fix llamaboard with ray

Former-commit-id: bd8a432d6a980b1b24a551626304fe3d394b1baf

src/llamafactory/train/tuner.py

@@ -46,11 +46,12 @@ if TYPE_CHECKING:
 logger = logging.get_logger(__name__)
 
 
-def training_function(config: Dict[str, Any]) -> None:
+def _training_function(config: Dict[str, Any]) -> None:
     args = config.get("args")
     callbacks: List[Any] = config.get("callbacks")
     model_args, data_args, training_args, finetuning_args, generating_args = get_train_args(args)
 
+    callbacks.append(LogCallback())
     if finetuning_args.pissa_convert:
         callbacks.append(PissaConvertCallback())
 
@@ -76,21 +77,19 @@ def training_function(config: Dict[str, Any]) -> None:
 
 
 def run_exp(args: Optional[Dict[str, Any]] = None, callbacks: Optional[List["TrainerCallback"]] = None) -> None:
-    callbacks = callbacks or []
-    callbacks.append(LogCallback())
-
     args = read_args(args)
     ray_args = get_ray_args(args)
+    callbacks = callbacks or []
     if ray_args.use_ray:
         callbacks.append(RayTrainReportCallback())
         trainer = get_ray_trainer(
-            training_function=training_function,
+            training_function=_training_function,
             train_loop_config={"args": args, "callbacks": callbacks},
             ray_args=ray_args,
         )
         trainer.fit()
     else:
-        training_function(config={"args": args, "callbacks": callbacks})
+        _training_function(config={"args": args, "callbacks": callbacks})
 
 
 def export_model(args: Optional[Dict[str, Any]] = None) -> None: