Update app.py

app.py

@@ -1,5 +1,7 @@
 #!/usr/bin/env python
 
+#!/usr/bin/env python
+
 import os
 import random
 import uuid
@@ -27,30 +29,29 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
 
 MAX_SEED = np.iinfo(np.int32).max
 
-if not torch.cuda.is_available():
-    DESCRIPTION += "\n<p>Running on CPU 🥶 This demo may not work on CPU.</p>"
-
-MAX_SEED = np.iinfo(np.int32).max
-
 USE_TORCH_COMPILE = 0
 ENABLE_CPU_OFFLOAD = 0
 
-
 if torch.cuda.is_available():
-    pipe = StableDiffusionXLPipeline.from_pretrained(
-        "fluently/Fluently-XL-Final",
-        torch_dtype=torch.float16,
-        use_safetensors=True,
-    )
-    pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
-    
-    
+    DESCRIPTION += "\n<p>Running on GPU 🚀</p>"
+    device = "cuda"
+else:
+    DESCRIPTION += "\n<p>Running on CPU 🥶 This demo may be slower on CPU.</p>"
+    device = "cpu"
+
+pipe = StableDiffusionXLPipeline.from_pretrained(
+    "fluently/Fluently-XL-Final",
+    torch_dtype=torch.float16 if device == "cuda" else torch.float32,
+    use_safetensors=True,
+)
+pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
+
+if device == "cuda":
     pipe.load_lora_weights("ehristoforu/dalle-3-xl-v2", weight_name="dalle-3-xl-lora-v2.safetensors", adapter_name="dalle")
     pipe.set_adapters("dalle")
-
-    pipe.to("cuda")
-    
-    
+    pipe.to(device)
+else:
+    pipe.to("cpu")  # Ensure compatibility with CPU
 
 @spaces.GPU(enable_queue=True)
 def generate(
@@ -64,13 +65,13 @@ def generate(
     randomize_seed: bool = False,
     progress=gr.Progress(track_tqdm=True),
 ):
-
-    
     seed = int(randomize_seed_fn(seed, randomize_seed))
 
     if not use_negative_prompt:
         negative_prompt = ""  # type: ignore
 
+    generator = torch.manual_seed(seed)
+
     images = pipe(
         prompt=prompt,
         negative_prompt=negative_prompt,
@@ -81,9 +82,10 @@ def generate(
         num_images_per_prompt=1,
         cross_attention_kwargs={"scale": 0.65},
         output_type="pil",
+        generator=generator,
     ).images
+
     image_paths = [save_image(img) for img in images]
-    print(image_paths)
     return image_paths, seed
 
 examples = [
@@ -102,6 +104,7 @@ footer {
     visibility: hidden
 }
 '''
+
 with gr.Blocks(css=css, theme="pseudolab/huggingface-korea-theme") as demo:
     gr.Markdown(DESCRIPTION)
     gr.DuplicateButton(
@@ -178,7 +181,6 @@ with gr.Blocks(css=css, theme="pseudolab/huggingface-korea-theme") as demo:
         outputs=negative_prompt,
         api_name=False,
     )
-    
 
     gr.on(
         triggers=[
@@ -200,6 +202,6 @@ with gr.Blocks(css=css, theme="pseudolab/huggingface-korea-theme") as demo:
         outputs=[result, seed],
         api_name="run",
     )
-    
+
 if __name__ == "__main__":
-    demo.queue(max_size=20).launch(show_api=False, debug=False)
+    demo.queue(max_size=20).launch(show_api=False, debug=False)