Fix Inpainting Issues (#3744)

- fix: Inpaint not working with some schedulers: Resolves #3732
- fix: LoRA's not working at all while inpainting.

invokeai/app/invocations/generate.py

@@ -154,18 +154,20 @@ class InpaintInvocation(BaseInvocation):
 
     @contextmanager
     def load_model_old_way(self, context, scheduler):
+        def _lora_loader():
+            for lora in self.unet.loras:
+                lora_info = context.services.model_manager.get_model(
+                    **lora.dict(exclude={"weight"}))
+                yield (lora_info.context.model, lora.weight)
+                del lora_info
+            return
+        
         unet_info = context.services.model_manager.get_model(**self.unet.unet.dict())
         vae_info = context.services.model_manager.get_model(**self.vae.vae.dict())
 
-        #unet = unet_info.context.model
-        #vae = vae_info.context.model
-
-        with ExitStack() as stack:
-            loras = [(stack.enter_context(context.services.model_manager.get_model(**lora.dict(exclude={"weight"}))), lora.weight) for lora in self.unet.loras]
-
         with vae_info as vae,\
-                 unet_info as unet,\
-                 ModelPatcher.apply_lora_unet(unet, loras):
+                ModelPatcher.apply_lora_unet(unet_info.context.model, _lora_loader()),\
+                unet_info as unet:
 
             device = context.services.model_manager.mgr.cache.execution_device
             dtype = context.services.model_manager.mgr.cache.precision

invokeai/backend/stable_diffusion/diffusers_pipeline.py

@@ -127,7 +127,7 @@ class AddsMaskGuidance:
 
     def _t_for_field(self, field_name: str, t):
         if field_name == "pred_original_sample":
-            return torch.zeros_like(t, dtype=t.dtype)  # it represents t=0
+            return self.scheduler.timesteps[-1]
         return t
 
     def apply_mask(self, latents: torch.Tensor, t) -> torch.Tensor: