support RemoteSparseUpdater

paddle/api/PaddleAPI.h

@@ -21,6 +21,7 @@ limitations under the License. */
 #include <vector>
 #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
@@ -468,9 +469,9 @@ private:
 };
 
 enum GradientMatchineCreateMode {
-  CREATE_MODE_NORMAL = 0,
-  CREATE_MODE_SGD_SPARSE_CPU_TRAINING = 3,
-  CREATE_MODE_TESTING = 4
+  CREATE_MODE_NORMAL = paddle::GradientMachine::kNormal,
+  CREATE_MODE_SGD_SPARSE_CPU_TRAINING = paddle::GradientMachine::kSgdSparseCpuTraining,
+  CREATE_MODE_TESTING = paddle::GradientMachine::kTesting
 };
 
 struct ParameterConfigPrivate;
@@ -818,7 +819,7 @@ private:
 public:
   static ParameterUpdater* createLocalUpdater(OptimizationConfig* config);
   static ParameterUpdater* createRemoteUpdater(OptimizationConfig* config,
-                                               int passCount);
+                                               int passCount, bool userSparseUpdater);
   ~ParameterUpdater();
 
   /**

paddle/api/ParameterUpdater.cpp

@@ -29,10 +29,19 @@ ParameterUpdater *ParameterUpdater::createLocalUpdater(
 }
 
 ParameterUpdater *ParameterUpdater::createRemoteUpdater(
-    OptimizationConfig *config, int passCount) {
+    OptimizationConfig *config, int passCount, bool userSparseUpdater) {
   auto updater = new ParameterUpdater();
-  updater->m->updater.reset(new paddle::RemoteParameterUpdater(
-      config->m->getConfig(), passCount, nullptr));
+  auto remoteUpdater = new paddle::RemoteParameterUpdater(
+          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));
+    updater->m->updater.reset(sparseRemoteUpdater);
+  } else {
+    updater->m->updater.reset(remoteUpdater);
+  }
   return updater;
 }
 

python/paddle/v2/optimizer.py

@@ -41,9 +41,9 @@ class Optimizer(object):
     def create_local_updater(self):
         return swig_api.ParameterUpdater.createLocalUpdater(self.__opt_conf__)
 
-    def create_remote_updater(self, pass_num):
+    def create_remote_updater(self, pass_num, use_sparse_updater):
         return swig_api.ParameterUpdater.createRemoteUpdater(self.__opt_conf__,
-                                                             pass_num)
+                                                             pass_num, use_sparse_updater)
 
 
 class Momentum(Optimizer):

python/paddle/v2/trainer.py

@@ -97,7 +97,8 @@ class SGD(object):
         if self.__is_local__:
             updater = self.__optimizer__.create_local_updater()
         else:
-            updater = self.__optimizer__.create_remote_updater(num_passes)
+            updater = self.__optimizer__.create_remote_updater(num_passes,
+                                                               self.__use_sparse_updater__)
         updater.init(self.__gradient_machine__)
 
         self.__gradient_machine__.start()