Update handler.py

handler.py

@@ -5,6 +5,12 @@ from torch import autocast
 from diffusers import StableDiffusionPipeline
 import base64
 from io import BytesIO
+from transformers.utils import logging
+
+logging.set_verbosity_info()
+logger = logging.get_logger("transformers")
+logger.info("INFO")
+logger.warning("WARN")
 
 
 # set device
@@ -28,19 +34,19 @@ class EndpointHandler():
             A :obj:`dict`:. base64 encoded image
         """
         inputs = data.pop("inputs", data)
-        print("Printing inputs")
-        print(inputs)
-        print("")
+        logger.info("Printing inputs")
+        logger.info(inputs)
+        logger.info("")
 
-        print("Printing image")
-        print(inputs['image'])
-        print("")
+        logger.info("Printing image")
+        logger.info(inputs['image'])
+        logger.info("")
 
         # decode base64 image to PIL
-        #image = Image.open(BytesIO(base64.b64decode(inputs['image'])))
-        #print("Printing loaded image into library")
-        #print(image)
-        #print("")
+        image = Image.open(BytesIO(base64.b64decode(inputs['image'])))
+        logger.info("Printing loaded image into library")
+        logger.info(image)
+        logger.info("")
         
         # run inference pipeline
         #upscaled_image = self.pipe(prompt="", image = image).images[0]