Update app.py

app.py

@@ -13,16 +13,16 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 
 pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-0.9", add_to_git_credential=True)
 pipe = pipe.to(device)
-pipe.unet = torch.compile(refiner.unet, mode="reduce-overhead", fullgraph=True)
+pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
 
 refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9")
 refiner = refiner.to(device)
-refiner.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
+refiner.unet = torch.compile(refiner.unet, mode="reduce-overhead", fullgraph=True)
 
 def genie (prompt, negative_prompt, scale, steps, seed):
      generator = torch.Generator(device=device).manual_seed(seed)
-     int_image = pipe(prompt, negative_prompt=negative_prompt, width=768, height=768, num_inference_steps=steps, guidance_scale=scale, num_images_per_prompt=1, generator=generator, output_type="latent").images
-     image = refiner(prompt=prompt, image=int_image).images
+     int_image = pipe(prompt, negative_prompt=negative_prompt, num_inference_steps=steps, guidance_scale=scale, num_images_per_prompt=1, generator=generator, output_type="latent").images #width=768, height=768
+     image = refiner(prompt=prompt, image=int_image).images[0]
      return image
     
 gr.Interface(fn=genie, inputs=[gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'), gr.Textbox(label='What you Do Not want the AI to generate.'), gr.Slider(1, 15, 10), gr.Slider(1, maximum=100, value=50, step=1), gr.Slider(minimum=1, step=1, maximum=999999999999999999, randomize=True)], outputs='image', title="Stable Diffusion XL .9 CPU", description="SDXL .9 CPU. <b>WARNING:</b> Extremely Slow. 130s/Iteration. Expect 14-28mins an image for 10-20 iterations respectively.", article = "Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(debug=True, max_threads=True)