Generator Evaluation Metric

How would we go if we wanted to implement an evaluation metric for generator part?

I have tried to load a pre-trained discriminator addition to the discriminator that trained during training. And tested the generator with pre-trained discriminator at the end of each epoch. But I am not sure if this is a good way to measure the performance of generator.

Are there any feasible methods? I have done a little literature survey to see what are the methods of evaluating gans, but they are usually for datasets with certain classes. Since we do not have classes in T2F (or do we?) I have hard time implementing methods such as Inception Score , Frechet Inception Distance etc.

One method that I found is CrossLID (https://arxiv.org/abs/1905.00643). Which also has implementation on GitHub. However I did not try to implement it yet as I am unsure if it is suitable for this dataset-model.