modify app

app.py

@@ -128,7 +128,7 @@ with gr.Blocks() as demo:
         
         with gr.Row():
             output_audio = gr.Audio(label="Output Audio", type='numpy')
-            param_output = gr.Textbox(label="Predicted Parameters", lines=10)
+            param_output = gr.Textbox(label="Predicted Parameters", lines=5)
 
         process_button.click(
             process_audio, 
@@ -139,21 +139,39 @@ with gr.Blocks() as demo:
     gr.Markdown("## Inference Time Optimization (ITO)")
     
     with gr.Row():
-        with gr.Column(scale=2):
-            ito_reference_audio = gr.Audio(label="ITO Reference Audio (optional)")
-            num_steps = gr.Slider(minimum=1, maximum=1000, value=100, step=1, label="Number of Steps")
+        ito_reference_audio = gr.Audio(label="ITO Reference Audio (optional)")
+        with gr.Column():
+            num_steps = gr.Slider(minimum=1, maximum=100, value=10, step=1, label="Number of Steps")
             optimizer = gr.Dropdown(["Adam", "RAdam", "SGD"], value="RAdam", label="Optimizer")
             learning_rate = gr.Slider(minimum=0.0001, maximum=0.1, value=0.001, step=0.0001, label="Learning Rate")
             af_weights = gr.Textbox(label="AudioFeatureLoss Weights (comma-separated)", value="0.1,0.001,1.0,1.0,0.1")
-            
-            ito_button = gr.Button("Perform ITO")
-            
+        
+    ito_button = gr.Button("Perform ITO")
+
+    with gr.Row():
+        with gr.Column():
             ito_output_audio = gr.Audio(label="ITO Output Audio")
-            ito_param_output = gr.Textbox(label="ITO Predicted Parameters", lines=10)
+            ito_param_output = gr.Textbox(label="ITO Predicted Parameters", lines=5)
+        with gr.Column():
             ito_steps_taken = gr.Number(label="ITO Steps Taken")
+            ito_log = gr.Textbox(label="ITO Log", lines=10)
+
+    # with gr.Row():
+    #     with gr.Column(scale=2):
+    #         ito_reference_audio = gr.Audio(label="ITO Reference Audio (optional)")
+    #         num_steps = gr.Slider(minimum=1, maximum=100, value=10, step=1, label="Number of Steps")
+    #         optimizer = gr.Dropdown(["Adam", "RAdam", "SGD"], value="RAdam", label="Optimizer")
+    #         learning_rate = gr.Slider(minimum=0.0001, maximum=0.1, value=0.001, step=0.0001, label="Learning Rate")
+    #         af_weights = gr.Textbox(label="AudioFeatureLoss Weights (comma-separated)", value="0.1,0.001,1.0,1.0,0.1")
+            
+    #         ito_button = gr.Button("Perform ITO")
+            
+    #         ito_output_audio = gr.Audio(label="ITO Output Audio")
+    #         ito_param_output = gr.Textbox(label="ITO Predicted Parameters", lines=10)
+    #         ito_steps_taken = gr.Number(label="ITO Steps Taken")
         
-        with gr.Column(scale=1):
-            ito_log = gr.Textbox(label="ITO Log", lines=30)
+    #     with gr.Column(scale=1):
+    #         ito_log = gr.Textbox(label="ITO Log", lines=30)
 
     def run_ito(input_audio, reference_audio, ito_reference_audio, num_steps, optimizer, learning_rate, af_weights):
         af_weights = [float(w.strip()) for w in af_weights.split(',')]