diff --git a/paddle/py_paddle/dataprovider_converter.py b/paddle/py_paddle/dataprovider_converter.py
index 60a0f2c04448636a39b6fc550c51faf33ea93b09..57e58e077d7fbe6f8a3700047625470652117c45 100644
--- a/paddle/py_paddle/dataprovider_converter.py
+++ b/paddle/py_paddle/dataprovider_converter.py
@@ -26,7 +26,14 @@ class IScanner(object):
         if not isinstance(self.input_type, dp2.InputType):
             raise ValueError("input type should be dataprovider2.InputType")
         self.pos = pos
-        self.use_gpu = True if swig_paddle.isUsingGpu() and (
+        # data_in_gpu is used to indicate whether to create argument on GPU
+        # or not in GPU mode. Now if using one thread (trainer_count=1),
+        # trainer uses NeuralNetwork which needs to create argument on GPU
+        # before calling forward function. So, set data_in_gpu to True.
+        # Otherwise, trainer uses MultiGradientMachine which will transfer
+        # data from CPU to GPU in the forward function, set data_in_gpu to
+        # False in this case.
+        self.data_in_gpu = True if swig_paddle.isUsingGpu() and (
             swig_paddle.getTrainerCount() == 1) else False
 
     def scan(self, dat):