Optimize RVC training: resumable training with checkpoints every 10 epochs and advanced UI options

app.py

@@ -248,6 +248,26 @@ with gr.Blocks(title="Voice Clone RVC", theme=gr.themes.Soft()) as app:
                         step=1,
                         label="Epochs (Iteraciones de entrenamiento)",
                     )
+                    with gr.Accordion("Opciones Avanzadas", open=False):
+                        rvc_f0_method = gr.Dropdown(
+                            choices=["rmvpe", "crepe", "fcpe"],
+                            value="rmvpe",
+                            label="Método de Extracción de Pitch (f0)"
+                        )
+                        rvc_batch_size = gr.Slider(
+                            minimum=1,
+                            maximum=24,
+                            value=4,
+                            step=1,
+                            label="Batch Size (Tamaño de lote)"
+                        )
+                        rvc_save_every = gr.Slider(
+                            minimum=1,
+                            maximum=50,
+                            value=10,
+                            step=1,
+                            label="Guardar Checkpoint cada (Epochs)"
+                        )
                     rvc_train_btn = gr.Button(
                         "Iniciar Entrenamiento RVC",
                         variant="primary",
@@ -265,14 +285,14 @@ with gr.Blocks(title="Voice Clone RVC", theme=gr.themes.Soft()) as app:
                     )
 
             gr.Markdown(
-                "**Advertencia sobre ZeroGPU:**\n"
-                "- El entrenamiento de modelos requiere mucho tiempo. ZeroGPU puede cancelar el proceso si supera el tiempo máximo asignado (usualmente 10 minutos).\n"
-                "- Si falla por timeout, considera bajar los epochs o usar menos audio."
+                "**🚀 Entrenamiento Resumible:**\n"
+                "- Si ZeroGPU corta el entrenamiento por tiempo (10 min), puedes volver a dar clic en el botón y el proceso continuará desde el último punto guardado.\n"
+                "- Los checkpoints se guardan cada **10 epochs** por defecto."
             )
 
             rvc_train_btn.click(
                 fn=train_rvc_model,
-                inputs=[rvc_audio, rvc_model_name, rvc_epochs],
+                inputs=[rvc_audio, rvc_model_name, rvc_epochs, rvc_batch_size, rvc_f0_method, rvc_save_every],
                 outputs=[rvc_status, rvc_download],
             )
 

pipeline/rvc_training.py

@@ -45,7 +45,7 @@ except Exception as e:
     RVC_LOGIC_AVAILABLE = False
 
 @spaces.GPU(duration=1000)
-def train_rvc_model(audio_path, model_name, epochs=100, progress=None):
+def train_rvc_model(audio_path, model_name, epochs=100, batch_size=4, f0_method="rmvpe", save_every=10, progress=None):
     if not RVC_LOGIC_AVAILABLE:
         return f"Error: rvc_logic module failed to load. Reason: {RVC_IMPORT_ERROR}", None
     
@@ -75,20 +75,20 @@ def train_rvc_model(audio_path, model_name, epochs=100, progress=None):
         )
         
         # 3. Extract Features
-        p(0.4, "Step 3/4: Extracting features (F0 & Content)...")
+        p(0.4, f"Step 3/4: Extracting features (Method: {f0_method})...")
         extract.extract_features(
             model_name=model_name,
-            f0_method=F0Method.RMVPE,
+            f0_method=f0_method,
             embedder_model=EmbedderModel.CONTENTVEC
         )
         
         # 4. Train
-        p(0.6, f"Step 4/4: Training for {epochs} epochs...")
+        p(0.6, f"Step 4/4: Training for {epochs} epochs (Batch: {batch_size}, Checkpoints: {save_every})...")
         result_paths = train.run_training(
             model_name=model_name,
             num_epochs=epochs,
-            batch_size=4,
-            save_interval=epochs
+            batch_size=batch_size,
+            save_interval=save_every
         )
         
         if not result_paths or len(result_paths) < 2: