diff --git a/pytorch_lightning/models/trainer.py b/pytorch_lightning/models/trainer.py
index 84695d2012..dc01f59cd1 100644
--- a/pytorch_lightning/models/trainer.py
+++ b/pytorch_lightning/models/trainer.py
@@ -495,27 +495,28 @@ If you want each process to load the full dataset, ignore this warning.
 """
             warnings.warn(msg)
 
-        if self.use_ddp and\
-                not all(isinstance(dataloader, DistributedSampler)
-                        for dataloader in self.val_dataloader):
-            msg = """
-You're val_dataloader(s) are not all DistributedSamplers.
-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.
+        if self.use_ddp and self.val_dataloader is not None:
+            for dataloader in self.val_dataloader:
+                if not isinstance(dataloader, DistributedSampler):
+                    msg = """
+                    Your val_dataloader(s) are not all DistributedSamplers.
+                    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()
-dataloader = Dataloader(dataset)
+                    ie: this:
+                    dataset = myDataset()
+                    dataloader = Dataloader(dataset)
 
-becomes:
-dataset = myDataset()
-dist_sampler = torch.utils.data.distributed.DistributedSampler(dataset)
-dataloader = Dataloader(dataset, sampler=dist_sampler)
+                    becomes:
+                    dataset = myDataset()
+                    dist_sampler = torch.utils.data.distributed.DistributedSampler(dataset)
+                    dataloader = Dataloader(dataset, sampler=dist_sampler)
 
-If you want each process to load the full dataset, ignore this warning.
-"""
-            warnings.warn(msg)
+                    If you want each process to load the full dataset, ignore this warning.
+                    """
+                    warnings.warn(msg)
+                    break
 
     # -----------------------------
     # MODEL TRAINING