// Copyright (c) 2019 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. #include #include #include #ifdef BCLOUD #include // bthread_set_worker_startfn #else #include // bthread_set_worker_startfn #endif #include #include #include "core/predictor/common/constant.h" #include "core/predictor/common/inner_common.h" #include "core/predictor/framework/manager.h" #include "core/predictor/framework/resource.h" #include "core/predictor/framework/server.h" #include "core/predictor/framework/service.h" #include "core/predictor/framework/workflow.h" using baidu::paddle_serving::predictor::ServerManager; using baidu::paddle_serving::predictor::WorkflowManager; using baidu::paddle_serving::predictor::InferServiceManager; using baidu::paddle_serving::predictor::Resource; using baidu::paddle_serving::predictor::FLAGS_workflow_path; using baidu::paddle_serving::predictor::FLAGS_workflow_file; using baidu::paddle_serving::predictor::FLAGS_inferservice_path; using baidu::paddle_serving::predictor::FLAGS_inferservice_file; using baidu::paddle_serving::predictor::FLAGS_logger_path; using baidu::paddle_serving::predictor::FLAGS_logger_file; using baidu::paddle_serving::predictor::FLAGS_resource_path; using baidu::paddle_serving::predictor::FLAGS_resource_file; using baidu::paddle_serving::predictor::FLAGS_general_model_path; using baidu::paddle_serving::predictor::FLAGS_general_model_file; using baidu::paddle_serving::predictor::FLAGS_reload_interval_s; using baidu::paddle_serving::predictor::FLAGS_port; using baidu::paddle_serving::configure::InferServiceConf; using baidu::paddle_serving::configure::read_proto_conf; void print_revision(std::ostream& os, void*) { #if defined(PDSERVING_VERSION) os << PDSERVING_VERSION; #else os << "undefined"; #endif #if defined(PDSERVING_BUILDTIME) os << ", BuildAt: " << PDSERVING_BUILDTIME; #endif } static bvar::PassiveStatus s_predictor_revision( "predictor_revision", print_revision, NULL); DEFINE_bool(V, false, "print version, bool"); DEFINE_bool(g, false, "user defined gflag path"); DECLARE_string(flagfile); namespace bthread { extern pthread_mutex_t g_task_control_mutex; } pthread_mutex_t g_worker_start_fn_mutex = PTHREAD_MUTEX_INITIALIZER; void pthread_worker_start_fn() { while (pthread_mutex_lock(&g_worker_start_fn_mutex) != 0) { } // Try to avoid deadlock in bthread int lock_status = pthread_mutex_trylock(&bthread::g_task_control_mutex); if (lock_status == EBUSY || lock_status == EAGAIN) { pthread_mutex_unlock(&bthread::g_task_control_mutex); } Resource::instance().thread_initialize(); // Try to avoid deadlock in bthread if (lock_status == EBUSY || lock_status == EAGAIN) { while (pthread_mutex_lock(&bthread::g_task_control_mutex) != 0) { } } pthread_mutex_unlock(&g_worker_start_fn_mutex); } static void g_change_server_port() { InferServiceConf conf; if (read_proto_conf(FLAGS_inferservice_path.c_str(), FLAGS_inferservice_file.c_str(), &conf) != 0) { LOG(WARNING) << "failed to load configure[" << FLAGS_inferservice_path << "," << FLAGS_inferservice_file << "]."; return; } uint32_t port = conf.port(); if (port != 0) { FLAGS_port = port; LOG(INFO) << "use configure[" << FLAGS_inferservice_path << "/" << FLAGS_inferservice_file << "] port[" << port << "] instead of flags"; } return; } #ifdef UNIT_TEST int ut_main(int argc, char** argv) { #else int main(int argc, char** argv) { #endif google::ParseCommandLineFlags(&argc, &argv, true); if (FLAGS_V) { print_revision(std::cout, NULL); std::cout << std::flush; return 0; } if (!FLAGS_g) { google::SetCommandLineOption("flagfile", "conf/gflags.conf"); } google::ParseCommandLineFlags(&argc, &argv, true); g_change_server_port(); // initialize logger instance #ifdef BCLOUD logging::LoggingSettings settings; settings.logging_dest = logging::LOG_TO_FILE; std::string filename(argv[0]); filename = filename.substr(filename.find_last_of('/') + 1); settings.log_file = strdup((std::string("./log/") + filename + ".log").c_str()); settings.delete_old = logging::DELETE_OLD_LOG_FILE; logging::InitLogging(settings); logging::ComlogSinkOptions cso; cso.process_name = filename; cso.enable_wf_device = true; logging::ComlogSink::GetInstance()->Setup(&cso); #else if (FLAGS_log_dir == "") { FLAGS_log_dir = "./log"; } struct stat st_buf; int ret = 0; if ((ret = stat(FLAGS_log_dir.c_str(), &st_buf)) != 0) { mkdir(FLAGS_log_dir.c_str(), 0777); ret = stat(FLAGS_log_dir.c_str(), &st_buf); if (ret != 0) { LOG(WARNING) << "Log path " << FLAGS_log_dir << " not exist, and create fail"; return -1; } } google::InitGoogleLogging(strdup(argv[0])); FLAGS_logbufsecs = 0; FLAGS_logbuflevel = -1; #endif LOG(INFO) << "Succ initialize logger"; // initialize resource manager if (Resource::instance().initialize(FLAGS_resource_path, FLAGS_resource_file) != 0) { LOG(ERROR) << "Failed initialize resource, conf:" << FLAGS_resource_path << "/" << FLAGS_resource_file; return -1; } LOG(INFO) << "Succ initialize resource"; // initialize workflow manager if (WorkflowManager::instance().initialize(FLAGS_workflow_path, FLAGS_workflow_file) != 0) { LOG(ERROR) << "Failed initialize workflow manager, conf:" << FLAGS_workflow_path << "/" << FLAGS_workflow_file; return -1; } LOG(INFO) << "Succ initialize workflow"; // initialize service manager if (InferServiceManager::instance().initialize( FLAGS_inferservice_path, FLAGS_inferservice_file) != 0) { LOG(ERROR) << "Failed initialize infer service manager, conf:" << FLAGS_inferservice_path << "/" << FLAGS_inferservice_file; return -1; } LOG(INFO) << "Succ initialize inferservice"; int errcode = bthread_set_worker_startfn(pthread_worker_start_fn); if (errcode != 0) { LOG(ERROR) << "Failed call pthread worker start function, error_code[" << errcode << "]"; return -1; } LOG(INFO) << "Succ call pthread worker start function"; if (Resource::instance().cube_initialize(FLAGS_resource_path, FLAGS_resource_file) != 0) { LOG(ERROR) << "Failed initialize cube, conf: " << FLAGS_resource_path << "/" << FLAGS_resource_file; return -1; } LOG(INFO) << "Succ initialize cube"; #ifndef BCLOUD if (Resource::instance().general_model_initialize( FLAGS_general_model_path, FLAGS_general_model_file) != 0) { LOG(ERROR) << "Failed to initialize general model conf: " << FLAGS_general_model_path << "/" << FLAGS_general_model_file; return -1; } LOG(INFO) << "Succ initialize general model"; // FATAL messages are output to stderr FLAGS_stderrthreshold = 3; #endif if (ServerManager::instance().start_and_wait() != 0) { LOG(ERROR) << "Failed start server and wait!"; return -1; } LOG(INFO) << "Succ start service manager"; if (InferServiceManager::instance().finalize() != 0) { LOG(ERROR) << "Failed finalize infer service manager."; } if (WorkflowManager::instance().finalize() != 0) { LOG(ERROR) << "Failed finalize workflow manager"; } if (Resource::instance().finalize() != 0) { LOG(ERROR) << "Failed finalize resource manager"; } #ifdef BCLOUD #else google::ShutdownGoogleLogging(); #endif LOG(INFO) << "Paddle Inference Server exit successfully!"; return 0; }