Remove RawModel - it was just creating a weird layer of indirection in the AnyModel type without adding any value.

invokeai/app/services/model_load/model_load_base.py

@@ -5,7 +5,8 @@ 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, SubModelType
+from invokeai.backend.model_manager import AnyModelConfig, SubModelType
+from invokeai.backend.model_manager.any_model_type import AnyModel
 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

invokeai/app/services/model_load/model_load_default.py

@@ -6,7 +6,8 @@ from typing import Optional, Type
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.shared.invocation_context import InvocationContextData
-from invokeai.backend.model_manager import AnyModel, AnyModelConfig, SubModelType
+from invokeai.backend.model_manager import AnyModelConfig, SubModelType
+from invokeai.backend.model_manager.any_model_type import AnyModel
 from invokeai.backend.model_manager.load import (
     LoadedModel,
     ModelLoaderRegistry,

invokeai/app/services/model_manager/__init__.py

@@ -1,6 +1,6 @@
 """Initialization file for model manager service."""
 
-from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
+from invokeai.backend.model_manager import AnyModelConfig, BaseModelType, ModelType, SubModelType
 from invokeai.backend.model_manager.load import LoadedModel
 
 from .model_manager_default import ModelManagerService, ModelManagerServiceBase
@@ -8,7 +8,6 @@ from .model_manager_default import ModelManagerService, ModelManagerServiceBase
 __all__ = [
     "ModelManagerServiceBase",
     "ModelManagerService",
-    "AnyModel",
     "AnyModelConfig",
     "BaseModelType",
     "ModelType",

invokeai/backend/ip_adapter/ip_adapter.py

@@ -12,7 +12,6 @@ from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
 
 from invokeai.backend.ip_adapter.ip_attention_weights import IPAttentionWeights
 
-from ..raw_model import RawModel
 from .resampler import Resampler
 
 
@@ -102,7 +101,7 @@ class MLPProjModel(torch.nn.Module):
         return clip_extra_context_tokens
 
 
-class IPAdapter(RawModel):
+class IPAdapter(torch.nn.Module):
     """IP-Adapter: https://arxiv.org/pdf/2308.06721.pdf"""
 
     def __init__(
@@ -112,6 +111,7 @@ class IPAdapter(RawModel):
         dtype: torch.dtype = torch.float16,
         num_tokens: int = 4,
     ):
+        super().__init__()
         self.device = device
         self.dtype = dtype
 

invokeai/backend/lora.py

@@ -11,8 +11,6 @@ from typing_extensions import Self
 
 from invokeai.backend.model_manager import BaseModelType
 
-from .raw_model import RawModel
-
 
 class LoRALayerBase:
     # rank: Optional[int]
@@ -368,15 +366,13 @@ class IA3Layer(LoRALayerBase):
 AnyLoRALayer = Union[LoRALayer, LoHALayer, LoKRLayer, FullLayer, IA3Layer]
 
 
-class LoRAModelRaw(RawModel):  # (torch.nn.Module):
-    _name: str
-    layers: Dict[str, AnyLoRALayer]
-
+class LoRAModelRaw(torch.nn.Module):
     def __init__(
         self,
         name: str,
         layers: Dict[str, AnyLoRALayer],
     ):
+        super().__init__()
         self._name = name
         self.layers = layers
 

invokeai/backend/model_manager/__init__.py

@@ -1,7 +1,6 @@
 """Re-export frequently-used symbols from the Model Manager backend."""
 
 from .config import (
-    AnyModel,
     AnyModelConfig,
     BaseModelType,
     InvalidModelConfigException,
@@ -18,7 +17,6 @@ from .probe import ModelProbe
 from .search import ModelSearch
 
 __all__ = [
-    "AnyModel",
     "AnyModelConfig",
     "BaseModelType",
     "ModelRepoVariant",

invokeai/backend/model_manager/any_model_type.py

@@ -0,0 +1,12 @@
+from typing import Union
+
+import torch
+from diffusers.models.modeling_utils import ModelMixin
+
+from invokeai.backend.ip_adapter.ip_adapter import IPAdapter
+from invokeai.backend.lora import LoRAModelRaw
+from invokeai.backend.onnx.onnx_runtime import IAIOnnxRuntimeModel
+from invokeai.backend.textual_inversion import TextualInversionModelRaw
+
+# ModelMixin is the base class for all diffusers and transformers models
+AnyModel = Union[ModelMixin, torch.nn.Module, IPAdapter, LoRAModelRaw, TextualInversionModelRaw, IAIOnnxRuntimeModel]

invokeai/backend/model_manager/config.py

@@ -24,20 +24,12 @@ import time
 from enum import Enum
 from typing import Literal, Optional, Type, TypeAlias, Union
 
-import torch
-from diffusers.models.modeling_utils import ModelMixin
 from pydantic import BaseModel, ConfigDict, Discriminator, Field, Tag, TypeAdapter
 from typing_extensions import Annotated, Any, Dict
 
 from invokeai.app.invocations.constants import SCHEDULER_NAME_VALUES
 from invokeai.app.util.misc import uuid_string
 
-from ..raw_model import RawModel
-
-# ModelMixin is the base class for all diffusers and transformers models
-# RawModel is the InvokeAI wrapper class for ip_adapters, loras, textual_inversion and onnx runtime
-AnyModel = Union[ModelMixin, RawModel, torch.nn.Module]
-
 
 class InvalidModelConfigException(Exception):
     """Exception for when config parser doesn't recognized this combination of model type and format."""

invokeai/backend/model_manager/convert_ckpt_to_diffusers.py

@@ -15,7 +15,7 @@ from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
 )
 from omegaconf import DictConfig
 
-from . import AnyModel
+from invokeai.backend.model_manager.any_model_type import AnyModel
 
 
 def convert_ldm_vae_to_diffusers(

invokeai/backend/model_manager/load/load_base.py

@@ -10,8 +10,8 @@ from pathlib import Path
 from typing import Any, Optional
 
 from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.backend.model_manager.any_model_type import AnyModel
 from invokeai.backend.model_manager.config import (
-    AnyModel,
     AnyModelConfig,
     SubModelType,
 )

invokeai/backend/model_manager/load/load_default.py

@@ -7,11 +7,11 @@ from typing import Optional
 
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.backend.model_manager import (
-    AnyModel,
     AnyModelConfig,
     InvalidModelConfigException,
     SubModelType,
 )
+from invokeai.backend.model_manager.any_model_type import AnyModel
 from invokeai.backend.model_manager.config import DiffusersConfigBase, ModelType
 from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.load_base import LoadedModel, ModelLoaderBase

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

@@ -14,7 +14,8 @@ from typing import Dict, Generic, Optional, TypeVar
 
 import torch
 
-from invokeai.backend.model_manager.config import AnyModel, SubModelType
+from invokeai.backend.model_manager.any_model_type import AnyModel
+from invokeai.backend.model_manager.config import SubModelType
 
 
 class ModelLockerBase(ABC):

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

@@ -28,7 +28,8 @@ from typing import Dict, List, Optional
 
 import torch
 
-from invokeai.backend.model_manager import AnyModel, SubModelType
+from invokeai.backend.model_manager import SubModelType
+from invokeai.backend.model_manager.any_model_type import AnyModel
 from invokeai.backend.model_manager.load.memory_snapshot import MemorySnapshot, get_pretty_snapshot_diff
 from invokeai.backend.util.devices import choose_torch_device
 from invokeai.backend.util.logging import InvokeAILogger

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

@@ -4,7 +4,7 @@ Base class and implementation of a class that moves models in and out of VRAM.
 
 import torch
 
-from invokeai.backend.model_manager import AnyModel
+from invokeai.backend.model_manager.any_model_type import AnyModel
 
 from .model_cache_base import CacheRecord, ModelCacheBase, ModelLockerBase
 

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

@@ -5,12 +5,12 @@ from pathlib import Path
 from typing import Optional
 
 from invokeai.backend.model_manager import (
-    AnyModel,
     AnyModelConfig,
     BaseModelType,
     ModelFormat,
     ModelType,
 )
+from invokeai.backend.model_manager.any_model_type import AnyModel
 from invokeai.backend.model_manager.config import CheckpointConfigBase
 from invokeai.backend.model_manager.convert_ckpt_to_diffusers import convert_controlnet_to_diffusers
 

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

@@ -9,7 +9,6 @@ from diffusers.configuration_utils import ConfigMixin
 from diffusers.models.modeling_utils import ModelMixin
 
 from invokeai.backend.model_manager import (
-    AnyModel,
     AnyModelConfig,
     BaseModelType,
     InvalidModelConfigException,
@@ -17,6 +16,7 @@ from invokeai.backend.model_manager import (
     ModelType,
     SubModelType,
 )
+from invokeai.backend.model_manager.any_model_type import AnyModel
 from invokeai.backend.model_manager.config import DiffusersConfigBase
 
 from .. import ModelLoader, ModelLoaderRegistry

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

@@ -7,9 +7,9 @@ from typing import Optional
 import torch
 
 from invokeai.backend.ip_adapter.ip_adapter import build_ip_adapter
-from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
+from invokeai.backend.model_manager import AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
+from invokeai.backend.model_manager.any_model_type import AnyModel
 from invokeai.backend.model_manager.load import ModelLoader, ModelLoaderRegistry
-from invokeai.backend.raw_model import RawModel
 
 
 @ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.IPAdapter, format=ModelFormat.InvokeAI)
@@ -25,7 +25,7 @@ class IPAdapterInvokeAILoader(ModelLoader):
         if submodel_type is not None:
             raise ValueError("There are no submodels in an IP-Adapter model.")
         model_path = Path(config.path)
-        model: RawModel = build_ip_adapter(
+        model = build_ip_adapter(
             ip_adapter_ckpt_path=model_path,
             device=torch.device("cpu"),
             dtype=self._torch_dtype,

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

@@ -8,13 +8,13 @@ from typing import Optional
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.backend.lora import LoRAModelRaw
 from invokeai.backend.model_manager import (
-    AnyModel,
     AnyModelConfig,
     BaseModelType,
     ModelFormat,
     ModelType,
     SubModelType,
 )
+from invokeai.backend.model_manager.any_model_type import AnyModel
 from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
 

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

@@ -6,13 +6,13 @@ from pathlib import Path
 from typing import Optional
 
 from invokeai.backend.model_manager import (
-    AnyModel,
     AnyModelConfig,
     BaseModelType,
     ModelFormat,
     ModelType,
     SubModelType,
 )
+from invokeai.backend.model_manager.any_model_type import AnyModel
 
 from .. import ModelLoaderRegistry
 from .generic_diffusers import GenericDiffusersLoader

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

@@ -5,7 +5,6 @@ from pathlib import Path
 from typing import Optional
 
 from invokeai.backend.model_manager import (
-    AnyModel,
     AnyModelConfig,
     BaseModelType,
     ModelFormat,
@@ -13,6 +12,7 @@ from invokeai.backend.model_manager import (
     SchedulerPredictionType,
     SubModelType,
 )
+from invokeai.backend.model_manager.any_model_type import AnyModel
 from invokeai.backend.model_manager.config import (
     CheckpointConfigBase,
     DiffusersConfigBase,

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

@@ -5,13 +5,13 @@ from pathlib import Path
 from typing import Optional
 
 from invokeai.backend.model_manager import (
-    AnyModel,
     AnyModelConfig,
     BaseModelType,
     ModelFormat,
     ModelType,
     SubModelType,
 )
+from invokeai.backend.model_manager.any_model_type import AnyModel
 from invokeai.backend.textual_inversion import TextualInversionModelRaw
 
 from .. import ModelLoader, ModelLoaderRegistry

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

@@ -14,7 +14,8 @@ from invokeai.backend.model_manager import (
     ModelFormat,
     ModelType,
 )
-from invokeai.backend.model_manager.config import AnyModel, CheckpointConfigBase
+from invokeai.backend.model_manager.any_model_type import AnyModel
+from invokeai.backend.model_manager.config import CheckpointConfigBase
 from invokeai.backend.model_manager.convert_ckpt_to_diffusers import convert_ldm_vae_to_diffusers
 
 from .. import ModelLoaderRegistry

invokeai/backend/model_manager/load/model_util.py

@@ -8,7 +8,7 @@ from typing import Optional
 import torch
 from diffusers import DiffusionPipeline
 
-from invokeai.backend.model_manager.config import AnyModel
+from invokeai.backend.model_manager.any_model_type import AnyModel
 from invokeai.backend.onnx.onnx_runtime import IAIOnnxRuntimeModel
 
 

invokeai/backend/model_patcher.py

@@ -13,7 +13,7 @@ from diffusers import OnnxRuntimeModel, UNet2DConditionModel
 from transformers import CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
 
 from invokeai.app.shared.models import FreeUConfig
-from invokeai.backend.model_manager import AnyModel
+from invokeai.backend.model_manager.any_model_type import AnyModel
 from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init
 from invokeai.backend.onnx.onnx_runtime import IAIOnnxRuntimeModel
 

invokeai/backend/onnx/onnx_runtime.py

@@ -6,17 +6,16 @@ from typing import Any, List, Optional, Tuple, Union
 
 import numpy as np
 import onnx
+import torch
 from onnx import numpy_helper
 from onnxruntime import InferenceSession, SessionOptions, get_available_providers
 
-from ..raw_model import RawModel
-
 ONNX_WEIGHTS_NAME = "model.onnx"
 
 
 # NOTE FROM LS: This was copied from Stalker's original implementation.
 # I have not yet gone through and fixed all the type hints
-class IAIOnnxRuntimeModel(RawModel):
+class IAIOnnxRuntimeModel(torch.nn.Module):
     class _tensor_access:
         def __init__(self, model):  # type: ignore
             self.model = model
@@ -103,7 +102,7 @@ class IAIOnnxRuntimeModel(RawModel):
 
         self.proto = onnx.load(model_path, load_external_data=False)
         """
-
+        super().__init__()
         self.proto = onnx.load(model_path, load_external_data=True)
         # self.data = dict()
         # for tensor in self.proto.graph.initializer:

invokeai/backend/raw_model.py

@@ -1,15 +0,0 @@
-"""Base class for 'Raw' models.
-
-The RawModel class is the base class of LoRAModelRaw and TextualInversionModelRaw,
-and is used for type checking of calls to the model patcher. Its main purpose
-is to avoid a circular import issues when lora.py tries to import BaseModelType
-from invokeai.backend.model_manager.config, and the latter tries to import LoRAModelRaw
-from lora.py.
-
-The term 'raw' was introduced to describe a wrapper around a torch.nn.Module
-that adds additional methods and attributes.
-"""
-
-
-class RawModel:
-    """Base class for 'Raw' model wrappers."""

invokeai/backend/textual_inversion.py

@@ -9,10 +9,8 @@ from safetensors.torch import load_file
 from transformers import CLIPTokenizer
 from typing_extensions import Self
 
-from .raw_model import RawModel
 
-
-class TextualInversionModelRaw(RawModel):
+class TextualInversionModelRaw(torch.nn.Module):
     embedding: torch.Tensor  # [n, 768]|[n, 1280]
     embedding_2: Optional[torch.Tensor] = None  # [n, 768]|[n, 1280]   - for SDXL models