nodes: skip self.model.to(device_to) walk in unpatch_model on mmap'd weights

nodes.py

@@ -67,15 +67,40 @@ def patch_weight_to_device(self, key, device_to=None, inplace_update=False):
             comfy.utils.set_attr_param(self.model, key, out_weight)
 
     def unpatch_model(self, device_to=None, unpatch_weights=True):
+        self.eject_model()
         if unpatch_weights:
             for p in self.model.parameters():
                 if is_torch_compatible(p):
                     continue
-                patches = getattr(p, "patches", [])
-                if len(patches) > 0:
+                if len(getattr(p, "patches", [])) > 0:
                     p.patches = []
-        # TODO: Find another way to not unload after patches
-        return super().unpatch_model(device_to=device_to, unpatch_weights=unpatch_weights)
+            # Mirror of base unpatch_model's unpatch_weights block, skipping the
+            # self.model.to(device_to) walk that faults on mmap'd quantized
+            # tensors (#444). Tracking upstream at Comfy-Org/ComfyUI#14142.
+            self.unpatch_hooks()
+            self.unpin_all_weights()
+            if self.model.model_lowvram:
+                for m in self.model.modules():
+                    comfy.model_patcher.move_weight_functions(m, device_to)
+                    comfy.model_patcher.wipe_lowvram_weight(m)
+                self.model.model_lowvram = False
+                self.model.lowvram_patch_counter = 0
+            for k in list(self.backup.keys()):
+                bk = self.backup[k]
+                if bk.inplace_update:
+                    comfy.utils.copy_to_param(self.model, k, bk.weight)
+                else:
+                    comfy.utils.set_attr_param(self.model, k, bk.weight)
+            self.model.current_weight_patches_uuid = None
+            self.backup.clear()
+            if device_to is not None:
+                self.model.device = device_to
+            self.model.model_loaded_weight_memory = 0
+            self.model.model_offload_buffer_memory = 0
+            for m in self.model.modules():
+                if hasattr(m, "comfy_patched_weights"):
+                    del m.comfy_patched_weights
+        return super().unpatch_model(device_to=device_to, unpatch_weights=False)
 
 
     def pin_weight_to_device(self, key):