>well it doesn't do those things' nonsense about then? clearly it can do that. There is a model that is trained to compress (very lossy) and decompress the lat

>well it doesn't do those things' nonsense about then? clearly it can do that. There is a model that is trained to compress (very lossy) and decompress the latent, but it's not the main generative model, of course the model doesn't store images in it, you just give the encoder an image and it will encode it and then you can decode it with the decoder and get a very similar image, this encoder and decoder is used during training so that the stage C can work on a compressed latent instead of directly at the pixel level because it's expensive, but the main generative model (stage C) should be able to generate any of the images that were present in the dataset or it fails to do its job. Stages C, B, and A do not store any images. The B and A stages work like an advanced image decoder, so unless you have something wrong with image decoders in general, I don't see how this could be a problem (a JPEG decoder doesn't store images either, of course).