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

invokeai/backend/ip_adapter/ip_adapter.py

@@ -9,7 +9,6 @@ from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
 
 from invokeai.backend.ip_adapter.ip_attention_weights import IPAttentionWeights
 
-from ..raw_model import RawModel
 from .resampler import Resampler
 
 
@@ -92,7 +91,7 @@ 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__(

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]
@@ -368,7 +366,7 @@ class IA3Layer(LoRALayerBase):
 AnyLoRALayer = Union[LoRALayer, LoHALayer, LoKRLayer, FullLayer, IA3Layer]
 
 
-class LoRAModelRaw(RawModel):  # (torch.nn.Module):
+class LoRAModelRaw(torch.nn.Module):
     _name: str
     layers: Dict[str, AnyLoRALayer]
 

invokeai/backend/model_manager/config.py

@@ -31,12 +31,13 @@ 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
+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
-# RawModel is the InvokeAI wrapper class for ip_adapters, loras, textual_inversion and onnx runtime
-AnyModel = Union[ModelMixin, RawModel, torch.nn.Module]
+AnyModel = Union[ModelMixin, torch.nn.Module, IPAdapter, LoRAModelRaw, TextualInversionModelRaw, IAIOnnxRuntimeModel]
 
 
 class InvalidModelConfigException(Exception):

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

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