update

app.py

@@ -174,7 +174,7 @@ def load_pipeline(use_distilled: bool = False, device: str = "cuda"):
         )
         pipeline.to('cpu')
         refiner_pipeline = pipeline.refiner_pipeline
-        refiner_pipeline.text_encoder = pipeline.text_encoder
+        # refiner_pipeline.text_encoder = pipeline.text_encoder
         refiner_pipeline.to('cpu')
         reprompt_model = pipeline.reprompt_model
 

hyimage/diffusion/pipelines/hunyuanimage_pipeline.py

@@ -816,8 +816,8 @@ class HunyuanImagePipeline:
         self.device = device
         if self.dit is not None:
             self.dit = self.dit.to(device, non_blocking=True)
-        # if self.text_encoder is not None:
-            # self.text_encoder = self.text_encoder.to(device, non_blocking=True)
+        if self.text_encoder is not None:
+            self.text_encoder = self.text_encoder.to(device, non_blocking=True)
         if self.vae is not None:
             self.vae = self.vae.to(device, non_blocking=True)
         return self

hyimage/diffusion/pipelines/hunyuanimage_refiner_pipeline.py

@@ -259,6 +259,25 @@ class HunYuanImageRefinerPipeline(HunyuanImagePipeline):
         """
         return cls(config=config)
 
+    def to(self, device: str | torch.device):
+        """
+        Move pipeline to specified device.
+
+        Args:
+            device: Target device string
+
+        Returns:
+            Self
+        """
+        self.device = device
+        if self.dit is not None:
+            self.dit = self.dit.to(device, non_blocking=True)
+        # if self.text_encoder is not None:
+            # self.text_encoder = self.text_encoder.to(device, non_blocking=True)
+        if self.vae is not None:
+            self.vae = self.vae.to(device, non_blocking=True)
+        return self
+
 
 # Convenience function for easy access
 def RefinerPipeline(