[MM] Add support for probing and loading SDXL VAE checkpoint files (#…

…6524)

* add support for probing and loading SDXL VAE checkpoint files

* broaden regexp probe for SDXL VAEs

---------

Co-authored-by: Lincoln Stein <lstein@gmail.com>

invokeai/backend/model_manager/load/model_loaders/vae.py

@@ -22,8 +22,7 @@
 
 
 @ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.VAE, format=ModelFormat.Diffusers)
-@ModelLoaderRegistry.register(base=BaseModelType.StableDiffusion1, type=ModelType.VAE, format=ModelFormat.Checkpoint)
-@ModelLoaderRegistry.register(base=BaseModelType.StableDiffusion2, type=ModelType.VAE, format=ModelFormat.Checkpoint)
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.VAE, format=ModelFormat.Checkpoint)
 class VAELoader(GenericDiffusersLoader):
     """Class to load VAE models."""
 
@@ -40,12 +39,8 @@ def _needs_conversion(self, config: AnyModelConfig, model_path: Path, dest_path:
             return True
 
     def _convert_model(self, config: AnyModelConfig, model_path: Path, output_path: Optional[Path] = None) -> AnyModel:
-        # TODO(MM2): check whether sdxl VAE models convert.
-        if config.base not in {BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2}:
-            raise Exception(f"VAE conversion not supported for model type: {config.base}")
-        else:
-            assert isinstance(config, CheckpointConfigBase)
-            config_file = self._app_config.legacy_conf_path / config.config_path
+        assert isinstance(config, CheckpointConfigBase)
+        config_file = self._app_config.legacy_conf_path / config.config_path
 
         if model_path.suffix == ".safetensors":
             checkpoint = safetensors_load_file(model_path, device="cpu")

invokeai/backend/model_manager/probe.py

@@ -451,8 +451,16 @@ def get_scheduler_prediction_type(self) -> SchedulerPredictionType:
 
 class VaeCheckpointProbe(CheckpointProbeBase):
     def get_base_type(self) -> BaseModelType:
-        # I can't find any standalone 2.X VAEs to test with!
-        return BaseModelType.StableDiffusion1
+        # VAEs of all base types have the same structure, so we wimp out and
+        # guess using the name.
+        for regexp, basetype in [
+            (r"xl", BaseModelType.StableDiffusionXL),
+            (r"sd2", BaseModelType.StableDiffusion2),
+            (r"vae", BaseModelType.StableDiffusion1),
+        ]:
+            if re.search(regexp, self.model_path.name, re.IGNORECASE):
+                return basetype
+        raise InvalidModelConfigException("Cannot determine base type")
 
 
 class LoRACheckpointProbe(CheckpointProbeBase):