[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>
This commit is contained in:
Lincoln Stein 2024-06-19 22:57:27 -04:00 committed by GitHub
parent a43d602f16
commit b03073d888
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2 changed files with 13 additions and 10 deletions

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@ -22,8 +22,7 @@ from .generic_diffusers import GenericDiffusersLoader
@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 @@ class VAELoader(GenericDiffusersLoader):
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")

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@ -451,8 +451,16 @@ class PipelineCheckpointProbe(CheckpointProbeBase):
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):