Update app.py

app.py

@@ -9,16 +9,14 @@ import gradio as gr
 from diffusers import AutoPipelineForText2Image
 from diffusers.utils import load_image
 
-# global variable
-device = "cuda" if torch.cuda.is_available() else "cpu"
-dtype = torch.float16 if str(device).__contains__("cuda") else torch.float32
-
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
     if randomize_seed:
         seed = random.randint(0, 2000)
     return seed
 
-pipeline = AutoPipelineForText2Image.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=dtype).to(device)
+device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
+torch.cuda.set_device(device)
+pipeline = AutoPipelineForText2Image.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16).to(device)
 pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="sdxl_models", weight_name="ip-adapter_sdxl.bin")
 
 @spaces.GPU()
@@ -54,7 +52,7 @@ def create_image(image_pil,
     
     style_image = load_image(image_pil)
 
-    generator = torch.Generator(device=device).manual_seed(randomize_seed_fn(seed, False))
+    generator = torch.Generator().manual_seed(randomize_seed_fn(seed, False))
     image = pipeline(
         prompt=prompt,
         ip_adapter_image=style_image,