Update app.py

app.py

@@ -13,9 +13,11 @@ from torchvision import transforms
 
 device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
 dtype = torch.float16 if torch.cuda.is_available() else torch.float32
-pipeline = AutoPipelineForText2Image.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float32).to('cuda:0')
+pipeline = AutoPipelineForText2Image.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float32).to(device)
 pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="sdxl_models", weight_name="ip-adapter_sdxl.bin")
 
+print(device)
+
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
     if randomize_seed:
         seed = random.randint(0, 2000)
@@ -32,6 +34,7 @@ def create_image(image_pil,
                  seed,
                  target="Load only style blocks",
                  ):
+    print(device)
     if target !="Load original IP-Adapter":
         if target=="Load only style blocks":
             scale = {
@@ -49,8 +52,9 @@ def create_image(image_pil,
         pipeline.set_ip_adapter_scale(scale)
 
     style_image = load_image(image_pil)
-    generator = torch.Generator(device='cuda:0').manual_seed(randomize_seed_fn(seed, True))
+    generator = torch.Generator(device=device).manual_seed(randomize_seed_fn(seed, True))
     torch.cuda.set_device(device)
+    print(device)
     image = pipeline(
         prompt=prompt,
         ip_adapter_image=style_image,
@@ -58,7 +62,7 @@ def create_image(image_pil,
         guidance_scale=guidance_scale,
         num_inference_steps=num_inference_steps,
         generator=generator,
-        device='cuda:0'
+        device=device
     )
     return image