Update handler.py

handler.py

@@ -58,7 +58,7 @@ DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 #     response = postprocess(model_outputs)
 #     return response
 
-class PreTrainedPipeline():
+class EndpointHandler():
     def __init__(self ):
         # Load processor and model
         self.PROCESSOR = AutoProcessor.from_pretrained(
@@ -102,7 +102,7 @@ class PreTrainedPipeline():
         return {"generated_text": generated_text}
         # return {"text":prediction[0]}
     
-    @classmethod
+    # @classmethod
     def convert_to_rgb(self, image):
         if image.mode == "RGB":
             return image
@@ -111,7 +111,7 @@ class PreTrainedPipeline():
         alpha_composite = Image.alpha_composite(background, image_rgba)
         alpha_composite = alpha_composite.convert("RGB")
         return alpha_composite
-    @classmethod
+    # @classmethod
     def custom_transform(self, x):
         x = self.convert_to_rgb(x)
         x = to_numpy_array(x)