How do you implement spectral normalization in GANs

Question

With the help of code, can you explain how to implement spectral normalization in GANs?

Answer 1

In order to implement spectral normalization in GANs, refer to the following code snippet:

In the code above, we used the spectral_norm wrapper to wrap around layers to apply spectral normalization. Here, it’s applied to convolution (conv1 and conv2) and fully connected (FC) layers and Usage so that the discriminator is built as usual, but each layer with spectral_norm constrains its weights for better stability in training.

This normalization technique can prevent the discriminator from becoming overly confident, improving GAN performance.