diff --git a/pytorch_lightning/overrides/data_parallel.py b/pytorch_lightning/overrides/data_parallel.py
index 4917010fdd4152..3945d770fe8d42 100644
--- a/pytorch_lightning/overrides/data_parallel.py
+++ b/pytorch_lightning/overrides/data_parallel.py
@@ -70,7 +70,7 @@ def forward(self, *inputs, **kwargs):
         if isinstance(outputs[0], Result):
             outputs = self.__gather_structured_result(outputs)
         else:
-            outputs = self.gather(outputs, self.output_device)
+            outputs = self.gather(outputs)
         return outputs
 
     def __gather_structured_result(self, outputs):
@@ -83,7 +83,7 @@ def __gather_structured_result(self, outputs):
         for i, output in enumerate(outputs):
             del output['meta']
 
-        outputs = self.gather(outputs, self.output_device)
+        outputs = self.gather(outputs)
 
         # pass minimize to constructor for TrainResult
         if 'minimize' in outputs:
@@ -106,16 +106,16 @@ def gather_map(outputs):
             if isinstance(elem, torch.Tensor):
                 return Gather.apply(self.output_device, self.dim, *outputs)
 
-            elif elem is None:
+            if elem is None:
                 return None
 
-            elif isinstance(elem, Mapping):
+            if isinstance(elem, Mapping):
                 if not all((len(elem) == len(d) for d in outputs)):
                     raise ValueError('All dicts must have the same number of keys')
                 return elem_type(((k, gather_map([d[k] for d in outputs]))
                                   for k in elem))
 
-            elif isinstance(elem, Iterable) and not isinstance(elem, str):
+            if isinstance(elem, Iterable) and not isinstance(elem, str):
                 return elem_type(map(gather_map, zip(*outputs)))
 
             return outputs