trigger set pipe on inputs change

app.py

@@ -7,6 +7,7 @@ from src.sdxl_inversion_pipeline import SDXLDDIMPipeline
 from src.config import RunConfig
 from src.editor import ImageEditorDemo
 import spaces
+
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 # if torch.cuda.is_available():
@@ -43,6 +44,7 @@ with gr.Blocks(css="style.css") as demo:
     """)
     editor_state = gr.State()
 
+
     @spaces.GPU
     def set_pipe(image_editor, 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):
@@ -50,16 +52,12 @@ with gr.Blocks(css="style.css") as demo:
             image_editor = image_editor.to('cpu')
         scheduler_class = MyEulerAncestralDiscreteScheduler
 
-        print('\n################## 1')
         pipe_inversion = SDXLDDIMPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)  # .to('cpu')
-        print('\n################## 2')
         pipe_inference = AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo",
                                                                     use_safetensors=True)  # .to('cpu')
-        print('\n################## 3')
         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)
-        print('\n################## 4')
 
         config = RunConfig(num_inference_steps=num_inference_steps,
                            num_inversion_steps=num_inversion_steps,
@@ -68,8 +66,9 @@ with gr.Blocks(css="style.css") as demo:
         image_editor = ImageEditorDemo(pipe_inversion, pipe_inference, input_image,
                                        description_prompt, config, device,
                                        [rnri_iterations, rnri_alpha, rnri_lr])
-        print('\n################## 5')
         return image_editor, "Input has set!"
+
+
     @spaces.GPU
     def edit(editor, target_prompt):
         if editor is None:
@@ -86,7 +85,6 @@ with gr.Blocks(css="style.css") as demo:
         with gr.Column(elem_id="col-container-1"):
             with gr.Row():
                 input_image = gr.Image(label="Input image", sources=['upload', 'webcam'], type="pil")
-
             with gr.Row():
                 description_prompt = gr.Text(
                     label="Image description",
@@ -172,12 +170,54 @@ with gr.Blocks(css="style.css") as demo:
                             inversion_max_step, rnri_iterations, rnri_alpha, rnri_lr],
                 )
 
-    set_button.click(
-        fn=set_pipe,
-        inputs=[editor_state, input_image, description_prompt, edit_guidance_scale, num_inference_steps,
-                num_inference_steps, inversion_max_step, rnri_iterations, rnri_alpha, rnri_lr],
-        outputs=[editor_state, is_set_text],
-    )
+    input_image.change(set_pipe,
+                       inputs=[editor_state, input_image, description_prompt, edit_guidance_scale, num_inference_steps,
+                               num_inference_steps, inversion_max_step, rnri_iterations, rnri_alpha, rnri_lr],
+                       outputs=[editor_state, is_set_text])
+
+    description_prompt.change(set_pipe, inputs=[editor_state, input_image, description_prompt, edit_guidance_scale,
+                                                num_inference_steps,
+                                                num_inference_steps, inversion_max_step, rnri_iterations, rnri_alpha,
+                                                rnri_lr],
+                              outputs=[editor_state, is_set_text])
+
+    edit_guidance_scale.change(set_pipe, inputs=[editor_state, input_image, description_prompt, edit_guidance_scale,
+                                                 num_inference_steps,
+                                                 num_inference_steps, inversion_max_step, rnri_iterations, rnri_alpha,
+                                                 rnri_lr],
+                               outputs=[editor_state, is_set_text])
+    num_inference_steps.change(set_pipe, inputs=[editor_state, input_image, description_prompt, edit_guidance_scale,
+                                                 num_inference_steps,
+                                                 num_inference_steps, inversion_max_step, rnri_iterations, rnri_alpha,
+                                                 rnri_lr],
+                               outputs=[editor_state, is_set_text])
+    inversion_max_step.change(set_pipe, inputs=[editor_state, input_image, description_prompt, edit_guidance_scale,
+                                                num_inference_steps,
+                                                num_inference_steps, inversion_max_step, rnri_iterations, rnri_alpha,
+                                                rnri_lr],
+                              outputs=[editor_state, is_set_text])
+    rnri_iterations.change(set_pipe, inputs=[editor_state, input_image, description_prompt, edit_guidance_scale,
+                                             num_inference_steps,
+                                             num_inference_steps, inversion_max_step, rnri_iterations, rnri_alpha,
+                                             rnri_lr],
+                           outputs=[editor_state, is_set_text])
+    rnri_alpha.change(set_pipe, inputs=[editor_state, input_image, description_prompt, edit_guidance_scale,
+                                        num_inference_steps,
+                                        num_inference_steps, inversion_max_step, rnri_iterations, rnri_alpha,
+                                        rnri_lr],
+                      outputs=[editor_state, is_set_text])
+    rnri_lr.change(set_pipe, inputs=[editor_state, input_image, description_prompt, edit_guidance_scale,
+                                     num_inference_steps,
+                                     num_inference_steps, inversion_max_step, rnri_iterations, rnri_alpha,
+                                     rnri_lr],
+                   outputs=[editor_state, is_set_text])
+
+    # set_button.click(
+    #     fn=set_pipe,
+    #     inputs=[editor_state, input_image, description_prompt, edit_guidance_scale, num_inference_steps,
+    #             num_inference_steps, inversion_max_step, rnri_iterations, rnri_alpha, rnri_lr],
+    #     outputs=[editor_state, is_set_text],
+    # )
 
     run_button.click(
         fn=edit,
@@ -186,6 +226,3 @@ with gr.Blocks(css="style.css") as demo:
     )
 
 demo.queue().launch()
-
-# im = infer(input_image, description_prompt, target_prompt, edit_guidance_scale, num_inference_steps=4, num_inversion_steps=4,
-#           inversion_max_step=0.6)