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@ -45,7 +45,7 @@ framework::BlockDesc* AppendPrefetchBlcok(framework::ProgramDesc* program) {
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op->SetOutput("Out", {"out"});
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auto& out = *root_block->Var("out");
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out.SetType(framework::proto::VarType::LOD_TENSOR);
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out.SetType(framework::proto::VarType::SELECTED_ROWS);
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out.SetShape({10, 10});
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return block;
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@ -53,35 +53,37 @@ framework::BlockDesc* AppendPrefetchBlcok(framework::ProgramDesc* program) {
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void CreateVarsOnScope(framework::Scope* scope, platform::CPUPlace* place) {
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auto w_var = scope->Var("w");
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auto w = w_var->GetMutable<framework::LoDTensor>();
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w->Resize({10, 10});
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w->mutable_data<float>(*place);
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w_var->GetMutable<framework::SelectedRows>();
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auto out_var = scope->Var("out");
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auto out = out_var->GetMutable<framework::LoDTensor>();
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out->Resize({5, 10});
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out->mutable_data<float>(*place);
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out_var->GetMutable<framework::SelectedRows>();
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auto ids_var = scope->Var("ids");
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auto ids = ids_var->GetMutable<framework::LoDTensor>();
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ids->Resize({5, 1});
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ids_var->GetMutable<framework::SelectedRows>();
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}
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void InitTensorsOnClient(framework::Scope* scope, platform::CPUPlace* place) {
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void InitTensorsOnClient(framework::Scope* scope, platform::CPUPlace* place,
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int64_t rows_numel) {
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CreateVarsOnScope(scope, place);
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auto ids = scope->Var("ids")->GetMutable<framework::LoDTensor>();
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auto ptr = ids->mutable_data<int64_t>(*place);
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for (int64_t i = 0; i < ids->numel(); ++i) {
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ptr[i] = i * 2;
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}
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auto ids_var = scope->Var("ids")->GetMutable<framework::SelectedRows>();
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auto rows = ids_var->mutable_rows();
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for (int64_t i = 0; i < rows_numel; ++i) rows->push_back(i * 2);
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ids_var->mutable_value()->Resize({rows_numel, 1});
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ids_var->mutable_value()->mutable_data<float>(*place);
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}
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void InitTensorsOnServer(framework::Scope* scope, platform::CPUPlace* place) {
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void InitTensorsOnServer(framework::Scope* scope, platform::CPUPlace* place,
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int64_t rows_numel) {
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CreateVarsOnScope(scope, place);
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auto w_var = scope->Var("w");
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auto w = w_var->GetMutable<framework::LoDTensor>();
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auto ptr = w->mutable_data<float>(*place);
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for (int64_t i = 0; i < w->numel(); ++i) {
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auto w = scope->Var("w")->GetMutable<framework::SelectedRows>();
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auto rows = w->mutable_rows();
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for (int64_t i = 0; i < rows_numel; ++i) rows->push_back(i);
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auto w_value = w->mutable_value();
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w_value->Resize({rows_numel, 10});
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auto ptr = w_value->mutable_data<float>(*place);
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for (int64_t i = 0; i < w_value->numel(); ++i) {
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ptr[i] = static_cast<float>(i / 10);
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}
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}
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@ -94,7 +96,7 @@ void StartServer(const std::string& endpoint) {
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framework::Executor exe(place);
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platform::CPUDeviceContext ctx(place);
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auto* block = AppendPrefetchBlcok(&program);
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InitTensorsOnServer(&scope, &place);
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InitTensorsOnServer(&scope, &place, 10);
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rpc_service_->SetProgram(&program);
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rpc_service_->SetPrefetchBlkdId(block->ID());
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@ -107,15 +109,14 @@ void StartServer(const std::string& endpoint) {
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TEST(PREFETCH, CPU) {
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// start up a server instance backend
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// TODO(Yancey1989): Need to start a server with optimize blocks and
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// prefetch blocks.
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std::thread server_thread(StartServer, "127.0.0.1:8889");
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sleep(2);
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framework::Scope scope;
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platform::CPUPlace place;
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platform::CPUDeviceContext ctx(place);
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// create var on local scope
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InitTensorsOnClient(&scope, &place);
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int64_t rows_numel = 5;
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InitTensorsOnClient(&scope, &place, rows_numel);
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std::string in_var_name("ids");
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std::string out_var_name("out");
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@ -124,18 +125,16 @@ TEST(PREFETCH, CPU) {
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out_var_name);
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client.Wait();
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auto out_var = scope.Var(out_var_name);
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auto out = out_var->Get<framework::LoDTensor>();
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// auto out_var = scope.Var(out_var_name);
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auto var = scope.Var(out_var_name);
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auto value = var->GetMutable<framework::SelectedRows>()->value();
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auto ptr = value.mutable_data<float>(place);
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auto out_ptr = out.data<float>();
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rpc_service_->ShutDown();
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server_thread.join();
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rpc_service_.reset(nullptr);
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EXPECT_EQ(out.dims().size(), 2);
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EXPECT_EQ(out_ptr[0], static_cast<float>(0));
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EXPECT_EQ(out_ptr[0 + 1 * out.dims()[1]], static_cast<float>(2));
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EXPECT_EQ(out_ptr[0 + 2 * out.dims()[1]], static_cast<float>(4));
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EXPECT_EQ(out_ptr[0 + 3 * out.dims()[1]], static_cast<float>(6));
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EXPECT_EQ(out_ptr[0 + 4 * out.dims()[1]], static_cast<float>(8));
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for (int64_t i = 0; i < rows_numel; ++i) {
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EXPECT_EQ(ptr[0 + i * value.dims()[1]], static_cast<float>(i * 2));
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}
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}
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