fix style probelm

paddle/api/PaddleAPI.h

@@ -19,9 +19,9 @@ limitations under the License. */
 #include <stdexcept>
 #include <string>
 #include <vector>
+#include "paddle/gserver/gradientmachines/GradientMachine.h"
 #include "paddle/utils/Common.h"
 #include "paddle/utils/GlobalConstants.h"
-#include "paddle/gserver/gradientmachines/GradientMachine.h"
 
 /// Import PaddlePaddle's enumeration into global namespace.
 using namespace paddle::enumeration_wrapper;  // NOLINT
@@ -470,7 +470,8 @@ private:
 
 enum GradientMatchineCreateMode {
   CREATE_MODE_NORMAL = paddle::GradientMachine::kNormal,
-  CREATE_MODE_SGD_SPARSE_CPU_TRAINING = paddle::GradientMachine::kSgdSparseCpuTraining,
+  CREATE_MODE_SGD_SPARSE_CPU_TRAINING =
+      paddle::GradientMachine::kSgdSparseCpuTraining,
   CREATE_MODE_TESTING = paddle::GradientMachine::kTesting
 };
 
@@ -819,7 +820,8 @@ private:
 public:
   static ParameterUpdater* createLocalUpdater(OptimizationConfig* config);
   static ParameterUpdater* createRemoteUpdater(OptimizationConfig* config,
-                                               int passCount, bool userSparseUpdater);
+                                               int passCount,
+                                               bool userSparseUpdater);
   ~ParameterUpdater();
 
   /**

paddle/api/ParameterUpdater.cpp

@@ -32,12 +32,16 @@ ParameterUpdater *ParameterUpdater::createRemoteUpdater(
     OptimizationConfig *config, int passCount, bool userSparseUpdater) {
   auto updater = new ParameterUpdater();
   auto remoteUpdater = new paddle::RemoteParameterUpdater(
-          config->m->getConfig(), passCount, nullptr);
+      config->m->getConfig(), passCount, nullptr);
   if (userSparseUpdater) {
     std::unique_ptr<paddle::ParameterUpdater> remoteUpdaterPtr;
     remoteUpdaterPtr.reset(remoteUpdater);
-    auto sparseRemoteUpdater = new paddle::SparseRemoteParameterUpdaterComposite(
-            config->m->getConfig(), passCount, false, std::move(remoteUpdaterPtr));
+    auto sparseRemoteUpdater =
+        new paddle::SparseRemoteParameterUpdaterComposite(
+            config->m->getConfig(),
+            passCount,
+            false,
+            std::move(remoteUpdaterPtr));
     updater->m->updater.reset(sparseRemoteUpdater);
   } else {
     updater->m->updater.reset(remoteUpdater);

paddle/function/BufferArgTest.cpp

@@ -12,8 +12,8 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
 
-#include "BufferArg.h"
 #include <gtest/gtest.h>
+#include "BufferArg.h"
 #include "paddle/math/MemoryHandle.h"
 
 namespace paddle {

paddle/function/FunctionTest.cpp

@@ -12,8 +12,8 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
 
-#include "Function.h"
 #include <gtest/gtest.h>
+#include "Function.h"
 #include "paddle/math/SparseMatrix.h"
 
 namespace paddle {

paddle/function/TensorShapeTest.cpp

@@ -12,8 +12,8 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
 
-#include "TensorShape.h"
 #include <gtest/gtest.h>
+#include "TensorShape.h"
 
 namespace paddle {
 

paddle/function/TensorTypeTest.cpp

@@ -12,8 +12,8 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
 
-#include "TensorType.h"
 #include <gtest/gtest.h>
+#include "TensorType.h"
 
 namespace paddle {
 

python/paddle/v2/optimizer.py

@@ -42,8 +42,8 @@ class Optimizer(object):
         return swig_api.ParameterUpdater.createLocalUpdater(self.__opt_conf__)
 
     def create_remote_updater(self, pass_num, use_sparse_updater):
-        return swig_api.ParameterUpdater.createRemoteUpdater(self.__opt_conf__,
-                                                             pass_num, use_sparse_updater)
+        return swig_api.ParameterUpdater.createRemoteUpdater(
+            self.__opt_conf__, pass_num, use_sparse_updater)
 
 
 class Momentum(Optimizer):

python/paddle/v2/trainer.py

@@ -42,7 +42,12 @@ class SGD(object):
     :type extra_layers: paddle.v2.config_base.Layer
     """
 
-    def __init__(self, cost, parameters, update_equation, extra_layers=None, is_local=True):
+    def __init__(self,
+                 cost,
+                 parameters,
+                 update_equation,
+                 extra_layers=None,
+                 is_local=True):
 
         if not isinstance(parameters, v2_parameters.Parameters):
             raise TypeError('parameters should be parameters')
@@ -97,8 +102,8 @@ class SGD(object):
         if self.__is_local__:
             updater = self.__optimizer__.create_local_updater()
         else:
-            updater = self.__optimizer__.create_remote_updater(num_passes,
-                                                               self.__use_sparse_updater__)
+            updater = self.__optimizer__.create_remote_updater(
+                num_passes, self.__use_sparse_updater__)
         updater.init(self.__gradient_machine__)
 
         self.__gradient_machine__.start()