Update app.py

app.py

@@ -11,7 +11,7 @@ flash_pipe.scheduler = EulerDiscreteScheduler.from_config(flash_pipe.scheduler.c
 clip_slider = CLIPSliderXL(flash_pipe, device=torch.device("cuda"))
 
 @spaces.GPU
-def generate(slider_x, slider_y, prompt, iterations, steps, 
+def generate(slider_x, slider_y, prompt, seed, iterations, steps, 
              x_concept_1, x_concept_2, y_concept_1, y_concept_2, 
              avg_diff_x_1, avg_diff_x_2,
              avg_diff_y_1, avg_diff_y_2):
@@ -27,7 +27,7 @@ def generate(slider_x, slider_y, prompt, iterations, steps,
     end_time = time.time()
     print(f"direction time: {end_time - start_time:.2f} ms")
     start_time = time.time()
-    image = clip_slider.generate(prompt, scale=0, scale_2nd=0, num_inference_steps=steps, avg_diff=avg_diff, avg_diff_2nd=avg_diff_2nd)
+    image = clip_slider.generate(prompt, scale=0, scale_2nd=0, seed=seed, num_inference_steps=steps, avg_diff=avg_diff, avg_diff_2nd=avg_diff_2nd)
     end_time = time.time()
     print(f"generation time: {end_time - start_time:.2f} ms")
     comma_concepts_x = ', '.join(slider_x)
@@ -41,19 +41,19 @@ def generate(slider_x, slider_y, prompt, iterations, steps,
     return gr.update(label=comma_concepts_x, interactive=True),gr.update(label=comma_concepts_y, interactive=True), x_concept_1, x_concept_2, y_concept_1, y_concept_2, avg_diff_x_1, avg_diff_x_2, avg_diff_y_1, avg_diff_y_2, image
 
 @spaces.GPU
-def update_x(x,y,prompt, steps, avg_diff_x_1, avg_diff_x_2, avg_diff_y_1, avg_diff_y_2):
+def update_x(x,y,prompt, seed, steps, avg_diff_x_1, avg_diff_x_2, avg_diff_y_1, avg_diff_y_2):
     avg_diff = (avg_diff_x_1.cuda(), avg_diff_x_2.cuda())
     avg_diff_2nd = (avg_diff_y_1.cuda(), avg_diff_y_2.cuda())
-    image = clip_slider.generate(prompt, scale=x, scale_2nd=y, num_inference_steps=steps, avg_diff=avg_diff,avg_diff_2nd=avg_diff_2nd) 
+    image = clip_slider.generate(prompt, scale=x, scale_2nd=y, seed=seed, num_inference_steps=steps, avg_diff=avg_diff,avg_diff_2nd=avg_diff_2nd) 
     return image
 
 @spaces.GPU
-def update_y(x,y,prompt, steps, avg_diff_x_1, avg_diff_x_2, avg_diff_y_1, avg_diff_y_2):
+def update_y(x,y,prompt, seed, steps, avg_diff_x_1, avg_diff_x_2, avg_diff_y_1, avg_diff_y_2):
     avg_diff = (avg_diff_x_1.cuda(), avg_diff_x_2.cuda())
     avg_diff_2nd = (avg_diff_y_1.cuda(), avg_diff_y_2.cuda())
-    image = clip_slider.generate(prompt, scale=x, scale_2nd=y, num_inference_steps=steps, avg_diff=avg_diff,avg_diff_2nd=avg_diff_2nd) 
+    image = clip_slider.generate(prompt, scale=x, scale_2nd=y, seed=seed, num_inference_steps=steps, avg_diff=avg_diff,avg_diff_2nd=avg_diff_2nd) 
     return image
-  
+
 css = '''
 #group {
     position: relative;
@@ -104,13 +104,13 @@ with gr.Blocks(css=css) as demo:
     with gr.Accordion(label="advanced options", open=False):
         iterations = gr.Slider(label = "num iterations", minimum=0, value=100, maximum=300)
         steps = gr.Slider(label = "num inference steps", minimum=1, value=8, maximum=30)
-        
+        seed  = gr.Slider(minimum=0, maximum=np.iinfo(np.int32).max, label="Seed", interactive=True, randomize=True)
     
     submit.click(fn=generate,
-                 inputs=[slider_x, slider_y, prompt, iterations, steps, x_concept_1, x_concept_2, y_concept_1, y_concept_2, avg_diff_x_1, avg_diff_x_2, avg_diff_y_1, avg_diff_y_2],
+                 inputs=[slider_x, slider_y, prompt, seed, iterations, steps, x_concept_1, x_concept_2, y_concept_1, y_concept_2, avg_diff_x_1, avg_diff_x_2, avg_diff_y_1, avg_diff_y_2],
                  outputs=[x, y, x_concept_1, x_concept_2, y_concept_1, y_concept_2, avg_diff_x_1, avg_diff_x_2, avg_diff_y_1, avg_diff_y_2, output_image])
-    x.change(fn=update_x, inputs=[x,y, prompt, steps, avg_diff_x_1, avg_diff_x_2, avg_diff_y_1, avg_diff_y_2], outputs=[output_image])
-    y.change(fn=update_y, inputs=[x,y, prompt, steps, avg_diff_x_1, avg_diff_x_2, avg_diff_y_1, avg_diff_y_2], outputs=[output_image])
+    x.change(fn=update_x, inputs=[x,y, prompt, seed, steps, avg_diff_x_1, avg_diff_x_2, avg_diff_y_1, avg_diff_y_2], outputs=[output_image])
+    y.change(fn=update_y, inputs=[x,y, prompt, seed, steps, avg_diff_x_1, avg_diff_x_2, avg_diff_y_1, avg_diff_y_2], outputs=[output_image])
 
 if __name__ == "__main__":
     demo.launch()