the encoder E to produce a meaning vector m with no information about the form f , the motivational loss encourages E to encode this information in the form vector by minimizing L M : The overall training procedure follows the methods for training GANs (Goodfellow et al., 2014;Arjovsky et al., 2017) and consists of two stages: training the discriminator D and the motivator M , and training the encoder E and the generator G. to Arjovsky et al.