diff --git a/CMakeLists.txt b/CMakeLists.txt index 3a96666de6283955363fa85d13b2e58d46a61011..8dab01f14a7a82213ae92d5fbcfce619e9939a96 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -75,7 +75,6 @@ include(generic) include(flags) if (NOT CLIENT_ONLY) -include(external/mklml) include(paddlepaddle) include(external/opencv) endif() diff --git a/cmake/external/mklml.cmake b/cmake/external/mklml.cmake deleted file mode 100644 index 2caff27357687018f29c1efc55b7b82c9dc3ccf6..0000000000000000000000000000000000000000 --- a/cmake/external/mklml.cmake +++ /dev/null @@ -1,76 +0,0 @@ -# Copyright (c) 2017 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. - -IF(NOT ${WITH_MKLML}) - return() -ENDIF(NOT ${WITH_MKLML}) - -IF(APPLE) - MESSAGE(WARNING "Mac is not supported with MKLML in Paddle yet. Force WITH_MKLML=OFF.") - SET(WITH_MKLML OFF CACHE STRING "Disable MKLML package in MacOS" FORCE) - return() -ENDIF() - -INCLUDE(ExternalProject) -SET(MKLML_DST_DIR "mklml") -SET(MKLML_INSTALL_ROOT "${THIRD_PARTY_PATH}/install") -SET(MKLML_INSTALL_DIR ${MKLML_INSTALL_ROOT}/${MKLML_DST_DIR}) -SET(MKLML_ROOT ${MKLML_INSTALL_DIR}) -SET(MKLML_INC_DIR ${MKLML_ROOT}/include) -SET(MKLML_LIB_DIR ${MKLML_ROOT}/lib) -SET(CMAKE_INSTALL_RPATH "${CMAKE_INSTALL_RPATH}" "${MKLML_ROOT}/lib") - -SET(TIME_VERSION "2019.0.1.20181227") -IF(WIN32) - SET(MKLML_VER "mklml_win_${TIME_VERSION}" CACHE STRING "" FORCE) - SET(MKLML_URL "https://paddlepaddledeps.cdn.bcebos.com/${MKLML_VER}.zip" CACHE STRING "" FORCE) - SET(MKLML_LIB ${MKLML_LIB_DIR}/mklml.lib) - SET(MKLML_IOMP_LIB ${MKLML_LIB_DIR}/libiomp5md.lib) - SET(MKLML_SHARED_LIB ${MKLML_LIB_DIR}/mklml.dll) - SET(MKLML_SHARED_IOMP_LIB ${MKLML_LIB_DIR}/libiomp5md.dll) -ELSE() - SET(MKLML_VER "mklml_lnx_${TIME_VERSION}" CACHE STRING "" FORCE) - SET(MKLML_URL "http://paddlepaddledeps.cdn.bcebos.com/${MKLML_VER}.tgz" CACHE STRING "" FORCE) - SET(MKLML_LIB ${MKLML_LIB_DIR}/libmklml_intel.so) - SET(MKLML_IOMP_LIB ${MKLML_LIB_DIR}/libiomp5.so) - SET(MKLML_SHARED_LIB ${MKLML_LIB_DIR}/libmklml_intel.so) - SET(MKLML_SHARED_IOMP_LIB ${MKLML_LIB_DIR}/libiomp5.so) -ENDIF() - -SET(MKLML_PROJECT "extern_mklml") -MESSAGE(STATUS "MKLML_VER: ${MKLML_VER}, MKLML_URL: ${MKLML_URL}") -SET(MKLML_SOURCE_DIR "${THIRD_PARTY_PATH}/mklml") -SET(MKLML_DOWNLOAD_DIR "${MKLML_SOURCE_DIR}/src/${MKLML_PROJECT}") - -ExternalProject_Add( - ${MKLML_PROJECT} - ${EXTERNAL_PROJECT_LOG_ARGS} - PREFIX ${MKLML_SOURCE_DIR} - URL ${MKLML_URL} - DOWNLOAD_DIR ${MKLML_DOWNLOAD_DIR} - DOWNLOAD_NO_PROGRESS 1 - CONFIGURE_COMMAND "" - BUILD_COMMAND "" - UPDATE_COMMAND "" - INSTALL_COMMAND - ${CMAKE_COMMAND} -E copy_directory ${MKLML_DOWNLOAD_DIR}/include ${MKLML_INC_DIR} && - ${CMAKE_COMMAND} -E copy_directory ${MKLML_DOWNLOAD_DIR}/lib ${MKLML_LIB_DIR} -) - -INCLUDE_DIRECTORIES(${MKLML_INC_DIR}) - -ADD_LIBRARY(mklml SHARED IMPORTED GLOBAL) -SET_PROPERTY(TARGET mklml PROPERTY IMPORTED_LOCATION ${MKLML_LIB}) -ADD_DEPENDENCIES(mklml ${MKLML_PROJECT}) -LIST(APPEND external_project_dependencies mklml) diff --git a/configure/proto/server_configure.proto b/configure/proto/server_configure.proto index ffd9f9afbc5165aea7964ab2b02d3bcbf29dd496..865234f0de29ee3989e26e95aff6ccaf86b00df4 100644 --- a/configure/proto/server_configure.proto +++ b/configure/proto/server_configure.proto @@ -40,6 +40,9 @@ message EngineDesc { } optional SparseParamServiceType sparse_param_service_type = 11; optional string sparse_param_service_table_name = 12; + optional bool enable_memory_optimization = 13; + optional bool static_optimization = 14; + optional bool force_update_static_cache = 15; }; // model_toolkit conf @@ -49,8 +52,7 @@ message ModelToolkitConf { repeated EngineDesc engines = 1; }; message ResourceConf { required string model_toolkit_path = 1; required string model_toolkit_file = 2; - optional string cube_config_path = 3; - optional string cube_config_file = 4; + optional string cube_config_file = 3; }; // DAG node depency info diff --git a/configure/tests/test_configure.cpp b/configure/tests/test_configure.cpp index 58dd0810da48fea4111c70432a89a6ea2d4e3399..361791c4bd454618e1dec3bdf0ce96d4711df763 100644 --- a/configure/tests/test_configure.cpp +++ b/configure/tests/test_configure.cpp @@ -68,6 +68,9 @@ int test_write_conf() { engine->set_enable_batch_align(0); engine->set_sparse_param_service_type(EngineDesc::LOCAL); engine->set_sparse_param_service_table_name("local_kv"); + engine->set_enable_memory_optimization(true); + engine->set_static_optimization(false); + engine->set_force_update_static_cache(false); int ret = baidu::paddle_serving::configure::write_proto_conf( &model_toolkit_conf, output_dir, model_toolkit_conf_file); @@ -79,6 +82,7 @@ int test_write_conf() { ResourceConf resource_conf; resource_conf.set_model_toolkit_path(output_dir); resource_conf.set_model_toolkit_file("model_toolkit.prototxt"); + resource_conf.set_cube_config_file("./conf/cube.conf"); ret = baidu::paddle_serving::configure::write_proto_conf( &resource_conf, output_dir, resource_conf_file); if (ret != 0) { diff --git a/cube/cube-agent/src/agent/define.go b/cube/cube-agent/src/agent/define.go index 9098a101679f31c7ed3b253c11548ff5d985c7ce..1b602b6fc0f2de86325f49ebdeff5b3321bb697a 100644 --- a/cube/cube-agent/src/agent/define.go +++ b/cube/cube-agent/src/agent/define.go @@ -17,9 +17,6 @@ package agent import ( "errors" _ "github.com/Badangel/logex" - "github.com/Badangel/pipeline" - "os/exec" - "strconv" "strings" "sync" ) @@ -89,26 +86,3 @@ func GetMaster(master string) (host, port string, err error) { return MasterHost[0], MasterPort[0], nil } } - -func init() { - dfCmd := "df -h | grep -E '/home|/ssd'" - stdout, _, err := pipeline.Run(exec.Command("/bin/bash", "-c", dfCmd)) - - if err == nil && stdout.String() != "" { - t := strings.TrimSpace(stdout.String()) - diskLi := strings.Split(t, "\n") - for _, diskStr := range diskLi { - disk := strings.Fields(diskStr) - usedPercent, _ := strconv.Atoi(strings.TrimRight(disk[4], "%")) - if usedPercent <= 40 { - disks = append(disks, disk[5]) - } - } - } - - if len(disks) == 0 { - disks = append(disks, "/home") - } - - //logex.Debugf("available disks found: (%+v)", disks) -} diff --git a/cube/cube-agent/src/agent/util.go b/cube/cube-agent/src/agent/util.go index c629c9c495c1857a0a2ba0c641466803a81b1c81..29d27682a3c2e1c46d7ca8cb71de53c2e95df71f 100644 --- a/cube/cube-agent/src/agent/util.go +++ b/cube/cube-agent/src/agent/util.go @@ -132,7 +132,7 @@ func getHostname(ip string) (hostname string, err error) { //logex.Warningf("cannot find the hostname of ip (%s), error (%v)", ip, err) } else { if len(hostnames) > 0 { - hostname = hostnames[0][:strings.LastIndex(hostnames[0], ".baidu.com.")] + hostname = hostnames[0] } else { hostname = ip } diff --git a/cube/cube-agent/src/agent/work.go b/cube/cube-agent/src/agent/work.go index 8f7229322ce046297270daee6108c9abb5ab4309..8fdd90a52b877e2c7624a6ce48e13f7b0c2336c5 100644 --- a/cube/cube-agent/src/agent/work.go +++ b/cube/cube-agent/src/agent/work.go @@ -725,7 +725,7 @@ func DoDownloadIndividual(source, downloadDir string, isService bool, timeOut in func checkSources(source string) ([]string, error) { sources := strings.Split(source, ";") for i := 0; i < len(sources); i++ { - if sources[i] == "" || !strings.HasPrefix(sources[i], "ftp://") { + if sources[i] == "" || (!strings.HasPrefix(sources[i], "ftp://") && !strings.HasPrefix(sources[i], "http://")) { return sources, errors.New("Invalid sources") } } diff --git a/cube/cube-server/src/main.cpp b/cube/cube-server/src/main.cpp index bacfb1ea92032815522c3c2dc6ec1eeaa3f90dfc..9ece4391a600b6c48da030bfdde4f9773c8ee4b0 100644 --- a/cube/cube-server/src/main.cpp +++ b/cube/cube-server/src/main.cpp @@ -12,6 +12,7 @@ // See the License for the specific language governing permissions and // limitations under the License. +#include #include #include diff --git a/cube/cube-transfer/conf/transfer.conf b/cube/cube-transfer/conf/transfer.conf index c3184231f95d259de1adcfa8a20e136dc756a3b9..2242e6c8a222a2e34d9aed9bc06221bcbd3a6a77 100755 --- a/cube/cube-transfer/conf/transfer.conf +++ b/cube/cube-transfer/conf/transfer.conf @@ -1,18 +1,19 @@ [default] dict_name: test_dict mode: base_only -storage_place: LOCAL +download_mode: http +wget_port: 8009 buildtool_local: /home/work/Serving/build/output/bin/cube-builder donefile_address: http://127.0.0.1/home/work/dangyifei/donefile output_address: /home/work/dangyifei/test-transfer/test_data/output tmp_address: /home/work/dangyifei/test-transfer/test_data/tmp -shard_num: 1 -copy_num: 2 +shard_num: 2 +copy_num: 1 deploy_path: /home/work/test_dict transfer_address: 127.0.0.1 [cube_agent] agent0_0: 127.0.0.1:8001 cube0_0: 127.0.0.1:8000:/ssd2/cube_open -agent0_1: 127.0.0.1:8001 -cube0_1: 127.0.0.1:8000:/home/disk1/cube_open +agent1_0: 127.0.0.1:8001 +cube1_0: 127.0.0.1:8000:/home/disk1/cube_open diff --git a/cube/cube-transfer/src/cube-transfer.go b/cube/cube-transfer/src/cube-transfer.go index 3e63d8bbcce6d41524eb53788ae069b9418d698b..e199a9ce1fefa566ab5c3b8b168368b230173f20 100755 --- a/cube/cube-transfer/src/cube-transfer.go +++ b/cube/cube-transfer/src/cube-transfer.go @@ -16,8 +16,8 @@ package main import ( "fmt" - "github.com/docopt/docopt-go" "github.com/Badangel/logex" + "github.com/docopt/docopt-go" "os" "path/filepath" "runtime" @@ -64,6 +64,7 @@ Log options: // settings: if opts["-p"] == nil { + logex.Fatal("ERROR: -p PORT must be set!") fmt.Fprintln(os.Stderr, "ERROR: -p PORT must be set!") fmt.Fprintln(os.Stderr, usage) os.Exit(1) @@ -72,6 +73,7 @@ Log options: logex.Notice(">>> port:", transfer.Port) if opts["--config"] == nil { + logex.Fatal("ERROR: --config config_file must be set!") fmt.Fprintln(os.Stderr, "ERROR: --config config_file must be set!") fmt.Fprintln(os.Stderr, usage) os.Exit(1) @@ -81,6 +83,7 @@ Log options: configMgr.Init(opts["--config"].(string)) transfer.Dict.DictName = configMgr.Read("default", "dict_name") if transfer.Dict.DictName == "" { + logex.Fatal("ERROR: nead [default] DictName in config_file!") fmt.Fprintln(os.Stderr, "ERROR: nead [default] DictName in config_file!") fmt.Fprintln(os.Stderr, usage) os.Exit(1) @@ -89,22 +92,40 @@ Log options: transfer.Dict.DictMode = configMgr.Read("default", "mode") if transfer.Dict.DictMode == "" { + logex.Fatal("ERROR: nead [default] DictMode in config_file!") fmt.Fprintln(os.Stderr, "ERROR: nead [default] DictMode in config_file!") fmt.Fprintln(os.Stderr, usage) os.Exit(1) } logex.Notice(">>> Mode:", transfer.Dict.DictMode) - transfer.Dict.StoragePlace = configMgr.Read("default", "storage_place") - if transfer.Dict.StoragePlace == "" || transfer.Dict.StoragePlace != "LOCAL" { - fmt.Fprintln(os.Stderr, "ERROR: nead [default] StoragePlace in config_file! only support Local") + transfer.Dict.DownloadMode = configMgr.Read("default", "download_mode") + if transfer.Dict.DownloadMode != "http" && transfer.Dict.DownloadMode != "ftp" { + logex.Fatal("ERROR: nead [default] download_mode in config_file! only support ftp or http") + fmt.Fprintln(os.Stderr, "ERROR: nead [default] download_mode in config_file! only support ftp or http") fmt.Fprintln(os.Stderr, usage) os.Exit(1) } - logex.Notice(">>> StoragePlace:", transfer.Dict.StoragePlace) + logex.Notice(">>> DownloadMode:", transfer.Dict.DownloadMode) + + transfer.Dict.WgetPort = configMgr.Read("default", "wget_port") + if transfer.Dict.WgetPort == "" { + logex.Fatal("ERROR: nead [default] wget_port in config_file!") + fmt.Fprintln(os.Stderr, "ERROR: nead [default] wget_port in config_file!") + fmt.Fprintln(os.Stderr, usage) + os.Exit(1) + } + var wget_port int + wget_port, err = strconv.Atoi(transfer.Dict.WgetPort) + if err != nil { + logex.Fatal("wget_port form is not right need int") + os.Exit(1) + } + logex.Notice(">>> WgetPort:", wget_port) transfer.BuildToolLocal = configMgr.Read("default", "buildtool_local") if transfer.BuildToolLocal == "" { + logex.Fatal("ERROR: nead [default] BuildToolLocal in config_file!") fmt.Fprintln(os.Stderr, "ERROR: nead [default] BuildToolLocal in config_file!") fmt.Fprintln(os.Stderr, usage) os.Exit(1) @@ -113,6 +134,7 @@ Log options: transfer.Dict.DonefileAddress = configMgr.Read("default", "donefile_address") if transfer.Dict.DonefileAddress == "" { + logex.Fatal("ERROR: nead [default] DonefileAddress in config_file!") fmt.Fprintln(os.Stderr, "ERROR: nead [default] DonefileAddress in config_file!") fmt.Fprintln(os.Stderr, usage) os.Exit(1) @@ -121,6 +143,7 @@ Log options: transfer.Dict.OutputAddress = configMgr.Read("default", "output_address") if transfer.Dict.OutputAddress == "" { + logex.Fatal("ERROR: nead [default] OutputAddress in config_file!") fmt.Fprintln(os.Stderr, "ERROR: nead [default] OutputAddress in config_file!") fmt.Fprintln(os.Stderr, usage) os.Exit(1) @@ -129,6 +152,7 @@ Log options: transfer.Dict.TmpAddress = configMgr.Read("default", "tmp_address") if transfer.Dict.TmpAddress == "" { + logex.Fatal("ERROR: nead [default] TmpAddress in config_file!") fmt.Fprintln(os.Stderr, "ERROR: nead [default] TmpAddress in config_file!") fmt.Fprintln(os.Stderr, usage) os.Exit(1) @@ -137,6 +161,7 @@ Log options: ShardNumStr := configMgr.Read("default", "shard_num") if ShardNumStr == "" { + logex.Fatal("ERROR: nead [default] ShardNum in config_file!") fmt.Fprintln(os.Stderr, "ERROR: nead [default] ShardNum in config_file!") fmt.Fprintln(os.Stderr, usage) os.Exit(1) @@ -150,6 +175,7 @@ Log options: CopyNumStr := configMgr.Read("default", "copy_num") if CopyNumStr == "" { + logex.Fatal("ERROR: nead [default] CopyNum in config_file!") fmt.Fprintln(os.Stderr, "ERROR: nead [default] CopyNum in config_file!") fmt.Fprintln(os.Stderr, usage) os.Exit(1) @@ -165,6 +191,7 @@ Log options: transfer.Dict.DeployPath = configMgr.Read("default", "deploy_path") if transfer.Dict.DeployPath == "" { + logex.Fatal("ERROR: nead [default] DeployPath in config_file!") fmt.Fprintln(os.Stderr, "ERROR: nead [default] DeployPath in config_file!") fmt.Fprintln(os.Stderr, usage) os.Exit(1) @@ -173,6 +200,7 @@ Log options: transfer.TransferAddr = configMgr.Read("default", "transfer_address") if transfer.TransferAddr == "" { + logex.Fatal("ERROR: nead [default] TransferAddr in config_file!") fmt.Fprintln(os.Stderr, "ERROR: nead [default] TransferAddr in config_file!") fmt.Fprintln(os.Stderr, usage) os.Exit(1) @@ -185,9 +213,17 @@ Log options: agentName := fmt.Sprintf("agent%d_%d", i, j) agentInfo := configMgr.Read("cube_agent", agentName) agentInfoSlice := strings.Split(agentInfo, ":") + if len(agentInfoSlice) != 2 { + logex.Fatal("agent conf format not right! sample: ip:port") + os.Exit(1) + } cubeName := fmt.Sprintf("cube%d_%d", i, j) cubeInfo := configMgr.Read("cube_agent", cubeName) cubeInfoSlice := strings.Split(cubeInfo, ":") + if len(cubeInfoSlice) != 3 { + logex.Fatal("cube conf format not right! sample: ip:port:deploy_path") + os.Exit(1) + } instance.DictName = transfer.Dict.DictName instance.AgentIp = agentInfoSlice[0] instance.AgentPort, _ = strconv.Atoi(agentInfoSlice[1]) diff --git a/cube/cube-transfer/src/transfer/deployer.go b/cube/cube-transfer/src/transfer/deployer.go index 6c4b1ca8b42b5e13556d8ad71c43b26bfdb0cf14..e054f1fbd89cb08884b1b80b45adc4770af0dd00 100755 --- a/cube/cube-transfer/src/transfer/deployer.go +++ b/cube/cube-transfer/src/transfer/deployer.go @@ -72,7 +72,7 @@ func CmdInstsDownload() { json_params.Mode = Dict.WaitVersionInfo.Mode json_params.ShardSeq = inst.Shard json_params.Port = strconv.Itoa(inst.Port) - json_params.Source = dict.GetFileHead(Dict.StoragePlace, TransferAddr) + Dict.WaitVersionInfo.Output + "/" + json_params.DictName + "_part" + strconv.Itoa(inst.Shard) + ".tar" + json_params.Source = dict.GetFileHead(Dict.DownloadMode, TransferAddr, Dict.WgetPort) + Dict.WaitVersionInfo.Output + "/" + json_params.DictName + "_part" + strconv.Itoa(inst.Shard) + ".tar" var address = fmt.Sprintf("http://%v:%v/agent/cmd", inst.AgentIp, inst.AgentPort) logex.Noticef("[download cmd]%v:%v", address, json_params) go nonBlockSendJsonReq("POST2", address, 120, &json_params, &keyAndRespSlice[i], chs[i]) @@ -121,7 +121,7 @@ func CmdInstsReload() { json_params.Mode = Dict.WaitVersionInfo.Mode json_params.ShardSeq = inst.Shard json_params.Port = strconv.Itoa(inst.Port) - json_params.Source = dict.GetFileHead(Dict.StoragePlace, TransferAddr) + Dict.WaitVersionInfo.Output + "/" + json_params.DictName + "_part" + strconv.Itoa(inst.Shard) + ".tar" + json_params.Source = dict.GetFileHead(Dict.DownloadMode, TransferAddr, Dict.WgetPort) + Dict.WaitVersionInfo.Output + "/" + json_params.DictName + "_part" + strconv.Itoa(inst.Shard) + ".tar" var address = fmt.Sprintf("http://%v:%v/agent/cmd", inst.AgentIp, inst.AgentPort) logex.Noticef("[reload cmd]%v:%v", address, json_params) @@ -170,7 +170,7 @@ func CmdInstsEnable() { json_params.Mode = Dict.WaitVersionInfo.Mode json_params.ShardSeq = inst.Shard json_params.Port = strconv.Itoa(inst.Port) - json_params.Source = dict.GetFileHead(Dict.StoragePlace, TransferAddr) + Dict.WaitVersionInfo.Output + "/" + json_params.DictName + "_part" + strconv.Itoa(inst.Shard) + ".tar" + json_params.Source = dict.GetFileHead(Dict.DownloadMode, TransferAddr, Dict.WgetPort) + Dict.WaitVersionInfo.Output + "/" + json_params.DictName + "_part" + strconv.Itoa(inst.Shard) + ".tar" var address = fmt.Sprintf("http://%v:%v/agent/cmd", inst.AgentIp, inst.AgentPort) logex.Noticef("[enable cmd]%v:%v", address, json_params) diff --git a/cube/cube-transfer/src/transfer/dict/dict_info.go b/cube/cube-transfer/src/transfer/dict/dict_info.go index 5e0bbbcf5a37600b5284a0bf5b95d50566615270..8692d5220dda33469220aeda1ee831ad549e3c0c 100755 --- a/cube/cube-transfer/src/transfer/dict/dict_info.go +++ b/cube/cube-transfer/src/transfer/dict/dict_info.go @@ -24,7 +24,8 @@ type DictInfo struct { DonefileAddress string `json:"donefile_addr"` OutputAddress string `json:"output_addr"` TmpAddress string `json:"tmp_addr"` - StoragePlace string `json:"storage_place"` + DownloadMode string `json:"download_mode"` + WgetPort string `json:"wget_port"` DownloadSuccInsts int `json:"download_inst"` ReloadSuccInsts int `json:"reload_insts"` EnableSuccInsts int `json:"enable_insts"` diff --git a/cube/cube-transfer/src/transfer/dict/dict_shard_info.go b/cube/cube-transfer/src/transfer/dict/dict_shard_info.go index 0c42a4bbbc6825a5330116db451b3a49d14c7ce3..a9816ec901784dc42c3e85e62308460718917880 100755 --- a/cube/cube-transfer/src/transfer/dict/dict_shard_info.go +++ b/cube/cube-transfer/src/transfer/dict/dict_shard_info.go @@ -36,7 +36,7 @@ type DictShardInfo struct { IsActive bool `json:"is_active,omitempty"` } -func GetDictShardScaler(shard int, dictVersionInfo DictVersionInfo, storagePlace string, transferaddr string)(info DictShardInfo){ +func GetDictShardScaler(shard int, dictVersionInfo DictVersionInfo, downloadMode string, transferAddr string, wgetPort string)(info DictShardInfo){ info.Name = dictVersionInfo.DictName info.Version = strconv.Itoa(dictVersionInfo.Version) info.Depend = strconv.Itoa(dictVersionInfo.Depend) @@ -44,16 +44,17 @@ func GetDictShardScaler(shard int, dictVersionInfo DictVersionInfo, storagePlace info.Key = strconv.Itoa(dictVersionInfo.Key) info.Mode = dictVersionInfo.Mode info.Shard = shard - info.Source = GetFileHead(storagePlace, transferaddr) + dictVersionInfo.Output+ "/" + info.Version + "/" + info.Name + "_part" + strconv.Itoa(shard) + ".tar" + info.Source = GetFileHead(downloadMode, transferAddr, wgetPort) + dictVersionInfo.Output+ "/" + info.Version + "/" + info.Name + "_part" + strconv.Itoa(shard) + ".tar" return } -func GetFileHead(storagePlace string, transferaddr string) string { - if storagePlace == "LOCAL"{ - return "ftp://" + transferaddr +func GetFileHead(downloadMode string, transferAddr string, wgetPort string) string { + if downloadMode == "http" { + return HTTP_HEADER + transferAddr + ":" + wgetPort + } else if downloadMode == "ftp" { + return FTP_HEADER + transferAddr + ":" + wgetPort } else { return "" } - } \ No newline at end of file diff --git a/cube/cube-transfer/src/transfer/http_get.go b/cube/cube-transfer/src/transfer/http_get.go index 2bc36808c9fbe32e6ebd34316751674e19a9696c..b623e7c047174ae4caf6d5319a7c127d04ef37f1 100755 --- a/cube/cube-transfer/src/transfer/http_get.go +++ b/cube/cube-transfer/src/transfer/http_get.go @@ -66,11 +66,11 @@ func GetDictScaler(subpath string, m map[string]string) (string, string, int, er } for _, version := range Dict.CurrentVersionInfo { - info := dict.GetDictShardScaler(shard, version, Dict.StoragePlace, TransferAddr) + info := dict.GetDictShardScaler(shard, version, Dict.DownloadMode, TransferAddr, Dict.WgetPort) infos = append(infos, info) } if Dict.WaitVersionInfo.Status > dict.Dict_Status_Deploying { - info := dict.GetDictShardScaler(shard, Dict.WaitVersionInfo, Dict.StoragePlace, TransferAddr) + info := dict.GetDictShardScaler(shard, Dict.WaitVersionInfo, Dict.DownloadMode, TransferAddr, Dict.WgetPort) infos = append(infos, info) } diff --git a/cube/cube-transfer/src/transfer/trigger.go b/cube/cube-transfer/src/transfer/trigger.go index c962726d20c1fee7bbbaa282000640df1c8036f6..b3696dc58b7ca33de307cbe7ea2d4509d269753c 100755 --- a/cube/cube-transfer/src/transfer/trigger.go +++ b/cube/cube-transfer/src/transfer/trigger.go @@ -52,7 +52,16 @@ func GetDoneFileInfo(addr string) (version dict.DictVersionInfo, err error) { } else { contentss := string(contents) lines := strings.Split(contentss, "\n") - index := len(lines) - 2 + index := len(lines) - 1 + //one line length smaller than 3 maybe blank or return + for len(lines[index]) < 3 { + index-- + } + if index < 0 { + logex.Noticef("[trigrer]get base donfile info error") + err = fmt.Errorf("[trigrer]get base donfile info error") + return + } var donefileInfo dict.DonefileInfo fmt.Printf("line %v: %v\n", index, lines[index]) if err = json.Unmarshal([]byte(lines[index]), &donefileInfo); err != nil { @@ -83,7 +92,13 @@ func GetDoneFileInfo(addr string) (version dict.DictVersionInfo, err error) { } else { contentss := string(contents) lines := strings.Split(contentss, "\n") + for index := 0; index < len(lines)-1; index++ { + if len(lines[index]) < 3 { + logex.Noticef("[trigrer]get patch donfile info error") + err = fmt.Errorf("[trigrer]get patch donfile info error") + return + } var donefileInfo dict.DonefileInfo if err = json.Unmarshal([]byte(lines[index]), &donefileInfo); err != nil { return diff --git a/cube/doc/performance.md b/cube/doc/performance.md new file mode 100644 index 0000000000000000000000000000000000000000..5fa297772c5fb3a0668e4a2a2f720b6f0a079ff7 --- /dev/null +++ b/cube/doc/performance.md @@ -0,0 +1,47 @@ +# Cube Server 社区版本性能报告 +## 机器配置 +Intel(R) Xeon(R) CPU E5-2650 v4 @ 2.20GHz + +## 测试数据 +100w条样例kv 数据。 key为uint_64类型，单条value长度 40 Byte （一般实际场景对应一个10维特征向量）。 + +## 单Key高qps访问场景 +一般来说实际预估服务生产环境下，单key访问场景较少，不过单机qps依然是一个比较重要的性能指标，故在下表提供了不同qps下单机Cube server性能指标。 + + +| qps | 10w | 50w | 100w | +|---|---|---|---| +|kps|10w|50w|100w| +|cpu(top)| 6.5% | 38.3% | 71.4% | +|client端延迟| avg 196 us
50% 160 us
70% 188 us
90% 292 us
95% 419 us
97% 547 us
99% 835 us
99.9% 1556 us
99.99% 1779 us| avg 563 us
50% 342 us
70% 502 us
90% 1063 us
95% 1703 us
97% 2399 us
99% 4036 us
99.9% 7195 us
99.99% 7340 us| avg 4234 us
50% 3120 us
70% 5459 us
90% 10657 us
95% 14074 us
97% 16215 us
99% 19434 us
99.9% 29398 us
99.99% 33921 us| + +## 高kps场景 +生产环境下，预估服务更多的会以batch形式访问cube server，这类情况kps相对qps能更准确的判断服务性能。我们以单次100key为例，给出不同kps下cube server的相关性能指标。 + + +| qps | 2w | 10w | 20w | +|---|---|---|---| +|kps|200w|1000w|2000w| +|cpu(top)| 3.5% | 17.8% | 37.6% | +|client端延迟| avg 375 us
50% 346 us
70% 390 us
90% 498 us
95% 582 us
97% 648 us
99% 908 us
99.9% 1623 us
99.99% 3312 us| avg 1141 us
50% 900 us
70% 1237 us
90% 2028 us
95% 2662 us
97% 3173 us
99% 4614 us
99.9% 6786 us
99.99% 6273 us| avg 1940 us
50% 1299 us
70% 1876 us
90% 3629 us
95% 5535 us
97% 7365 us
99% 10529 us
99.9% 14060 us
99.99% 16028 us| + +## 分布式场景客户端延迟 +在batch查询场景下，单次batch查询耗时是业务方（特别是在线预估服务）非常关心的敏感指标。在分布式场景下，单次batch查询往往要并发请求下游所有分片server，此时batch查询耗时取决于最慢的分片请求。我们在下文给出了一个典型分布式场景下的batch查询耗时。 + +测试条件: +cube分片数:10 +client机器ping下游server机器约0.06ms + + +| batch size | 100 | 500 | 1000 | +|---|---|---|---| +|qps|100|100|100| +|kps|1w| 5w| 10w| +|client端延迟|avg 324 us
80% 346 us
99% 1190 us
99.9% 3662 us
99.99% 9392 us|avg 466 us
80% 488 us
99% 1492 us
99.9% 4122 us
99.99% 10612 us|avg 675 us
80% 691 us
99% 2101 us
99.9% 5169 us
99.99% 14867 us| + +## 结语 +上述表格主要阐述了cube server单机性能，在生产环境下，对于更高的kps(qps)压力我们可以方便地通过增加副本的方式来增强集群负载能力。 在模型大小超过单机内存限制时，我们亦可通过部署多数据分片的分布式集群来提供服务。 +整体来说，cube性能能够满足当前业界各类预估服务的kv访问需求。 + +## PS +本文所列性能均为cube原始代码版本性能，如果根据实际情情况做适当调优：如链入tcmalloc or jemalloc、 进行numa绑定 以及 打开编译优化参数等等，都有可能进一步明显提升cube server的性能表现。 diff --git a/demo-client/CMakeLists.txt b/demo-client/CMakeLists.txt index 1649265788af18357d15f05c65c89dff6dde1bf6..97602a6c44b9600d796969628d9b0ae3d4bdefa4 100644 --- a/demo-client/CMakeLists.txt +++ b/demo-client/CMakeLists.txt @@ -83,6 +83,10 @@ install(TARGETS echo RUNTIME DESTINATION ${PADDLE_SERVING_INSTALL_DIR}/demo/client/echo/bin) install(DIRECTORY ${CMAKE_CURRENT_LIST_DIR}/conf DESTINATION ${PADDLE_SERVING_INSTALL_DIR}/demo/client/echo/) +install(FILES ${CMAKE_CURRENT_LIST_DIR}/python/echo.py + DESTINATION ${PADDLE_SERVING_INSTALL_DIR}/demo/client/echo/python) +install(FILES ${CMAKE_CURRENT_LIST_DIR}/php/echo.php + DESTINATION ${PADDLE_SERVING_INSTALL_DIR}/demo/client/echo/php) install(TARGETS echo_kvdb RUNTIME DESTINATION ${PADDLE_SERVING_INSTALL_DIR}/demo/client/echo_kvdb/bin) @@ -114,6 +118,14 @@ install(DIRECTORY ${CMAKE_CURRENT_LIST_DIR}/conf DESTINATION ${PADDLE_SERVING_INSTALL_DIR}/demo/client/text_classification/) install(DIRECTORY ${CMAKE_CURRENT_LIST_DIR}/data/text_classification DESTINATION ${PADDLE_SERVING_INSTALL_DIR}/demo/client/text_classification/data) +install(FILES ${CMAKE_CURRENT_LIST_DIR}/python/text_classification.py + DESTINATION + ${PADDLE_SERVING_INSTALL_DIR}/demo/client/text_classification/python) +install(FILES ${CMAKE_CURRENT_LIST_DIR}/php/text_classification.php + DESTINATION + ${PADDLE_SERVING_INSTALL_DIR}/demo/client/text_classification/php) + + install(TARGETS ctr_prediction RUNTIME DESTINATION diff --git a/demo-client/php/echo.php b/demo-client/php/echo.php new file mode 100644 index 0000000000000000000000000000000000000000..cfc50a4e2ef837c1899043abd14798b935fb43cb --- /dev/null +++ b/demo-client/php/echo.php @@ -0,0 +1,40 @@ +value ,key1 => value1 ,.... +echo http_post('http://127.0.0.1:8010/BuiltinTestEchoService/inference', array("a" => 1, "b" => 0.5)); +?> diff --git a/demo-client/php/text_classification.php b/demo-client/php/text_classification.php new file mode 100644 index 0000000000000000000000000000000000000000..f924135e284bd6807ff648944d3447635409bd73 --- /dev/null +++ b/demo-client/php/text_classification.php @@ -0,0 +1,113 @@ + $sample); + $labels[] = $label; + + unset($x); + unset($buffer); + unset($ids); + unset($sample); + unset($label); + } + + if (!feof($handle)) { + echo "Unexpected fgets() fail"; + return -1; + } + fclose($handle); +} + +function &http_connect($url) { + $ch = curl_init($url); + curl_setopt($ch, CURLOPT_CUSTOMREQUEST, "POST"); + // true是获取文本，不直接输出 + curl_setopt($ch, CURLOPT_RETURNTRANSFER, true); + // 强制curl不使用100-continue + curl_setopt($ch, CURLOPT_HTTPHEADER, array('Expect:')); + // set header + curl_setopt($ch, + CURLOPT_HTTPHEADER, + array( + 'Content-Type: application/json' + ) + ); + + return $ch; +} + +function http_post(&$ch, $data) { + // array to json string + $data_string = json_encode($data); + + // post data 封装 + curl_setopt($ch, CURLOPT_POSTFIELDS, $data_string); + + // set header + curl_setopt($ch, + CURLOPT_HTTPHEADER, + array( + 'Content-Length: ' . strlen($data_string) + ) + ); + + // 执行 + $result = curl_exec($ch); + return $result; +} + +if ($argc != 2) { + echo "Usage: php text_classification.php DATA_SET_FILE\n"; + return -1; +} + +ini_set('memory_limit', '-1'); + +$samples = array(); +$labels = array(); +read_data($argv[1], $samples, $labels); +echo count($samples) . "\n"; + +$ch = &http_connect('http://127.0.0.1:8010/TextClassificationService/inference'); + +$count = 0; +for ($i = 0; $i < count($samples) - BATCH_SIZE; $i += BATCH_SIZE) { + $instances = array_slice($samples, $i, BATCH_SIZE); + echo http_post($ch, array("instances" => $instances)) . "\n"; +} + +curl_close($ch); + +?> diff --git a/demo-client/python/echo.py b/demo-client/python/echo.py new file mode 100644 index 0000000000000000000000000000000000000000..5f447e6dd8b70a0110ebd623d2a0c94680bd42ed --- /dev/null +++ b/demo-client/python/echo.py @@ -0,0 +1,26 @@ +# 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. + +import json +import urllib2 + +data = {"a": 1, "b": 0.5} +request_json = json.dumps(data) + +req = urllib2.Request("http://127.0.0.1:8010/BuiltinTestEchoService/inference") +try: + response = urllib2.urlopen(req, request_json, 1) + print response.read() +except urllib2.HTTPError as e: + print e.reason diff --git a/demo-client/python/text_classification.py b/demo-client/python/text_classification.py new file mode 100644 index 0000000000000000000000000000000000000000..3f1bf76e13c501646fc4ad1e535327bc47500a05 --- /dev/null +++ b/demo-client/python/text_classification.py @@ -0,0 +1,70 @@ +# 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. + +import json +import httplib +import sys +import os + +BATCH_SIZE = 10 + + +def data_reader(data_file, samples, labels): + if not os.path.exists(data_file): + print "Path %s not exist" % data_file + return -1 + + with open(data_file, "r") as f: + for line in f: + line = line.replace('(', ' ') + line = line.replace(')', ' ') + line = line.replace('[', ' ') + line = line.replace(']', ' ') + ids = line.split(',') + ids = [int(x) for x in ids] + label = ids[-1] + ids = ids[0:-1] + samples.append(ids) + labels.append(label) + + +if __name__ == "__main__": + """ main + """ + if len(sys.argv) != 2: + print "Usage: python text_classification.py DATA_FILE" + sys.exit(-1) + + samples = [] + labels = [] + ret = data_reader(sys.argv[1], samples, labels) + + conn = httplib.HTTPConnection("127.0.0.1", 8010) + + for i in range(0, len(samples) - BATCH_SIZE, BATCH_SIZE): + batch = samples[i:i + BATCH_SIZE] + ids = [] + for x in batch: + ids.append({"ids": x}) + ids = {"instances": ids} + + request_json = json.dumps(ids) + + try: + conn.request('POST', "/TextClassificationService/inference", + request_json, {"Content-Type": "application/json"}) + response = conn.getresponse() + print response.read() + except httplib.HTTPException as e: + print e.reason diff --git a/demo-serving/CMakeLists.txt b/demo-serving/CMakeLists.txt index dcb6e3105583c9e299295afaf5f521f58541d613..6491827958ccb014bd22e369b0d8b7a834211d3a 100644 --- a/demo-serving/CMakeLists.txt +++ b/demo-serving/CMakeLists.txt @@ -25,7 +25,12 @@ if (NOT EXISTS endif() include_directories(SYSTEM ${CMAKE_CURRENT_LIST_DIR}/../kvdb/include) -find_library(MKLML_LIBS NAMES libmklml_intel.so libiomp5.so) + +find_library(MKLML_LIB NAMES libmklml_intel.so PATHS + ${CMAKE_BINARY_DIR}/Paddle/third_party/install/mklml/lib/) +find_library(MKLML_IOMP_LIB NAMES libiomp5.so PATHS + ${CMAKE_BINARY_DIR}/Paddle/third_party/install/mklml/lib) + include(op/CMakeLists.txt) include(proto/CMakeLists.txt) add_executable(serving ${serving_srcs}) @@ -75,8 +80,7 @@ install(FILES ${inc} DESTINATION ${PADDLE_SERVING_INSTALL_DIR}/include/serving) if (${WITH_MKL}) - install(FILES ${THIRD_PARTY_PATH}/install/mklml/lib/libmklml_intel.so - ${THIRD_PARTY_PATH}/install/mklml/lib/libmklml_gnu.so - ${THIRD_PARTY_PATH}/install/mklml/lib/libiomp5.so DESTINATION + install(FILES ${CMAKE_BINARY_DIR}/Paddle/third_party/install/mklml/lib/libmklml_intel.so + ${CMAKE_BINARY_DIR}/Paddle/third_party/install/mklml/lib/libiomp5.so DESTINATION ${PADDLE_SERVING_INSTALL_DIR}/demo/serving/bin) endif() diff --git a/demo-serving/conf/model_toolkit.prototxt b/demo-serving/conf/model_toolkit.prototxt index 8bd10bc96d861dabd11edb0d40a1a9b0edc84be6..7e1e8542383b7f7a30c5f998a84a8c866fec79d8 100644 --- a/demo-serving/conf/model_toolkit.prototxt +++ b/demo-serving/conf/model_toolkit.prototxt @@ -1,13 +1,17 @@ engines { name: "image_classification_resnet" - type: "FLUID_CPU_NATIVE_DIR" + type: "FLUID_CPU_ANALYSIS_DIR" reloadable_meta: "./data/model/paddle/fluid_time_file" reloadable_type: "timestamp_ne" model_data_path: "./data/model/paddle/fluid/SE_ResNeXt50_32x4d" runtime_thread_num: 0 batch_infer_size: 0 enable_batch_align: 0 + enable_memory_optimization: true + static_optimization: false + force_update_static_cache: false } + engines { name: "text_classification_bow" type: "FLUID_CPU_ANALYSIS_DIR" diff --git a/doc/HTTP_INTERFACE.md b/doc/HTTP_INTERFACE.md new file mode 100644 index 0000000000000000000000000000000000000000..5be35c745010ef87caae66e60dd577f04408b167 --- /dev/null +++ b/doc/HTTP_INTERFACE.md @@ -0,0 +1,131 @@ +# HTTP Inferface + +Paddle Serving服务均可以通过HTTP接口访问，客户端只需按照Service定义的Request消息格式构造json字符串即可。客户端构造HTTP请求，将json格式数据以POST请求发给serving端，serving端**自动**按Service定义的Protobuf消息格式，将json数据转换成protobuf消息。 + +本文档介绍以python和PHP语言访问Serving的HTTP服务接口的用法。 + +## 1. 访问地址 + +访问Serving节点的HTTP服务与C++服务使用同一个端口（例如8010），访问URL规则为： + +``` +http://127.0.0.1:8010/ServiceName/inference +http://127.0.0.1:8010/ServiceName/debug +``` + +其中ServiceName应该与Serving的配置文件`conf/services.prototxt`中配置的一致，假如有如下2个service： + +```protobuf +services { + name: "BuiltinTestEchoService" + workflows: "workflow3" +} + +services { + name: "TextClassificationService" + workflows: "workflow6" +} +``` + +则访问上述2个Serving服务的HTTP URL分别为： + +``` +http://127.0.0.1:8010/BuiltinTestEchoService/inference +http://127.0.0.1:8010/BuiltinTestEchoService/debug + +http://127.0.0.1:8010/TextClassificationService/inference +http://127.0.0.1:8010/TextClassificationService/debug +``` + +## 2. Python访问HTTP Serving + +Python语言访问HTTP Serving，关键在于构造json格式的请求数据，可以通过以下步骤完成： + +1) 按照Service定义的Request消息格式构造python object +2) `json.dump()` / `json.dumps()` 等函数将python object转换成json格式字符串 + +以TextClassificationService为例，关键代码如下： + +```python +# Connect to server +conn = httplib.HTTPConnection("127.0.0.1", 8010) + +# samples是一个list，其中每个元素是一个ids字典： +# samples[0] = [190, 1, 70, 382, 914, 5146, 190...] +for i in range(0, len(samples) - BATCH_SIZE, BATCH_SIZE): + # 构建批量预测数据 + batch = samples[i: i + BATCH_SIZE] + ids = [] + for x in batch: + ids.append({"ids" : x}) + ids = {"instances": ids} + + # python object转成json + request_json = json.dumps(ids) + + # 请求HTTP服务，打印response + try: + conn.request('POST', "/TextClassificationService/inference", request_json, {"Content-Type": "application/json"}) + response = conn.getresponse() + print response.read() + except httplib.HTTPException as e: + print e.reason +``` + +完整示例请参考[text_classification.py](../demo-client/python/text_classification.py) + +## 3. PHP访问HTTP Serving + +PHP语言构造json格式字符串的步骤如下： + +1) 按照Service定义的Request消息格式，构造PHP array +2) `json_encode()`函数将PHP array转换成json字符串 + +以TextCLassificationService为例，关键代码如下： + +```PHP +function http_post(&$ch, $data) { + // array to json string + $data_string = json_encode($data); + + // post data 封装 + curl_setopt($ch, CURLOPT_POSTFIELDS, $data_string); + + // set header + curl_setopt($ch, + CURLOPT_HTTPHEADER, + array( + 'Content-Length: ' . strlen($data_string) + ) + ); + + // 执行 + $result = curl_exec($ch); + return $result; +} + +$ch = &http_connect('http://127.0.0.1:8010/TextClassificationService/inference'); + +$count = 0; + +# $samples是一个2层array，其中每个元素是一个如下array： +# $samples[0] = array( +# "ids" => array( +# [0] => int(190), +# [1] => int(1), +# [2] => int(70), +# [3] => int(382), +# [4] => int(914), +# [5] => int(5146), +# [6] => int(190)...) +# ) + +for ($i = 0; $i < count($samples) - BATCH_SIZE; $i += BATCH_SIZE) { + $instances = array_slice($samples, $i, BATCH_SIZE); + echo http_post($ch, array("instances" => $instances)) . "\n"; +} + +curl_close($ch); +``` + +完整代码请参考[text_classification.php](../demo-client/php/text_classification.php) diff --git a/doc/SERVING_CONFIGURE.md b/doc/SERVING_CONFIGURE.md index 30966b4776486d1bf7700f1116f1acc098f600f5..95055407d10a5f8f592b34ee10e57c459698bcd6 100644 --- a/doc/SERVING_CONFIGURE.md +++ b/doc/SERVING_CONFIGURE.md @@ -18,9 +18,8 @@ services { 其中 -port: 该字段标明本机serving实例启动的监听端口。默认为8010。还可以通过--port=8010命令行参数指定。 - -services: 可以配置多个services。Paddle Serving被设计为单个Serving实例可以同时承载多个预测服务，服务间通过service name进行区分。例如以下代码配置2个预测服务： +- port: 该字段标明本机serving实例启动的监听端口。默认为8010。还可以通过--port=8010命令行参数指定。 +- services: 可以配置多个services。Paddle Serving被设计为单个Serving实例可以同时承载多个预测服务，服务间通过service name进行区分。例如以下代码配置2个预测服务： ```JSON port: 8010 services { @@ -33,7 +32,7 @@ services { } ``` -service.name: 请填写serving/proto/xx.proto文件的service名称，例如，在serving/proto/image_class.proto中，service名称如下声明： +- service.name: 请填写serving/proto/xx.proto文件的service名称，例如，在serving/proto/image_class.proto中，service名称如下声明： ```JSON service ImageClassifyService { rpc inference(Request) returns (Response); @@ -43,11 +42,11 @@ service ImageClassifyService { ``` 则service name就是`ImageClassifyService` -service.workflows: 用于指定该service下所配的workflow列表。可以配置多个workflow。在本例中，为`ImageClassifyService`配置了一个workflow：`workflow1`。`workflow1`的具体定义在workflow.prototxt +- service.workflows: 用于指定该service下所配的workflow列表。可以配置多个workflow。在本例中，为`ImageClassifyService`配置了一个workflow：`workflow1`。`workflow1`的具体定义在workflow.prototxt ## 2. workflow.prototxt -workflow.prototxt用来描述每一个具体的workflow，他的protobuf格式可参考`configure/server_configure.protobuf`的`Workflow`类型。具体的磁盘文件路径可通过--workflow_path和--workflow_file指定。一个例子如下： +workflow.prototxt用来描述每一个具体的workflow，他的protobuf格式可参考`configure/server_configure.protobuf`的`Workflow`类型。具体的磁盘文件路径可通过`--workflow_path`和`--workflow_file`指定。一个例子如下： ```JSON workflows { @@ -86,32 +85,32 @@ workflows { ``` 以上样例配置了2个workflow：`workflow1`和`workflow2`。以`workflow1`为例： -name: workflow名称，用于从service.prototxt索引到具体的workflow - -workflow_type: 可选"Sequence", "Parallel"，表示本workflow下节点所代表的OP是否可并行。**当前只支持Sequence类型，如配置了Parallel类型，则该workflow不会被执行** - -nodes: 用于串联成workflow的所有节点，可配置多个nodes。nodes间通过配置dependencies串联起来 - -node.name: 随意，建议取一个能代表当前node所执行OP的类 - -node.type: 当前node所执行OP的类名称，与serving/op/下每个具体的OP类的名称对应 - -node.dependencies: 依赖的上游node列表 - -node.dependencies.name: 与workflow内节点的name保持一致 - -node.dependencies.mode: RO-Read Only, RW-Read Write +- name: workflow名称，用于从service.prototxt索引到具体的workflow +- workflow_type: 可选"Sequence", "Parallel"，表示本workflow下节点所代表的OP是否可并行。**当前只支持Sequence类型，如配置了Parallel类型，则该workflow不会被执行** +- nodes: 用于串联成workflow的所有节点，可配置多个nodes。nodes间通过配置dependencies串联起来 +- node.name: 随意，建议取一个能代表当前node所执行OP的类 +- node.type: 当前node所执行OP的类名称，与serving/op/下每个具体的OP类的名称对应 +- node.dependencies: 依赖的上游node列表 +- node.dependencies.name: 与workflow内节点的name保持一致 +- node.dependencies.mode: RO-Read Only, RW-Read Write # 3. resource.prototxt -Serving端resource配置的入口是resource.prototxt，用于配置模型信息。它的protobuf格式参考`configure/proto/server_configure.proto`的ResourceConf。具体的磁盘文件路径可用--resource_path和--resource_file指定。样例如下： +Serving端resource配置的入口是resource.prototxt，用于配置模型信息。它的protobuf格式参考`configure/proto/server_configure.proto`的ResourceConf。具体的磁盘文件路径可用`--resource_path`和`--resource_file`指定。样例如下： ```JSON -model_manager_path: ./conf -model_manager_file: model_toolkit.prototxt +model_toolkit_path: "./conf" +model_toolkit_file: "model_toolkit.prototxt" +cube_config_file: "./conf/cube.conf" ``` -主要用来指定model_toolkit.prototxt路径 +其中： + +- model_toolkit_path:用来指定model_toolkit.prototxt所在的目录 +- model_toolkit_file: 用来指定model_toolkit.prototxt所在的文件名 +- cube_config_file: 用来指定cube配置文件所在路径与文件名 + +Cube是Paddle Serving中用于大规模稀疏参数的组件。 # 4. model_toolkit.prototxt @@ -127,14 +126,18 @@ engines { runtime_thread_num: 0 batch_infer_size: 0 enable_batch_align: 0 + sparse_param_service_type: LOCAL + sparse_param_service_table_name: "local_kv" + enable_memory_optimization: true + static_optimization: false + force_update_static_cache: false } ``` 其中 -name: 模型名称。InferManager通过此名称，找到要使用的模型和预测引擎。可参考serving/op/classify_op.h与serving/op/classify_op.cpp的InferManager::instance().infer()方法的参数来了解。 - -type: 预测引擎的类型。可在inferencer-fluid-cpu/src/fluid_cpu_engine.cpp找到当前注册的预测引擎列表 +- name: 模型名称。InferManager通过此名称，找到要使用的模型和预测引擎。可参考serving/op/classify_op.h与serving/op/classify_op.cpp的InferManager::instance().infer()方法的参数来了解。 +- type: 预测引擎的类型。可在inferencer-fluid-cpu/src/fluid_cpu_engine.cpp找到当前注册的预测引擎列表 |预测引擎|含义| |--------|----| @@ -152,9 +155,8 @@ type: 预测引擎的类型。可在inferencer-fluid-cpu/src/fluid_cpu_engine.cp Analysis API在模型加载过程中，会对模型计算逻辑进行多种优化，包括但不限于zero copy tensor，相邻OP的fuse等。**但优化逻辑不是一定对所有模型都有加速作用，有时甚至会有反作用，请以实测结果为准**。 -reloadable_meta: 目前实际内容无意义，用来通过对该文件的mtime判断是否超过reload时间阈值 - -reloadable_type: 检查reload条件：timestamp_ne/timestamp_gt/md5sum/revision/none +- reloadable_meta: 目前实际内容无意义，用来通过对该文件的mtime判断是否超过reload时间阈值 +- reloadable_type: 检查reload条件：timestamp_ne/timestamp_gt/md5sum/revision/none |reloadable_type|含义| |---------------|----| @@ -163,13 +165,22 @@ reloadable_type: 检查reload条件：timestamp_ne/timestamp_gt/md5sum/revision/ |md5sum|目前无用，配置后永远不reload| |revision|目前无用，配置后用于不reload| -model_data_path: 模型文件路径 - -runtime_thread_num: 若大于0， 则启用bsf多线程调度框架，在每个预测bthread worker内启动多线程预测。要注意的是，当启用worker内多线程预测，workflow中OP需要用Serving框架的BatchTensor类做预测的输入和输出 (predictor/framework/infer_data.h, `class BatchTensor`)。 - -batch_infer_size: 启用bsf多线程预测时，每个预测线程的batch size - -enable_batch_align: +- model_data_path: 模型文件路径 +- runtime_thread_num: 若大于0， 则启用bsf多线程调度框架，在每个预测bthread worker内启动多线程预测。要注意的是，当启用worker内多线程预测，workflow中OP需要用Serving框架的BatchTensor类做预测的输入和输出 (predictor/framework/infer_data.h, `class BatchTensor`)。 +- batch_infer_size: 启用bsf多线程预测时，每个预测线程的batch size +- enable_batch_align: +- sparse_param_service_type: 枚举类型，可选参数，大规模稀疏参数服务类型 + +|sparse_param_service_type|含义| +|-------------------------|--| +|NONE|不使用大规模稀疏参数服务| +|LOCAL|单机本地大规模稀疏参数服务，以rocksdb作为引擎| +|REMOTE|分布式大规模稀疏参数服务，以Cube作为引擎| + +- sparse_param_service_table_name: 可选参数，大规模稀疏参数服务承载本模型所用参数的表名。 +- enable_memory_optimization: bool类型，可选参数，是否启用内存优化。只在使用fluid Analysis预测API时有意义。需要说明的是，在GPU预测时，会执行显存优化 +- static_optimization: bool类型，是否执行静态优化。只有当启用内存优化时有意义。 +- force_update_static_cache: bool类型，是否强制更新静态优化cache。只有当启用内存优化时有意义。 ## 5. 命令行配置参数 diff --git a/inferencer-fluid-cpu/include/fluid_cpu_engine.h b/inferencer-fluid-cpu/include/fluid_cpu_engine.h index 24109ef0226a510d48e0cade4d9bc6039d7d5754..41ab63992361f70f1434efe2c4982342e34b5525 100644 --- a/inferencer-fluid-cpu/include/fluid_cpu_engine.h +++ b/inferencer-fluid-cpu/include/fluid_cpu_engine.h @@ -93,7 +93,7 @@ class FluidFamilyCore { return true; } - virtual int create(const std::string& data_path) = 0; + virtual int create(const predictor::InferEngineCreationParams& params) = 0; virtual int clone(void* origin_core) { if (origin_core == NULL) { @@ -119,7 +119,8 @@ class FluidFamilyCore { // infer interface class FluidCpuAnalysisCore : public FluidFamilyCore { public: - int create(const std::string& data_path) { + int create(const predictor::InferEngineCreationParams& params) { + std::string data_path = params.get_path(); if (access(data_path.c_str(), F_OK) == -1) { LOG(ERROR) << "create paddle predictor failed, path not exits: " << data_path; @@ -131,6 +132,12 @@ class FluidCpuAnalysisCore : public FluidFamilyCore { analysis_config.SetProgFile(data_path + "/__model__"); analysis_config.DisableGpu(); analysis_config.SetCpuMathLibraryNumThreads(1); + + if (params.enable_memory_optimization()) { + analysis_config.EnableMemoryOptim(params.static_optimization(), + params.force_update_static_cache()); + } + analysis_config.SwitchSpecifyInputNames(true); AutoLock lock(GlobalPaddleCreateMutex::instance()); _core = @@ -147,7 +154,8 @@ class FluidCpuAnalysisCore : public FluidFamilyCore { class FluidCpuNativeCore : public FluidFamilyCore { public: - int create(const std::string& data_path) { + int create(const predictor::InferEngineCreationParams& params) { + std::string data_path = params.get_path(); if (access(data_path.c_str(), F_OK) == -1) { LOG(ERROR) << "create paddle predictor failed, path not exits: " << data_path; @@ -177,7 +185,8 @@ class FluidCpuNativeCore : public FluidFamilyCore { class FluidCpuAnalysisDirCore : public FluidFamilyCore { public: - int create(const std::string& data_path) { + int create(const predictor::InferEngineCreationParams& params) { + std::string data_path = params.get_path(); if (access(data_path.c_str(), F_OK) == -1) { LOG(ERROR) << "create paddle predictor failed, path not exits: " << data_path; @@ -189,6 +198,12 @@ class FluidCpuAnalysisDirCore : public FluidFamilyCore { analysis_config.DisableGpu(); analysis_config.SwitchSpecifyInputNames(true); analysis_config.SetCpuMathLibraryNumThreads(1); + + if (params.enable_memory_optimization()) { + analysis_config.EnableMemoryOptim(params.static_optimization(), + params.force_update_static_cache()); + } + AutoLock lock(GlobalPaddleCreateMutex::instance()); _core = paddle::CreatePaddlePredictor(analysis_config); @@ -204,7 +219,8 @@ class FluidCpuAnalysisDirCore : public FluidFamilyCore { class FluidCpuNativeDirCore : public FluidFamilyCore { public: - int create(const std::string& data_path) { + int create(const predictor::InferEngineCreationParams& params) { + std::string data_path = params.get_path(); if (access(data_path.c_str(), F_OK) == -1) { LOG(ERROR) << "create paddle predictor failed, path not exits: " << data_path; @@ -380,7 +396,8 @@ class FluidCpuWithSigmoidCore : public FluidFamilyCore { virtual ~FluidCpuWithSigmoidCore() {} public: - int create(const std::string& model_path) { + int create(const predictor::InferEngineCreationParams& params) { + std::string model_path = params.get_path(); size_t pos = model_path.find_last_of("/\\"); std::string conf_path = model_path.substr(0, pos); std::string conf_file = model_path.substr(pos); @@ -393,7 +410,9 @@ class FluidCpuWithSigmoidCore : public FluidFamilyCore { _core.reset(new SigmoidFluidModel); std::string fluid_model_data_path = conf.dnn_model_path(); - int ret = load_fluid_model(fluid_model_data_path); + predictor::InferEngineCreationParams new_params(params); + new_params.set_path(fluid_model_data_path); + int ret = load_fluid_model(new_params); if (ret < 0) { LOG(ERROR) << "fail to load fluid model."; return -1; @@ -442,7 +461,8 @@ class FluidCpuWithSigmoidCore : public FluidFamilyCore { virtual SigmoidFluidModel* get() { return _core.get(); } - virtual int load_fluid_model(const std::string& data_path) = 0; + virtual int load_fluid_model( + const predictor::InferEngineCreationParams& params) = 0; int softmax(float x, double& o) { // NOLINT return _core->_sigmoid_core->softmax(x, o); @@ -454,7 +474,8 @@ class FluidCpuWithSigmoidCore : public FluidFamilyCore { class FluidCpuNativeDirWithSigmoidCore : public FluidCpuWithSigmoidCore { public: - int load_fluid_model(const std::string& data_path) { + int load_fluid_model(const predictor::InferEngineCreationParams& params) { + std::string data_path = params.get_path(); if (access(data_path.c_str(), F_OK) == -1) { LOG(ERROR) << "create paddle predictor failed, path not exits: " << data_path; @@ -483,7 +504,8 @@ class FluidCpuNativeDirWithSigmoidCore : public FluidCpuWithSigmoidCore { class FluidCpuAnalysisDirWithSigmoidCore : public FluidCpuWithSigmoidCore { public: - int load_fluid_model(const std::string& data_path) { + int load_fluid_model(const predictor::InferEngineCreationParams& params) { + std::string data_path = params.get_path(); if (access(data_path.c_str(), F_OK) == -1) { LOG(ERROR) << "create paddle predictor failed, path not exits: " << data_path; @@ -495,6 +517,12 @@ class FluidCpuAnalysisDirWithSigmoidCore : public FluidCpuWithSigmoidCore { analysis_config.DisableGpu(); analysis_config.SwitchSpecifyInputNames(true); analysis_config.SetCpuMathLibraryNumThreads(1); + + if (params.enable_memory_optimization()) { + analysis_config.EnableMemoryOptim(params.static_optimization(), + params.force_update_static_cache()); + } + AutoLock lock(GlobalPaddleCreateMutex::instance()); _core->_fluid_core = paddle::CreatePaddlePredictor(analysis_config); diff --git a/inferencer-fluid-gpu/include/fluid_gpu_engine.h b/inferencer-fluid-gpu/include/fluid_gpu_engine.h index b07789300eb688f6f1be6ee4419ad54634a911e3..226e114f8cea32eda110cde6d7810506f7236d61 100644 --- a/inferencer-fluid-gpu/include/fluid_gpu_engine.h +++ b/inferencer-fluid-gpu/include/fluid_gpu_engine.h @@ -95,7 +95,7 @@ class FluidFamilyCore { return true; } - virtual int create(const std::string& data_path) = 0; + virtual int create(const predictor::InferEngineCreationParams& params) = 0; virtual int clone(void* origin_core) { if (origin_core == NULL) { @@ -121,7 +121,8 @@ class FluidFamilyCore { // infer interface class FluidGpuAnalysisCore : public FluidFamilyCore { public: - int create(const std::string& data_path) { + int create(const predictor::InferEngineCreationParams& params) { + std::string data_path = params.get_path(); if (access(data_path.c_str(), F_OK) == -1) { LOG(ERROR) << "create paddle predictor failed, path not exits: " << data_path; @@ -133,7 +134,12 @@ class FluidGpuAnalysisCore : public FluidFamilyCore { analysis_config.SetProgFile(data_path + "/__model__"); analysis_config.EnableUseGpu(100, FLAGS_gpuid); analysis_config.SetCpuMathLibraryNumThreads(1); - analysis_config.EnableMemoryOptim(false, false); + + if (params.enable_memory_optimization()) { + analysis_config.EnableMemoryOptim(params.static_optimization(), + params.force_update_static_cache()); + } + analysis_config.SwitchSpecifyInputNames(true); AutoLock lock(GlobalPaddleCreateMutex::instance()); @@ -151,7 +157,8 @@ class FluidGpuAnalysisCore : public FluidFamilyCore { class FluidGpuNativeCore : public FluidFamilyCore { public: - int create(const std::string& data_path) { + int create(const predictor::InferEngineCreationParams& params) { + std::string data_path = params.get_path(); if (access(data_path.c_str(), F_OK) == -1) { LOG(ERROR) << "create paddle predictor failed, path not exits: " << data_path; @@ -180,7 +187,8 @@ class FluidGpuNativeCore : public FluidFamilyCore { class FluidGpuAnalysisDirCore : public FluidFamilyCore { public: - int create(const std::string& data_path) { + int create(const predictor::InferEngineCreationParams& params) { + std::string data_path = params.get_path(); if (access(data_path.c_str(), F_OK) == -1) { LOG(ERROR) << "create paddle predictor failed, path not exits: " << data_path; @@ -192,7 +200,11 @@ class FluidGpuAnalysisDirCore : public FluidFamilyCore { analysis_config.EnableUseGpu(100, FLAGS_gpuid); analysis_config.SwitchSpecifyInputNames(true); analysis_config.SetCpuMathLibraryNumThreads(1); - analysis_config.EnableMemoryOptim(false, false); + + if (params.enable_memory_optimization()) { + analysis_config.EnableMemoryOptim(params.static_optimization(), + params.force_update_static_cache()); + } AutoLock lock(GlobalPaddleCreateMutex::instance()); _core = @@ -209,7 +221,8 @@ class FluidGpuAnalysisDirCore : public FluidFamilyCore { class FluidGpuNativeDirCore : public FluidFamilyCore { public: - int create(const std::string& data_path) { + int create(const predictor::InferEngineCreationParams& params) { + std::string data_path = params.get_path(); if (access(data_path.c_str(), F_OK) == -1) { LOG(ERROR) << "create paddle predictor failed, path not exits: " << data_path; @@ -385,7 +398,8 @@ class FluidGpuWithSigmoidCore : public FluidFamilyCore { virtual ~FluidGpuWithSigmoidCore() {} public: - int create(const std::string& model_path) { + int create(const predictor::InferEngineCreationParams& params) { + std::string model_path = params.get_path(); size_t pos = model_path.find_last_of("/\\"); std::string conf_path = model_path.substr(0, pos); std::string conf_file = model_path.substr(pos); @@ -398,7 +412,9 @@ class FluidGpuWithSigmoidCore : public FluidFamilyCore { _core.reset(new SigmoidFluidModel); std::string fluid_model_data_path = conf.dnn_model_path(); - int ret = load_fluid_model(fluid_model_data_path); + predictor::InferEngineCreationParams new_params(params); + new_params.set_path(fluid_model_data_path); + int ret = load_fluid_model(new_params); if (ret < 0) { LOG(ERROR) << "fail to load fluid model."; return -1; @@ -447,7 +463,8 @@ class FluidGpuWithSigmoidCore : public FluidFamilyCore { virtual SigmoidFluidModel* get() { return _core.get(); } - virtual int load_fluid_model(const std::string& data_path) = 0; + virtual int load_fluid_model( + const predictor::InferEngineCreationParams& params) = 0; int softmax(float x, double& o) { // NOLINT return _core->_sigmoid_core->softmax(x, o); @@ -459,7 +476,8 @@ class FluidGpuWithSigmoidCore : public FluidFamilyCore { class FluidGpuNativeDirWithSigmoidCore : public FluidGpuWithSigmoidCore { public: - int load_fluid_model(const std::string& data_path) { + int load_fluid_model(const predictor::InferEngineCreationParams& params) { + std::string data_path = params.get_path(); if (access(data_path.c_str(), F_OK) == -1) { LOG(ERROR) << "create paddle predictor failed, path not exits: " << data_path; @@ -488,7 +506,8 @@ class FluidGpuNativeDirWithSigmoidCore : public FluidGpuWithSigmoidCore { class FluidGpuAnalysisDirWithSigmoidCore : public FluidGpuWithSigmoidCore { public: - int load_fluid_model(const std::string& data_path) { + int load_fluid_model(const predictor::InferEngineCreationParams& params) { + std::string data_path = params.get_path(); if (access(data_path.c_str(), F_OK) == -1) { LOG(ERROR) << "create paddle predictor failed, path not exits: " << data_path; @@ -500,7 +519,12 @@ class FluidGpuAnalysisDirWithSigmoidCore : public FluidGpuWithSigmoidCore { analysis_config.EnableUseGpu(100, FLAGS_gpuid); analysis_config.SwitchSpecifyInputNames(true); analysis_config.SetCpuMathLibraryNumThreads(1); - analysis_config.EnableMemoryOptim(false, false); + + if (params.enable_memory_optimization()) { + analysis_config.EnableMemoryOptim(params.static_optimization(), + params.force_update_static_cache()); + } + AutoLock lock(GlobalPaddleCreateMutex::instance()); _core->_fluid_core = paddle::CreatePaddlePredictor(analysis_config); diff --git a/predictor/framework/infer.h b/predictor/framework/infer.h index d305d59a16de850e8da3661eaa736d6999eec920..c2823f5e3d8cbd2484f02053ffd36e6a3a275846 100644 --- a/predictor/framework/infer.h +++ b/predictor/framework/infer.h @@ -29,6 +29,55 @@ namespace predictor { using configure::ModelToolkitConf; +class InferEngineCreationParams { + public: + InferEngineCreationParams() { + _path = ""; + _enable_memory_optimization = false; + _static_optimization = false; + _force_update_static_cache = false; + } + + void set_path(const std::string& path) { _path = path; } + + void set_enable_memory_optimization(bool enable_memory_optimization) { + _enable_memory_optimization = enable_memory_optimization; + } + + bool enable_memory_optimization() const { + return _enable_memory_optimization; + } + + void set_static_optimization(bool static_optimization = false) { + _static_optimization = static_optimization; + } + + void set_force_update_static_cache(bool force_update_static_cache = false) { + _force_update_static_cache = force_update_static_cache; + } + + bool static_optimization() const { return _static_optimization; } + + bool force_update_static_cache() const { return _force_update_static_cache; } + + std::string get_path() const { return _path; } + + void dump() const { + LOG(INFO) << "InferEngineCreationParams: " + << "model_path = " << _path << ", " + << "enable_memory_optimization = " << _enable_memory_optimization + << ", " + << "static_optimization = " << _static_optimization << ", " + << "force_update_static_cache = " << _force_update_static_cache; + } + + private: + std::string _path; + bool _enable_memory_optimization; + bool _static_optimization; + bool _force_update_static_cache; +}; + class InferEngine { public: virtual ~InferEngine() {} @@ -75,7 +124,7 @@ class ReloadableInferEngine : public InferEngine { typedef im::bsf::Task TaskT; - virtual int load(const std::string& data_path) = 0; + virtual int load(const InferEngineCreationParams& params) = 0; int proc_initialize_impl(const configure::EngineDesc& conf, bool version) { _reload_tag_file = conf.reloadable_meta(); @@ -84,7 +133,31 @@ class ReloadableInferEngine : public InferEngine { _infer_thread_num = conf.runtime_thread_num(); _infer_batch_size = conf.batch_infer_size(); _infer_batch_align = conf.enable_batch_align(); - if (!check_need_reload() || load(_model_data_path) != 0) { + + bool enable_memory_optimization = false; + if (conf.has_enable_memory_optimization()) { + enable_memory_optimization = conf.enable_memory_optimization(); + } + + bool static_optimization = false; + if (conf.has_static_optimization()) { + static_optimization = conf.static_optimization(); + } + + bool force_update_static_cache = false; + if (conf.has_force_update_static_cache()) { + force_update_static_cache = conf.force_update_static_cache(); + } + + _infer_engine_params.set_path(_model_data_path); + if (enable_memory_optimization) { + _infer_engine_params.set_enable_memory_optimization(true); + _infer_engine_params.set_static_optimization(static_optimization); + _infer_engine_params.set_force_update_static_cache( + force_update_static_cache); + } + + if (!check_need_reload() || load(_infer_engine_params) != 0) { LOG(ERROR) << "Failed load model_data_path" << _model_data_path; return -1; } @@ -175,7 +248,7 @@ class ReloadableInferEngine : public InferEngine { int reload() { if (check_need_reload()) { LOG(WARNING) << "begin reload model[" << _model_data_path << "]."; - return load(_model_data_path); + return load(_infer_engine_params); } return 0; } @@ -243,6 +316,7 @@ class ReloadableInferEngine : public InferEngine { protected: std::string _model_data_path; + InferEngineCreationParams _infer_engine_params; private: std::string _reload_tag_file; @@ -281,32 +355,35 @@ class DBReloadableInferEngine : public ReloadableInferEngine { return ReloadableInferEngine::proc_initialize(conf, version); } - virtual int load(const std::string& model_data_dir) { + virtual int load(const InferEngineCreationParams& params) { if (_reload_vec.empty()) { return 0; } for (uint32_t ti = 0; ti < _reload_vec.size(); ++ti) { - if (load_data(_reload_vec[ti], model_data_dir) != 0) { + if (load_data(_reload_vec[ti], params) != 0) { LOG(ERROR) << "Failed reload engine model: " << ti; return -1; } } - LOG(WARNING) << "Succ load engine, path: " << model_data_dir; + LOG(WARNING) << "Succ load engine, path: " << params.get_path(); return 0; } - int load_data(ModelData* md, const std::string& data_path) { + int load_data(ModelData* md, + const InferEngineCreationParams& params) { uint32_t next_idx = (md->current_idx + 1) % 2; if (md->cores[next_idx]) { delete md->cores[next_idx]; } md->cores[next_idx] = new (std::nothrow) EngineCore; - if (!md->cores[next_idx] || md->cores[next_idx]->create(data_path) != 0) { - LOG(ERROR) << "Failed create model, path: " << data_path; + + params.dump(); + if (!md->cores[next_idx] || md->cores[next_idx]->create(params) != 0) { + LOG(ERROR) << "Failed create model, path: " << params.get_path(); return -1; } md->current_idx = next_idx; @@ -321,8 +398,9 @@ class DBReloadableInferEngine : public ReloadableInferEngine { } ModelData* md = new (std::nothrow) ModelData; - if (!md || load_data(md, _model_data_path) != 0) { - LOG(ERROR) << "Failed create thread data from " << _model_data_path; + if (!md || load_data(md, _infer_engine_params) != 0) { + LOG(ERROR) << "Failed create thread data from " + << _infer_engine_params.get_path(); return -1; } @@ -383,17 +461,16 @@ class CloneDBReloadableInferEngine return DBReloadableInferEngine::proc_initialize(conf, version); } - virtual int load(const std::string& model_data_dir) { + virtual int load(const InferEngineCreationParams& params) { // 加载进程级模型数据 if (!_pd || - DBReloadableInferEngine::load_data(_pd, model_data_dir) != - 0) { - LOG(ERROR) << "Failed to create common model from [" << model_data_dir + DBReloadableInferEngine::load_data(_pd, params) != 0) { + LOG(ERROR) << "Failed to create common model from [" << params.get_path() << "]."; return -1; } LOG(WARNING) << "Succ load common model[" << _pd->cores[_pd->current_idx] - << "], path[" << model_data_dir << "]."; + << "], path[" << params.get_path() << "]."; if (DBReloadableInferEngine::_reload_vec.empty()) { return 0; @@ -409,7 +486,7 @@ class CloneDBReloadableInferEngine } } - LOG(WARNING) << "Succ load clone model, path[" << model_data_dir << "]"; + LOG(WARNING) << "Succ load clone model, path[" << params.get_path() << "]"; return 0; } diff --git a/predictor/framework/resource.cpp b/predictor/framework/resource.cpp index 29c5b20765c99cd4d9223ea845326f032f726a06..74e3c95204dfb4fb0dcf32201c244550b6df08c2 100644 --- a/predictor/framework/resource.cpp +++ b/predictor/framework/resource.cpp @@ -110,12 +110,6 @@ int Resource::cube_initialize(const std::string& path, } int err = 0; - std::string cube_config_path = resource_conf.cube_config_path(); - if (err != 0) { - LOG(ERROR) << "reade cube_config_path failed, path[" << path << "], file[" - << cube_config_path << "]"; - return -1; - } std::string cube_config_file = resource_conf.cube_config_file(); if (err != 0) { LOG(ERROR) << "reade cube_config_file failed, path[" << path << "], file[" @@ -124,8 +118,8 @@ int Resource::cube_initialize(const std::string& path, } err = CubeAPI::instance()->init(cube_config_file.c_str()); if (err != 0) { - LOG(ERROR) << "failed initialize cube, config: " << cube_config_path << "/" - << cube_config_file << " error code : " << err; + LOG(ERROR) << "failed initialize cube, config: " << cube_config_file + << " error code : " << err; return -1; }