refine code style for async_executor.h and async_executor.cc

paddle/fluid/framework/async_executor.cc

@@ -66,15 +66,20 @@ void PrepareReaders(std::vector<std::shared_ptr<DataFeed>>& readers,  // NOLINT
 }
 
 void AsyncExecutor::InitServer(const std::string& dist_desc, int index) {
-    _pslib_ptr = std::shared_ptr<paddle::distributed::PSlib>(new paddle::distributed::PSlib());
-    _pslib_ptr->init_server(dist_desc, index);//TODO done
-
+    _pslib_ptr =
+        std::shared_ptr<paddle::distributed::PSlib>(
+            new paddle::distributed::PSlib());
+    _pslib_ptr->init_server(dist_desc, index);
     InitParamConfig();
 }
 
-void AsyncExecutor::InitWorker(const std::string& dist_desc, std::vector<uint64_t>& host_sign_list, int node_num, int index) {
-    _pslib_ptr = std::shared_ptr<paddle::distributed::PSlib>(new paddle::distributed::PSlib());
-    _pslib_ptr->init_worker(dist_desc, host_sign_list.data(), node_num, index);//TODO done
+void AsyncExecutor::InitWorker(const std::string& dist_desc,
+                               const std::vector<uint64_t>& host_sign_list,
+                               int node_num, int index) {
+    _pslib_ptr = std::shared_ptr<paddle::distributed::PSlib>(
+        new paddle::distributed::PSlib());
+    _pslib_ptr->init_worker(
+        dist_desc, host_sign_list.data(), node_num, index);
 
     InitParamConfig();
 }
@@ -87,43 +92,65 @@ void AsyncExecutor::StopServer() {
     _pslib_ptr->stop_server();
 }
 
-void AsyncExecutor::GatherServers(std::vector<uint64_t>& host_sign_list, int node_num) {
+void AsyncExecutor::GatherServers(
+    std::vector<uint64_t>& host_sign_list, int node_num) {
     _pslib_ptr->gather_servers(host_sign_list.data(), node_num);
 }
 
 void AsyncExecutor::InitParamConfig() {
-    for (int i = 0; i < _pslib_ptr->get_param()->server_param().downpour_server_param().downpour_table_param_size(); ++i) {
-        if (_pslib_ptr->get_param()->server_param().downpour_server_param().downpour_table_param(i).table_class().find("SparseTable") != -1) {
-            _param_config.fea_dim = _pslib_ptr->get_param()->server_param().downpour_server_param().downpour_table_param(i).accessor().fea_dim(); //TODO
+    for (int i = 0; i <
+        _pslib_ptr->get_param()->server_param().\
+                 downpour_server_param().\
+                 downpour_table_param_size();
+         ++i) {
+        if (_pslib_ptr->get_param()->server_param().\
+            downpour_server_param().downpour_table_param(i).\
+            table_class().find("SparseTable") != -1) {
+            _param_config.fea_dim = _pslib_ptr->get_param()->server_param().\
+                                    downpour_server_param().\
+                                    downpour_table_param(i).\
+                                    accessor().fea_dim();
             break;
         }
     }
-    _param_config.slot_dim = _param_config.fea_dim - 2; //TODO
-    _param_config.tmp_push_dense_wait_times = (int32_t)(_pslib_ptr->get_param()->trainer_param().push_dense_per_batch());
-    _param_config.tmp_push_sparse_wait_times = (int32_t)(_pslib_ptr->get_param()->trainer_param().push_sparse_per_batch());
-
-    for (auto t = 0u; t < _pslib_ptr->get_param()->trainer_param().skip_op_size(); ++t) {
-        _param_config.skip_op.push_back(_pslib_ptr->get_param()->trainer_param().skip_op(t));
+    _param_config.slot_dim = _param_config.fea_dim - 2;
+    _param_config.tmp_push_dense_wait_times = static_cast<int32_t>(
+        _pslib_ptr->get_param()->trainer_param().push_dense_per_batch());
+    _param_config.tmp_push_sparse_wait_times = static_cast<int32_t>(
+        _pslib_ptr->get_param()->trainer_param().push_sparse_per_batch());
+
+    for (auto t = 0u;
+         t < _pslib_ptr->get_param()->trainer_param().skip_op_size();
+         ++t) {
+        _param_config.skip_op.push_back(
+            _pslib_ptr->get_param()->trainer_param().skip_op(t));
     }
-    //sparse
-    for (auto t = 0u; t < _pslib_ptr->get_param()->trainer_param().sparse_table_size(); ++t) {
+
+    for (auto t = 0u;
+         t < _pslib_ptr->get_param()->trainer_param().sparse_table_size();
+         ++t) {
         auto& table = _pslib_ptr->get_param()->trainer_param().sparse_table(t);
         std::vector<std::string> tmp_sparse_variable_name;
         for (int i = 0u; i < table.slot_value_size(); ++i) {
             tmp_sparse_variable_name.push_back(table.slot_value(i));
-            _param_config.slot_alias_to_table[table.slot_key(i)] = table.table_id();
+            _param_config.slot_alias_to_table[table.slot_key(i)] =
+                table.table_id();
         }
         std::vector<std::string> tmp_sparse_gradient_variable_name;
         for (auto i = 0u; i < table.slot_gradient_size(); ++i) {
             tmp_sparse_gradient_variable_name.push_back(
                     table.slot_gradient(i));
         }
-        _param_config.slot_input_vec[table.table_id()] = std::move(tmp_sparse_variable_name);
-        _param_config.gradient_var[table.table_id()] = std::move(tmp_sparse_gradient_variable_name);
+        _param_config.slot_input_vec[table.table_id()] =
+            std::move(tmp_sparse_variable_name);
+        _param_config.gradient_var[table.table_id()] =
+            std::move(tmp_sparse_gradient_variable_name);
         _param_config.sparse_table_id.push_back(table.table_id());
     }
-    //dense
-    for (auto t = 0u; t < _pslib_ptr->get_param()->trainer_param().dense_table_size(); ++t) {
+
+    for (auto t = 0u;
+         t < _pslib_ptr->get_param()->trainer_param().dense_table_size();
+         ++t) {
         auto& table = _pslib_ptr->get_param()->trainer_param().dense_table(t);
         std::vector<std::string> tmp_dense_variable_name;
         for (int i = 0u; i < table.dense_variable_name_size(); ++i) {
@@ -134,20 +161,18 @@ void AsyncExecutor::InitParamConfig() {
             tmp_dense_gradient_variable_name.push_back(
                     table.dense_gradient_variable_name(i));
         }
-        _param_config.dense_variable_name[table.table_id()] = std::move(tmp_dense_variable_name);
-        _param_config.dense_gradient_variable_name[table.table_id()] = std::move(tmp_dense_gradient_variable_name);
+        _param_config.dense_variable_name[table.table_id()] =
+            std::move(tmp_dense_variable_name);
+        _param_config.dense_gradient_variable_name[table.table_id()] =
+            std::move(tmp_dense_gradient_variable_name);
         _param_config.dense_table_id.push_back(table.table_id());
-        _param_config.dense_table_size.push_back(table.fea_dim()); //TODO
+        _param_config.dense_table_size.push_back(table.fea_dim());
     }
 }
 
 void AsyncExecutor::InitModel() {
-    //TODO only rank = 0 do this
-    //std::vector<int> all_dense_table_id; //TODO 
-    //all_dense_table_id.push_back(0); //done
-    for (auto table_id: _param_config.dense_table_id) {
+    for (auto table_id : _param_config.dense_table_id) {
         std::vector<paddle::ps::Region> regions;
-        //std::vector<std::string> variables;  //TODO
         for (auto& t : _param_config.dense_variable_name[table_id]) {
             Variable* var = root_scope_->FindVar(t);
             CHECK(var != nullptr) << "var[" << t << "] not found";
@@ -169,13 +194,15 @@ void AsyncExecutor::InitModel() {
             regions.emplace_back(std::move(reg));
         }
 
-        auto push_status = _pslib_ptr->_worker_ptr->push_dense_param(regions.data(), regions.size(), table_id);
+        auto push_status =
+            _pslib_ptr->_worker_ptr->push_dense_param(
+                regions.data(), regions.size(), table_id);
         push_status.wait();
         auto status = push_status.get();
         if (status != 0) {
             LOG(FATAL) << "push dense param failed, status[" << status << "]";
             exit(-1);
-        } 
+        }
     }
 }
 
@@ -185,7 +212,7 @@ void AsyncExecutor::SaveModel(const std::string& path) {
     ret = _pslib_ptr->_worker_ptr->save(path, 0);
     ret.wait();
     int32_t feasign_cnt = ret.get();
-    if (feasign_cnt == -1) { // TODO should be feasign_cnt < 0, because server bug
+    if (feasign_cnt == -1) {  // (colourful-tree) TODO should be feasign_cnt < 0
         LOG(FATAL) << "save model failed";
         exit(-1);
     }
@@ -195,13 +222,13 @@ void AsyncExecutor::PrepareDenseThread(const std::string& mode) {
     if (mode == "mpi") {
         DensePullThreadParam param;
         param.ps_client = _pslib_ptr->_worker_ptr;;
-        param.threshold = 1;//GlobalConfig::instance().pull_dense_per_batch; //TODO
+        param.threshold = 1;
         param.training_thread_num = actual_thread_num;
         param.root_scope = root_scope_;
-        //param.dense_params = &GlobalConfig::instance().dense_variable_name; //TODO
         param.dense_params = &_param_config.dense_variable_name;
 
-        _pull_dense_thread = std::shared_ptr<DensePullThread>(new DensePullThread(param));
+        _pull_dense_thread = std::shared_ptr<DensePullThread>(
+            new DensePullThread(param));
         _pull_dense_thread->start();
     }
 }

paddle/fluid/framework/async_executor.h

@@ -14,6 +14,7 @@ limitations under the License. */
 
 #pragma once
 
+#include <time.h>
 #include <map>
 #include <memory>
 #include <mutex>  // NOLINT
@@ -22,8 +23,7 @@ limitations under the License. */
 #include <thread>  // NOLINT
 #include <typeinfo>
 #include <vector>
-#include <random> //local_random_engine
-#include <time.h> //local_random_engine
+#include <random>  // local_random_engine
 #include "paddle/fluid/framework/data_feed.pb.h"
 #include "paddle/fluid/framework/executor.h"
 #include "paddle/fluid/framework/executor_thread_worker.h"
@@ -43,9 +43,10 @@ inline std::default_random_engine& local_random_engine() {
     struct engine_wrapper_t {
         std::default_random_engine engine;
         engine_wrapper_t() {
-            static std::atomic<unsigned long> x(0);
-            std::seed_seq sseq = {x++, x++, x++, (unsigned long)(current_realtime() * 1000)};
-            engine.seed(sseq);
+          static std::atomic<uint64> x(0);
+          std::seed_seq sseq = {x++, x++, x++,
+                                static_cast<uint64>(current_realtime() * 1000)};
+          engine.seed(sseq);
         }
     };
     thread_local engine_wrapper_t r;
@@ -61,18 +62,20 @@ class AsyncExecutor {
                    const std::vector<std::string>& filelist,
                    const int thread_num,
                    const std::vector<std::string>& fetch_names,
-                   const std::string& mode, 
+                   const std::string& mode,
                    const bool debug = false);
-  //void ConfigPslib(const char* dist_desc, uint64_t* host_sign_list, int node_num, int index);
   void InitServer(const std::string& dist_desc, int index);
-  void InitWorker(const std::string& dist_desc, std::vector<uint64_t>& host_sign_list, int node_num, int index);
-  //void ConfigWorker() {}
+  void InitWorker(
+      const std::string& dist_desc,
+      const std::vector<uint64_t>& host_sign_list,
+      int node_num, int index);
   uint64_t StartServer();
   void StopServer();
-  void GatherServers(std::vector<uint64_t>& host_sign_list, int node_num);
+  void GatherServers(const std::vector<uint64_t>& host_sign_list, int node_num);
   void InitModel();
   void SaveModel(const std::string& path);
   void InitParamConfig();
+
  private:
   void CreateThreads(ExecutorThreadWorker* worker,
                      const ProgramDesc& main_program,
@@ -81,6 +84,7 @@ class AsyncExecutor {
                      Scope* root_scope, const int thread_index,
                      const bool debug);
   void PrepareDenseThread(const std::string& mode);
+
  public:
   std::shared_ptr<paddle::distributed::PSlib>  _pslib_ptr;
   std::shared_ptr<DensePullThread>  _pull_dense_thread;
@@ -88,6 +92,7 @@ class AsyncExecutor {
   platform::Place place_;
   
   AsyncWorkerParamConfig _param_config;
+
  private:
   int actual_thread_num;