Rename model_cache_default.py -> model_cache.py.

invokeai/backend/model_manager/load/__init__.py

@@ -8,7 +8,7 @@ from pathlib import Path
 
 from invokeai.backend.model_manager.load.load_base import LoadedModel, LoadedModelWithoutConfig, ModelLoaderBase
 from invokeai.backend.model_manager.load.load_default import ModelLoader
-from invokeai.backend.model_manager.load.model_cache.model_cache_default import ModelCache
+from invokeai.backend.model_manager.load.model_cache.model_cache import ModelCache
 from invokeai.backend.model_manager.load.model_loader_registry import ModelLoaderRegistry, ModelLoaderRegistryBase
 
 # This registers the subclasses that implement loaders of specific model types

invokeai/backend/model_manager/load/load_base.py

@@ -18,7 +18,7 @@ from invokeai.backend.model_manager.config import (
     AnyModelConfig,
     SubModelType,
 )
-from invokeai.backend.model_manager.load.model_cache.model_cache_default import ModelCache
+from invokeai.backend.model_manager.load.model_cache.model_cache import ModelCache
 from invokeai.backend.model_manager.load.model_cache.model_locker import ModelLocker
 
 

invokeai/backend/model_manager/load/load_default.py

@@ -14,7 +14,7 @@ from invokeai.backend.model_manager import (
 )
 from invokeai.backend.model_manager.config import DiffusersConfigBase
 from invokeai.backend.model_manager.load.load_base import LoadedModel, ModelLoaderBase
-from invokeai.backend.model_manager.load.model_cache.model_cache_default import ModelCache
+from invokeai.backend.model_manager.load.model_cache.model_cache import ModelCache
 from invokeai.backend.model_manager.load.model_cache.model_locker import ModelLocker
 from invokeai.backend.model_manager.load.model_util import calc_model_size_by_fs
 from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init

invokeai/backend/model_manager/load/model_cache/cache_record.py

@@ -1,13 +1,11 @@
 from dataclasses import dataclass
-from typing import Dict, Generic, Optional, TypeVar
+from typing import Any, Dict, Optional
 
 import torch
 
-T = TypeVar("T")
-
 
 @dataclass
-class CacheRecord(Generic[T]):
+class CacheRecord:
     """
     Elements of the cache:
 
@@ -30,7 +28,7 @@ class CacheRecord(Generic[T]):
     """
 
     key: str
-    model: T
+    model: Any
     device: torch.device
     state_dict: Optional[Dict[str, torch.Tensor]]
     size: int

invokeai/backend/model_manager/load/model_cache/model_cache.py

@@ -95,7 +95,7 @@ class ModelCache:
         self._log_memory_usage = log_memory_usage
         self._stats: Optional[CacheStats] = None
 
-        self._cached_models: Dict[str, CacheRecord[AnyModel]] = {}
+        self._cached_models: Dict[str, CacheRecord] = {}
         self._cache_stack: List[str] = []
 
     @property

invokeai/backend/model_manager/load/model_cache/model_locker.py

@@ -8,7 +8,7 @@ import torch
 
 from invokeai.backend.model_manager import AnyModel
 from invokeai.backend.model_manager.load.model_cache.cache_record import CacheRecord
-from invokeai.backend.model_manager.load.model_cache.model_cache_default import ModelCache
+from invokeai.backend.model_manager.load.model_cache.model_cache import ModelCache
 
 
 class ModelLocker:

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

@@ -18,7 +18,7 @@ from invokeai.backend.model_manager import (
     SubModelType,
 )
 from invokeai.backend.model_manager.load.load_default import ModelLoader
-from invokeai.backend.model_manager.load.model_cache.model_cache_default import ModelCache
+from invokeai.backend.model_manager.load.model_cache.model_cache import ModelCache
 from invokeai.backend.model_manager.load.model_loader_registry import ModelLoaderRegistry
 from invokeai.backend.patches.lora_conversions.flux_control_lora_utils import (
     is_state_dict_likely_flux_control,