diff --git a/pytorch_lightning/root_module/model_saving.py b/pytorch_lightning/root_module/model_saving.py
index 493aa05bcc..557b5d7d79 100644
--- a/pytorch_lightning/root_module/model_saving.py
+++ b/pytorch_lightning/root_module/model_saving.py
@@ -41,6 +41,11 @@ class ModelIO(object):
 
 class TrainerIO(object):
 
+    def __get_model(self):
+        is_dp_module = type(self.model) is LightningDistributedDataParallel or type(self.model) is LightningDataParallel
+        model = self.model.module if is_dp_module else self.model
+        return model
+
     # --------------------
     # MODEL SAVE CHECKPOINT
     # --------------------
@@ -71,8 +76,7 @@ class TrainerIO(object):
         checkpoint['optimizer_states'] = optimizer_states
 
         # request what to save from the model
-        is_dp_module = type(self.model) is LightningDistributedDataParallel or type(self.model) is LightningDataParallel
-        model = self.model.module if is_dp_module else self.model
+        model = self.__get_model()
         checkpoint_dict = model.get_save_dict()
 
         # merge trainer and model saving items
@@ -144,7 +148,7 @@ class TrainerIO(object):
         filepath = '{}/hpc_ckpt_{}.ckpt'.format(folderpath, ckpt_number)
 
         # give model a chance to do something on hpc_save
-        model = self.model.module if type(self.model) is LightningDataParallel else self.model
+        model = self.__get_model()
         model.on_hpc_save()
 
         # request what to save from the model
@@ -165,7 +169,7 @@ class TrainerIO(object):
         self.restore_training_state(checkpoint)
 
         # load model state
-        model = self.model.module if type(self.model) is LightningDataParallel else self.model
+        model = self.__get_model()
         model.load_model_specific(checkpoint)
 
         # call model hook