r/MachineLearning - [D] How is the log marginal likelihood of generative models reported?

Many papers on generative models report the log-marginal likelihood in order to quantitatively compare different generative models. Since the log-marginal likelihood is intractable, the Importance Weighted Autoencoder (IWAE)'s bound is commonly reported instead. I don't understand how the bound is computed. I assume that the IWAE is first trained on the dataset and then some synthetic samples from the model in question are used to compute the marginal LL bound. However, I am not entirely sure about the procedure.