Remove patch_unet logic for now

invokeai/backend/stable_diffusion/extensions_manager.py

@@ -108,35 +108,5 @@ class ExtensionsManager:
 
     @contextmanager
     def patch_unet(self, state_dict: Dict[str, torch.Tensor], unet: UNet2DConditionModel):
-        exit_stack = ExitStack()
-        try:
-            changed_keys = set()
-            changed_unknown_keys = {}
-
-            for ext in self.extensions:
-                patch_result = exit_stack.enter_context(ext.patch_unet(state_dict, unet))
-                if patch_result is None:
-                    continue
-                new_keys, new_unk_keys = patch_result
-                changed_keys.update(new_keys)
-                # skip already seen keys, as new weight might be changed
-                for k, v in new_unk_keys.items():
-                    if k in changed_unknown_keys:
-                        continue
-                    changed_unknown_keys[k] = v
-
-            yield None
-
-        finally:
-            exit_stack.close()
-            assert hasattr(unet, "get_submodule")  # mypy not picking up fact that torch.nn.Module has get_submodule()
-            with torch.no_grad():
-                for module_key in changed_keys:
-                    weight = state_dict[module_key]
-                    unet.get_submodule(module_key).weight.copy_(
-                        weight, non_blocking=TorchDevice.get_non_blocking(weight.device)
-                    )
-                for module_key, weight in changed_unknown_keys.items():
-                    unet.get_submodule(module_key).weight.copy_(
-                        weight, non_blocking=TorchDevice.get_non_blocking(weight.device)
-                    )
+        # TODO: create logic in PR with extension which uses it
+        yield None