Update app.py

app.py

@@ -9,15 +9,6 @@ from src.editor import ImageEditorDemo
 import spaces
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
-scheduler_class = MyEulerAncestralDiscreteScheduler
-
-pipe_inversion = SDXLDDIMPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True).to(device)
-pipe_inference = AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True).to(device)
-pipe_inference.scheduler = scheduler_class.from_config(pipe_inference.scheduler.config)
-pipe_inversion.scheduler = scheduler_class.from_config(pipe_inversion.scheduler.config)
-pipe_inversion.scheduler_inference = scheduler_class.from_config(pipe_inference.scheduler.config)
-
-
 # if torch.cuda.is_available():
 #     torch.cuda.max_memory_allocated(device=device)
 #     pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
@@ -65,13 +56,24 @@ with gr.Blocks(css="style.css") as demo:
     @spaces.GPU
     def set_pipe(input_image, description_prompt, edit_guidance_scale, num_inference_steps=4,
                  num_inversion_steps=4, inversion_max_step=0.6, rnri_iterations=2, rnri_alpha=0.1, rnri_lr=0.2):
+                    
+        scheduler_class = MyEulerAncestralDiscreteScheduler
+        
+        pipe_inversion = SDXLDDIMPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True).to(device)
+        pipe_inference = AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True).to(device)
+        pipe_inference.scheduler = scheduler_class.from_config(pipe_inference.scheduler.config)
+        pipe_inversion.scheduler = scheduler_class.from_config(pipe_inversion.scheduler.config)
+        pipe_inversion.scheduler_inference = scheduler_class.from_config(pipe_inference.scheduler.config)
+
+
         config = RunConfig(num_inference_steps=num_inference_steps,
                            num_inversion_steps=num_inversion_steps,
                            edit_guidance_scale=edit_guidance_scale,
                            inversion_max_step=inversion_max_step)
-        return ImageEditorDemo(pipe_inversion, pipe_inference, input_image,
+        image_editor = ImageEditorDemo(pipe_inversion, pipe_inference, input_image,
                                description_prompt, config, device,
-                               [rnri_iterations, rnri_alpha, rnri_lr]), "Input has set!"
+                               [rnri_iterations, rnri_alpha, rnri_lr])
+        return image_editor, "Input has set!"
     
     @spaces.GPU
     def edit(editor, target_prompt):