Update handler.py

handler.py

@@ -103,19 +103,22 @@ class EndpointHandler():
         image = self.decode_base64_image(image)
         control_image = CONTROLNET_MAPPING[self.control_type]["hinter"](image)
         
-        # run inference pipeline
-        out = self.pipe(
-            prompt=prompt, 
-            negative_prompt=negative_prompt,
-            image=control_image,
-            num_inference_steps=num_inference_steps, 
-            guidance_scale=guidance_scale,
-            num_images_per_prompt=1,
-            height=height,
-            width=width,
-            controlnet_conditioning_scale=controlnet_conditioning_scale,
-            generator=self.generator
-        )
+        image = image.resize((512, 512))
+        
+        with torch.no_grad():
+            # run inference pipeline
+            out = self.pipe(
+                prompt=prompt, 
+                negative_prompt=negative_prompt,
+                image=control_image,
+                num_inference_steps=num_inference_steps, 
+                guidance_scale=guidance_scale,
+                num_images_per_prompt=1,
+                height=height,
+                width=width,
+                controlnet_conditioning_scale=controlnet_conditioning_scale,
+                generator=self.generator
+            )
 
         
         # return first generate PIL image