send_recv variables (#7161)

* send_recv variable

* delete unused logs

* fix ci failed

* update

* resize tensor before tensor copy

* add selectedrows unit test

* check rows

paddle/framework/lod_tensor.cc

@@ -217,9 +217,10 @@ void SerializeToStream(std::ostream &os, const LoDTensor &tensor,
   SerializeToStream(os, static_cast<Tensor>(tensor), dev_ctx);
 }
 
-void DeserializeFromStream(std::istream &is, LoDTensor *tensor) {
+void DeserializeFromStream(std::istream &is, LoDTensor *tensor,
+                           const platform::DeviceContext &dev_ctx) {
   {
-    // the 1st field, unit32_t version for SelectedRows
+    // the 1st field, unit32_t version for LoDTensor
     uint32_t version;
     is.read(reinterpret_cast<char *>(&version), sizeof(version));
     PADDLE_ENFORCE_EQ(version, 0U, "Only version 0 is supported");
@@ -240,7 +241,7 @@ void DeserializeFromStream(std::istream &is, LoDTensor *tensor) {
     }
   }
   // the 3st filed, Tensor
-  DeserializeFromStream(is, static_cast<Tensor *>(tensor));
+  DeserializeFromStream(is, static_cast<Tensor *>(tensor), dev_ctx);
 }
 
 }  // namespace framework

paddle/framework/lod_tensor.h

@@ -208,7 +208,8 @@ void AppendLoD(LoD* lod, const LoD& lod_length);
  */
 void SerializeToStream(std::ostream& os, const LoDTensor& tensor,
                        const platform::DeviceContext& dev_ctx);
-void DeserializeFromStream(std::istream& is, LoDTensor* tensor);
+void DeserializeFromStream(std::istream& is, LoDTensor* tensor,
+                           const platform::DeviceContext& dev_ctx);
 
 }  // namespace framework
 }  // namespace paddle

paddle/framework/lod_tensor_test.cc

@@ -132,7 +132,7 @@ TEST_F(LoDTensorTester, SerializeAndDeserialize) {
   std::ostringstream oss;
   SerializeToStream(oss, lod_tensor_, cpu_ctx);
   std::istringstream iss(oss.str());
-  DeserializeFromStream(iss, &dst_tensor);
+  DeserializeFromStream(iss, &dst_tensor, cpu_ctx);
   float* dst_ptr = dst_tensor.mutable_data<float>(platform::CPUPlace());
   for (int i = 0; i < kLodTensorSize; ++i) {
     EXPECT_EQ(dst_ptr[i], i);

paddle/framework/selected_rows.cc

@@ -37,8 +37,8 @@ void SerializeToStream(std::ostream& os, const SelectedRows& selected_rows,
   SerializeToStream(os, selected_rows.value(), dev_ctx);
 }
 
-void DeserializeFromStream(std::istream& is, SelectedRows* selected_rows) {
-  auto tensor = *selected_rows->mutable_value();
+void DeserializeFromStream(std::istream& is, SelectedRows* selected_rows,
+                           const platform::DeviceContext& dev_ctx) {
   {
     // the 1st field, unit32_t version for SelectedRows
     uint32_t version;
@@ -62,7 +62,7 @@ void DeserializeFromStream(std::istream& is, SelectedRows* selected_rows) {
     selected_rows->set_height(height);
   }
   // the 4st field, tensor which contains the data
-  DeserializeFromStream(is, &tensor);
+  DeserializeFromStream(is, selected_rows->mutable_value(), dev_ctx);
 }
 
 }  // namespace framework

paddle/framework/selected_rows.h

@@ -66,7 +66,8 @@ class SelectedRows {
  */
 void SerializeToStream(std::ostream& os, const SelectedRows& selected_rows,
                        const platform::DeviceContext& dev_ctx);
-void DeserializeFromStream(std::istream& is, SelectedRows* selected_rows);
+void DeserializeFromStream(std::istream& is, SelectedRows* selected_rows,
+                           const platform::DeviceContext& dev_ctx);
 
 }  // namespace framework
 }  // namespace paddle

paddle/framework/selected_rows_test.cc

@@ -51,10 +51,12 @@ TEST_F(SelectedRowsTester, SerializeAndDeseralize) {
   SerializeToStream(oss, *selected_rows_, cpu_ctx);
 
   std::istringstream iss(oss.str());
-  DeserializeFromStream(iss, &dst_tensor);
+  DeserializeFromStream(iss, &dst_tensor, cpu_ctx);
 
   ASSERT_EQ(selected_rows_->rows(), dst_tensor.rows());
   ASSERT_EQ(selected_rows_->height(), dst_tensor.height());
+  ASSERT_EQ(selected_rows_->value().dims(), dst_tensor.value().dims());
+  ASSERT_EQ(selected_rows_->GetCompleteDims(), dst_tensor.GetCompleteDims());
 }
 
 }  // namespace framework

paddle/framework/tensor_util.h

@@ -270,7 +270,23 @@ inline void SerializeToStream(std::ostream& os, const Tensor& tensor,
   }
 }
 
-inline void DeserializeFromStream(std::istream& is, Tensor* tensor) {
+struct DeserializedDataFunctor {
+  DeserializedDataFunctor(void** buf, Tensor* tensor,
+                          const platform::Place& place)
+      : buf_(buf), tensor_(tensor), place_(place) {}
+
+  template <typename T>
+  void operator()() {
+    *buf_ = tensor_->mutable_data<T>(place_);
+  }
+
+  void** buf_;
+  Tensor* tensor_;
+  platform::Place place_;
+};
+
+inline void DeserializeFromStream(std::istream& is, Tensor* tensor,
+                                  const platform::DeviceContext& dev_ctx) {
   uint32_t version;
   is.read(reinterpret_cast<char*>(&version), sizeof(version));
   PADDLE_ENFORCE_EQ(version, 0U, "Only version 0 is supported");
@@ -289,28 +305,29 @@ inline void DeserializeFromStream(std::istream& is, Tensor* tensor) {
     dims.reserve(static_cast<size_t>(desc.dims().size()));
     std::copy(desc.dims().begin(), desc.dims().end(), std::back_inserter(dims));
     tensor->Resize(framework::make_ddim(dims));
-
     void* buf;
-    platform::Place cpu = platform::CPUPlace();
-    // TODO(Yancey1989): use VisiterDataType instead of DataType switch
-    switch (desc.data_type()) {
-      case proto::FP32:
-        buf = tensor->mutable_data<float>(cpu);
-        break;
-      case proto::FP64:
-        buf = tensor->mutable_data<double>(cpu);
-        break;
-      case proto::INT32:
-        buf = tensor->mutable_data<int>(cpu);
-        break;
-      case proto::INT64:
-        buf = tensor->mutable_data<int64_t>(cpu);
-        break;
-      default:
-        PADDLE_THROW("DataType %d not supported", desc.data_type());
-    }
+    auto ctx = platform::CPUDeviceContext();
+    if (platform::is_gpu_place(dev_ctx.GetPlace())) {
+#ifdef PADDLE_WITH_CUDA
+      Tensor cpu_tensor;
+      cpu_tensor.Resize(framework::make_ddim(dims));
+      framework::VisitDataType(
+          desc.data_type(),
+          DeserializedDataFunctor(&buf, &cpu_tensor, ctx.GetPlace()));
+      is.read(static_cast<char*>(buf), cpu_tensor.memory_size());
+      auto cpu_place = new platform::CPUPlace();
+      framework::CopyFrom(cpu_tensor, *cpu_place, dev_ctx, tensor);
+      delete cpu_place;
+#else
+      PADDLE_THROW("Unexpected branch");
+#endif
+    } else {
+      framework::VisitDataType(
+          desc.data_type(),
+          DeserializedDataFunctor(&buf, tensor, ctx.GetPlace()));
       is.read(static_cast<char*>(buf), tensor->memory_size());
     }
+  }
 }
 
 }  // namespace framework

paddle/framework/tensor_util_test.cc

@@ -270,11 +270,12 @@ TEST(Tensor, SerializeAndDeserialize) {
     SerializeToStream(oss, src_tensor, cpu_ctx);
 
     std::istringstream iss(oss.str());
-    DeserializeFromStream(iss, &dst_tensor);
+    DeserializeFromStream(iss, &dst_tensor, cpu_ctx);
     int* dst_ptr = dst_tensor.mutable_data<int>(platform::CPUPlace());
     for (int i = 0; i < 5; ++i) {
       ASSERT_EQ(dst_ptr[i], array[i]);
     }
+    ASSERT_EQ(dst_tensor.dims(), src_tensor.dims());
     delete place;
   }
 #ifdef PADDLE_WITH_CUDA
@@ -292,13 +293,12 @@ TEST(Tensor, SerializeAndDeserialize) {
     SerializeToStream(oss, gpu_tensor, gpu_ctx);
 
     std::istringstream iss(oss.str());
-    DeserializeFromStream(iss, &dst_tensor);
+    DeserializeFromStream(iss, &dst_tensor, gpu_ctx);
 
     int* dst_ptr = dst_tensor.mutable_data<int>(platform::CPUPlace());
     for (int i = 0; i < 6; ++i) {
       ASSERT_EQ(dst_ptr[i], array[i]);
     }
-
     delete gpu_place;
   }
 #endif

paddle/framework/var_type.h

@@ -17,6 +17,8 @@ limitations under the License. */
 #include "paddle/framework/lod_rank_table.h"
 #include "paddle/framework/lod_tensor.h"
 #include "paddle/framework/lod_tensor_array.h"
+#include "paddle/framework/selected_rows.h"
+#include "paddle/framework/variable.h"
 
 namespace paddle {
 namespace framework {
@@ -35,7 +37,7 @@ inline proto::VarDesc::VarType ToVarType(std::type_index type) {
 }
 
 template <typename Visitor>
-inline void VisitVarType(const Variable& var, Visitor visitor) {
+inline void VisitVarType(const framework::Variable& var, Visitor visitor) {
   switch (ToVarType(var.Type())) {
     case proto::VarDesc_VarType_LOD_TENSOR:
       visitor(var.Get<framework::LoDTensor>());

paddle/operators/detail/recv_impl.cc

@@ -21,14 +21,9 @@ namespace detail {
 Status SendRecvServerImpl::SendVariable(ServerContext *context,
                                         const VariableMessage *in_var,
                                         VoidMessage *out_var) {
-  // TODO(typhoonzero): support different variable types.
-  std::istringstream iss(in_var->serialized());
-  framework::LoDTensor t;
-  framework::DeserializeFromStream(iss, &t);
-  TensorWithName tensor_with_name =
-      std::make_pair(in_var->varname(), std::move(t));
-
-  var_recv_queue_.Push(std::move(tensor_with_name));
+  MessageWithName msg_with_name =
+      std::make_pair(in_var->varname(), std::move(*in_var));
+  var_recv_queue_.Push(std::move(msg_with_name));
   return Status::OK;
 }
 
@@ -37,14 +32,8 @@ Status SendRecvServerImpl::GetVariable(ServerContext *context,
                                        VariableMessage *out_var) {
   std::string get_var_name = in_var->varname();
   auto *var = scope_->FindVar(get_var_name);
-  auto tensor = var->Get<framework::LoDTensor>();
-  std::ostringstream oss;
-  framework::SerializeToStream(oss, tensor, platform::CPUDeviceContext());
 
-  std::string *varname = out_var->mutable_varname();
-  *varname = get_var_name;
-  std::string *serialized = out_var->mutable_serialized();
-  *serialized = oss.str();
+  SerializeToMessage(get_var_name, var, platform::CPUDeviceContext(), out_var);
   return Status::OK;
 }
 

paddle/operators/detail/send_impl.cc

@@ -27,14 +27,8 @@ bool RPCClient::SendVariable(const framework::Scope& scope,
   auto ctx = platform::CPUDeviceContext();
   auto* var = scope.FindVar(inname);
   PADDLE_ENFORCE(var);
-  // TODO(typhoonzero): support SelectedRows
-  PADDLE_ENFORCE(var->IsType<framework::LoDTensor>(),
-                 "Only support LoDTensor, %s has wrong type", inname);
-  const framework::LoDTensor& tensor = var->Get<framework::LoDTensor>();
-  std::ostringstream oss;
-  framework::SerializeToStream(oss, tensor, ctx);
-  msg.set_varname(inname);
-  msg.set_serialized(oss.str());
+  SerializeToMessage(inname, var, ctx, &msg);
+
   Status status = stub_->SendVariable(&context, msg, &out_msg);
   if (!status.ok()) {
     LOG(ERROR) << "gRPC error: " << status.error_message();
@@ -50,19 +44,15 @@ bool RPCClient::GetVariable(const framework::Scope& scope,
   call_msg.set_varname(outname);
   auto ctx = platform::CPUDeviceContext();
   Status status = stub_->GetVariable(&context, call_msg, &ret_msg);
+  auto* outvar = scope.FindVar(outname);
   if (!status.ok()) {
     LOG(ERROR) << "gRPC error: " << status.error_message();
     return false;
   }
 
   std::istringstream iss(ret_msg.serialized());
+  DeserializeFromMessage(ret_msg, ctx, outvar);
 
-  framework::LoDTensor ret_tensor;
-  framework::DeserializeFromStream(iss, &ret_tensor);
-  auto* outvar = scope.FindVar(outname);
-  framework::LoDTensor* out_tensor = outvar->GetMutable<framework::LoDTensor>();
-  // FIXME(typhoonzero): do not copy.
-  framework::CopyFrom(ret_tensor, ctx.GetPlace(), ctx, out_tensor);
   return true;
 }
 

paddle/operators/detail/send_recv.proto

-/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. 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
@@ -13,7 +12,6 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 syntax = "proto3";
-
 package sendrecv;
 
 service SendRecvService {
@@ -29,12 +27,18 @@ service SendRecvService {
 
 // VariableMessage is serialized paddle variable message.
 // It can be:
-// Tensor
 // LoDTensor
 // SelectedRows
+enum VarType {
+  LOD_TENSOR = 0;
+  SELECTED_ROWS = 1;
+}
+
 message VariableMessage {
   string varname = 1;
-  bytes serialized = 2;
+  // TODO(Yancey1989): reference framework::proto::VarDesc::VarType
+  VarType type = 2;
+  bytes serialized = 3;
 }
 
 message VoidMessage {}

paddle/operators/detail/send_recv_impl.h

@@ -14,10 +14,10 @@ limitations under the License. */
 
 #pragma once
 
-#include "paddle/framework/data_type.h"
 #include "paddle/framework/lod_tensor.h"
 #include "paddle/framework/scope.h"
 #include "paddle/framework/selected_rows.h"
+#include "paddle/framework/var_type.h"
 #include "paddle/operators/detail/simple_block_queue.h"
 
 #include "paddle/operators/detail/send_recv.grpc.pb.h"
@@ -44,7 +44,7 @@ namespace paddle {
 namespace operators {
 namespace detail {
 
-typedef std::pair<std::string, framework::LoDTensor> TensorWithName;
+typedef std::pair<std::string, sendrecv::VariableMessage> MessageWithName;
 
 class SendRecvServerImpl final : public SendRecvService::Service {
  public:
@@ -60,13 +60,13 @@ class SendRecvServerImpl final : public SendRecvService::Service {
   void Done();
   void SetScope(framework::Scope *scope) { scope_ = scope; };
 
-  const TensorWithName Get() { return this->var_recv_queue_.Pop(); }
+  const MessageWithName Get() { return this->var_recv_queue_.Pop(); }
 
-  void Push(const TensorWithName &msg) { this->var_recv_queue_.Push(msg); }
+  void Push(const MessageWithName &msg) { this->var_recv_queue_.Push(msg); }
 
  private:
   // received variable from RPC, operators fetch variable from this queue.
-  SimpleBlockQueue<TensorWithName> var_recv_queue_;
+  SimpleBlockQueue<MessageWithName> var_recv_queue_;
   framework::Scope *scope_;
   // condition of the sub program
   std::mutex mutex_;
@@ -89,6 +89,53 @@ class RPCClient {
   std::unique_ptr<SendRecvService::Stub> stub_;
 };
 
+inline void SerializeToMessage(const std::string &name,
+                               const framework::Variable *var,
+                               const platform::DeviceContext &ctx,
+                               VariableMessage *msg) {
+  msg->set_varname(name);
+  std::ostringstream oss;
+  switch (framework::ToVarType(var->Type())) {
+    case framework::proto::VarDesc_VarType_LOD_TENSOR:
+      msg->set_type(sendrecv::VarType::LOD_TENSOR);
+      framework::SerializeToStream(oss, var->Get<framework::LoDTensor>(), ctx);
+      break;
+    case framework::proto::VarDesc_VarType_SELECTED_ROWS:
+      msg->set_type(sendrecv::VarType::SELECTED_ROWS);
+      framework::SerializeToStream(oss, var->Get<framework::SelectedRows>(),
+                                   ctx);
+      break;
+    default: {
+      PADDLE_THROW("Serialize does not support type: %s",
+                   typeid(var->Type()).name());
+      break;
+    }
+  }
+  msg->set_serialized(oss.str());
+}
+
+inline void DeserializeFromMessage(const VariableMessage &msg,
+                                   const platform::DeviceContext &ctx,
+                                   framework::Variable *var) {
+  using namespace paddle::framework::proto;
+  std::istringstream iss(msg.serialized());
+  switch (msg.type()) {
+    case sendrecv::VarType::LOD_TENSOR:
+      DeserializeFromStream(iss, var->GetMutable<framework::LoDTensor>(), ctx);
+      break;
+    case sendrecv::VarType::SELECTED_ROWS: {
+      DeserializeFromStream(iss, var->GetMutable<framework::SelectedRows>(),
+                            ctx);
+      break;
+    }
+    default: {
+      PADDLE_THROW("Deserialize does not support type: %s",
+                   typeid(var->Type()).name());
+      break;
+    }
+  }
+}
+
 }  // namespace detail
 }  // namespace operators
 }  // namespace paddle

paddle/operators/load_op.cc

@@ -38,10 +38,10 @@ class LoadOp : public framework::OperatorBase {
                    out_var_name);
 
     auto *tensor = out_var->GetMutable<framework::LoDTensor>();
-    DeserializeFromStream(fin, tensor);
 
     platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
     auto &dev_ctx = *pool.Get(place);
+    DeserializeFromStream(fin, tensor, dev_ctx);
 
     if (platform::is_gpu_place(place)) {
       // copy CPU to GPU

paddle/operators/recv_op.cc

@@ -60,7 +60,7 @@ class RecvOp : public framework::OperatorBase {
   }
 
   void Stop() override {
-    detail::TensorWithName term_msg;
+    detail::MessageWithName term_msg;
     term_msg.first = LISTEN_TERMINATE_MESSAGE;
     rpc_service_->Push(term_msg);
     rpc_server_->Shutdown();
@@ -94,7 +94,7 @@ class RecvOp : public framework::OperatorBase {
       // the gradient arrives, just add suffix 0~n then average the gradient.
       for (size_t i = 0; i < param_count * trainer_count; ++i) {
         // blocking get one var from client.
-        const detail::TensorWithName &v = rpc_service_->Get();
+        const detail::MessageWithName &v = rpc_service_->Get();
         auto grad_var_name = v.first;
         if (grad_var_name == LISTEN_TERMINATE_MESSAGE) {
           exit_flag = true;
@@ -121,11 +121,10 @@ class RecvOp : public framework::OperatorBase {
         }
 
         auto *var = recv_scope.Var(grad_var_name);
-        auto *tensor = var->GetMutable<framework::LoDTensor>();
-        // FIXME(typhoonzero): do not copy
-        platform::DeviceContextPool &pool = platform::DeviceContextPool::Get();
-        auto &dev_ctx = *pool.Borrow(dev_place);
-        framework::CopyFrom(v.second, dev_place, dev_ctx, tensor);
+        platform::DeviceContextPool &pool =
+            platform::DeviceContextPool::Instance();
+        auto &dev_ctx = *pool.Get(dev_place);
+        detail::DeserializeFromMessage(v.second, dev_ctx, var);
       }
       if (exit_flag) {
         break;

paddle/operators/send_recv_op_test.cc

@@ -20,22 +20,27 @@ limitations under the License. */
 #include "paddle/framework/op_registry.h"
 #include "paddle/framework/operator.h"
 #include "paddle/framework/program_desc.h"
+#include "paddle/operators/math/math_function.h"
+#include "paddle/operators/math/selected_rows_functor.h"
 #include "paddle/string/printf.h"
 
 USE_NO_KERNEL_OP(send);
 USE_NO_KERNEL_OP(recv);
 USE_OP(sum);
 
+namespace f = paddle::framework;
+namespace p = paddle::platform;
+namespace m = paddle::operators::math;
+
 // global for simplicity.
-std::unique_ptr<paddle::framework::OperatorBase> recv_op;
+std::unique_ptr<f::OperatorBase> recv_op;
 
-void InitTensorsInScope(paddle::framework::Scope &scope,
-                        paddle::platform::CPUPlace &place) {
-  paddle::platform::CPUDeviceContext ctx(place);
+void InitTensorsInScope(f::Scope &scope, p::CPUPlace &place) {
+  p::CPUDeviceContext ctx(place);
   for (int i = 0; i < 2; ++i) {
     auto var_name = paddle::string::Sprintf("x%d", i);
     auto var = scope.Var(var_name);
-    auto tensor = var->GetMutable<paddle::framework::LoDTensor>();
+    auto tensor = var->GetMutable<f::LoDTensor>();
     tensor->Resize({10, 10});
     float *expect = tensor->mutable_data<float>(place);
     for (int64_t i = 0; i < tensor->numel(); ++i) {
@@ -44,21 +49,53 @@ void InitTensorsInScope(paddle::framework::Scope &scope,
   }
 
   auto out_var = scope.Var("Out");
-  auto out_tensor = out_var->GetMutable<paddle::framework::LoDTensor>();
+  auto out_tensor = out_var->GetMutable<f::LoDTensor>();
   out_tensor->Resize({10, 10});
   out_tensor->mutable_data<float>(place);  // allocate
 }
 
-void AddOp(const std::string &type,
-           const paddle::framework::VariableNameMap &inputs,
-           const paddle::framework::VariableNameMap &outputs,
-           paddle::framework::AttributeMap attrs,
-           paddle::framework::BlockDesc *block) {
+void InitSelectedRowsInScope(f::Scope &scope, p::CPUPlace &place) {
+  p::CPUDeviceContext ctx(place);
+  int64_t height = 10;
+  int64_t row_numel = 10;
+  m::SetConstant<p::CPUDeviceContext, float> set_one;
+  // init x0
+  std::vector<int64_t> rows0{0, 4, 7};
+  auto x0_var = scope.Var("x0");
+  auto x0 = x0_var->GetMutable<f::SelectedRows>();
+  x0->set_rows(rows0);
+  x0->set_height(height);
+  auto x0_value = x0->mutable_value();
+  x0_value->mutable_data<float>(
+      f::make_ddim({static_cast<int64_t>(rows0.size()), row_numel}), place);
+  set_one(ctx, x0_value, 1.0);
+
+  // init x1
+  std::vector<int64_t> rows1{2, 9};
+  auto x1_var = scope.Var("x1");
+  auto x1 = x1_var->GetMutable<f::SelectedRows>();
+  x1->set_rows(rows1);
+  x1->set_height(height);
+  auto x1_value = x1->mutable_value();
+  x1_value->mutable_data<float>(
+      f::make_ddim({static_cast<int64_t>(rows1.size()), row_numel}), place);
+  set_one(ctx, x1_value, 1.0);
+
+  auto out_var = scope.Var("Out");
+  auto out = out_var->GetMutable<f::SelectedRows>();
+  auto out_value = out->mutable_value();
+  out->set_height(height);
+  out_value->mutable_data<float>(f::make_ddim({5, 10}), place);
+}
+
+void AddOp(const std::string &type, const f::VariableNameMap &inputs,
+           const f::VariableNameMap &outputs, f::AttributeMap attrs,
+           f::BlockDesc *block) {
   // insert output
   for (auto kv : outputs) {
     for (auto v : kv.second) {
       auto var = block->Var(v);
-      var->SetDataType(paddle::framework::proto::DataType::FP32);
+      var->SetDataType(f::proto::DataType::FP32);
     }
   }
 
@@ -74,58 +111,99 @@ void AddOp(const std::string &type,
   op->SetAttrMap(attrs);
 }
 
-void StartServerNet() {
-  paddle::framework::Scope scope;
-  paddle::platform::CPUPlace place;
+void StartServerNet(bool is_sparse) {
+  f::Scope scope;
+  p::CPUPlace place;
+  if (is_sparse) {
+    InitSelectedRowsInScope(scope, place);
+  } else {
     InitTensorsInScope(scope, place);
+  }
 
   // sub program run in recv_op, for simple test we use sum
-  paddle::framework::ProgramDesc program;
-  paddle::framework::BlockDesc *block = program.MutableBlock(0);
+  f::ProgramDesc program;
+  f::BlockDesc *block = program.MutableBlock(0);
   // X for server side tensors, RX for received tensers, must be of same shape.
-  AddOp("sum", {{"X", {"x0", "x1"}}}, {{"Out", {"x0"}}}, {}, block);
+  AddOp("sum", {{"X", {"x0", "x1"}}}, {{"Out", {"Out"}}}, {}, block);
 
-  paddle::framework::AttributeMap attrs;
+  f::AttributeMap attrs;
   attrs.insert({"endpoint", std::string("127.0.0.1:6174")});
-  attrs.insert({"ParamList", std::vector<std::string>({"x0"})});
+  attrs.insert({"ParamList", std::vector<std::string>({"Out"})});
   attrs.insert({"GradList", std::vector<std::string>({"x1"})});
   std::string program_proto;
   PADDLE_ENFORCE(program.Proto()->SerializeToString(&program_proto));
 
   attrs.insert({"OptimizeProgram", program_proto});
-  recv_op = paddle::framework::OpRegistry::CreateOp("recv", {{"RX", {"x1"}}},
-                                                    {}, attrs);
+  recv_op = f::OpRegistry::CreateOp("recv", {{"RX", {"x1"}}}, {}, attrs);
   recv_op->Run(scope, place);
 }
 
-TEST(SendRecvOp, CPU) {
-  std::thread server_thread(StartServerNet);
-  sleep(5);  // wait server to start
+TEST(SendRecvOp, CPUDense) {
+  std::thread server_thread(StartServerNet, false);
+  sleep(3);  // wait server to start
   // local net
-  paddle::framework::Scope scope;
-  paddle::platform::CPUPlace place;
+  f::Scope scope;
+  p::CPUPlace place;
   InitTensorsInScope(scope, place);
 
-  paddle::framework::AttributeMap attrs;
+  f::AttributeMap attrs;
   attrs.insert({"endpoints", std::vector<std::string>({"127.0.0.1:6174"})});
   attrs.insert({"epmap", std::vector<std::string>({"127.0.0.1:6174"})});
-  auto send_op = paddle::framework::OpRegistry::CreateOp(
-      "send", {{"X", {"x1"}}}, {{"Out", {"x0"}}}, attrs);
+  auto send_op = f::OpRegistry::CreateOp("send", {{"X", {"x1"}}},
+                                         {{"Out", {"Out"}}}, attrs);
   send_op->Run(scope, place);
 
   auto in_var = scope.Var("x1");
-  auto tensor = in_var->GetMutable<paddle::framework::LoDTensor>();
+  auto tensor = in_var->GetMutable<f::LoDTensor>();
   float *expected = tensor->data<float>();
-  auto out_var = scope.Var("x0");
-  auto target = out_var->GetMutable<paddle::framework::LoDTensor>();
+  auto out_var = scope.Var("Out");
+  auto target = out_var->GetMutable<f::LoDTensor>();
   // x1 * 2 == x0
   EXPECT_NE(target->memory_size(), size_t(0));
   float *actual = target->data<float>();
   for (int64_t i = 0; i < target->numel(); ++i) {
     EXPECT_EQ(expected[i] * 2, actual[i]);
   }
+  recv_op->Stop();
+  server_thread.join();
+  recv_op.reset(nullptr);
+}
 
+TEST(SendRecvOp, CPUSparse) {
+  std::thread server_thread(StartServerNet, true);
+  sleep(3);  // wait server to start
+  // local net
+  f::Scope scope;
+  p::CPUPlace place;
+  p::CPUDeviceContext ctx(place);
+  InitSelectedRowsInScope(scope, place);
+  f::AttributeMap attrs;
+  attrs.insert({"endpoints", std::vector<std::string>({"127.0.0.1:6174"})});
+  attrs.insert({"epmap", std::vector<std::string>({"127.0.0.1:6174"})});
+  auto send_op = f::OpRegistry::CreateOp("send", {{"X", {"x1"}}},
+                                         {{"Out", {"Out"}}}, attrs);
+  send_op->Run(scope, place);
+
+  auto x0 = scope.Var("x0")->GetMutable<f::SelectedRows>();
+  auto x1 = scope.Var("x1")->GetMutable<f::SelectedRows>();
+  auto out = scope.Var("Out")->GetMutable<f::SelectedRows>();
+  auto actual = out->mutable_value();
+
+  std::unique_ptr<f::SelectedRows> expect{new f::SelectedRows()};
+  auto expect_value = expect->mutable_value();
+  expect_value->mutable_data<float>(f::make_ddim({5, 10}), place);
+
+  m::SelectedRowsAdd<p::CPUDeviceContext, float> add_functor;
+  add_functor(ctx, *x0, *x1, expect.get());
+
+  EXPECT_EQ(actual->numel(), expect_value->numel());
+  EXPECT_EQ(out->rows().size(), x0->rows().size() + x1->rows().size());
+
+  for (int64_t i = 0; i < expect_value->numel(); ++i) {
+    EXPECT_EQ(expect_value->mutable_data<float>(place)[i],
+              actual->mutable_data<float>(place)[i]);
+  }
   recv_op->Stop();
   server_thread.join();
-  // recv_op.reset();
+  recv_op.reset();
 }