add custom seed parameter

app.py

@@ -57,7 +57,7 @@ def start_over(gallery_state, loaded_model_setup):
         loaded_model_setup = None  # Reset loaded model setup to prevent re-triggering old state
     return gallery_state, None, None, gr.update(visible=False), loaded_model_setup
 
-def setup_model(prompt, model, num_iterations, learning_rate, hps_w, imgrw_w, pcks_w, clip_w, progress=gr.Progress(track_tqdm=True)):
+def setup_model(prompt, model, seed, num_iterations, learning_rate, hps_w, imgrw_w, pcks_w, clip_w, progress=gr.Progress(track_tqdm=True)):
 
     """Clear CUDA memory before starting the training."""
     torch.cuda.empty_cache()  # Free up cached memory
@@ -67,6 +67,7 @@ def setup_model(prompt, model, num_iterations, learning_rate, hps_w, imgrw_w, pc
     args.task = "single"
     args.prompt = prompt
     args.model = model
+    args.seed = seed
     args.n_iters = num_iterations
     args.lr = learning_rate
     args.cache_dir = "./HF_model_cache"
@@ -209,6 +210,7 @@ with gr.Blocks(analytics_enabled=False) as demo:
                 prompt = gr.Textbox(label="Prompt")
                 with gr.Row():
                     chosen_model = gr.Dropdown(["sd-turbo", "sdxl-turbo", "pixart", "hyper-sd"], label="Model", value="sd-turbo")
+                    seed = gr.Number(label="seed", value=0)
                     model_status = gr.Textbox(label="model status", visible=False)
                 
                 with gr.Row():
@@ -247,7 +249,7 @@ with gr.Blocks(analytics_enabled=False) as demo:
         outputs = [gallery_state, output_image, status, iter_gallery, loaded_model_setup]  # Ensure loaded_model_setup is reset
     ).then(
         fn = setup_model,
-        inputs = [prompt, chosen_model, n_iter, hps_w, imgrw_w, pcks_w, clip_w, learning_rate],
+        inputs = [prompt, chosen_model, seed, n_iter, hps_w, imgrw_w, pcks_w, clip_w, learning_rate],
         outputs = [output_image, loaded_model_setup]  # Load the new setup into the state
     ).then(
         fn = generate_image,