config.yml

#worker_num, 最大并发数。当build_dag_each_worker=True时, 框架会创建worker_num个进程，每个进程内构建grpcSever和DAG
##当build_dag_each_worker=False时，框架会设置主线程grpc线程池的max_workers=worker_num
worker_num: 1

#http端口, rpc_port和http_port不允许同时为空。当rpc_port可用且http_port为空时，不自动生成http_port
http_port: 18081
rpc_port: 9994

dag:
    #op资源类型, True, 为线程模型；False，为进程模型
    is_thread_op: False
op:
    rec:
        #并发数，is_thread_op=True时，为线程并发；否则为进程并发
        concurrency: 1

        #当op配置没有server_endpoints时，从local_service_conf读取本地服务配置
        local_service_conf:

            #uci模型路径
            model_config: ../../models/general_PPLCNet_x2_5_lite_v1.0_serving

            #计算硬件类型: 空缺时由devices决定(CPU/GPU)，0=cpu, 1=gpu, 2=tensorRT, 3=arm cpu, 4=kunlun xpu
            device_type: 1

            #计算硬件ID，当devices为""或不写时为CPU预测；当devices为"0", "0,1,2"时为GPU预测，表示使用的GPU卡
            devices: "0" # "0,1"

            #client类型，包括brpc, grpc和local_predictor.local_predictor不启动Serving服务，进程内预测
            client_type: local_predictor

            #Fetch结果列表，以client_config中fetch_var的alias_name为准
            fetch_list: ["features"]
            
    det:
        concurrency: 1
        local_service_conf:
            client_type: local_predictor
            device_type: 1
            devices: '0'
            fetch_list:
            - save_infer_model/scale_0.tmp_1
            model_config: ../../models/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_serving/