diff --git a/paddle/framework/executor.cc b/paddle/framework/executor.cc
index f4cc37cfa68d38bf648c1c38ec79d39a5f4486da..def1d1fd06a740dec6d16411fdb203e97f68fe25 100644
--- a/paddle/framework/executor.cc
+++ b/paddle/framework/executor.cc
@@ -72,7 +72,7 @@ void Executor::Run(const ProgramDesc& pdesc, Scope* scope, int block_id) {
   Scope& local_scope = scope->NewScope();
 
   std::vector<bool> should_run = Prune(pdesc, block_id);
-  PADDLE_ENFORCE_EQ(should_run.size(), block.ops_size());
+  PADDLE_ENFORCE_EQ(should_run.size(), static_cast<size_t>(block.ops_size()));
   for (size_t i = 0; i < should_run.size(); ++i) {
     if (should_run[i]) {
       for (auto& var : block.ops(i).outputs()) {
@@ -82,17 +82,7 @@ void Executor::Run(const ProgramDesc& pdesc, Scope* scope, int block_id) {
           }
         }
       }
-      LOG(INFO) << block.ops(i).type();
-      if (block.ops(i).type() == "sum") {
-        LOG(INFO) << "Here";
-        for (auto& var : block.ops(i).inputs()) {
-          for (auto& argu : var.arguments()) {
-            LOG(INFO) << var.parameter() << " " << argu;
-          }
-        }
-      }
       auto op = paddle::framework::OpRegistry::CreateOp(block.ops(i));
-      LOG(INFO) << op->DebugString();
       op->Run(local_scope, *device);
     }
   }
@@ -152,10 +142,8 @@ std::vector<bool> Executor::Prune(const ProgramDesc& pdesc, int block_id) {
         }
       }
 
-      LOG(INFO) << "1 " << op_desc.type();
       should_run.push_back(true);
     } else {
-      LOG(INFO) << "0 " << op_desc.type();
       should_run.push_back(false);
     }
   }
diff --git a/paddle/framework/executor_test.cc b/paddle/framework/executor_test.cc
index ce8b599e0e53c28f1a4b75fa359043e2fd8f09d1..5ad5b98e7b20ecead226cb7c533ed117fb22d61b 100644
--- a/paddle/framework/executor_test.cc
+++ b/paddle/framework/executor_test.cc
@@ -131,15 +131,13 @@ class ExecutorTesterRandom : public ::testing::Test {
     paddle::framework::BlockDescBind* root_block = program.Block(0);
 
     // feed data
-    inputs_.push_back({1.0, 2.0, 3.0, 4.0, 5.0, 6.0});
+    inputs_.push_back({1.0, 1.0, 1.0, 1.0, 1.0, 1.0});
     dims_.push_back({batch_size, input_dim});
     AddOp("feed", {}, {{"Out", {"a"}}},
           {{"dims", std::vector<int>{batch_size, input_dim}}, {"col", 0}},
           root_block);
 
     // forward
-    // AddOp("gaussian_random", {}, {{"Out", {"a"}}},
-    //       {{"dims", std::vector<int>{batch_size, input_dim}}}, root_block);
     AddOp("mul", {{"X", {"a"}}, {"Y", {"w1"}}}, {{"Out", {"b"}}}, {},
           root_block);
     AddOp("mul", {{"X", {"b"}}, {"Y", {"w2"}}}, {{"Out", {"a_out"}}}, {},
@@ -156,7 +154,8 @@ class ExecutorTesterRandom : public ::testing::Test {
 
     // update
     AddOp("fill_constant", {}, {{"Out", {"learning_rate"}}},
-          {{"shape", std::vector<int>{1}}, {"value", float(1.0)}}, root_block);
+          {{"shape", std::vector<int>{1}}, {"value", float(0.001)}},
+          root_block);
     AddOp("sgd", {{"Param", {"w1"}},
                   {"LearningRate", {"learning_rate"}},
                   {"Grad", {"w1@GRAD"}}},
@@ -285,7 +284,6 @@ TEST_F(ExecutorTesterRandom, GPU) {
   for (int batch_id = 0; batch_id < 3; batch_id++) {
     SetFeedVariable<float>(inputs_, dims_);
     executor->Run(pdesc_, GetGlobalScope(), 0);
-    std::vector<std::vector<float>> result = GetFetchVariable<float>();
   }
 }