diff --git a/mindspore/ccsrc/parallel/ps/worker.h b/mindspore/ccsrc/parallel/ps/worker.h
new file mode 100644
index 0000000000000000000000000000000000000000..b9d0cdcc85ea57803d45d3e9b23681f94569fee4
--- /dev/null
+++ b/mindspore/ccsrc/parallel/ps/worker.h
@@ -0,0 +1,259 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * 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.
+ */
+
+#ifndef MINDSPORE_MINDSPORE_CCSRC_PARALLEL_PS_WORKER_H_
+#define MINDSPORE_MINDSPORE_CCSRC_PARALLEL_PS_WORKER_H_
+
+#include <utility>
+#include <memory>
+#include <vector>
+#include <string>
+#include <map>
+#include "ps/ps.h"
+#include "utils/log_adapter.h"
+#include "parallel/ps/util.h"
+#include "parallel/ps/common.h"
+#include "parallel/ps/worker_proxy.h"
+
+namespace mindspore {
+namespace parallel {
+namespace ps {
+template <typename T>
+class Worker {
+ public:
+  static Worker &GetInstance() {
+    static Worker instance;
+    return instance;
+  }
+
+  void Run();
+  void Push(const std::vector<size_t> &keys, std::vector<uintptr_t> addrs, const std::vector<int> &sizes);
+  void Pull(const size_t key, void *dev_addr, const size_t size);
+  size_t SetParamKey(const std::string &param_name);
+  void SetKeyOptimId(size_t key, const std::string &optimizer_name);
+  void SetOptimInputShapes(size_t key, const std::vector<int> &shape);
+  void AddEmbeddingTable(const ::ps::Key &key, const size_t &row_count);
+  void InitPSEmbeddingTable(const std::vector<size_t> &keys, std::vector<size_t> shapes, const std::vector<int> &sizes);
+  void InitPSParamAndOptim(const std::string &param_name, void *param_data, size_t param_size);
+  void DoPSEmbeddingLookup(const ::ps::SArray<::ps::Key> &keys, const ::ps::SArray<T> &lookup_ids,
+                           const ::ps::SArray<int> &lens, ::ps::SArray<T> *lookup_result, int cmd);
+
+ private:
+  Worker() : kv_worker_(nullptr), running_(false), key_cnt_(0) {}
+  ~Worker() { ::ps::Finalize(0, true); }
+  Worker(const Worker &) = delete;
+  Worker &operator=(const Worker &) = delete;
+
+  bool IsKeyInit(const size_t key);
+  size_t GetParamKey(const std::string &param_name);
+  void InitPSOptimId(const size_t param_key);
+  void InitPSOptimInputShapes(const size_t key);
+  void InitPSParamData(const std::vector<size_t> &keys, void *origin_addr, size_t size);
+  static void EmbeddingLookupIdSlicer(const ::ps::KVPairs<T> &send, const std::vector<::ps::Range> &ranges,
+                                      std::vector<std::pair<bool, ::ps::KVPairs<T>>> *sliced) {}
+
+  std::shared_ptr<WorkerProxy<T>> kv_worker_;
+  bool running_;
+  size_t key_cnt_;
+  std::map<std::string, size_t> param_to_key_;
+  std::map<size_t, bool> init_keys_;
+  std::map<size_t, int> key_to_optimId_;
+  std::map<size_t, std::vector<std::vector<int>>> key_to_optim_shapes_;
+};
+
+template <typename T>
+void Worker<T>::Run() {
+  if (running_) {
+    MS_LOG(INFO) << "'Worker is already running.";
+    return;
+  }
+
+  ::ps::Start(0);
+  if (!::ps::IsWorker()) {
+    MS_LOG(EXCEPTION) << "The role is not worker.";
+  }
+  kv_worker_ = std::make_shared<WorkerProxy<T>>(0, 0, 1);
+  running_ = true;
+}
+
+template <typename T>
+void Worker<T>::Push(const std::vector<size_t> &keys, std::vector<uintptr_t> addrs, const std::vector<int> &sizes) {
+  size_t total_size = 0;
+  for (auto size : sizes) {
+    total_size += size;
+  }
+  ::ps::SArray<T> total_buffer(total_size, 0);
+  size_t offset = 0;
+  for (size_t i = 0; i < sizes.size(); i++) {
+    memcpy(total_buffer.data() + offset / sizeof(T), addrs[i], sizes[i] * sizeof(T));
+    offset += sizes[i] * sizeof(T);
+  }
+  kv_worker_->PushData(::ps::SArray<::ps::Key>(keys), total_buffer, ::ps::SArray<int>(sizes));
+}
+
+template <typename T>
+void Worker<T>::Pull(const size_t key, void *dev_addr, const size_t size) {
+  ::ps::SArray<T> variables(size / sizeof(T), 0);
+  kv_worker_->Wait(kv_worker_->ZPull({key}, &variables));
+  memcpy(dev_addr, variables.data(), size);
+}
+
+template <typename T>
+void Worker<T>::DoPSEmbeddingLookup(const ::ps::SArray<::ps::Key> &keys, const ::ps::SArray<T> &lookup_ids,
+                                    const ::ps::SArray<int> &lens, ::ps::SArray<T> *lookup_result, int cmd) {
+  kv_worker_->EmbeddingLookup(keys, lookup_ids, lens, &lookup_result, cmd);
+}
+
+template <typename T>
+void Worker<T>::InitPSParamData(const std::vector<size_t> &keys, void *origin_addr, size_t size) {
+  ::ps::SArray<T> addr(reinterpret_cast<T *>(origin_addr), size / sizeof(T));
+  ::ps::SArray<::ps::Key> key(keys);
+  ::ps::SArray<int> lens;
+  lens.push_back(addr.size());
+  kv_worker_->Wait(kv_worker_->ZPush(key, addr, lens, kInitWeightsCmd));
+  init_keys_[key[0]] = true;
+}
+
+template <typename T>
+void Worker<T>::SetOptimInputShapes(size_t key, const std::vector<int> &shape) {
+  if (key_to_optim_shapes_.find(key) == key_to_optim_shapes_.end()) {
+    key_to_optim_shapes_[key] = {shape};
+  } else {
+    key_to_optim_shapes_[key].push_back(shape);
+  }
+}
+
+template <typename T>
+void Worker<T>::InitPSOptimInputShapes(const size_t key) {
+  ::ps::SArray<::ps::Key> keys;
+  ::ps::SArray<int> shape_len;
+  ::ps::SArray<T> all_shape;
+  std::vector<std::vector<int>> shapes = key_to_optim_shapes_[key];
+  for (auto shape : shapes) {
+    keys.push_back(key);
+    if (shape.size() == 0) {
+      shape_len.push_back(1);
+      all_shape.push_back(1);
+    } else {
+      shape_len.push_back(SizeToInt(shape.size()));
+      for (auto dim : shape) {
+        all_shape.push_back(static_cast<T>(dim));
+      }
+    }
+  }
+  MS_LOG(ERROR) << "keys:" << keys;
+  MS_LOG(ERROR) << "shape_len:" << shape_len;
+  MS_LOG(ERROR) << "all_shape:" << all_shape;
+  if (!init_keys_[key]) {
+    init_keys_[key] = true;
+  }
+  kv_worker_->PushData(keys, all_shape, shape_len, kInitOptimInputsShapeCmd);
+}
+
+template <typename T>
+bool Worker<T>::IsKeyInit(const size_t key) {
+  if (init_keys_.find(key) == init_keys_.end() || !init_keys_[key]) {
+    return false;
+  }
+  return true;
+}
+
+template <typename T>
+size_t Worker<T>::SetParamKey(const std::string &param_name) {
+  size_t key = UINT64_MAX;
+  if (param_to_key_.count(param_name)) {
+    key = param_to_key_[param_name];
+    MS_LOG(INFO) << param_name << " key is already set: key value is " << key;
+  } else {
+    key = key_cnt_++;
+    param_to_key_[param_name] = key;
+    MS_LOG(INFO) << "Set key " << key << " for parameter " << param_name;
+  }
+  return key;
+}
+
+template <typename T>
+size_t Worker<T>::GetParamKey(const std::string &param_name) {
+  size_t key = kInvalidKey;
+  if (param_to_key_.find(param_name) != param_to_key_.end()) {
+    key = param_to_key_[param_name];
+    MS_LOG(ERROR) << "Get key of parameter " << param_name << " key is " << key;
+  }
+  return key;
+}
+
+template <typename T>
+void Worker<T>::SetKeyOptimId(size_t key, const std::string &optimizer_name) {
+  key_to_optimId_[key] = Util::optimizer_id(optimizer_name);
+}
+
+template <typename T>
+void Worker<T>::InitPSOptimId(const size_t param_key) {
+  if (key_to_optimId_.count(param_key) == 0) {
+    MS_LOG(EXCEPTION) << "Can't find optimizer id of parameter key " << param_key;
+  }
+  int optim_id = key_to_optimId_[param_key];
+
+  ::ps::SArray<::ps::Key> keys = {param_key};
+  ::ps::SArray<T> optim_id_vals = {static_cast<T>(optim_id)};
+  ::ps::SArray<int> optim_id_lens = {optim_id_vals.size()};
+  kv_worker_->PushData(keys, optim_id_vals, optim_id_lens, kInitWeightToOptimIdCmd);
+}
+
+template <typename T>
+void Worker<T>::InitPSEmbeddingTable(const std::vector<size_t> &keys, std::vector<size_t> shapes,
+                                     const std::vector<int> &sizes) {
+  bool has_init = IsKeyInit(keys[0]);
+  if (has_init) {
+    MS_LOG(DEBUG) << "The key embedding table of key " << keys[0] << " is initialized.";
+    return;
+  }
+  ::ps::SArray<T> shapes_val;
+  for (auto dim : shapes) {
+    shapes_val.push_back(static_cast<T>(dim));
+  }
+  kv_worker_->Wait(kv_worker_->InitEmbeddingTable(::ps::SArray<::ps::Key>(keys), shapes_val, ::ps::SArray<int>(sizes)));
+}
+
+template <typename T>
+// Initialize parameters and optimizer kernels of Parameter Server.
+void Worker<T>::InitPSParamAndOptim(const std::string &param_name, void *param_data, size_t param_size) {
+  size_t param_key = GetParamKey(param_name);
+  if (param_key == kInvalidKey) {
+    MS_LOG(INFO) << "Parameter " << param_name << " has no key assigned.";
+    return;
+  }
+  bool init = IsKeyInit(param_key);
+  if (!init) {
+    MS_LOG(INFO) << "Init paramter and optimizer in parameter server side for " << param_name;
+    // No need to push embedding table data to Parameter Server.
+    if (param_name.find("embedding_table") == std::string::npos && param_name.find("wide_w") == std::string::npos) {
+      InitPSParamData({param_key}, param_data, param_size);
+    }
+    InitPSOptimId(param_key);
+    InitPSOptimInputShapes(param_key);
+  }
+}
+
+template <typename T>
+void Worker<T>::AddEmbeddingTable(const ::ps::Key &key, const size_t &row_count) {
+  kv_worker_->AddEmbeddingTable(key, row_count);
+}
+
+}  // namespace ps
+}  // namespace parallel
+}  // namespace mindspore
+#endif  // MINDSPORE_MINDSPORE_CCSRC_PARALLEL_PS_WORKER_H_