set dp as default backend

pytorch_lightning/models/trainer.py

@@ -311,6 +311,7 @@ class Trainer(TrainerIO):
 
         # when using multi-node or DDP within a node start each module in a separate process
         if self.use_ddp:
+            print('using ddp')
             # must copy only the meta of the exp so it survives pickle/unpickle when going to new process
             self.experiment = self.experiment.get_meta_copy()
             mp.spawn(self.ddp_train, nprocs=len(self.data_parallel_device_ids), args=(model, ))
@@ -318,6 +319,7 @@ class Trainer(TrainerIO):
         # 1 gpu or dp option triggers training using DP module
         # easier to avoid NCCL issues
         elif self.use_dp:
+            print('using dp')
             self.dp_train(model)
 
         # ON CPU