allow OSFT to be configurable

Author: RobotSail

src/training_hub/algorithms/osft.py

@@ -346,11 +346,16 @@ def execute_training(self, algorithm_params: dict[str, any]) -> any:
         # adjust arguments to align with the API definition 
         training_args_pre = {k: v for k, v in algorithm_params.items() if k in training_args_fields and v is not None}
         training_args_pre['data_path'] = training_ready_data_path  # replaces raw data path with processed
-        
+
         # mini trainer can support multiple modes, but we don't expose this feature by default
         # to prevent the current API from becoming overly complicated
-        training_args_pre['training_mode'] = TrainingMode(training_args_pre.get('training_mode', 'epoch'))
-        training_args_pre['osft'] = True
+        if not isinstance(train_mode := training_args_pre.get('training_mode', TrainingMode.EPOCH), TrainingMode):
+            train_mode = TrainingMode(train_mode)
+        training_args_pre['training_mode'] = train_mode
+
+        # user may want to control this API field for debug purposes, so we allow for it to be read
+        # but default it to True
+        training_args_pre['osft'] = training_args_pre.get('osft', True)
 
         torchrun_args_pre = {k: v for k, v in algorithm_params.items() if k in torchrun_args_fields and v is not None}