diff --git a/paddle/fluid/operators/reader/create_py_reader_op.cc b/paddle/fluid/operators/reader/create_py_reader_op.cc
index aac81d181354b7c54f024adc9ab50f353f1f6390..36587360f7347a10e01d4e994482027d9a9bb5d0 100644
--- a/paddle/fluid/operators/reader/create_py_reader_op.cc
+++ b/paddle/fluid/operators/reader/create_py_reader_op.cc
@@ -28,7 +28,7 @@ class PyReader : public framework::ReaderBase {
 
   void ReadNext(std::vector<framework::LoDTensor>* out) override {
     bool success;
-    *out = queue_->Dequeue(&success);
+    *out = queue_->Pop(&success);
     if (!success) out->clear();
   }
 
@@ -45,6 +45,10 @@ class CreatePyReaderOp : public framework::OperatorBase {
  private:
   void RunImpl(const framework::Scope& scope,
                const platform::Place& dev_place) const override {
+    auto* out = scope.FindVar(Output("Out"))
+                    ->template GetMutable<framework::ReaderHolder>();
+    if (out->Get() != nullptr) return;
+
     const std::string& queue_name = Input("blocking_queue");
     auto* queue_holder_var = scope.FindVar(queue_name);
     PADDLE_ENFORCE(
@@ -53,8 +57,7 @@ class CreatePyReaderOp : public framework::OperatorBase {
         queue_name);
     auto* queue_holder =
         queue_holder_var->template GetMutable<LoDTensorBlockingQueueHolder>();
-    auto* out = scope.FindVar(Output("Out"))
-                    ->template GetMutable<framework::ReaderHolder>();
+
     out->Reset(new PyReader(queue_holder->GetQueue()));
   }
 };
diff --git a/paddle/fluid/operators/reader/lod_tensor_blocking_queue.h b/paddle/fluid/operators/reader/lod_tensor_blocking_queue.h
index a2129f6af4c6714f162a94a23e3a39ec00daf61f..30d962ba10a954a837f9771d21cedf0feb643439 100644
--- a/paddle/fluid/operators/reader/lod_tensor_blocking_queue.h
+++ b/paddle/fluid/operators/reader/lod_tensor_blocking_queue.h
@@ -34,36 +34,33 @@ class LoDTensorBlockingQueue {
  private:
   LoDTensorBlockingQueue(size_t capacity,
                          const std::vector<framework::DDim>& dims)
-      : dims_(dims) {
-    queue_.reset(
-        new BlockingQueue<std::vector<framework::LoDTensor>>(capacity));
-  }
+      : queue_(capacity), dims_(dims) {}
 
  public:
-  bool Enqueue(const std::vector<framework::LoDTensor>& lod_tensor_vec) {
+  bool Push(const std::vector<framework::LoDTensor>& lod_tensor_vec) {
     CheckDims(lod_tensor_vec);
-    return queue_->Send(lod_tensor_vec);
+    return queue_.Send(lod_tensor_vec);
   }
 
-  bool Enqueue(std::vector<framework::LoDTensor>&& lod_tensor_vec) {
+  bool Push(std::vector<framework::LoDTensor>&& lod_tensor_vec) {
     CheckDims(lod_tensor_vec);
-    return queue_->Send(std::move(lod_tensor_vec));
+    return queue_.Send(std::move(lod_tensor_vec));
   }
 
-  std::vector<framework::LoDTensor> Dequeue(bool* ok = nullptr) {
+  std::vector<framework::LoDTensor> Pop(bool* ok = nullptr) {
     std::vector<framework::LoDTensor> lod_tensor_vec;
-    bool success = queue_->Receive(&lod_tensor_vec);
+    bool success = queue_.Receive(&lod_tensor_vec);
     if (ok != nullptr) *ok = success;
     return lod_tensor_vec;
   }
 
-  inline size_t Cap() const { return queue_->Cap(); }
+  inline size_t Cap() const { return queue_.Cap(); }
 
-  inline size_t Size() const { return queue_->Size(); }
+  inline size_t Size() const { return queue_.Size(); }
 
-  inline void Close() { return queue_->Close(); }
+  inline void Close() { return queue_.Close(); }
 
-  inline bool IsClosed() const { return queue_->IsClosed(); }
+  inline bool IsClosed() const { return queue_.IsClosed(); }
 
  private:
   void CheckDims(const std::vector<framework::LoDTensor>& lod_tensor_vec) {
@@ -71,15 +68,16 @@ class LoDTensorBlockingQueue {
                    "Expect input size is %d but found %s", dims_.size(),
                    lod_tensor_vec.size());
     for (size_t i = 0; i < dims_.size(); ++i) {
-      const auto& in_dims = lod_tensor_vec[i].dims();
+      const auto& in_dims = framework::slice_ddim(
+          lod_tensor_vec[i].dims(), 1, lod_tensor_vec[i].dims().size());
       const auto& expect_dims =
           framework::slice_ddim(dims_[i], 1, dims_[i].size());
       PADDLE_ENFORCE(in_dims == expect_dims,
-                     "Dims of the %d-th input tensor does not match", i);
+                     "Dims of the %d-th input tensor do not match", i);
     }
   }
 
-  std::unique_ptr<BlockingQueue<std::vector<framework::LoDTensor>>> queue_;
+  BlockingQueue<std::vector<framework::LoDTensor>> queue_;
   std::vector<framework::DDim> dims_;
 };
 
@@ -92,8 +90,6 @@ class LoDTensorBlockingQueueHolder {
     queue_.reset(new LoDTensorBlockingQueue(capacity, dims));
   }
 
-  inline std::shared_ptr<LoDTensorBlockingQueue> GetQueue() { return queue_; }
-
   inline const std::shared_ptr<LoDTensorBlockingQueue>& GetQueue() const {
     return queue_;
   }
diff --git a/paddle/fluid/pybind/pybind.cc b/paddle/fluid/pybind/pybind.cc
index 6963a0c101603884df26585c51b45d7fb779cc89..36d080996831d4ad90d92baeafbe964693e2332a 100644
--- a/paddle/fluid/pybind/pybind.cc
+++ b/paddle/fluid/pybind/pybind.cc
@@ -303,19 +303,16 @@ All parameter, weight, gradient are variables in Paddle.
   using LoDTensorBlockingQueueHolder =
       ::paddle::operators::reader::LoDTensorBlockingQueueHolder;
   py::class_<LoDTensorBlockingQueue>(m, "LoDTensorBlockingQueue", "")
-      .def("enqueue",
+      .def("push",
            [](LoDTensorBlockingQueue &self,
               const std::vector<framework::LoDTensor> &lod_tensor_vec) {
              pybind11::gil_scoped_release release;
-             return self.Enqueue(lod_tensor_vec);
+             return self.Push(lod_tensor_vec);
            })
-      .def("size",
-           [](const LoDTensorBlockingQueue &self) { return self.Size(); })
-      .def("capacity",
-           [](const LoDTensorBlockingQueue &self) { return self.Cap(); })
-      .def("close", [](LoDTensorBlockingQueue &self) { return self.Close(); })
-      .def("is_closed",
-           [](const LoDTensorBlockingQueue &self) { return self.IsClosed(); });
+      .def("size", &LoDTensorBlockingQueue::Size)
+      .def("capacity", &LoDTensorBlockingQueue::Cap)
+      .def("close", &LoDTensorBlockingQueue::Close)
+      .def("is_closed", &LoDTensorBlockingQueue::IsClosed);
 
   m.def("init_lod_tensor_blocking_queue",
         [](Variable &var, size_t capacity,