44 lines
1.7 KiB
YAML
44 lines
1.7 KiB
YAML
#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
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##当build_dag_each_worker=False时，框架会设置主线程grpc线程池的max_workers=worker_num
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worker_num: 1
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#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
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http_port: 18081
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rpc_port: 9994
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dag:
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#op资源类型, True, 为线程模型；False，为进程模型
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is_thread_op: False
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op:
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rec:
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#并发数，is_thread_op=True时，为线程并发；否则为进程并发
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concurrency: 1
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#当op配置没有server_endpoints时，从local_service_conf读取本地服务配置
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local_service_conf:
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#uci模型路径
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model_config: ../../models/general_PPLCNet_x2_5_lite_v1.0_serving
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#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
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device_type: 1
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#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
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devices: "0" # "0,1"
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#client类型，包括brpc, grpc和local_predictor.local_predictor不启动Serving服务，进程内预测
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client_type: local_predictor
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#Fetch结果列表，以client_config中fetch_var的alias_name为准
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fetch_list: ["features"]
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det:
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concurrency: 1
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local_service_conf:
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client_type: local_predictor
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device_type: 1
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devices: '0'
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fetch_list:
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- save_infer_model/scale_0.tmp_1
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model_config: ../../models/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_serving/
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