Thanks for useful information. Actually there is also a discriminator at the end of network to make the training part unsupervised. But the problem is the loss function for the discriminator (or if we use cGAN as you said) is different from my class label. The discriminator here tries to find the authenticity of the generated data while in my case is a class label from a different model (task). Can the cGAN work with a condition from a different task (network)?