diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index f79cdb1a21..63bf187c67 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -639,7 +639,8 @@ class Trainer(TrainerIO):
         # call warnings from proc zero only which triggers dataloaders
         # if those have to download data it will only happen on proc 0
         if self.proc_rank == 0:
-            if self.use_ddp or self.use_ddp2 and not isinstance(self.get_train_dataloader().sampler, DistributedSampler):
+            on_ddp = self.use_ddp or self.use_ddp2
+            if on_ddp and not isinstance(self.get_train_dataloader().sampler, DistributedSampler):
                 msg = """
                 You're using multiple gpus and multiple nodes without using a DistributedSampler
                 to assign a subset of your data to each process. To silence this warning, pass a
@@ -658,14 +659,14 @@ class Trainer(TrainerIO):
                 """
                 warnings.warn(msg)
 
-            if self.use_ddp or self.use_ddp2 and self.get_val_dataloaders is not None:
+            if on_ddp and self.get_val_dataloaders is not None:
                 for dataloader in self.get_val_dataloaders():
                     if not isinstance(dataloader.sampler, DistributedSampler):
                         msg = """
                         Your val_dataloader(s) don't use DistributedSampler.
-                        You're using multiple gpus and multiple nodes without using a DistributedSampler
-                        to assign a subset of your data to each process. To silence this warning, pass a
-                        DistributedSampler to your DataLoader.
+                        You're using multiple gpus and multiple nodes without using a
+                        DistributedSampler to assign a subset of your data to each process.
+                        To silence this warning, pass a DistributedSampler to your DataLoader.
 
                         ie: this:
                         dataset = myDataset()
@@ -681,14 +682,14 @@ class Trainer(TrainerIO):
                         warnings.warn(msg)
                         break
 
-            if self.use_ddp or self.use_ddp2 and self.get_test_dataloaders is not None:
+            if on_ddp and self.get_test_dataloaders is not None:
                 for dataloader in self.get_test_dataloaders():
                     if not isinstance(dataloader.sampler, DistributedSampler):
                         msg = """
                         Your test_dataloader(s) don't use DistributedSampler.
-                        You're using multiple gpus and multiple nodes without using a DistributedSampler
-                        to assign a subset of your data to each process. To silence this warning, pass a
-                        DistributedSampler to your DataLoader.
+                        You're using multiple gpus and multiple nodes without using a
+                        DistributedSampler to assign a subset of your data to each process.
+                        To silence this warning, pass a DistributedSampler to your DataLoader.
 
                         ie: this:
                         dataset = myDataset()