diff --git a/paddle/trainer/Trainer.cpp b/paddle/trainer/Trainer.cpp
index 8465addaf9e03831e914be2c73901c3b1a9d537f..bd84545375117b178d4324f0ad03f5bc35ae925d 100644
--- a/paddle/trainer/Trainer.cpp
+++ b/paddle/trainer/Trainer.cpp
@@ -90,16 +90,6 @@ DEFINE_string(model_list, "", "File that saves the model list when evaluation");
 
 namespace paddle {
 
-void Trainer::init(int argc, char** argv) {
-  initMain(argc, argv);
-  initPython(argc, argv);
-
-  auto config = TrainerConfigHelper::createFromFlagConfig();
-  feenableexcept(FE_INVALID | FE_DIVBYZERO | FE_OVERFLOW);
-
-  init(config);
-}
-
 void Trainer::init(const std::shared_ptr<TrainerConfigHelper>& config,
                    bool testing,
                    const std::shared_ptr<GradientMachine>& gradientMachine,
diff --git a/paddle/trainer/Trainer.h b/paddle/trainer/Trainer.h
index 7cbf18ace7a5fed053653c73e62d36c388b15123..c8ee4726c24c335ceda22ea3a20049b01d11c149 100644
--- a/paddle/trainer/Trainer.h
+++ b/paddle/trainer/Trainer.h
@@ -71,11 +71,6 @@ public:
       const std::shared_ptr<DataProvider>& dataProvider = nullptr,
       const std::shared_ptr<DataProvider>& testDataProvider = nullptr);
 
-  /**
-   * Initialize Trainer from command line flags.
-   */
-  void init(int argc, char** argv);
-
   /**
    * Train until num_passes reached.
    * One pass means neural network train through all training data.