Updated handler.py

handler.py

@@ -7,7 +7,7 @@ from io import BytesIO
 import torch
 import os
 
-device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+
 
 class EndpointHandler:
     def __init__(self, path=""):
@@ -15,8 +15,7 @@ class EndpointHandler:
 
         self.processor = Blip2Processor.from_pretrained("Salesforce/blip2-opt-2.7b") 
         self.model = Blip2ForConditionalGeneration.from_pretrained("Salesforce/blip2-opt-2.7b", device_map="auto")
-        self.model.eval()
-        self.model = self.model.to("cuda")
+
 
 
     def __call__(self, data: Any) -> Dict[str, Any]:
@@ -28,9 +27,10 @@ class EndpointHandler:
             A :obj:`dict`:. The object returned should be a dict of one list like {"captions": ["A hugging face at the office"]} containing :
                 - "caption": A string corresponding to the generated caption.
         """
-        
+
         inputs = data.pop("inputs", data)
-        parameters = data.pop("parameters", {})
+        # parameters = data.pop("parameters", {})
+        device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
  
         raw_images = Image.open(BytesIO(inputs))