fix: make DA Pipeline a subclass of RawModel

Author: blessedcoolant

invokeai/backend/image_util/depth_anything/depth_anything_pipeline.py

@@ -1,10 +1,13 @@
-from typing import cast
+from typing import Optional, cast
 
+import torch
 from PIL import Image
 from transformers.pipelines import DepthEstimationPipeline
 
+from invokeai.backend.raw_model import RawModel
 
-class DepthAnythingPipeline:
+
+class DepthAnythingPipeline(RawModel):
     """Custom wrapper for the Depth Estimation pipeline from transformers adding compatibility
     for Invoke's Model Management System"""
 
@@ -20,6 +23,9 @@ def generate_depth(self, image: Image.Image, resolution: int = 512):
         depth_map = depth_map.resize((resolution, new_height))
         return depth_map
 
+    def to(self, device: Optional[torch.device] = None, dtype: Optional[torch.dtype] = None):
+        pass
+
     def calc_size(self) -> int:
         from invokeai.backend.model_manager.load.model_util import calc_module_size
 

invokeai/backend/model_manager/config.py

@@ -31,16 +31,13 @@
 from typing_extensions import Annotated, Any, Dict
 
 from invokeai.app.util.misc import uuid_string
-from invokeai.backend.image_util.depth_anything.depth_anything_pipeline import DepthAnythingPipeline
 from invokeai.backend.model_hash.hash_validator import validate_hash
 from invokeai.backend.raw_model import RawModel
 from invokeai.backend.stable_diffusion.schedulers.schedulers import SCHEDULER_NAME_VALUES
 
 # 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, Dict[str, torch.Tensor], diffusers.DiffusionPipeline, DepthAnythingPipeline
-]
+AnyModel = Union[ModelMixin, RawModel, torch.nn.Module, Dict[str, torch.Tensor], diffusers.DiffusionPipeline]
 
 
 class InvalidModelConfigException(Exception):