#include #include #include #include #include "server_configure.pb.h" #include "sdk_configure.pb.h" #include "inferencer_configure.pb.h" #include "configure_parser.h" using baidu::paddle_serving::configure::EngineDesc; using baidu::paddle_serving::configure::ModelToolkitConf; using baidu::paddle_serving::configure::ResourceConf; using baidu::paddle_serving::configure::DAGNodeDependency; using baidu::paddle_serving::configure::DAGNode; using baidu::paddle_serving::configure::Workflow; using baidu::paddle_serving::configure::WorkflowConf; using baidu::paddle_serving::configure::InferService; using baidu::paddle_serving::configure::InferServiceConf; using baidu::paddle_serving::configure::ConnectionConf; using baidu::paddle_serving::configure::WeightedRandomRenderConf; using baidu::paddle_serving::configure::NamingConf; using baidu::paddle_serving::configure::RpcParameter; using baidu::paddle_serving::configure::Predictor; using baidu::paddle_serving::configure::VariantConf; using baidu::paddle_serving::configure::SDKConf; using baidu::paddle_serving::configure::SigmoidConf; const std::string output_dir = "./conf/"; const std::string model_toolkit_conf_file = "model_toolkit.prototxt"; const std::string resource_conf_file = "resource.prototxt"; const std::string workflow_conf_file = "workflow.prototxt"; const std::string service_conf_file = "service.prototxt"; const std::string sdk_conf_file = "predictors.prototxt"; const std::string sigmoid_conf_file = "inferencer.prototxt"; int test_write_conf() { // model_toolkit conf ModelToolkitConf model_toolkit_conf; // This engine has a default version EngineDesc *engine = model_toolkit_conf.add_engines(); engine->set_name("image_classification_resnet"); engine->set_type("FLUID_CPU_NATIVE_DIR"); engine->set_reloadable_meta("./data/model/paddle/fluid_time_file"); engine->set_reloadable_type("timestamp_ne"); engine->set_model_data_path("./data/model/paddle/fluid/SE_ResNeXt50_32x4d"); engine->set_runtime_thread_num(0); engine->set_batch_infer_size(0); engine->set_enable_batch_align(0); int ret = baidu::paddle_serving::configure::write_proto_conf(&model_toolkit_conf, output_dir, model_toolkit_conf_file); if (ret != 0) { return ret; } // resource conf ResourceConf resource_conf; resource_conf.set_model_toolkit_path(output_dir); resource_conf.set_model_toolkit_file("model_toolkit.prototxt"); ret = baidu::paddle_serving::configure::write_proto_conf(&resource_conf, output_dir, resource_conf_file); if (ret != 0) { return ret; } // workflow entries conf WorkflowConf workflow_conf; Workflow *workflow = workflow_conf.add_workflows(); workflow->set_name("workflow1"); workflow->set_workflow_type("Sequence"); DAGNode *dag_node = workflow->add_nodes(); dag_node->set_name("image_reader_op"); dag_node->set_type("ReaderOp"); dag_node = workflow->add_nodes(); dag_node->set_name("imag_classify_op"); dag_node->set_type("ClassifyOp"); DAGNodeDependency *node_dependency = dag_node->add_dependencies(); node_dependency->set_name("image_reader_op"); node_dependency->set_mode("RO"); dag_node = workflow->add_nodes(); dag_node->set_name("write_json_op"); dag_node->set_type("WriteOp"); node_dependency = dag_node->add_dependencies(); node_dependency->set_name("image_classify_op"); node_dependency->set_mode("RO"); workflow = workflow_conf.add_workflows(); workflow->set_name("workflow2"); workflow->set_workflow_type("Sequence"); dag_node = workflow->add_nodes(); dag_node->set_name("dense_op"); dag_node->set_type("DenseOp"); ret = baidu::paddle_serving::configure::write_proto_conf(&workflow_conf, output_dir, workflow_conf_file); if (ret != 0) { return ret; } InferServiceConf infer_service_conf; infer_service_conf.set_port(0); InferService *infer_service = infer_service_conf.add_services(); infer_service->set_name("ImageClassifyService"); infer_service->add_workflows("workflow1"); infer_service->add_workflows("workflow2"); infer_service = infer_service_conf.add_services(); infer_service->set_name("BuiltinDenseFormatService"); infer_service->add_workflows("workflow2"); ret = baidu::paddle_serving::configure::write_proto_conf(&infer_service_conf, output_dir, service_conf_file); if (ret != 0) { return ret; } SDKConf sdk_conf; VariantConf *default_variant_conf = sdk_conf.mutable_default_variant_conf(); default_variant_conf->set_tag("default"); ConnectionConf *connection_conf = default_variant_conf->mutable_connection_conf(); connection_conf->set_connect_timeout_ms(2000); connection_conf->set_rpc_timeout_ms(20000); connection_conf->set_connect_retry_count(2); connection_conf->set_max_connection_per_host(100); connection_conf->set_hedge_request_timeout_ms(-1); connection_conf->set_hedge_fetch_retry_count(2); connection_conf->set_connection_type("pooled"); NamingConf *naming_conf = default_variant_conf->mutable_naming_conf(); naming_conf->set_cluster_filter_strategy("Default"); naming_conf->set_load_balance_strategy("la"); RpcParameter *rpc_parameter = default_variant_conf->mutable_rpc_parameter(); rpc_parameter->set_compress_type(0); rpc_parameter->set_package_size(20); rpc_parameter->set_protocol("baidu_std"); rpc_parameter->set_max_channel_per_request(3); Predictor *predictor = sdk_conf.add_predictors(); predictor->set_name("ximage"); predictor->set_service_name("baidu.paddle_serving.predictor.image_classification.ImageClassifyService"); predictor->set_endpoint_router("WeightedRandomRender"); WeightedRandomRenderConf *weighted_random_render_conf = predictor->mutable_weighted_random_render_conf(); weighted_random_render_conf->set_variant_weight_list("50"); VariantConf *variant_conf = predictor->add_variants(); variant_conf->set_tag("var1"); naming_conf = variant_conf->mutable_naming_conf(); naming_conf->set_cluster("list://127.0.0.1:8010"); ret = baidu::paddle_serving::configure::write_proto_conf(&sdk_conf, output_dir, sdk_conf_file); if (ret != 0) { return ret; } SigmoidConf sigmoid_conf; sigmoid_conf.set_dnn_model_path("data/dnn_model"); sigmoid_conf.set_sigmoid_w_file("data/dnn_model/_sigmoid_.w_0"); sigmoid_conf.set_sigmoid_b_file("data/dnn_model/_sigmoid_.b_0"); sigmoid_conf.set_exp_max_input(0.75); sigmoid_conf.set_exp_min_input(0.25); ret = baidu::paddle_serving::configure::write_proto_conf(&sigmoid_conf, output_dir, sigmoid_conf_file); if (ret != 0) { return ret; } return 0; } int test_read_conf() { int ret = 0; ModelToolkitConf model_toolkit_conf; ret = baidu::paddle_serving::configure::read_proto_conf(output_dir, model_toolkit_conf_file, &model_toolkit_conf); if (ret != 0) { std::cout << "Read conf fail: " << model_toolkit_conf_file << std::endl; return -1; } ResourceConf resource_conf; ret = baidu::paddle_serving::configure::read_proto_conf(output_dir, resource_conf_file, &resource_conf); if (ret != 0) { std::cout << "Read conf fail: " << resource_conf_file << std::endl; return -1; } WorkflowConf workflow_conf; ret = baidu::paddle_serving::configure::read_proto_conf(output_dir, workflow_conf_file, &workflow_conf); if (ret != 0) { std::cout << "Read conf fail: " << workflow_conf_file << std::endl; return -1; } InferServiceConf service_conf; ret = baidu::paddle_serving::configure::read_proto_conf(output_dir, service_conf_file, &service_conf); if (ret != 0) { std::cout << "Read conf fail: " << service_conf_file << std::endl; return -1; } SDKConf sdk_conf; ret = baidu::paddle_serving::configure::read_proto_conf(output_dir, sdk_conf_file, &sdk_conf); if (ret != 0) { std::cout << "Read conf fail: " << sdk_conf_file << std::endl; return -1; } SigmoidConf sigmoid_conf; ret = baidu::paddle_serving::configure::read_proto_conf(output_dir, sigmoid_conf_file, &sigmoid_conf); if (ret != 0) { std::cout << "Read conf fail: " << sdk_conf_file << std::endl; return -1; } return 0; } int main() { int ret = 0; struct stat stat_buf; if (stat(output_dir.c_str(), &stat_buf) != 0) { int ret = mkdir("./conf", 0777); if (ret != 0) { std::cout << "mkdir ./conf fail" << std::endl; return -1; } if (stat("./conf", &stat_buf) != 0) { std::cout << "./conf not exist and creating it failed" << std::endl; return -1; } } ret = test_write_conf(); if (ret != 0) { std::cout << "test_write_conf fail" << std::endl; return -1; } std::cout << "test_write_conf success" << std::endl; ret = test_read_conf(); if (ret != 0) { std::cout << "test_read_conf fail" << std::endl; return -1; } std::cout << "test_read_conf success" << std::endl; return 0; } /* vim: set expandtab ts=4 sw=4 sts=4 tw=100: */