Lincoln Stein 488334710b enable fast switching between models in invoke.py ... - This PR enables two new commands in the invoke.py script !models -- list the available models and their cache status !switch <model> -- switch to the indicated model Example: invoke> !models laion400m not loaded Latent Diffusion LAION400M model stable-diffusion-1.4 active Stable Diffusion inference model version 1.4 waifu-1.3 cached Waifu anime model version 1.3 invoke> !switch waifu-1.3 >> Caching model stable-diffusion-1.4 in system RAM >> Retrieving model waifu-1.3 from system RAM cache The name and descriptions of the models are taken from `config/models.yaml`. A future enhancement to `model_cache.py` will be to enable new model stanzas to be added to the file programmatically. This will be useful for the WebGUI. More details: - Use fast switching algorithm described in PR #948 - Models are selected using their configuration stanza name given in models.yaml. - To avoid filling up CPU RAM with cached models, this PR implements an LRU cache that monitors available CPU RAM. - The caching code allows the minimum value of available RAM to be adjusted, but invoke.py does not currently have a command-line argument that allows you to set it. The minimum free RAM is arbitrarily set to 2 GB. - Add optional description field to configs/models.yaml Unrelated fixes: - Added ">>" to CompViz model loading messages in order to make user experience more consistent. - When generating an image greater than defaults, will only warn about possible VRAM filling the first time. - Fixed bug that was causing help message to be printed twice. This involved moving the import line for the web backend into the section where it is called. Coauthored by: @ArDiouscuros		2022-10-12 02:37:42 -04:00
..
diffusion	enable fast switching between models in invoke.py	2022-10-12 02:37:42 -04:00
autoencoder.py	prettified all the code using "blue" at the urging of @tildebyte	2022-08-26 03:15:42 -04:00