Update handler.py

handler.py

@@ -4,6 +4,8 @@ from diffusers import DPMSolverMultistepScheduler, StableDiffusionInpaintPipelin
 from PIL import Image
 import base64
 from io import BytesIO
+from datetime import datetime
+import time
 
 
 # set device
@@ -12,6 +14,12 @@ device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 if device.type != 'cuda':
     raise ValueError("need to run on GPU")
 
+begin_runtime = datetime.now()
+    
+def print_current_time(tag: str):
+    global begin_runtime
+    print(str(tag).upper() + ": " + str(datetime.now() - begin_runtime))
+
 class EndpointHandler():
     def __init__(self, path=""):
         # load StableDiffusionInpaintPipeline pipeline
@@ -43,6 +51,8 @@ class EndpointHandler():
         width = data.pop("width", None)
 
         # process image
+        print_current_time("Start decoding")
+        
         if encoded_image is not None and encoded_mask_image is not None:
             image = self.decode_base64_image(encoded_image)
             mask_image = self.decode_base64_image(encoded_mask_image)
@@ -50,6 +60,8 @@ class EndpointHandler():
             image = None
             mask_image = None
 
+        print_current_time("Finish decoding")
+            
         # run inference pipeline
         out = self.pipe(inputs,
                         image=image,
@@ -69,6 +81,8 @@ class EndpointHandler():
           out.images[i].save(buffered, format="PNG")
           img_str = base64.b64encode(buffered.getvalue())
           json_imgs[f"{i}"] = img_str.decode()
+
+        print_current_time("Complete Stable diffusion")
         return json_imgs
 
     # helper to decode input image