Update app.py

app.py

@@ -13,22 +13,20 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 
 torch.cuda.max_memory_allocated(device=device)
 
-def genie (refiner, prompt, negative_prompt, int_image, scale, steps, seed):
-    if refiner == 'Base':
+def genie (prompt, negative_prompt, scale, steps, seed):
         pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
         pipe = pipe.to(device)
         pipe.enable_xformers_memory_efficient_attention()
         torch.cuda.empty_cache()
     
         generator = torch.Generator(device=device).manual_seed(seed)
-        image = pipe(prompt, negative_prompt=negative_prompt, num_inference_steps=steps, guidance_scale=scale, num_images_per_prompt=1, generator=generator).images[0]
-    else:
+        int_image = pipe(prompt, negative_prompt=negative_prompt, num_inference_steps=steps, guidance_scale=scale, num_images_per_prompt=1, generator=generator, ).images
         torch.cuda.empty_cache()
-        refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
-        refiner = refiner.to(device)
-        refiner.enable_xformers_memory_efficient_attention()
+        pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
+        pipe = refiner.to(device)
+        pipe.enable_xformers_memory_efficient_attention()
         torch.cuda.empty_cache()
-        image = refiner(prompt=prompt, image=int_image).images[0]
+        image = pipe(prompt=prompt, image=int_image).images[0]
     return image
   
 
@@ -36,5 +34,5 @@ def genie (refiner, prompt, negative_prompt, int_image, scale, steps, seed):
     
 
     
-gr.Interface(fn=genie, inputs=[gr.Radio(['Base', 'Refiner'], value='Base'),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.'), 'image', gr.Slider(1, 15, 10), gr.Slider(25, maximum=50, value=25, 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. 65s/Iteration. Expect 25-50mins an image for 25-50 iterations respectively.", article = "Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(debug=True, max_threads=80)
+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(25, maximum=50, value=25, 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. 65s/Iteration. Expect 25-50mins an image for 25-50 iterations respectively.", article = "Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(debug=True, max_threads=80)
 #gr.Interface(fn=refiner, inputs='image', outputs='image').launch(debug=True)