Frechet Inception Distance for DC GAN trained on MNIST Dataset

Question

I'm starting out with GANs and I am training a DC-GAN on MNIST dataset. I want to evaluate my model using Frechet Inception Distance (FID).

1. Since Inception network is not trained to classify MNIST digits, can I use any simple MNIST classifier or are there any conditions on what kind of classifier I need to use? Or should I use Inception net only? I have few other questions
2. Does it make sense to compute FID for MNIST GAN?
3. How many images from real dataset should be used while computing FID
4. For a classifier I'm using, I'm getting FID in the order of 10^6. Is the value okay or is something horribly wrong?

If you can answer any of these questions, even partially, that would be of immense help to me. Thanks!

Answer 1

you can refer this. Use a auto-encoder trained on MNIST and the bottleneck activations as the features as explained here