Deep Variational Autoencoder Latent Layer Loss • /r/MachineLearning

I was reading this paper and I noticed they used two layers for encoder/decoder, but up to five layers for latent variables. My question is how do you calculate loss for more than one latent later? Do you just tack an extra KL Divergence to the loss function for each additional latent layer?