Files
InvokeAI/invokeai/backend/model_manager/load/model_loader_registry.py
psychedelicious 5a3195f757 final tidying before marking PR as ready for review
- Replace AnyModelLoader with ModelLoaderRegistry
- Fix type check errors in multiple files
- Remove apparently unneeded `get_model_config_enum()` method from model manager
- Remove last vestiges of old model manager
- Updated tests and documentation

resolve conflict with seamless.py
2024-03-01 10:42:33 +11:00

123 lines
4.8 KiB
Python

# Copyright (c) 2024 Lincoln D. Stein and the InvokeAI Development team
"""
This module implements a system in which model loaders register the
type, base and format of models that they know how to load.
Use like this:
cls, model_config, submodel_type = ModelLoaderRegistry.get_implementation(model_config, submodel_type) # type: ignore
loaded_model = cls(
app_config=app_config,
logger=logger,
ram_cache=ram_cache,
convert_cache=convert_cache
).load_model(model_config, submodel_type)
"""
import hashlib
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Callable, Dict, Optional, Tuple, Type
from ..config import (
AnyModelConfig,
BaseModelType,
ModelConfigBase,
ModelFormat,
ModelType,
SubModelType,
VaeCheckpointConfig,
VaeDiffusersConfig,
)
from . import ModelLoaderBase
class ModelLoaderRegistryBase(ABC):
"""This class allows model loaders to register their type, base and format."""
@classmethod
@abstractmethod
def register(
cls, type: ModelType, format: ModelFormat, base: BaseModelType = BaseModelType.Any
) -> Callable[[Type[ModelLoaderBase]], Type[ModelLoaderBase]]:
"""Define a decorator which registers the subclass of loader."""
@classmethod
@abstractmethod
def get_implementation(
cls, config: AnyModelConfig, submodel_type: Optional[SubModelType]
) -> Tuple[Type[ModelLoaderBase], ModelConfigBase, Optional[SubModelType]]:
"""
Get subclass of ModelLoaderBase registered to handle base and type.
Parameters:
:param config: Model configuration record, as returned by ModelRecordService
:param submodel_type: Submodel to fetch (main models only)
:return: tuple(loader_class, model_config, submodel_type)
Note that the returned model config may be different from one what passed
in, in the event that a submodel type is provided.
"""
class ModelLoaderRegistry:
"""
This class allows model loaders to register their type, base and format.
"""
_registry: Dict[str, Type[ModelLoaderBase]] = {}
@classmethod
def register(
cls, type: ModelType, format: ModelFormat, base: BaseModelType = BaseModelType.Any
) -> Callable[[Type[ModelLoaderBase]], Type[ModelLoaderBase]]:
"""Define a decorator which registers the subclass of loader."""
def decorator(subclass: Type[ModelLoaderBase]) -> Type[ModelLoaderBase]:
key = cls._to_registry_key(base, type, format)
if key in cls._registry:
raise Exception(
f"{subclass.__name__} is trying to register as a loader for {base}/{type}/{format}, but this type of model has already been registered by {cls._registry[key].__name__}"
)
cls._registry[key] = subclass
return subclass
return decorator
@classmethod
def get_implementation(
cls, config: AnyModelConfig, submodel_type: Optional[SubModelType]
) -> Tuple[Type[ModelLoaderBase], ModelConfigBase, Optional[SubModelType]]:
"""Get subclass of ModelLoaderBase registered to handle base and type."""
# We have to handle VAE overrides here because this will change the model type and the corresponding implementation returned
conf2, submodel_type = cls._handle_subtype_overrides(config, submodel_type)
key1 = cls._to_registry_key(conf2.base, conf2.type, conf2.format) # for a specific base type
key2 = cls._to_registry_key(BaseModelType.Any, conf2.type, conf2.format) # with wildcard Any
implementation = cls._registry.get(key1) or cls._registry.get(key2)
if not implementation:
raise NotImplementedError(
f"No subclass of LoadedModel is registered for base={config.base}, type={config.type}, format={config.format}"
)
return implementation, conf2, submodel_type
@classmethod
def _handle_subtype_overrides(
cls, config: AnyModelConfig, submodel_type: Optional[SubModelType]
) -> Tuple[ModelConfigBase, Optional[SubModelType]]:
if submodel_type == SubModelType.Vae and hasattr(config, "vae") and config.vae is not None:
model_path = Path(config.vae)
config_class = (
VaeCheckpointConfig if model_path.suffix in [".pt", ".safetensors", ".ckpt"] else VaeDiffusersConfig
)
hash = hashlib.md5(model_path.as_posix().encode("utf-8")).hexdigest()
new_conf = config_class(path=model_path.as_posix(), name=model_path.stem, base=config.base, key=hash)
submodel_type = None
else:
new_conf = config
return new_conf, submodel_type
@staticmethod
def _to_registry_key(base: BaseModelType, type: ModelType, format: ModelFormat) -> str:
return "-".join([base.value, type.value, format.value])