Update handler.py

handler.py

@@ -98,8 +98,12 @@ class EndpointHandler():
         # run inference pipeline
         out = self.pipe(prompt=prompt, negative_prompt=negative_prompt, image=image, mask_image=mask_image)
 
+        print("1st pipeline part successful!")
+
         image = out.images[0].resize((1024, 1024))
 
+        print("image resizing successful!")
+
         self.pipe2.enable_xformers_memory_efficient_attention()
 
         image = self.pipe2(
@@ -112,6 +116,8 @@ class EndpointHandler():
             strength=strength, #0.2
             output_type="latent",  # let's keep in latent to save some VRAM
         ).images[0]
+
+        print("2nd pipeline part successful!")
         
         self.pipe3.enable_xformers_memory_efficient_attention()
         
@@ -122,6 +128,8 @@ class EndpointHandler():
             num_inference_steps=num_inference_steps, #100
             strength=strength, #0.2
         ).images[0]
+
+        print("3rd pipeline part successful!")
         
             
         # return first generate PIL image