# How discriminator loss generated?

The images generated by generator has no labels, then how do Discriminator loss is generated on the basis of classification of generator generated images.

We already know that the images from the generator are fake and those from our training set are real. So, we assign them labels manually, real images as $$0$$ and fake ones as $$1$$, which gives us labelled data. Check the definition of loss function in any implementation of a GAN and you'll find that we assign the labels ourselves. For example, take a look here.
So, Discriminator is considered as perfect classifier if it outputs TRUE for input real image and FALSE for generated image.
Discriminator Real Loss: Prediction of real image as fake image