How can I address the issue of the generator not learning during GAN training

Question

With the help of code, can you tell me how I can address the issue of the generator not learning during GAN training?

Answer 1

You can address the issue of the generator not learning during GAN training by following the approaches given below:

• Improve Loss Functions: Use a stable loss like Wasserstein Loss.
• Balance Training: Ensure the discriminator doesn't overpower the generator.
• Learning Rate Adjustments: Use separate learning rates for the generator and discriminator.
• Gradient Clipping: Prevent exploding gradients.
• Label Smoothing: Apply slight noise to discriminator labels.

In the above code, we are using the following strategies:

• Wasserstein Loss: Stabilizes training by avoiding vanishing gradients.
• Separate Learning Rates: Faster learning for discriminator.
• Gradient Clipping: Keeps discriminator weights bounded to stabilize training.

Hence, by referring to the above, you can address the issue of the generator not learning during GAN training.