diff --git a/paddle/fluid/operators/reader/py_array_feed_queue.h b/paddle/fluid/operators/reader/py_array_feed_queue.h
deleted file mode 100644
index f9552f73a66e4d75b9ae60c23efe5d4cb93fa62b..0000000000000000000000000000000000000000
--- a/paddle/fluid/operators/reader/py_array_feed_queue.h
+++ /dev/null
@@ -1,207 +0,0 @@
-// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-#pragma once
-
-#include <algorithm>
-#include <condition_variable>  //NOLINT
-#include <memory>
-#include <mutex>  // NOLINT
-#include <vector>
-#include "glog/logging.h"
-#include "paddle/fluid/framework/lod_tensor.h"
-#include "paddle/fluid/operators/reader/py_blocking_queue.h"
-#include "paddle/fluid/operators/reader/reader_op_registry.h"
-#include "paddle/fluid/pybind/tensor_py.h"
-
-namespace paddle {
-namespace operators {
-namespace reader {
-
-using PyTuple = ::pybind11::tuple;
-using PyArray = ::pybind11::array;
-
-template <typename T>
-using PyArrayT = ::pybind11::array_t<T, ::pybind11::array::c_style |
-                                            ::pybind11::array::forcecast>;
-
-class PyArrayToTensorVisitor : public boost::static_visitor<void> {
- public:
-#define PY_ARRAY_TO_TENSOR_WITH_TYPE(dtype, func_name)                       \
-  pybind::func_name(tensor_, static_cast<const PyArrayT<dtype>&>(py_array_), \
-                    place)
-
-#define PY_ARRAY_TO_TENSOR(func_name)                  \
-  if (IsType<size_t>()) {                              \
-    PY_ARRAY_TO_TENSOR_WITH_TYPE(size_t, func_name);   \
-  } else if (IsType<int64_t>()) {                      \
-    PY_ARRAY_TO_TENSOR_WITH_TYPE(int64_t, func_name);  \
-  } else if (IsType<int32_t>()) {                      \
-    PY_ARRAY_TO_TENSOR_WITH_TYPE(int32_t, func_name);  \
-  } else if (IsType<int16_t>()) {                      \
-    PY_ARRAY_TO_TENSOR_WITH_TYPE(int16_t, func_name);  \
-  } else if (IsType<uint8_t>()) {                      \
-    PY_ARRAY_TO_TENSOR_WITH_TYPE(uint8_t, func_name);  \
-  } else if (IsType<float>()) {                        \
-    PY_ARRAY_TO_TENSOR_WITH_TYPE(float, func_name);    \
-  } else if (IsType<double>()) {                       \
-    PY_ARRAY_TO_TENSOR_WITH_TYPE(double, func_name);   \
-  } else {                                             \
-    PADDLE_THROW("unsupported dtype of python array"); \
-  }
-
-  PyArrayToTensorVisitor(const PyArray& py_array, framework::Tensor* tensor)
-      : py_array_(py_array), tensor_(tensor) {}
-
-  void operator()(const platform::CPUPlace& place) {
-    PY_ARRAY_TO_TENSOR(PyCPUTensorSetFromArray);
-  }
-
-  void operator()(const platform::CUDAPlace& place) {
-#ifdef PADDLE_WITH_CUDA
-    PY_ARRAY_TO_TENSOR(PyCUDATensorSetFromArray);
-#else
-    PADDLE_THROW("CUDAPlace is not supported in CPU only version");
-#endif
-  }
-
-  void operator()(const platform::CUDAPinnedPlace& place) {
-#ifdef PADDLE_WITH_CUDA
-    PY_ARRAY_TO_TENSOR(PyCUDAPinnedTensorSetFromArray);
-#else
-    PADDLE_THROW("CUDAPinnedPlace is not supported in CPU only version");
-#endif
-  }
-
-#undef PY_ARRAY_TO_TENSOR
-#undef PY_ARRAY_TO_TENSOR_WITH_TYPE
-
- private:
-  template <typename T>
-  inline bool IsType() const {
-    return ::pybind11::isinstance<PyArrayT<T>>(py_array_);
-  }
-
- private:
-  const PyArray& py_array_;
-  framework::Tensor* tensor_;
-};
-
-class PyArrayFeedQueueHolder;
-
-// PyArrayFeedQueue must be thread-safe
-class PyArrayFeedQueue {
-  friend class PyArrayFeedQueueHolder;
-
- private:
-  PyArrayFeedQueue(size_t capacity, const std::vector<framework::DDim>& dims,
-                   const platform::Place& place)
-      : dims_(dims), place_(place) {
-    queue_.reset(
-        new PyBlockingQueue<std::vector<framework::LoDTensor>>(capacity));
-  }
-
- public:
-  ~PyArrayFeedQueue() { Close(); }
-
-  bool Enqueue(const std::vector<PyArray>& py_array_vec) {
-    auto lod_tensor_vec = PyArrayVecToLoDTensorVec(py_array_vec);
-    VLOG(5) << "Enqueue at address " << reinterpret_cast<void*>(this);
-    return queue_->Send(std::move(lod_tensor_vec));
-  }
-
-  bool Enqueue(const std::vector<framework::LoDTensor>& tensor_vec) {
-    VLOG(5) << "Enqueue at address " << reinterpret_cast<void*>(this);
-    return queue_->Send(tensor_vec);
-  }
-
-  std::vector<framework::LoDTensor> Dequeue() {
-    VLOG(5) << "Dequeue at address " << reinterpret_cast<void*>(this);
-    std::vector<framework::LoDTensor> ret;
-    return queue_->Receive(&ret) ? ret : std::vector<framework::LoDTensor>();
-  }
-
-  inline size_t Size() const { return queue_->Size(); }
-
-  inline size_t Cap() const { return queue_->Cap(); }
-
-  inline bool IsClosed() const { return queue_->IsClosed(); }
-
-  inline void Close() { queue_->Close(); }
-
- private:
-  std::vector<framework::LoDTensor> PyArrayVecToLoDTensorVec(
-      const std::vector<PyArray>& py_array_vec) {
-    PADDLE_ENFORCE(dims_.size() == py_array_vec.size(),
-                   "expected input tensor number %d but found %d", dims_.size(),
-                   py_array_vec.size());
-
-    size_t i = 0;
-    if (py_array_vec.size() > 1) {
-      size_t dim0 = py_array_vec[0].shape()[0];
-      for (size_t j = 1; j < py_array_vec.size(); ++j) {
-        PADDLE_ENFORCE(dim0 == py_array_vec[j].shape()[0],
-                       "0-dim of the %d-th input tensor is %d, but 0-dim of "
-                       "the 0-th input tensor is %d",
-                       j, py_array_vec[j].shape()[0], dim0);
-      }
-    }
-
-    std::vector<framework::LoDTensor> lod_tensor_vec;
-    lod_tensor_vec.reserve(py_array_vec.size());
-
-    std::for_each(
-        py_array_vec.begin(), py_array_vec.end(), [&](const PyArray& py_array) {
-          for (int64_t j = 1; j < dims_[i].size(); ++j) {
-            PADDLE_ENFORCE(
-                dims_[i][j] == static_cast<int64_t>(py_array.shape()[j]),
-                "expected %d-dim of %d-th input tensor is %d but found %d", j,
-                i, dims_[i][j], py_array.shape()[j]);
-          }
-
-          lod_tensor_vec.emplace_back(framework::LoDTensor());
-          PyArrayToTensorVisitor visitor(py_array, &(lod_tensor_vec.back()));
-          boost::apply_visitor(visitor, place_);
-          ++i;
-        });
-    return lod_tensor_vec;
-  }
-
-  std::unique_ptr<PyBlockingQueue<std::vector<framework::LoDTensor>>> queue_;
-  std::vector<framework::DDim> dims_;
-  platform::Place place_;
-};
-
-class PyArrayFeedQueueHolder {
- public:
-  PyArrayFeedQueueHolder() {}
-
-  void InitOnce(size_t capacity, const std::vector<framework::DDim>& dims,
-                const platform::Place& place) {
-    PADDLE_ENFORCE(
-        feeder_ == nullptr,
-        "PyArrayFeedQueueHolder::InitOnce() can only be called once");
-    feeder_.reset(new PyArrayFeedQueue(capacity, dims, place));
-  }
-
-  std::shared_ptr<PyArrayFeedQueue> GetFeeder() { return feeder_; }
-  const std::shared_ptr<PyArrayFeedQueue>& GetFeeder() const { return feeder_; }
-
- private:
-  std::shared_ptr<PyArrayFeedQueue> feeder_;
-};
-
-}  // namespace reader
-}  // namespace operators
-}  // namespace paddle