Update demo.py

demo.py

@@ -348,18 +348,18 @@ with gr.Blocks() as demo:
                 f0_output = gr.Textbox(label="F0 Feature Extraction Log")
                 train_output = gr.Textbox(label="Training Log")
 
-                #preprocess_btn.click(preprocess_data, inputs=[model_name, dataset_folder], outputs=preprocess_output)
-                #f0_btn.click(extract_f0_feature, inputs=[model_name, f0method], outputs=f0_output)
-                #train_btn.click(train_index, inputs=[model_name, "v2"], outputs=train_output)
+                preprocess_btn.click(preprocess_data, inputs=[model_name, dataset_folder], outputs=preprocess_output)
+                f0_btn.click(extract_f0_feature, inputs=[model_name, f0method], outputs=f0_output)
+                train_btn.click(train_index, inputs=[model_name, "v2"], outputs=train_output)
             with gr.TabItem("Train Your Model"):
                 model_name_input = gr.Textbox(label="Model Name", placeholder="Enter the model name", interactive=True)
-                epochs_slider = gr.Slider(minimum=50, maximum=2000, value=200, step=10, label="Epochs")
-                save_frequency_slider = gr.Slider(minimum=10, maximum=100, value=50, step=10, label="Save Frequency")
-                batch_size_slider = gr.Slider(minimum=1, maximum=20, value=8, step=1, label="Batch Size")
+                epochs_slider = gr.Slider(minimum=50, maximum=2000, value=200, step=10, label="Epochs", interactive=True)
+                save_frequency_slider = gr.Slider(minimum=10, maximum=100, value=50, step=10, label="Save Frequency", interactive=True)
+                batch_size_slider = gr.Slider(minimum=1, maximum=20, value=8, step=1, label="Batch Size", interactive=True)
     
-                train_button = gr.Button("Train Model")
+                train_button = gr.Button("Train Model", interactive=True)
                 training_output = gr.Textbox(label="Training Log", interactive=False)
     
-                #train_button.click(launch_training, inputs=[model_name_input, epochs_slider, save_frequency_slider, batch_size_slider], outputs=training_output)
+                train_button.click(launch_training, inputs=[model_name_input, epochs_slider, save_frequency_slider, batch_size_slider], outputs=training_output)
     
 demo.launch()