docs

pytorch_lightning/models/trainer.py

@@ -87,7 +87,6 @@ class Trainer(TrainerIO):
         # if gpus = -1 then use all available devices
         # otherwise, split the string using commas
         if gpus is not None:
-
             if gpus == '-1':
                 self.data_parallel_device_ids = list(range(0, torch.cuda.device_count()))
             else:
@@ -123,7 +122,7 @@ class Trainer(TrainerIO):
         self.__determine_data_use_amount(train_percent_check, val_percent_check, test_percent_check, overfit_pct)
         print('gpu available: {}, used: {}'.format(torch.cuda.is_available(), self.on_gpu))
 
-        # apex test
+        # 16 bit mixed precision training using apex
         self.use_amp = use_amp and APEX_AVAILABLE
         if self.use_amp:
             print('using 16bit precision')
@@ -169,7 +168,7 @@ class Trainer(TrainerIO):
 
         return tqdm_dic
 
-    def __layout_bookeeping(self, model):
+    def __layout_bookeeping(self):
         # training bookeeping
         self.total_batch_nb = 0
         self.running_loss = []
@@ -410,7 +409,7 @@ class Trainer(TrainerIO):
         self.__get_dataloaders(ref_model)
 
         # init training constants
-        self.__layout_bookeeping(ref_model)
+        self.__layout_bookeeping()
 
         # add lr schedulers
         if self.lr_scheduler_milestones is not None: