diff --git a/paddle/framework/executor_test.cc b/paddle/framework/executor_test.cc
index 259205f7c1ddaeca0b1537956966a9ef5b83c44b..0710eb577979ba436c60757d0c9a46617a1e3b58 100644
--- a/paddle/framework/executor_test.cc
+++ b/paddle/framework/executor_test.cc
@@ -116,12 +116,8 @@ class ExecutorTesterRandom : public ::testing::Test {
           {{"dims", std::vector<int>{input_dim, embed_dim}}}, init_root_block);
     AddOp("gaussian_random", {}, {{"Out", {"w2"}}},
           {{"dims", std::vector<int>{embed_dim, input_dim}}}, init_root_block);
-    AddOp("fetch", {{"Input", {"w1"}}}, {},
-          {{"dims", std::vector<int>{input_dim, embed_dim}}, {"col", 0}},
-          init_root_block);
-    AddOp("fetch", {{"Input", {"w2"}}}, {},
-          {{"dims", std::vector<int>{embed_dim, input_dim}}, {"col", 1}},
-          init_root_block);
+    AddOp("fetch", {{"Input", {"w1"}}}, {}, {{"col", 0}}, init_root_block);
+    AddOp("fetch", {{"Input", {"w2"}}}, {}, {{"col", 1}}, init_root_block);
 
     // flush
     init_program.Proto();
@@ -163,12 +159,8 @@ class ExecutorTesterRandom : public ::testing::Test {
                   {"Grad", {"w2@GRAD"}}},
           {{"ParamOut", {"w2"}}}, {}, root_block);
 
-    AddOp("fetch", {{"Input", {"w1"}}}, {},
-          {{"dims", std::vector<int>{input_dim, embed_dim}}, {"col", 0}},
-          root_block);
-    AddOp("fetch", {{"Input", {"w2"}}}, {},
-          {{"dims", std::vector<int>{embed_dim, input_dim}}, {"col", 1}},
-          root_block);
+    AddOp("fetch", {{"Input", {"w1"}}}, {}, {{"col", 0}}, root_block);
+    AddOp("fetch", {{"Input", {"w2"}}}, {}, {{"col", 1}}, root_block);
 
     // flush
     program.Proto();
@@ -197,10 +189,8 @@ class ExecutorTesterFeedAndFetch : public ::testing::Test {
           root_block);
     AddOp("feed", {}, {{"Out", {"b"}}}, {{"dims", dim}, {"col", 1}},
           root_block);
-    AddOp("fetch", {{"Input", {"a"}}}, {}, {{"dims", dim}, {"col", 0}},
-          root_block);
-    AddOp("fetch", {{"Input", {"b"}}}, {}, {{"dims", dim}, {"col", 1}},
-          root_block);
+    AddOp("fetch", {{"Input", {"a"}}}, {}, {{"col", 0}}, root_block);
+    AddOp("fetch", {{"Input", {"b"}}}, {}, {{"col", 1}}, root_block);
 
     // flush
     program.Proto();
diff --git a/paddle/operators/feed_op.cc b/paddle/operators/feed_op.cc
index 1d65c2bb4693c8c4a131c073637bc7f5b860ab64..fa325bb28299afe24a67772473529fb76b9c73e1 100644
--- a/paddle/operators/feed_op.cc
+++ b/paddle/operators/feed_op.cc
@@ -24,15 +24,6 @@ class FeedOp : public framework::OperatorWithKernel {
  protected:
   void InferShape(framework::InferShapeContext* ctx) const override {
     PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output should be not null.");
-    int col = ctx->Attrs().Get<int>("col");
-    framework::Variable* g_feed_variable =
-        framework::GetGlobalScope()->FindVar("feed_value");
-
-    const auto& tensors =
-        g_feed_variable->Get<std::vector<framework::Tensor>>();
-
-    PADDLE_ENFORCE_GT(tensors.size(), static_cast<size_t>(col));
-
     auto& shape = ctx->Attrs().Get<std::vector<int>>("dims");
     std::vector<int64_t> shape_int64(shape.size(), 0);
     std::transform(shape.begin(), shape.end(), shape_int64.begin(),
@@ -43,7 +34,7 @@ class FeedOp : public framework::OperatorWithKernel {
 
   framework::DataType IndicateDataType(
       const framework::ExecutionContext& ctx) const override {
-    return static_cast<framework::DataType>(Attr<int>("data_type"));
+    return static_cast<framework::DataType>(Attr<int>("dataType"));
   }
 };
 
@@ -51,7 +42,7 @@ class FeedOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
   FeedOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
-    AddAttr<int>("data_type", "output data type")
+    AddAttr<int>("dataType", "output data type")
         .SetDefault(framework::DataType::FP32);
     AddAttr<int>("col", "The col in global feed variable").SetDefault(0);
     AddAttr<std::vector<int>>("dims", "The dimension of feed tensor.");
diff --git a/paddle/operators/feed_op.h b/paddle/operators/feed_op.h
index 96e3bf52bd12faaa5a3fef125499e17afbb89741..47344e309ce381e25a51b7162d8b5e28ccec09cf 100644
--- a/paddle/operators/feed_op.h
+++ b/paddle/operators/feed_op.h
@@ -27,9 +27,10 @@ class FeedKernel : public framework::OpKernel<T> {
     out->mutable_data<T>(ctx.GetPlace());
     framework::Variable* g_feed_variable =
         framework::GetGlobalScope()->FindVar("feed_value");
-    int col = ctx.template Attr<int>("col");
     const auto& tensors =
         g_feed_variable->Get<std::vector<framework::Tensor>>();
+    int col = ctx.template Attr<int>("col");
+    PADDLE_ENFORCE_GT(tensors.size(), static_cast<size_t>(col));
     out->CopyFrom<T>(tensors[col], ctx.GetPlace());
   }
 };
diff --git a/paddle/operators/fetch_op.cc b/paddle/operators/fetch_op.cc
index 77e3450a73fb43997aa36967977b66b942f82bcd..90737c8c550ca18f03c6a9ad0d9323d0b4d0b96d 100644
--- a/paddle/operators/fetch_op.cc
+++ b/paddle/operators/fetch_op.cc
@@ -24,26 +24,11 @@ class FetchOp : public framework::OperatorWithKernel {
  protected:
   void InferShape(framework::InferShapeContext* ctx) const override {
     PADDLE_ENFORCE(ctx->HasInput("Input"), "Input should be not null.");
-    int col = ctx->Attrs().Get<int>("col");
-    framework::Variable* g_fetch_variable =
-        framework::GetGlobalScope()->FindVar("fetch_value");
-
-    auto* tensors =
-        g_fetch_variable->GetMutable<std::vector<framework::Tensor>>();
-    if (tensors->size() < static_cast<size_t>(col + 1)) {
-      tensors->resize(col + 1);
-    }
-
-    auto input_dim = ctx->GetInputDim("Input");
-    PADDLE_ENFORCE_GT(tensors->size(), col);
-    (*tensors)[col].Resize(input_dim);
-
-    // TODO(qijun): need to handle LodTensor later
   }
 
   framework::DataType IndicateDataType(
       const framework::ExecutionContext& ctx) const override {
-    return static_cast<framework::DataType>(Attr<int>("data_type"));
+    return static_cast<framework::DataType>(Attr<int>("dataType"));
   }
 };
 
@@ -51,10 +36,9 @@ class FetchOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
   FetchOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
-    AddAttr<int>("data_type", "output data type")
+    AddAttr<int>("dataType", "output data type")
         .SetDefault(framework::DataType::FP32);
     AddAttr<int>("col", "The col in global fetch variable").SetDefault(0);
-    AddAttr<std::vector<int>>("dims", "The dimension of fetch tensor.");
     AddInput("Input", "The output of fetch op.");
     AddComment(R"DOC(Fetch data to global fetch variable)DOC");
   }
diff --git a/paddle/operators/fetch_op.h b/paddle/operators/fetch_op.h
index fd98552055f95bc21f47a4808735a6fb4ecced3d..6fee8b05892687d06eb1d3f7c92f0df92a8a63e6 100644
--- a/paddle/operators/fetch_op.h
+++ b/paddle/operators/fetch_op.h
@@ -24,13 +24,19 @@ class FetchKernel : public framework::OpKernel<T> {
  public:
   void Compute(const framework::ExecutionContext& ctx) const override {
     const framework::Tensor* input = ctx.Input<framework::Tensor>("Input");
-    int col = ctx.template Attr<int>("col");
     framework::Variable* g_fetch_variable =
         framework::GetGlobalScope()->FindVar("fetch_value");
     auto* tensors =
         g_fetch_variable->GetMutable<std::vector<framework::Tensor>>();
+    int col = ctx.template Attr<int>("col");
+    if (tensors->size() < static_cast<size_t>(col + 1)) {
+      tensors->resize(col + 1);
+    }
+    PADDLE_ENFORCE_GT(tensors->size(), static_cast<size_t>(col));
+    (*tensors)[col].Resize(input->dims());
     (*tensors)[col].mutable_data<T>(platform::CPUPlace());
     (*tensors)[col].CopyFrom<T>(*input, platform::CPUPlace());
+    // TODO(qijun): need to handle LodTensor later
   }
 };