adding support for cpu devices too, by using to(device) instead of to(cuda)

app.py

@@ -9,6 +9,8 @@ import io
 import os
 from PIL import Image
 
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+
 from diffusers import (
     StableDiffusionPipeline,
     StableDiffusionControlNetImg2ImgPipeline,
@@ -36,7 +38,7 @@ pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
     controlnet=controlnet,
     safety_checker=None,
     torch_dtype=torch.float16,
-).to("cuda")
+).to(device)
 pipe.enable_xformers_memory_efficient_attention()