mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
add route for model conversion from safetensors to diffusers
- Begin to add SwaggerUI documentation for AnyModelConfig and other discriminated Unions.
This commit is contained in:
parent
46c8ce9fed
commit
0845a0ed84
@ -2,6 +2,7 @@
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"""FastAPI route for model configuration records."""
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import pathlib
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import shutil
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from hashlib import sha1
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from random import randbytes
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from typing import Any, Dict, List, Optional, Set
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@ -24,8 +25,10 @@ from invokeai.app.services.shared.pagination import PaginatedResults
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from invokeai.backend.model_manager.config import (
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AnyModelConfig,
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BaseModelType,
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MainCheckpointConfig,
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ModelFormat,
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ModelType,
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SubModelType,
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)
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from invokeai.backend.model_manager.merge import MergeInterpolationMethod, ModelMerger
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from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata
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@ -318,7 +321,7 @@ async def heuristic_import(
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@model_manager_v2_router.post(
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"/import",
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"/install",
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operation_id="import_model",
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responses={
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201: {"description": "The model imported successfully"},
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@ -490,6 +493,81 @@ async def sync_models_to_config() -> Response:
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return Response(status_code=204)
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@model_manager_v2_router.put(
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"/convert/{key}",
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operation_id="convert_model",
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responses={
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200: {"description": "Model converted successfully"},
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400: {"description": "Bad request"},
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404: {"description": "Model not found"},
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409: {"description": "There is already a model registered at this location"},
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},
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)
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async def convert_model(
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key: str = Path(description="Unique key of the safetensors main model to convert to diffusers format."),
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) -> AnyModelConfig:
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"""
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Permanently convert a model into diffusers format, replacing the safetensors version.
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Note that the key and model hash will change. Use the model configuration record returned
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by this call to get the new values.
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"""
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logger = ApiDependencies.invoker.services.logger
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loader = ApiDependencies.invoker.services.model_manager.load
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store = ApiDependencies.invoker.services.model_manager.store
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installer = ApiDependencies.invoker.services.model_manager.install
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try:
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model_config = store.get_model(key)
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except UnknownModelException as e:
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logger.error(str(e))
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raise HTTPException(status_code=424, detail=str(e))
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if not isinstance(model_config, MainCheckpointConfig):
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logger.error(f"The model with key {key} is not a main checkpoint model.")
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raise HTTPException(400, f"The model with key {key} is not a main checkpoint model.")
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# loading the model will convert it into a cached diffusers file
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loader.load_model_by_config(model_config, submodel_type=SubModelType.Scheduler)
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# Get the path of the converted model from the loader
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cache_path = loader.convert_cache.cache_path(key)
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assert cache_path.exists()
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# temporarily rename the original safetensors file so that there is no naming conflict
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original_name = model_config.name
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model_config.name = f"{original_name}.DELETE"
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store.update_model(key, config=model_config)
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# install the diffusers
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try:
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new_key = installer.install_path(
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cache_path,
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config={
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"name": original_name,
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"description": model_config.description,
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"original_hash": model_config.original_hash,
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"source": model_config.source,
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},
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)
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except DuplicateModelException as e:
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logger.error(str(e))
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raise HTTPException(status_code=409, detail=str(e))
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# get the original metadata
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if orig_metadata := store.get_metadata(key):
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store.metadata_store.add_metadata(new_key, orig_metadata)
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# delete the original safetensors file
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installer.delete(key)
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# delete the cached version
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shutil.rmtree(cache_path)
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# return the config record for the new diffusers directory
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new_config: AnyModelConfig = store.get_model(new_key)
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return new_config
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@model_manager_v2_router.put(
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"/merge",
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operation_id="merge",
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@ -162,8 +162,10 @@ class ModelInstallService(ModelInstallServiceBase):
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config["source"] = model_path.resolve().as_posix()
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info: AnyModelConfig = self._probe_model(Path(model_path), config)
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old_hash = info.original_hash
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dest_path = self.app_config.models_path / info.base.value / info.type.value / model_path.name
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old_hash = info.current_hash
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dest_path = (
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self.app_config.models_path / info.base.value / info.type.value / (config.get("name") or model_path.name)
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)
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try:
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new_path = self._copy_model(model_path, dest_path)
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except FileExistsError as excp:
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@ -5,8 +5,10 @@ from abc import ABC, abstractmethod
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from typing import Optional
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from invokeai.app.invocations.baseinvocation import InvocationContext
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from invokeai.backend.model_manager import AnyModelConfig, BaseModelType, ModelType, SubModelType
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from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
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from invokeai.backend.model_manager.load import LoadedModel
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from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
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from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
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class ModelLoadServiceBase(ABC):
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@ -70,3 +72,13 @@ class ModelLoadServiceBase(ABC):
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NotImplementedException -- a model loader was not provided at initialization time
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ValueError -- more than one model matches this combination
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"""
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@property
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@abstractmethod
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def ram_cache(self) -> ModelCacheBase[AnyModel]:
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"""Return the RAM cache used by this loader."""
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@property
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@abstractmethod
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def convert_cache(self) -> ModelConvertCacheBase:
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"""Return the checkpoint convert cache used by this loader."""
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@ -10,7 +10,7 @@ from invokeai.app.services.model_records import ModelRecordServiceBase, UnknownM
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from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
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from invokeai.backend.model_manager.load import AnyModelLoader, LoadedModel, ModelCache, ModelConvertCache
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from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
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from invokeai.backend.model_manager.load.model_cache import ModelCacheBase
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from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
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from invokeai.backend.util.logging import InvokeAILogger
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from .model_load_base import ModelLoadServiceBase
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@ -46,6 +46,16 @@ class ModelLoadService(ModelLoadServiceBase):
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),
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)
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@property
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def ram_cache(self) -> ModelCacheBase[AnyModel]:
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"""Return the RAM cache used by this loader."""
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return self._any_loader.ram_cache
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@property
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def convert_cache(self) -> ModelConvertCacheBase:
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"""Return the checkpoint convert cache used by this loader."""
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return self._any_loader.convert_cache
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def load_model_by_key(
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self,
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key: str,
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@ -17,7 +17,6 @@ from invokeai.backend.model_manager import (
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ModelFormat,
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ModelType,
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)
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from invokeai.backend.model_manager.load import AnyModelLoader
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from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore
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@ -195,12 +194,6 @@ class ModelRecordServiceBase(ABC):
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"""
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pass
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@property
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@abstractmethod
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def loader(self) -> Optional[AnyModelLoader]:
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"""Return the model loader used by this instance."""
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pass
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def all_models(self) -> List[AnyModelConfig]:
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"""Return all the model configs in the database."""
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return self.search_by_attr()
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@ -54,7 +54,6 @@ from invokeai.backend.model_manager.config import (
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ModelFormat,
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ModelType,
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)
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from invokeai.backend.model_manager.load import AnyModelLoader
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from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore, UnknownMetadataException
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from ..shared.sqlite.sqlite_database import SqliteDatabase
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@ -70,28 +69,21 @@ from .model_records_base import (
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class ModelRecordServiceSQL(ModelRecordServiceBase):
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"""Implementation of the ModelConfigStore ABC using a SQL database."""
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def __init__(self, db: SqliteDatabase, loader: Optional[AnyModelLoader] = None):
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def __init__(self, db: SqliteDatabase):
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"""
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Initialize a new object from preexisting sqlite3 connection and threading lock objects.
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:param db: Sqlite connection object
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:param loader: Initialized model loader object (optional)
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"""
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super().__init__()
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self._db = db
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self._cursor = db.conn.cursor()
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self._loader = loader
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@property
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def db(self) -> SqliteDatabase:
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"""Return the underlying database."""
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return self._db
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@property
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def loader(self) -> Optional[AnyModelLoader]:
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"""Return the model loader used by this instance."""
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return self._loader
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def add_model(self, key: str, config: Union[Dict[str, Any], AnyModelConfig]) -> AnyModelConfig:
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"""
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Add a model to the database.
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@ -117,6 +117,11 @@ class AnyModelLoader:
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"""Return the RAM cache associated used by the loaders."""
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return self._ram_cache
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@property
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def convert_cache(self) -> ModelConvertCacheBase:
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"""Return the convert cache associated used by the loaders."""
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return self._convert_cache
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def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
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"""
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Return a model given its configuration.
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