<abbr title='Variational autoencoder'>VAE</abbr> is a neural network that transforms a standard <abbr title='red/green/blue'>RGB</abbr>
image into latent space representation and back. Latent space representation is what stable diffusion is working on during sampling
(i.e. when the progress bar is between empty and full). For txt2img, VAE is used to create a resulting image after the sampling is finished.
For img2img, VAE is used to process user's input image before the sampling, and to create an image after sampling.
"""),
"sd_vae_checkpoint_cache":OptionInfo(0,"VAE Checkpoints to cache in RAM",gr.Slider,{"minimum":0,"maximum":10,"step":1}),
"sd_vae":OptionInfo("Automatic","SD VAE",gr.Dropdown,lambda:{"choices":shared_items.sd_vae_items()},refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"),
"sd_vae_as_default":OptionInfo(True,"Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"),
...
...
@@ -619,6 +633,9 @@ class Options:
assertnotcmd_opts.freeze_settings,"changing settings is disabled"