I was learning about GAN's and how it can be used for creating images of cat, dog, mouse and bird. This is how I think in supervised learning system we train the features and labels to generate images.
cat,dog,mouse, bird = 0,1,2,3 X Y 1 dog.jpg 3 bird.jpg 0 cat.jpg 0 cat1.jpg . . . . train(X,Y)
after training for generating a image
predict(0) #generates cat image predict(2) #generates mouse image
Because GAN is an unsupervised learning system it learns to generate images using adversarial training. What I have seen in others implementation of GANs is that they add a noise as an input to the generator. The noise is generally a continuous number between 0 and 1. Why do they add random number as noise? why cant they simply add some numbers for example
cat,dog,mouse, bird = [0,1,2,3]?