diff --git a/paddle/trainer/NewRemoteParameterUpdater.cpp b/paddle/trainer/NewRemoteParameterUpdater.cpp
index 7d5216a9669195eeed442828b9be5d379d069c3e..7efd1dec6adb9bbd03e72bdb524cec2399028204 100644
--- a/paddle/trainer/NewRemoteParameterUpdater.cpp
+++ b/paddle/trainer/NewRemoteParameterUpdater.cpp
@@ -110,43 +110,10 @@ void NewRemoteParameterUpdater::init(
 
     // overwrite optimizerConfigV2 for per-parameter(layer) configs
     for (int i = 0; i < parameterSize(); ++i) {
-      auto paramConfig = parameters_[i]->getConfig();
-      if (paramConfig.has_momentum() &&
-          trainerConfig_.learning_method() == "momentum") {
-        optimizerConfigV2.mutable_sgd()->set_momentum(paramConfig.momentum());
-      }
-      if (paramConfig.has_learning_rate()) {
-        switch (optimizerConfigV2.lr_policy()) {
-          case 0:
-            optimizerConfigV2.mutable_const_lr()->set_learning_rate(
-                paramConfig.learning_rate());
-            break;
-          case 1:
-            optimizerConfigV2.mutable_linear_lr()->set_learning_rate(
-                paramConfig.learning_rate());
-            break;
-        }
-      }
-      if (paramConfig.has_decay_rate()) {
-        switch (optimizerConfigV2.optimizer()) {
-          case 1:  // SGD
-            optimizerConfigV2.mutable_sgd()->set_decay(
-                paramConfig.decay_rate());
-            break;
-          case 2:  // Adadelta
-            optimizerConfigV2.mutable_adadelta()->set_decay(
-                paramConfig.decay_rate());
-            break;
-          case 3:  // Adagrad
-            optimizerConfigV2.mutable_adagrad()->set_decay(
-                paramConfig.decay_rate());
-            break;
-          case 4:  // Adam
-            optimizerConfigV2.mutable_adam()->set_decay(
-                paramConfig.decay_rate());
-            break;
-        }
-      }
+      // FIXME(typhoonzero): paramConfig always have default values,
+      // how to check if it's default?
+      // TODO: log output: optimizerConfigV2.DebugString();
+      LOG(INFO) << "trainerConfig_: " << trainerConfig_.DebugString();
       // send param and config to pserver
       std::string bytes = optimizerConfigV2.SerializeAsString();
       const char *array = bytes.data();