diff --git a/CMakeLists.txt b/CMakeLists.txt index 83f9ca4c7dd09b428863f5492996f355fa4b0f07..544564e050bad8b3b95a27941dbbe57dd5b3da86 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -122,3 +122,6 @@ add_subdirectory(inferencer-fluid-gpu) endif() add_subdirectory(demo-serving) endif() + +# Paddle Serving Solutions +add_subdirectory(elastic-ctr) diff --git a/demo-serving/scripts/start.sh b/demo-serving/scripts/start.sh deleted file mode 100755 index 5083ba04dbbb29ec0c07428a7e04912ec68120e5..0000000000000000000000000000000000000000 --- a/demo-serving/scripts/start.sh +++ /dev/null @@ -1 +0,0 @@ -/home/work/image-class/bin/image_class --workflow_path=/home/work/image-class/conf/ --inferservice_path=/home/work/image-class/conf/ --logger_path=/home/work/image-class/conf/ --resource_path=/home/work/image-class/conf/ diff --git a/elastic-ctr/CMakeLists.txt b/elastic-ctr/CMakeLists.txt new file mode 100644 index 0000000000000000000000000000000000000000..efaf744d946b6a9336e5207918763b7852512649 --- /dev/null +++ b/elastic-ctr/CMakeLists.txt @@ -0,0 +1,2 @@ +add_subdirectory(client) +add_subdirectory(serving) diff --git a/elastic-ctr/client/CMakeLists.txt b/elastic-ctr/client/CMakeLists.txt new file mode 100644 index 0000000000000000000000000000000000000000..3224b1c716094119a178d5e0311b1264634e17c9 --- /dev/null +++ b/elastic-ctr/client/CMakeLists.txt @@ -0,0 +1,22 @@ +include(proto/CMakeLists.txt) + +file(GLOB sdk_cpp_srcs ${CMAKE_SOURCE_DIR}/sdk-cpp/src/*.cpp) +list(APPEND elasticctr_srcs ${elastic_ctr_cpp_srcs}) +list(APPEND elasticctr_srcs ${sdk_cpp_srcs}) +list(APPEND elasticctr_srcs + ${CMAKE_CURRENT_LIST_DIR}/api/elastic_ctr_api.cpp) + +add_library(elasticctr ${elasticctr_srcs}) +target_link_libraries(elasticctr brpc configure protobuf leveldb) + +add_executable(elastic_ctr_demo ${CMAKE_CURRENT_LIST_DIR}/demo/demo.cpp) +target_link_libraries(elastic_ctr_demo elasticctr -lpthread -lcrypto -lm -lrt -lssl -ldl -lz) + +# install +install(TARGETS elastic_ctr_demo + RUNTIME DESTINATION + ${PADDLE_SERVING_INSTALL_DIR}/elastic_ctr/client/bin) +install(DIRECTORY ${CMAKE_CURRENT_LIST_DIR}/demo/conf DESTINATION + ${PADDLE_SERVING_INSTALL_DIR}/elastic_ctr/client/) +install(DIRECTORY ${CMAKE_CURRENT_LIST_DIR}/demo/data/ctr_prediction DESTINATION + ${PADDLE_SERVING_INSTALL_DIR}/elastic_ctr/client/data) diff --git a/elastic-ctr/client/api/elastic_ctr_api.cpp b/elastic-ctr/client/api/elastic_ctr_api.cpp new file mode 100644 index 0000000000000000000000000000000000000000..c568c32e250a8f1a4eff7dcb9a9ae8c53871fe86 --- /dev/null +++ b/elastic-ctr/client/api/elastic_ctr_api.cpp @@ -0,0 +1,289 @@ +// 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 "elastic-ctr/client/api/elastic_ctr_api.h" +#include +#include +#include +#include +#include + +namespace baidu { +namespace paddle_serving { +namespace elastic_ctr { + +const int VARIABLE_NAME_LEN = 256; + +static void thread_resource_delete(void *d) { +#if 1 + LOG(INFO) << "thread_resource_delete on " << bthread_self(); +#endif + delete static_cast(d); +} + +std::set ElasticCTRPredictorApi::slot_names_; + +int ThreadResource::clear() { + request_.clear_instances(); + response_.clear_predictions(); + + for (auto it : instance_map_) { + delete it.second; + } + return 0; +} + +ReqInstance *ThreadResource::add_instance() { + ReqInstance *instance = request_.add_instances(); + + InstanceInfo *instance_info = new InstanceInfo(); + instance_map_[instance] = instance_info; + + return instance; +} + +int ThreadResource::add_slot(ReqInstance *instance, + const std::string &slot_name, + uint64_t value) { + auto instance_it = instance_map_.find(instance); + if (instance_it == instance_map_.end()) { + return -1; + } + + InstanceInfo *instance_info = instance_it->second; + + auto slot_it = instance_info->slot_map_.find(slot_name); + Slot *slot = NULL; + + if (slot_it == instance_info->slot_map_.end()) { + slot = instance->add_slots(); + instance_info->slot_map_[slot_name] = slot; + } else { + slot = slot_it->second; + } + slot->set_slot_name(slot_name); + slot->add_feasigns(value); + + return 0; +} + +void ThreadResource::validate_request(const std::set &slot_names) { + for (auto it : instance_map_) { + ReqInstance *req_instance = it.first; + InstanceInfo *instance_info = it.second; + + for (auto slot_name : slot_names) { + if (instance_info->slot_map_.find(slot_name) == + instance_info->slot_map_.end()) { + LOG(INFO) << "Missing values for slot " << slot_name.c_str(); + add_slot(req_instance, slot_name, 0); + } + } + } +} + +void ElasticCTRPredictorApi::read_slot_conf(const char *path, + const char *slot_conf_file) { + struct stat stat_buf; + char name[VARIABLE_NAME_LEN]; + snprintf(name, VARIABLE_NAME_LEN, "%s/%s", path, slot_conf_file); + if (stat(name, &stat_buf) != 0) { + LOG(ERROR) << "Error stating file" << name; + return; + } + + std::ifstream fs(name); + for (std::string line; std::getline(fs, line);) { + slot_names_.insert(line); + } + +#if 1 + for (auto x : slot_names_) { + LOG(INFO) << "slot: " << x.c_str(); + } +#endif +} + +int ElasticCTRPredictorApi::init(const char *path, + const char *slot_conf_file, + const char *serving_conf_file) { + api_.create(path, serving_conf_file); + read_slot_conf(path, slot_conf_file); + + // Thread-local storage + if (pthread_key_create(&tls_bspec_key_, thread_resource_delete) != 0) { + LOG(ERROR) << "unable to create tls_bthread_key of thrd_data"; + return -1; + } + + return 0; +} + +int ElasticCTRPredictorApi::thrd_initialize() { + api_.thrd_initialize(); + + ThreadResource *thread_resource = + reinterpret_cast(pthread_getspecific(tls_bspec_key_)); + if (thread_resource == NULL) { + thread_resource = new (std::nothrow) ThreadResource; + + if (thread_resource == NULL) { + LOG(ERROR) << "failed to create thread local resource"; + return -1; + } + + if (pthread_setspecific(tls_bspec_key_, thread_resource) != 0) { + LOG(ERROR) << "unable to set tls thread local resource"; + delete thread_resource; + thread_resource = NULL; + return -1; + } + } + + return 0; +} + +int ElasticCTRPredictorApi::thrd_clear() { + api_.thrd_clear(); + + ThreadResource *thread_resource = + reinterpret_cast(pthread_getspecific(tls_bspec_key_)); + if (thread_resource == NULL) { + if (thread_resource == NULL) { + LOG(ERROR) << "ERROR: thread local resource is null"; + return -1; + } + } + + if (thread_resource->clear() != 0) { + LOG(ERROR) << "ElasticCTRPredictorApi: thrd_clear() fail"; + } + + return 0; +} + +int ElasticCTRPredictorApi::thrd_finalize() { + api_.thrd_finalize(); + return 0; +} + +void ElasticCTRPredictorApi::destroy() { + pthread_key_delete(tls_bspec_key_); + return; +} + +ReqInstance *ElasticCTRPredictorApi::add_instance() { + ThreadResource *thread_resource = + reinterpret_cast(pthread_getspecific(tls_bspec_key_)); + if (thread_resource == NULL) { + if (thread_resource == NULL) { + LOG(ERROR) << "ERROR: thread local resource is null"; + return NULL; + } + } + + ReqInstance *instance = thread_resource->add_instance(); + return instance; +} + +int ElasticCTRPredictorApi::add_slot(ReqInstance *instance, + const std::string slot_name, + int64_t value) { + ThreadResource *thread_resource = + reinterpret_cast(pthread_getspecific(tls_bspec_key_)); + if (thread_resource == NULL) { + if (thread_resource == NULL) { + LOG(ERROR) << "ERROR: thread local resource is null"; + return -1; + } + } + + if (slot_names_.find(slot_name) == slot_names_.end()) { + LOG(ERROR) << "Slot name not match with those in slot.conf: " + << slot_name.c_str(); + return -1; + } + + return thread_resource->add_slot(instance, slot_name, value); +} + +void ElasticCTRPredictorApi::validate_request() { + ThreadResource *thread_resource = + reinterpret_cast(pthread_getspecific(tls_bspec_key_)); + if (thread_resource == NULL) { + if (thread_resource == NULL) { + LOG(ERROR) << "ERROR: thread local resource is null"; + return; + } + } + + thread_resource->validate_request(slot_names_); +} + +int ElasticCTRPredictorApi::inference() { + ThreadResource *thread_resource = + reinterpret_cast(pthread_getspecific(tls_bspec_key_)); + if (thread_resource == NULL) { + if (thread_resource == NULL) { + LOG(ERROR) << "ERROR: thread local resource is null"; + return -1; + } + } + + Predictor *predictor = api_.fetch_predictor("ctr_prediction_service"); + if (!predictor) { + LOG(ERROR) << "Failed fetch predictor: ctr_prediction_service"; + return -1; + } + + validate_request(); + + int ret = predictor->inference(thread_resource->get_request(), + thread_resource->get_response()); + if (ret != 0) { + LOG(ERROR) << "Failed call predictor with req " + << thread_resource->get_request()->ShortDebugString(); + return ret; + } + + return 0; +} + +std::vector ElasticCTRPredictorApi::get_results() { + std::vector prediction_vec; + + ThreadResource *thread_resource = + reinterpret_cast(pthread_getspecific(tls_bspec_key_)); + if (thread_resource == NULL) { + if (thread_resource == NULL) { + LOG(ERROR) << "ERROR: thread local resource is null"; + return prediction_vec; + } + } + + Response *response = thread_resource->get_response(); + + for (int i = 0; i < response->predictions_size(); ++i) { + const ResInstance &res_instance = response->predictions(i); + Prediction prediction; + prediction.prob0 = res_instance.prob0(); + prediction.prob1 = res_instance.prob1(); + prediction_vec.push_back(prediction); + } + + return prediction_vec; +} +} // namespace elastic_ctr +} // namespace paddle_serving +} // namespace baidu diff --git a/elastic-ctr/client/api/elastic_ctr_api.h b/elastic-ctr/client/api/elastic_ctr_api.h new file mode 100644 index 0000000000000000000000000000000000000000..efc16c5b8a36aefbc742d4366ef36b9c69f578a6 --- /dev/null +++ b/elastic-ctr/client/api/elastic_ctr_api.h @@ -0,0 +1,107 @@ +// 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. + +#pragma once +#include +#include +#include +#include +#include "elastic-ctr/client/elastic_ctr_prediction.pb.h" +#include "sdk-cpp/include/common.h" +#include "sdk-cpp/include/predictor_sdk.h" + +using baidu::paddle_serving::sdk_cpp::Predictor; +using baidu::paddle_serving::sdk_cpp::PredictorApi; +using baidu::paddle_serving::predictor::elastic_ctr::Slot; +using baidu::paddle_serving::predictor::elastic_ctr::Request; +using baidu::paddle_serving::predictor::elastic_ctr::ReqInstance; +using baidu::paddle_serving::predictor::elastic_ctr::Response; +using baidu::paddle_serving::predictor::elastic_ctr::ResInstance; + +namespace baidu { +namespace paddle_serving { +namespace elastic_ctr { + +struct InstanceInfo { + std::map slot_map_; +}; + +class ThreadResource { + public: + int clear(); + + Request *get_request() { return &request_; } + + Response *get_response() { return &response_; } + + ReqInstance *add_instance(); + int add_slot(ReqInstance *instance, + const std::string &slot_name, + uint64_t value); + void validate_request(const std::set &slot_names); + + private: + Request request_; + Response response_; + + std::map instance_map_; +}; + +struct Prediction { + float prob0; + float prob1; +}; + +class ElasticCTRPredictorApi { + public: + ElasticCTRPredictorApi() {} + + int init(const char *path, + const char *slot_conf_file, + const char *serving_conf_file); + + int thrd_initialize(); + + int thrd_clear(); + + int thrd_finalize(); + + void destroy(); + + static ElasticCTRPredictorApi &instance() { + static ElasticCTRPredictorApi api; + return api; + } + + public: + ReqInstance *add_instance(); + int add_slot(ReqInstance *instance, + const std::string slot_name, + int64_t value); + int inference(); + std::vector get_results(); + + private: + static void read_slot_conf(const char *path, const char *slot_conf_file); + void validate_request(); + + private: + PredictorApi api_; + pthread_key_t tls_bspec_key_; + static std::set slot_names_; +}; + +} // namespace elastic_ctr +} // namespace paddle_serving +} // namespace baidu diff --git a/elastic-ctr/client/demo/conf/predictors.prototxt b/elastic-ctr/client/demo/conf/predictors.prototxt new file mode 100644 index 0000000000000000000000000000000000000000..61c304ccb7019ba94436f1b882fc945a18b5f367 --- /dev/null +++ b/elastic-ctr/client/demo/conf/predictors.prototxt @@ -0,0 +1,36 @@ +default_variant_conf { + tag: "default" + connection_conf { + connect_timeout_ms: 2000 + rpc_timeout_ms: 20000 + connect_retry_count: 2 + max_connection_per_host: 100 + hedge_request_timeout_ms: -1 + hedge_fetch_retry_count: 2 + connection_type: "pooled" + } + naming_conf { + cluster_filter_strategy: "Default" + load_balance_strategy: "la" + } + rpc_parameter { + compress_type: 0 + package_size: 20 + protocol: "baidu_std" + max_channel_per_request: 3 + } +} +predictors { + name: "ctr_prediction_service" + service_name: "baidu.paddle_serving.predictor.elastic_ctr.ElasticCTRPredictionService" + endpoint_router: "WeightedRandomRender" + weighted_random_render_conf { + variant_weight_list: "50" + } + variants { + tag: "var1" + naming_conf { + cluster: "list://127.0.0.1:8010" + } + } +} diff --git a/elastic-ctr/client/demo/data/ctr_prediction/data.txt b/elastic-ctr/client/demo/data/ctr_prediction/data.txt new file mode 100644 index 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b/elastic-ctr/client/demo/demo.cpp @@ -0,0 +1,180 @@ +// 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 +#include +#include +#include +#include +#include // NOLINT +#include "elastic-ctr/client/api/elastic_ctr_api.h" + +using baidu::paddle_serving::elastic_ctr::ElasticCTRPredictorApi; +using baidu::paddle_serving::elastic_ctr::Prediction; + +DEFINE_int32(batch_size, 10, "Infernce batch_size"); + +DEFINE_string(test_file, "", "test file"); + +const int VARIABLE_NAME_LEN = 256; +const int CTR_EMBEDDING_TABLE_SIZE = 400000001; + +struct Sample { + std::map> slots; +}; + +std::vector samples; + +int read_samples(const char* file) { + std::ifstream fs(file); + + for (std::string line; std::getline(fs, line);) { + std::vector tokens; + std::stringstream ss(line); + std::string token; + + Sample sample; + + while (std::getline(ss, token, ' ')) { + tokens.push_back(token); + } + + if (tokens.size() <= 3) { + continue; + } + + for (std::size_t i = 2; i < tokens.size(); ++i) { + std::size_t pos = tokens[i].find(':'); + if (pos == std::string::npos) { + continue; + } + + uint64_t x = std::strtoull(tokens[i].substr(0, pos).c_str(), NULL, 10); + std::string slot_name = tokens[i].substr(pos + 1); + + if (sample.slots.find(slot_name) == sample.slots.end()) { + std::vector values; + values.push_back(x % 400000001); + sample.slots[slot_name] = values; + } else { + auto it = sample.slots.find(slot_name); + it->second.push_back(x); + } + } + + samples.push_back(sample); + } + + LOG(INFO) << "Samples size = " << samples.size(); + +#if 1 + for (std::size_t i = 0; i < samples.size(); ++i) { + LOG(INFO) << "=============Sample " << i << "========="; + for (auto slot : samples[i].slots) { + LOG(INFO) << "slot_name: " << slot.first.c_str(); + for (auto x : slot.second) { + LOG(INFO) << x; + } + } + LOG(INFO) << "========================================"; + } +#endif + return 0; +} + +int main(int argc, char** argv) { + google::ParseCommandLineFlags(&argc, &argv, true); + + ElasticCTRPredictorApi api; + +#ifdef BCLOUD + logging::LoggingSettings settings; + settings.logging_dest = logging::LOG_TO_FILE; + std::string log_filename(argv[0]); + log_filename = log_filename.substr(log_filename.find_last_of('/') + 1); + settings.log_file = (std::string("./log/") + log_filename + ".log").c_str(); + settings.delete_old = logging::DELETE_OLD_LOG_FILE; + logging::InitLogging(settings); + logging::ComlogSinkOptions cso; + cso.process_name = log_filename; + cso.enable_wf_device = true; + logging::ComlogSink::GetInstance()->Setup(&cso); +#else + struct stat st_buf; + int ret = 0; + if ((ret = stat("./log", &st_buf)) != 0) { + mkdir("./log", 0777); + ret = stat("./log", &st_buf); + if (ret != 0) { + LOG(WARNING) << "Log path ./log not exist, and create fail"; + return -1; + } + } + FLAGS_log_dir = "./log"; + google::InitGoogleLogging(strdup(argv[0])); + FLAGS_logbufsecs = 0; + FLAGS_logbuflevel = -1; +#endif + // predictor conf + if (api.init("./conf", "slot.conf", "predictors.prototxt") != 0) { + LOG(ERROR) << "Failed create predictors api!"; + return -1; + } + + api.thrd_initialize(); + + ret = read_samples(FLAGS_test_file.c_str()); + + std::size_t index = 0; + while (index < samples.size()) { + api.thrd_clear(); + + for (int i = 0; i < FLAGS_batch_size && index < samples.size(); ++i) { + ReqInstance* ins = api.add_instance(); + if (!ins) { + LOG(ERROR) << "Failed create req instance"; + return -1; + } + + for (auto slot : samples[index].slots) { + for (auto x : slot.second) { + api.add_slot(ins, slot.first.c_str(), x); + } + } + + ++index; + } + + Response res; + if (api.inference() != 0) { + LOG(ERROR) << "failed call predictor"; + return -1; + } + + std::vector ret = api.get_results(); +#if 1 + for (std::size_t i = 0; i < ret.size(); ++i) { + LOG(INFO) << "sample " << i << ": [" << ret[i].prob0 << ", " + << ret[i].prob1 << "]"; + } +#endif + } // end while + + api.thrd_finalize(); + + api.destroy(); + return 0; +} diff --git a/elastic-ctr/client/proto/CMakeLists.txt b/elastic-ctr/client/proto/CMakeLists.txt new file mode 100644 index 0000000000000000000000000000000000000000..b384d1d2159a91e9bd29626d2ae2ad13b594330d --- /dev/null +++ b/elastic-ctr/client/proto/CMakeLists.txt @@ -0,0 +1,5 @@ +FILE(GLOB protos ${CMAKE_CURRENT_LIST_DIR}/*.proto) +list(APPEND protos ${CMAKE_SOURCE_DIR}/predictor/proto/pds_option.proto + ${CMAKE_SOURCE_DIR}/predictor/proto/builtin_format.proto) +PROTOBUF_GENERATE_SERVING_CPP(FALSE PROTO_SRCS PROTO_HDRS ${protos}) +LIST(APPEND elastic_ctr_cpp_srcs ${PROTO_SRCS}) diff --git a/elastic-ctr/client/proto/elastic_ctr_prediction.proto b/elastic-ctr/client/proto/elastic_ctr_prediction.proto new file mode 100644 index 0000000000000000000000000000000000000000..8dfdd09835522dcb14e09e21407949caac85533e --- /dev/null +++ b/elastic-ctr/client/proto/elastic_ctr_prediction.proto @@ -0,0 +1,46 @@ +// 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. + +syntax = "proto2"; +import "pds_option.proto"; +import "builtin_format.proto"; +package baidu.paddle_serving.predictor.elastic_ctr; + +option cc_generic_services = true; + +message Slot { + required string slot_name = 1; + repeated int64 feasigns = 2; +}; + +message ReqInstance { repeated Slot slots = 1; }; + +message Request { repeated ReqInstance instances = 1; }; + +message ResInstance { + required float prob0 = 1; + required float prob1 = 2; +}; + +message Response { + repeated ResInstance predictions = 1; + required int64 err_code = 2; + optional string err_msg = 3; +}; + +service ElasticCTRPredictionService { + rpc inference(Request) returns (Response); + rpc debug(Request) returns (Response); + option (pds.options).generate_stub = true; +}; diff --git a/elastic-ctr/serving/CMakeLists.txt b/elastic-ctr/serving/CMakeLists.txt new file mode 100644 index 0000000000000000000000000000000000000000..9a5dfe6e39192762280a23a3fd87fcf60c616a24 --- /dev/null +++ b/elastic-ctr/serving/CMakeLists.txt @@ -0,0 +1,56 @@ +if (NOT EXISTS + ${CMAKE_CURRENT_LIST_DIR}/data/model/paddle/fluid/ctr_prediction) + execute_process(COMMAND wget --no-check-certificate + https://paddle-serving.bj.bcebos.com/data/ctr_prediction/ctr_prediction.tar.gz + --output-document + ${CMAKE_CURRENT_LIST_DIR}/data/model/paddle/fluid/ctr_prediction.tar.gz) + execute_process(COMMAND ${CMAKE_COMMAND} -E tar xzf + "${CMAKE_CURRENT_LIST_DIR}/data/model/paddle/fluid/ctr_prediction.tar.gz" + WORKING_DIRECTORY + ${CMAKE_CURRENT_LIST_DIR}/data/model/paddle/fluid) +endif() + +include_directories(SYSTEM ${CMAKE_CURRENT_LIST_DIR}/../kvdb/include) + +include(op/CMakeLists.txt) +include(proto/CMakeLists.txt) +add_executable(elastic_serving ${serving_srcs}) +add_dependencies(elastic_serving pdcodegen fluid_cpu_engine pdserving paddle_fluid cube-api) + +target_include_directories(elastic_serving PUBLIC + ${CMAKE_CURRENT_BINARY_DIR}/../../predictor + ) + +target_link_libraries(elastic_serving -Wl,--whole-archive fluid_cpu_engine + -Wl,--no-whole-archive) + +target_link_libraries(elastic_serving paddle_fluid ${paddle_depend_libs}) + +target_link_libraries(elastic_serving pdserving) +target_link_libraries(elastic_serving cube-api) + +target_link_libraries(elastic_serving kvdb rocksdb) + +target_link_libraries(elastic_serving -liomp5 -lmklml_intel -lmkldnn -lpthread + -lcrypto -lm -lrt -lssl -ldl -lz -lbz2) + +install(TARGETS elastic_serving + RUNTIME DESTINATION + ${PADDLE_SERVING_INSTALL_DIR}/elastic_ctr/serving/bin) +install(DIRECTORY ${CMAKE_CURRENT_LIST_DIR}/conf DESTINATION + ${PADDLE_SERVING_INSTALL_DIR}/elastic_ctr/serving/) +install(DIRECTORY ${CMAKE_CURRENT_LIST_DIR}/data DESTINATION + ${PADDLE_SERVING_INSTALL_DIR}/elastic_ctr/serving/) + +FILE(GLOB inc ${CMAKE_CURRENT_BINARY_DIR}/*.pb.h) +install(FILES ${inc} + DESTINATION ${PADDLE_SERVING_INSTALL_DIR}/include/serving) + +if (${WITH_MKL}) + install(FILES + ${CMAKE_BINARY_DIR}/third_party/install/Paddle/third_party/install/mklml/lib/libmklml_intel.so + ${CMAKE_BINARY_DIR}/third_party/install/Paddle/third_party/install/mklml/lib/libiomp5.so + ${CMAKE_BINARY_DIR}/third_party/install/Paddle/third_party/install/mkldnn/lib/libmkldnn.so + DESTINATION + ${PADDLE_SERVING_INSTALL_DIR}/elastic_ctr/serving/bin) +endif() diff --git a/elastic-ctr/serving/conf/cube.conf b/elastic-ctr/serving/conf/cube.conf new file mode 100644 index 0000000000000000000000000000000000000000..a462dd23376308a4e3f2f62b4b87d4a1a7acb9e4 --- /dev/null +++ b/elastic-ctr/serving/conf/cube.conf @@ -0,0 +1,15 @@ +[{ + "dict_name": "test_dict", + "shard": 2, + "dup": 1, + "timeout": 200, + "retry": 3, + "backup_request": 100, + "type": "ipport_list", + "load_balancer": "rr", + "nodes": [{ + "ipport_list": "list://xxx.xxx.xxx.xxx:8000" + },{ + "ipport_list": "list://xxx.xxx.xxx.xxx:8000" + }] +}] diff --git a/elastic-ctr/serving/conf/gflags.conf b/elastic-ctr/serving/conf/gflags.conf new file mode 100644 index 0000000000000000000000000000000000000000..b4eedcc8d9d554b4ce159456b0614b139aa979c2 --- /dev/null +++ b/elastic-ctr/serving/conf/gflags.conf @@ -0,0 +1,2 @@ +--enable_model_toolkit +--enable_cube=true diff --git a/elastic-ctr/serving/conf/model_toolkit.prototxt b/elastic-ctr/serving/conf/model_toolkit.prototxt new file mode 100644 index 0000000000000000000000000000000000000000..b1f6b5114b8006d9e749bc9b8fdd02206303a02a --- /dev/null +++ b/elastic-ctr/serving/conf/model_toolkit.prototxt @@ -0,0 +1,12 @@ +engines { + name: "ctr_prediction" + type: "FLUID_CPU_ANALYSIS_DIR" + reloadable_meta: "./data/model/paddle/fluid_time_file" + reloadable_type: "timestamp_ne" + model_data_path: "./data/model/paddle/fluid/ctr_prediction" + runtime_thread_num: 0 + batch_infer_size: 0 + enable_batch_align: 0 + sparse_param_service_type: REMOTE + sparse_param_service_table_name: "test_dict" +} diff --git a/elastic-ctr/serving/conf/resource.prototxt b/elastic-ctr/serving/conf/resource.prototxt new file mode 100644 index 0000000000000000000000000000000000000000..0a0d6678fe99a89517ba9855140c0c01f919742e --- /dev/null +++ b/elastic-ctr/serving/conf/resource.prototxt @@ -0,0 +1,3 @@ +model_toolkit_path: "./conf/" +model_toolkit_file: "model_toolkit.prototxt" +cube_config_file: "./conf/cube.conf" diff --git a/elastic-ctr/serving/conf/service.prototxt b/elastic-ctr/serving/conf/service.prototxt new file mode 100644 index 0000000000000000000000000000000000000000..4b9281707b8067dfb59d8e5c3be6cd3240ab0d2c --- /dev/null +++ b/elastic-ctr/serving/conf/service.prototxt @@ -0,0 +1,4 @@ +services { + name: "ElasticCTRPredictionService" + workflows: "workflow1" +} diff --git a/elastic-ctr/serving/conf/workflow.prototxt b/elastic-ctr/serving/conf/workflow.prototxt new file mode 100644 index 0000000000000000000000000000000000000000..fad65dc3cda76924a3cab8b17f79ae08f1131cc8 --- /dev/null +++ b/elastic-ctr/serving/conf/workflow.prototxt @@ -0,0 +1,8 @@ +workflows { + name: "workflow1" + workflow_type: "Sequence" + nodes { + name: "elastic_ctr_prediction_op" + type: "ElasticCTRPredictionOp" + } +} diff --git a/elastic-ctr/serving/data/model/paddle/fluid_reload_flag b/elastic-ctr/serving/data/model/paddle/fluid_reload_flag new file mode 100644 index 0000000000000000000000000000000000000000..a1866984b04a26a09bbfc4ef4f08dec5e38f818d --- /dev/null +++ b/elastic-ctr/serving/data/model/paddle/fluid_reload_flag @@ -0,0 +1,2 @@ +paddle fluid model +time:20180531 diff --git a/elastic-ctr/serving/data/model/paddle/fluid_time_file b/elastic-ctr/serving/data/model/paddle/fluid_time_file new file mode 100644 index 0000000000000000000000000000000000000000..4d9422cd37f6c51800055f1b1dc625e2c455fc6d --- /dev/null +++ b/elastic-ctr/serving/data/model/paddle/fluid_time_file @@ -0,0 +1,2 @@ +201805311000 +model paddle fluid diff --git a/elastic-ctr/serving/op/CMakeLists.txt b/elastic-ctr/serving/op/CMakeLists.txt new file mode 100644 index 0000000000000000000000000000000000000000..9287408e5e64fa284acbbdb18563703510114e87 --- /dev/null +++ b/elastic-ctr/serving/op/CMakeLists.txt @@ -0,0 +1,2 @@ +FILE(GLOB op_srcs ${CMAKE_CURRENT_LIST_DIR}/*.cpp) +LIST(APPEND serving_srcs ${op_srcs}) diff --git a/elastic-ctr/serving/op/elastic_ctr_prediction_op.cpp b/elastic-ctr/serving/op/elastic_ctr_prediction_op.cpp new file mode 100644 index 0000000000000000000000000000000000000000..04f8b7d81cdd42db20f83695540e130c7b348601 --- /dev/null +++ b/elastic-ctr/serving/op/elastic_ctr_prediction_op.cpp @@ -0,0 +1,440 @@ +// 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 "elastic-ctr/serving/op/elastic_ctr_prediction_op.h" +#include +#include +#include "cube/cube-api/include/cube_api.h" +#include "predictor/framework/infer.h" +#include "predictor/framework/kv_manager.h" +#include "predictor/framework/memory.h" + +// Flag where enable profiling mode +DECLARE_bool(enable_ctr_profiling); + +namespace baidu { +namespace paddle_serving { +namespace serving { + +using baidu::paddle_serving::predictor::MempoolWrapper; +using baidu::paddle_serving::predictor::elastic_ctr::Slot; +using baidu::paddle_serving::predictor::elastic_ctr::ResInstance; +using baidu::paddle_serving::predictor::elastic_ctr::Response; +using baidu::paddle_serving::predictor::elastic_ctr::ReqInstance; +using baidu::paddle_serving::predictor::elastic_ctr::Request; + +const int VARIABLE_NAME_LEN = 256; + +const int CTR_PREDICTION_DENSE_DIM = 13; +const int CTR_PREDICTION_EMBEDDING_SIZE = 10; + +bthread::Mutex ElasticCTRPredictionOp::mutex_; +int64_t ElasticCTRPredictionOp::cube_time_us_ = 0; +int32_t ElasticCTRPredictionOp::cube_req_num_ = 0; +int32_t ElasticCTRPredictionOp::cube_req_key_num_ = 0; + +void fill_response_with_message(Response *response, + int err_code, + std::string err_msg) { + if (response == NULL) { + LOG(ERROR) << "response is NULL"; + return; + } + + response->set_err_code(err_code); + response->set_err_msg(err_msg); + return; +} + +int ElasticCTRPredictionOp::inference() { + const Request *req = dynamic_cast(get_request_message()); + + TensorVector *in = butil::get_object(); + Response *res = mutable_data(); + + uint32_t sample_size = req->instances_size(); + if (sample_size <= 0) { + LOG(WARNING) << "No instances need to inference!"; + fill_response_with_message(res, -1, "Sample size invalid"); + return 0; + } + + // Verify all request instances have same slots + int slot_num = req->instances(0).slots_size(); +#if 1 + LOG(INFO) << "slot_num =" << slot_num; +#endif + for (int i = 1; i < req->instances_size(); ++i) { + if (req->instances(i).slots_size() != slot_num) { + LOG(WARNING) << "Req " << i + << " has different slot num with that of req 0"; + fill_response_with_message( + res, -1, "Req intance has varying slot numbers"); + } + } + + // Query cube API for sparse embeddings + std::vector keys; + std::vector values; + + // How to organize feasigns in the above `keys` vector: + // + // Assuming N instances, each instance having M feature slots: + // + // ins1: + // slot_1: ins1_slot1_1|ins1_slot1_2 slot2: ins1_slot2_1|ins1_slot2_2 + // + // ins2: + // slot_1: ins2_slot1_1 slot2: ins2_slot2_1|ins2_slot2_2 + // + // ... + // + // insN: + // slot_1: insN_slot1_1|insN_slot1_2 slot2: insN_slot2_1 + // + // We organize the features in such a way that all slot_1 features are before + // slot_2 features: + // + // ins1_slot1_1|ins1_slot1_2|ins2_slot1_1|...|insN_slot1_1|insN_slot1_2 + // ins1_slot2_1|ins1_slot2_2|ins2_slot2_1|ins2_slot2_2|...|insN_slot2_1 + // + // With this placement, after querying KV service, we can retrieve the + // embeddings for each feature slot from the returned `values` vector easily, + // as they are grouped togegher. + + // Level of details of each feature slot + std::vector> feature_slot_lods; + feature_slot_lods.resize(slot_num); + + // Number of feature signs in each slot + std::vector feature_slot_sizes; + feature_slot_sizes.resize(slot_num); + + // Iterate over each feature slot + for (int i = 0; i < slot_num; ++i) { + feature_slot_lods[i].push_back(0); + feature_slot_sizes[i] = 0; + + // Extract feature i values from each instance si + for (int si = 0; si < sample_size; ++si) { +#if 1 + LOG(INFO) << "slot " << i << " sample " << si; +#endif + const ReqInstance &req_instance = req->instances(si); + const Slot &slot = req_instance.slots(i); + feature_slot_lods[i].push_back(feature_slot_lods[i].back() + + slot.feasigns_size()); + feature_slot_sizes[i] += slot.feasigns_size(); + + for (int j = 0; j < slot.feasigns_size(); ++j) { + keys.push_back(slot.feasigns(j)); + } + } + } + +#if 0 + rec::mcube::CubeAPI *cube = rec::mcube::CubeAPI::instance(); + predictor::KVManager &kv_manager = predictor::KVManager::instance(); + const predictor::KVInfo *kvinfo = + kv_manager.get_kv_info(CTR_PREDICTION_MODEL_NAME); + if (kvinfo == NULL) { + LOG(ERROR) << "Sparse param service info not found for model " + << CTR_PREDICTION_MODEL_NAME + << ". Maybe forgot to specify sparse_param_service_type and " + << "sparse_param_service_table_name in " + << "conf/model_toolkit.prototxt"; + fill_response_with_message(res, -1, "Sparse param service info not found"); + return 0; + } + + std::string table_name; + if (kvinfo->sparse_param_service_type != configure::EngineDesc::NONE) { + table_name = kvinfo->sparse_param_service_table_name; + if (table_name.empty()) { + LOG(ERROR) << "sparse_param_service_table_name not specified. " + << "Please specify it in conf/model_toolkit.protxt for model " + << CTR_PREDICTION_MODEL_NAME; + fill_response_with_message( + res, -1, "sparse_param_service_table_name not specified"); + return 0; + } + } + + if (kvinfo->sparse_param_service_type == configure::EngineDesc::LOCAL) { + // Query local KV service + LOG(ERROR) << "Local kv service not supported for model " + << CTR_PREDICTION_MODEL_NAME; + + fill_response_with_message( + res, -1, "Local kv service not supported for this model"); + return 0; + } else if (kvinfo->sparse_param_service_type == + configure::EngineDesc::REMOTE) { + struct timeval start; + struct timeval end; + + int ret; + + gettimeofday(&start, NULL); + ret = cube->seek(table_name, keys, &values); + gettimeofday(&end, NULL); + uint64_t usec = + end.tv_sec * 1e6 + end.tv_usec - start.tv_sec * 1e6 - start.tv_usec; + + // Statistics + mutex_.lock(); + cube_time_us_ += usec; + ++cube_req_num_; + cube_req_key_num_ += keys.size(); + + if (cube_req_num_ >= 1000) { + LOG(INFO) << "Cube request count: " << cube_req_num_; + LOG(INFO) << "Cube request key count: " << cube_req_key_num_; + LOG(INFO) << "Cube request total time: " << cube_time_us_ << "us"; + LOG(INFO) << "Average " + << static_cast(cube_time_us_) / cube_req_num_ + << "us/req"; + LOG(INFO) << "Average " + << static_cast(cube_time_us_) / cube_req_key_num_ + << "us/key"; + + cube_time_us_ = 0; + cube_req_num_ = 0; + cube_req_key_num_ = 0; + } + mutex_.unlock(); + // Statistics end + + if (ret != 0) { + fill_response_with_message(res, -1, "Query cube for embeddings error"); + LOG(ERROR) << "Query cube for embeddings error"; + return 0; + } + } + + if (values.size() != keys.size()) { + LOG(ERROR) << "Sparse embeddings not ready; " + << "maybe forgot to set sparse_param_service_type and " + << "sparse_param_sevice_table_name for " + << CTR_PREDICTION_MODEL_NAME + << " in conf/model_toolkit.prototxt"; + fill_response_with_message( + res, -1, "Sparse param service not configured properly"); + return 0; + } + + for (int i = 0; i < keys.size(); ++i) { + std::ostringstream oss; + oss << keys[i] << ": "; + const char *value = (values[i].buff.data()); + if (values[i].buff.size() != + sizeof(float) * CTR_PREDICTION_EMBEDDING_SIZE) { + LOG(WARNING) << "Key " << keys[i] << " has values less than " + << CTR_PREDICTION_EMBEDDING_SIZE; + } + +#if 0 + for (int j = 0; j < values[i].buff.size(); ++j) { + oss << std::hex << std::uppercase << std::setw(2) << std::setfill('0') + << (static_cast(value[j]) & 0xff); + } + + LOG(INFO) << oss.str().c_str(); +#endif + } + + // Fill feature embedding into feed tensors + std::vector lod_tensors; + lod_tensors.resize(slot_num); + + const ReqInstance &instance = req->instances(0); + for (int i = 0; i < slot_num; ++i) { + paddle::PaddleTensor &lod_tensor = lod_tensors[i]; + + char name[VARIABLE_NAME_LEN]; + snprintf(name, + VARIABLE_NAME_LEN, + "embedding_%s.tmp_0", + instance.slots(i).slot_name().c_str()); + lod_tensor.name = std::string(name); + + lod_tensors[i].dtype = paddle::PaddleDType::INT64; + std::vector> &lod = lod_tensors[i].lod; + lod.resize(1); + lod[0].push_back(0); + } + + int base = 0; + + // Iterate over all slots + for (int i = 0; i < slot_num; ++i) { + paddle::PaddleTensor &lod_tensor = lod_tensors[i]; + std::vector> &lod = lod_tensor.lod; + + lod[0] = feature_slot_lods[i]; + + lod_tensor.shape = {lod[0].back(), CTR_PREDICTION_EMBEDDING_SIZE}; + lod_tensor.data.Resize(lod[0].back() * sizeof(float) * + CTR_PREDICTION_EMBEDDING_SIZE); + + int offset = 0; + // Copy all slot i feature embeddings to lod_tensor[i] + for (uint32_t j = 0; j < feature_slot_sizes[i]; ++j) { + float *data_ptr = static_cast(lod_tensor.data.data()) + offset; + + int idx = base + j; + if (values[idx].buff.size() != + sizeof(float) * CTR_PREDICTION_EMBEDDING_SIZE) { + LOG(ERROR) << "Embedding vector size not expected"; + fill_response_with_message( + res, -1, "Embedding vector size not expected"); + return 0; + } + + memcpy(data_ptr, values[idx].buff.data(), values[idx].buff.size()); + offset += CTR_PREDICTION_EMBEDDING_SIZE; + } + + in->push_back(lod_tensor); + + // Bump base counter + base += feature_slot_sizes[i]; + } +#else + + // Fill all tensors + std::vector lod_tensors; + lod_tensors.resize(slot_num); + + const ReqInstance &instance = req->instances(0); + for (int i = 0; i < slot_num; ++i) { + paddle::PaddleTensor &lod_tensor = lod_tensors[i]; + + lod_tensor.name = instance.slots(i).slot_name(); + + LOG(INFO) << "slot " << i << "name: " << lod_tensor.name.c_str(); + lod_tensors[i].dtype = paddle::PaddleDType::INT64; + } + + // Iterate over all slots + for (int i = 0; i < slot_num; ++i) { + paddle::PaddleTensor &lod_tensor = lod_tensors[i]; + std::vector> &lod = lod_tensor.lod; + + lod.push_back(feature_slot_lods[i]); + + lod_tensor.shape = {lod[0].back(), 1}; + lod_tensor.data.Resize(lod[0].back() * sizeof(uint64_t)); + + int offset = 0; + // Copy all slot i features to lod_tensor[i] + uint64_t *keys_block = keys.data(); + uint64_t *data_ptr = static_cast(lod_tensor.data.data()); + + memcpy(data_ptr, + keys_block + offset, + feature_slot_sizes[i] * sizeof(uint64_t)); + offset += feature_slot_sizes[i]; + + in->push_back(lod_tensor); + + // Bump base counter + offset += feature_slot_sizes[i]; + } +#endif + TensorVector *out = butil::get_object(); + if (!out) { + LOG(ERROR) << "Failed get tls output object"; + fill_response_with_message(res, -1, "Failed get thread local resource"); + return 0; + } + + // call paddle fluid model for inference + if (predictor::InferManager::instance().infer( + CTR_PREDICTION_MODEL_NAME, in, out, sample_size)) { + LOG(ERROR) << "Failed do infer in fluid model: " + << CTR_PREDICTION_MODEL_NAME; + fill_response_with_message(res, -1, "Failed do infer in fluid model"); + return 0; + } + + if (out->size() != 1) { + LOG(ERROR) << "Model returned number of fetch tensor more than 1"; + fill_response_with_message( + res, -1, "Model returned number of fetch tensor more than 1"); + return 0; + } + + int output_shape_dim = out->at(0).shape.size(); + if (output_shape_dim != 2) { + LOG(ERROR) << "Fetch LoDTensor should be shape of [sample_size, 2]"; + fill_response_with_message( + res, -1, "Fetch LoDTensor should be shape of [sample_size, 2]"); + return 0; + } + + if (out->at(0).dtype != paddle::PaddleDType::FLOAT32) { + LOG(ERROR) << "Fetch LoDTensor data type should be FLOAT32"; + fill_response_with_message( + res, -1, "Fetch LoDTensor data type should be FLOAT32"); + return 0; + } + + int dim1 = out->at(0).shape[0]; + int dim2 = out->at(0).shape[1]; + + if (dim1 != sample_size) { + LOG(ERROR) << "Returned result count not equal to sample_size"; + fill_response_with_message( + res, -1, "Returned result count not equal to sample size"); + return 0; + } + + if (dim2 != 2) { + LOG(ERROR) << "Returned result is not expected, should be 2 floats for " + "each sample"; + fill_response_with_message( + res, -1, "Retunred result is not 2 floats for each sample"); + return 0; + } + + float *data = static_cast(out->at(0).data.data()); + for (int i = 0; i < dim1; ++i) { + ResInstance *res_instance = res->add_predictions(); + res_instance->set_prob0(data[i * dim2]); + res_instance->set_prob1(data[i * dim2 + 1]); + } + + for (size_t i = 0; i < in->size(); ++i) { + (*in)[i].shape.clear(); + } + in->clear(); + butil::return_object(in); + + for (size_t i = 0; i < out->size(); ++i) { + (*out)[i].shape.clear(); + } + out->clear(); + butil::return_object(out); + + res->set_err_code(0); + res->set_err_msg(std::string("")); + return 0; +} + +DEFINE_OP(ElasticCTRPredictionOp); + +} // namespace serving +} // namespace paddle_serving +} // namespace baidu diff --git a/elastic-ctr/serving/op/elastic_ctr_prediction_op.h b/elastic-ctr/serving/op/elastic_ctr_prediction_op.h new file mode 100644 index 0000000000000000000000000000000000000000..34ff1827992464fb169e5e828fb4ba8cfa47f5f4 --- /dev/null +++ b/elastic-ctr/serving/op/elastic_ctr_prediction_op.h @@ -0,0 +1,58 @@ +// 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. + +#pragma once +#include +#ifdef BCLOUD +#ifdef WITH_GPU +#include "paddle/paddle_inference_api.h" +#else +#include "paddle/fluid/inference/api/paddle_inference_api.h" +#endif +#else +#include "paddle_inference_api.h" // NOLINT +#endif +#include "elastic-ctr/serving/elastic_ctr_prediction.pb.h" + +namespace baidu { +namespace paddle_serving { +namespace serving { + +static const char* CTR_PREDICTION_MODEL_NAME = "elastic_ctr_prediction"; + +/** + * ElasticCTRPredictionOp: Serve CTR prediction requests. + * + */ + +class ElasticCTRPredictionOp + : public baidu::paddle_serving::predictor::OpWithChannel< + baidu::paddle_serving::predictor::elastic_ctr::Response> { + public: + typedef std::vector TensorVector; + + DECLARE_OP(ElasticCTRPredictionOp); + + int inference(); + + private: + static bthread::Mutex mutex_; + static int64_t cube_time_us_; + static int32_t cube_req_num_; + static int32_t cube_req_key_num_; +}; + +} // namespace serving +} // namespace paddle_serving +} // namespace baidu diff --git a/elastic-ctr/serving/proto/CMakeLists.txt b/elastic-ctr/serving/proto/CMakeLists.txt new file mode 100644 index 0000000000000000000000000000000000000000..a52340d4dd54e166e1d9c7f8ae988de3f9740a86 --- /dev/null +++ b/elastic-ctr/serving/proto/CMakeLists.txt @@ -0,0 +1,6 @@ +LIST(APPEND protofiles + ${CMAKE_CURRENT_LIST_DIR}/elastic_ctr_prediction.proto +) + +PROTOBUF_GENERATE_SERVING_CPP(TRUE PROTO_SRCS PROTO_HDRS ${protofiles}) +LIST(APPEND serving_srcs ${PROTO_SRCS}) diff --git a/elastic-ctr/serving/proto/elastic_ctr_prediction.proto b/elastic-ctr/serving/proto/elastic_ctr_prediction.proto new file mode 100644 index 0000000000000000000000000000000000000000..b31474bac067e196f153909e046971165b92f110 --- /dev/null +++ b/elastic-ctr/serving/proto/elastic_ctr_prediction.proto @@ -0,0 +1,46 @@ +// 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. + +syntax = "proto2"; +import "pds_option.proto"; +import "builtin_format.proto"; +package baidu.paddle_serving.predictor.elastic_ctr; + +option cc_generic_services = true; + +message Slot { + required string slot_name = 1; + repeated int64 feasigns = 2; +}; + +message ReqInstance { repeated Slot slots = 1; }; + +message Request { repeated ReqInstance instances = 1; }; + +message ResInstance { + required float prob0 = 1; + required float prob1 = 2; +}; + +message Response { + repeated ResInstance predictions = 1; + required int64 err_code = 2; + optional string err_msg = 3; +}; + +service ElasticCTRPredictionService { + rpc inference(Request) returns (Response); + rpc debug(Request) returns (Response); + option (pds.options).generate_impl = true; +};