From 566e5f1fcbe77e2e2f931e977064fcb878d4908b Mon Sep 17 00:00:00 2001 From: dangqingqing Date: Wed, 1 Mar 2017 13:25:51 +0800 Subject: [PATCH] rename use_gpu to data_in_gpu --- paddle/py_paddle/dataprovider_converter.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/paddle/py_paddle/dataprovider_converter.py b/paddle/py_paddle/dataprovider_converter.py index 57e58e077d..c009b05cde 100644 --- a/paddle/py_paddle/dataprovider_converter.py +++ b/paddle/py_paddle/dataprovider_converter.py @@ -33,8 +33,8 @@ class IScanner(object): # 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 + self.data_in_gpu = swig_paddle.isUsingGpu( + ) and swig_paddle.getTrainerCount() == 1 def scan(self, dat): pass @@ -63,7 +63,7 @@ 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.data_in_gpu) argument.setSlotValue(self.pos, m) @@ -115,7 +115,7 @@ 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.data_in_gpu) assert isinstance(argument, swig_paddle.Arguments) argument.setSlotIds(self.pos, ids) -- GitLab