Don't convert namedtuple to tuple (#1589)

* Don't convert namedtuple to tuple

* Test namedtuples sent to device correctly

pytorch_lightning/trainer/distrib_parts.py

@@ -461,10 +461,15 @@ class TrainerDPMixin(ABC):
 
         # when tuple
         if isinstance(batch, tuple):
-            batch = list(batch)
-            for i, x in enumerate(batch):
-                batch[i] = self.__transfer_data_to_device(x, device, gpu_id)
-            return tuple(batch)
+            # when namedtuple
+            if hasattr(batch, '_fields'):
+                elem_type = type(batch)
+                return elem_type(*(self.__transfer_data_to_device(x, device, gpu_id) for x in batch))
+            else:
+                batch = list(batch)
+                for i, x in enumerate(batch):
+                    batch[i] = self.__transfer_data_to_device(x, device, gpu_id)
+                return tuple(batch)
 
         # when dict
         if isinstance(batch, dict):

tests/models/test_cpu.py

@@ -1,3 +1,4 @@
+from collections import namedtuple
 import platform
 
 import pytest
@@ -221,6 +222,13 @@ def test_single_gpu_batch_parse():
     assert batch[1][0]['b'].device.index == 0
     assert batch[1][0]['b'].type() == 'torch.cuda.FloatTensor'
 
+    # namedtuple of tensor
+    BatchType = namedtuple('BatchType', ['a', 'b'])
+    batch = [BatchType(a=torch.rand(2, 3), b=torch.rand(2, 3)) for _ in range(2)]
+    batch = trainer.transfer_batch_to_gpu(batch, 0)
+    assert batch[0].a.device.index == 0
+    assert batch[0].a.type() == 'torch.cuda.FloatTensor'
+
 
 def test_simple_cpu(tmpdir):
     """Verify continue training session on CPU."""