Files
InvokeAI/invokeai/app/services/model_load/model_load_base.py

85 lines
3.2 KiB
Python

# Copyright (c) 2024 Lincoln D. Stein and the InvokeAI Team
"""Base class for model loader."""
from abc import ABC, abstractmethod
from typing import Optional
from invokeai.app.services.shared.invocation_context import InvocationContextData
from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
from invokeai.backend.model_manager.load import LoadedModel
from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
class ModelLoadServiceBase(ABC):
"""Wrapper around AnyModelLoader."""
@abstractmethod
def load_model_by_key(
self,
key: str,
submodel_type: Optional[SubModelType] = None,
context_data: Optional[InvocationContextData] = None,
) -> LoadedModel:
"""
Given a model's key, load it and return the LoadedModel object.
:param key: Key of model config to be fetched.
:param submodel: For main (pipeline models), the submodel to fetch.
:param context_data: Invocation context data used for event reporting
"""
pass
@abstractmethod
def load_model_by_config(
self,
model_config: AnyModelConfig,
submodel_type: Optional[SubModelType] = None,
context_data: Optional[InvocationContextData] = None,
) -> LoadedModel:
"""
Given a model's configuration, load it and return the LoadedModel object.
:param model_config: Model configuration record (as returned by ModelRecordBase.get_model())
:param submodel: For main (pipeline models), the submodel to fetch.
:param context_data: Invocation context data used for event reporting
"""
pass
@abstractmethod
def load_model_by_attr(
self,
model_name: str,
base_model: BaseModelType,
model_type: ModelType,
submodel: Optional[SubModelType] = None,
context_data: Optional[InvocationContextData] = None,
) -> LoadedModel:
"""
Given a model's attributes, search the database for it, and if found, load and return the LoadedModel object.
This is provided for API compatability with the get_model() method
in the original model manager. However, note that LoadedModel is
not the same as the original ModelInfo that ws returned.
:param model_name: Name of to be fetched.
:param base_model: Base model
:param model_type: Type of the model
:param submodel: For main (pipeline models), the submodel to fetch
:param context_data: The invocation context data.
Exceptions: UnknownModelException -- model with these attributes not known
NotImplementedException -- a model loader was not provided at initialization time
ValueError -- more than one model matches this combination
"""
@property
@abstractmethod
def ram_cache(self) -> ModelCacheBase[AnyModel]:
"""Return the RAM cache used by this loader."""
@property
@abstractmethod
def convert_cache(self) -> ModelConvertCacheBase:
"""Return the checkpoint convert cache used by this loader."""