A conditioning augmentation (CA) network samples random latent variables 
from a distribution, which is represented as 
. We will learn more about this distribution in later sections. There are many advantages to adding a CA block, as follows:
- It adds randomness to the network.
- It makes the generator network robust by capturing various objects with various poses and appearances.
- It produces more image-text pairs. With a higher number of image-text pairs, we can train a robust network that can handle perturbations. ...
