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paddle/api/PaddleAPI.h

@@ -47,7 +47,7 @@ void setUseGpu(bool useGpu);
 /// Return true if this py_paddle is compiled in GPU Version
 bool isGpuVersion();
 
-/// Return FLAGS_use_gpu
+/// Return FLAGS_trainer_count
 int getTrainerCount();
 
 /// The Error of IO Operation. Such as file not found, etc.

paddle/py_paddle/dataprovider_converter.py

@@ -26,6 +26,8 @@ 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 (
+            swig_paddle.getTrainerCount() == 1) else False
 
     def scan(self, dat):
         pass
@@ -33,11 +35,6 @@ class IScanner(object):
     def finish_scan(self, argument):
         pass
 
-    def use_gpu(self):
-        gpu = True if swig_paddle.isUsingGpu() and (
-            swig_paddle.getTrainerCount() == 1) else False
-        return gpu
-
 
 class DenseScanner(IScanner):
     """
@@ -59,7 +56,7 @@ class DenseScanner(IScanner):
         if self.__mat__.dtype != numpy.float32:
             self.__mat__ = self.__mat__.astype(numpy.float32)
         m = swig_paddle.Matrix.createDenseFromNumpy(self.__mat__, True,
-                                                    self.use_gpu())
+                                                    self.use_gpu)
         argument.setSlotValue(self.pos, m)
 
 
@@ -111,7 +108,7 @@ class IndexScanner(IScanner):
         self.__ids__.append(dat)
 
     def finish_scan(self, argument):
-        ids = swig_paddle.IVector.create(self.__ids__, self.use_gpu())
+        ids = swig_paddle.IVector.create(self.__ids__, self.use_gpu)
         assert isinstance(argument, swig_paddle.Arguments)
         argument.setSlotIds(self.pos, ids)
 

python/paddle/v2/tests/test_data_feeder.py

@@ -240,4 +240,3 @@ if __name__ == '__main__':
     if api.isGpuVersion():
         api.setUseGpu(True)
         unittest.main()
-    unittest.main()