319 lines
14 KiB
Bash
319 lines
14 KiB
Bash
#!/bin/bash
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source test_tipc/common_func.sh
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FILENAME=$1
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MODE=$2
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dataline=$(awk 'NR==1, NR==19{print}' $FILENAME)
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# parser params
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IFS=$'\n'
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lines=(${dataline})
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function func_get_url_file_name(){
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strs=$1
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IFS="/"
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array=(${strs})
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tmp=${array[${#array[@]}-1]}
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echo ${tmp}
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}
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# parser serving
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model_name=$(func_parser_value "${lines[1]}")
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python=$(func_parser_value "${lines[2]}")
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trans_model_py=$(func_parser_value "${lines[4]}")
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infer_model_dir_key=$(func_parser_key "${lines[5]}")
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infer_model_dir_value=$(func_parser_value "${lines[5]}")
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model_filename_key=$(func_parser_key "${lines[6]}")
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model_filename_value=$(func_parser_value "${lines[6]}")
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params_filename_key=$(func_parser_key "${lines[7]}")
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params_filename_value=$(func_parser_value "${lines[7]}")
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serving_server_key=$(func_parser_key "${lines[8]}")
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serving_server_value=$(func_parser_value "${lines[8]}")
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serving_client_key=$(func_parser_key "${lines[9]}")
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serving_client_value=$(func_parser_value "${lines[9]}")
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serving_dir_value=$(func_parser_value "${lines[10]}")
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web_service_py=$(func_parser_value "${lines[11]}")
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web_use_gpu_key=$(func_parser_key "${lines[12]}")
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web_use_gpu_list=$(func_parser_value "${lines[12]}")
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pipeline_py=$(func_parser_value "${lines[13]}")
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function func_serving_cls(){
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LOG_PATH="test_tipc/output/${model_name}/${MODE}"
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mkdir -p ${LOG_PATH}
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LOG_PATH="../../${LOG_PATH}"
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status_log="${LOG_PATH}/results_serving.log"
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IFS='|'
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# pdserving
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set_dirname=$(func_set_params "${infer_model_dir_key}" "${infer_model_dir_value}")
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set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}")
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set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}")
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set_serving_server=$(func_set_params "${serving_server_key}" "${serving_server_value}")
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set_serving_client=$(func_set_params "${serving_client_key}" "${serving_client_value}")
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for python_ in ${python[*]}; do
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if [[ ${python_} =~ "python" ]]; then
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trans_model_cmd="${python_} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}"
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eval ${trans_model_cmd}
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break
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fi
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done
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# modify the alias_name of fetch_var to "outputs"
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server_fetch_var_line_cmd="sed -i '/fetch_var/,/is_lod_tensor/s/alias_name: .*/alias_name: \"prediction\"/' ${serving_server_value}/serving_server_conf.prototxt"
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eval ${server_fetch_var_line_cmd}
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client_fetch_var_line_cmd="sed -i '/fetch_var/,/is_lod_tensor/s/alias_name: .*/alias_name: \"prediction\"/' ${serving_client_value}/serving_client_conf.prototxt"
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eval ${client_fetch_var_line_cmd}
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prototxt_dataline=$(awk 'NR==1, NR==3{print}' ${serving_server_value}/serving_server_conf.prototxt)
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IFS=$'\n'
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prototxt_lines=(${prototxt_dataline})
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feed_var_name=$(func_parser_value "${prototxt_lines[2]}")
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IFS='|'
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cd ${serving_dir_value}
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unset https_proxy
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unset http_proxy
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# python serving
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# modify the input_name in "classification_web_service.py" to be consistent with feed_var.name in prototxt
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set_web_service_feed_var_cmd="sed -i '/preprocess/,/input_imgs}/s/{.*: input_imgs}/{${feed_var_name}: input_imgs}/' ${web_service_py}"
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eval ${set_web_service_feed_var_cmd}
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model_config=21
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serving_server_dir_name=$(func_get_url_file_name "$serving_server_value")
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set_model_config_cmd="sed -i '${model_config}s/model_config: .*/model_config: ${serving_server_dir_name}/' config.yml"
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eval ${set_model_config_cmd}
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for use_gpu in ${web_use_gpu_list[*]}; do
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if [[ ${use_gpu} = "null" ]]; then
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device_type_line=24
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set_device_type_cmd="sed -i '${device_type_line}s/device_type: .*/device_type: 0/' config.yml"
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eval ${set_device_type_cmd}
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devices_line=27
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set_devices_cmd="sed -i '${devices_line}s/devices: .*/devices: \"\"/' config.yml"
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eval ${set_devices_cmd}
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web_service_cmd="${python_} ${web_service_py} &"
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eval ${web_service_cmd}
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last_status=${PIPESTATUS[0]}
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status_check $last_status "${web_service_cmd}" "${status_log}" "${model_name}"
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sleep 5s
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for pipeline in ${pipeline_py[*]}; do
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_save_log_path="${LOG_PATH}/server_infer_cpu_${pipeline%_client*}_batchsize_1.log"
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pipeline_cmd="${python_} ${pipeline} > ${_save_log_path} 2>&1 "
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eval ${pipeline_cmd}
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last_status=${PIPESTATUS[0]}
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eval "cat ${_save_log_path}"
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status_check $last_status "${pipeline_cmd}" "${status_log}" "${model_name}"
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sleep 5s
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done
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eval "${python_} -m paddle_serving_server.serve stop"
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elif [ ${use_gpu} -eq 0 ]; then
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if [[ ${_flag_quant} = "False" ]] && [[ ${precision} =~ "int8" ]]; then
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continue
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fi
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if [[ ${precision} =~ "fp16" || ${precision} =~ "int8" ]] && [ ${use_trt} = "False" ]; then
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continue
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fi
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if [[ ${use_trt} = "False" || ${precision} =~ "int8" ]] && [[ ${_flag_quant} = "True" ]]; then
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continue
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fi
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device_type_line=24
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set_device_type_cmd="sed -i '${device_type_line}s/device_type: .*/device_type: 1/' config.yml"
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eval ${set_device_type_cmd}
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devices_line=27
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set_devices_cmd="sed -i '${devices_line}s/devices: .*/devices: \"${use_gpu}\"/' config.yml"
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eval ${set_devices_cmd}
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web_service_cmd="${python_} ${web_service_py} & "
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eval ${web_service_cmd}
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last_status=${PIPESTATUS[0]}
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status_check $last_status "${web_service_cmd}" "${status_log}" "${model_name}"
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sleep 5s
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for pipeline in ${pipeline_py[*]}; do
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_save_log_path="${LOG_PATH}/server_infer_gpu_${pipeline%_client*}_batchsize_1.log"
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pipeline_cmd="${python_} ${pipeline} > ${_save_log_path} 2>&1"
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eval ${pipeline_cmd}
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last_status=${PIPESTATUS[0]}
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eval "cat ${_save_log_path}"
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status_check $last_status "${pipeline_cmd}" "${status_log}" "${model_name}"
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sleep 5s
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done
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eval "${python_} -m paddle_serving_server.serve stop"
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else
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echo "Does not support hardware [${use_gpu}] other than CPU and GPU Currently!"
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fi
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done
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}
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function func_serving_rec(){
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LOG_PATH="test_tipc/output/${model_name}/${MODE}"
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mkdir -p ${LOG_PATH}
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LOG_PATH="../../../${LOG_PATH}"
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status_log="${LOG_PATH}/results_serving.log"
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trans_model_py=$(func_parser_value "${lines[5]}")
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cls_infer_model_dir_key=$(func_parser_key "${lines[6]}")
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cls_infer_model_dir_value=$(func_parser_value "${lines[6]}")
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det_infer_model_dir_key=$(func_parser_key "${lines[7]}")
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det_infer_model_dir_value=$(func_parser_value "${lines[7]}")
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model_filename_key=$(func_parser_key "${lines[8]}")
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model_filename_value=$(func_parser_value "${lines[8]}")
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params_filename_key=$(func_parser_key "${lines[9]}")
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params_filename_value=$(func_parser_value "${lines[9]}")
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cls_serving_server_key=$(func_parser_key "${lines[10]}")
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cls_serving_server_value=$(func_parser_value "${lines[10]}")
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cls_serving_client_key=$(func_parser_key "${lines[11]}")
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cls_serving_client_value=$(func_parser_value "${lines[11]}")
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det_serving_server_key=$(func_parser_key "${lines[12]}")
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det_serving_server_value=$(func_parser_value "${lines[12]}")
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det_serving_client_key=$(func_parser_key "${lines[13]}")
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det_serving_client_value=$(func_parser_value "${lines[13]}")
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serving_dir_value=$(func_parser_value "${lines[14]}")
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web_service_py=$(func_parser_value "${lines[15]}")
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web_use_gpu_key=$(func_parser_key "${lines[16]}")
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web_use_gpu_list=$(func_parser_value "${lines[16]}")
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pipeline_py=$(func_parser_value "${lines[17]}")
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IFS='|'
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for python_ in ${python[*]}; do
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if [[ ${python_} =~ "python" ]]; then
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python_interp=${python_}
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break
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fi
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done
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# pdserving
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cd ./deploy
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set_dirname=$(func_set_params "${cls_infer_model_dir_key}" "${cls_infer_model_dir_value}")
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set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}")
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set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}")
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set_serving_server=$(func_set_params "${cls_serving_server_key}" "${cls_serving_server_value}")
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set_serving_client=$(func_set_params "${cls_serving_client_key}" "${cls_serving_client_value}")
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cls_trans_model_cmd="${python_interp} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}"
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eval ${cls_trans_model_cmd}
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set_dirname=$(func_set_params "${det_infer_model_dir_key}" "${det_infer_model_dir_value}")
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set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}")
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set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}")
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set_serving_server=$(func_set_params "${det_serving_server_key}" "${det_serving_server_value}")
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set_serving_client=$(func_set_params "${det_serving_client_key}" "${det_serving_client_value}")
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det_trans_model_cmd="${python_interp} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}"
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eval ${det_trans_model_cmd}
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# modify the alias_name of fetch_var to "outputs"
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server_fetch_var_line_cmd="sed -i '/fetch_var/,/is_lod_tensor/s/alias_name: .*/alias_name: \"features\"/' $cls_serving_server_value/serving_server_conf.prototxt"
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eval ${server_fetch_var_line_cmd}
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client_fetch_var_line_cmd="sed -i '/fetch_var/,/is_lod_tensor/s/alias_name: .*/alias_name: \"features\"/' $cls_serving_client_value/serving_client_conf.prototxt"
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eval ${client_fetch_var_line_cmd}
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prototxt_dataline=$(awk 'NR==1, NR==3{print}' ${cls_serving_server_value}/serving_server_conf.prototxt)
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IFS=$'\n'
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prototxt_lines=(${prototxt_dataline})
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feed_var_name=$(func_parser_value "${prototxt_lines[2]}")
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IFS='|'
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cd ${serving_dir_value}
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unset https_proxy
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unset http_proxy
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# modify the input_name in "recognition_web_service.py" to be consistent with feed_var.name in prototxt
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set_web_service_feed_var_cmd="sed -i '/preprocess/,/input_imgs}/s/{.*: input_imgs}/{${feed_var_name}: input_imgs}/' ${web_service_py}"
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eval ${set_web_service_feed_var_cmd}
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# python serving
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for use_gpu in ${web_use_gpu_list[*]}; do
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if [[ ${use_gpu} = "null" ]]; then
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device_type_line=24
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set_device_type_cmd="sed -i '${device_type_line}s/device_type: .*/device_type: 0/' config.yml"
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eval ${set_device_type_cmd}
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devices_line=27
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set_devices_cmd="sed -i '${devices_line}s/devices: .*/devices: \"\"/' config.yml"
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eval ${set_devices_cmd}
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web_service_cmd="${python} ${web_service_py} &"
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eval ${web_service_cmd}
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last_status=${PIPESTATUS[0]}
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status_check $last_status "${web_service_cmd}" "${status_log}" "${model_name}"
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sleep 5s
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for pipeline in ${pipeline_py[*]}; do
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_save_log_path="${LOG_PATH}/server_infer_cpu_${pipeline%_client*}_batchsize_1.log"
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pipeline_cmd="${python} ${pipeline} > ${_save_log_path} 2>&1 "
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eval ${pipeline_cmd}
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last_status=${PIPESTATUS[0]}
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eval "cat ${_save_log_path}"
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status_check $last_status "${pipeline_cmd}" "${status_log}" "${model_name}"
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sleep 5s
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done
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eval "${python_} -m paddle_serving_server.serve stop"
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elif [ ${use_gpu} -eq 0 ]; then
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if [[ ${_flag_quant} = "False" ]] && [[ ${precision} =~ "int8" ]]; then
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continue
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fi
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if [[ ${precision} =~ "fp16" || ${precision} =~ "int8" ]] && [ ${use_trt} = "False" ]; then
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continue
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fi
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if [[ ${use_trt} = "False" || ${precision} =~ "int8" ]] && [[ ${_flag_quant} = "True" ]]; then
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continue
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fi
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device_type_line=24
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set_device_type_cmd="sed -i '${device_type_line}s/device_type: .*/device_type: 1/' config.yml"
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eval ${set_device_type_cmd}
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devices_line=27
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set_devices_cmd="sed -i '${devices_line}s/devices: .*/devices: \"${use_gpu}\"/' config.yml"
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eval ${set_devices_cmd}
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web_service_cmd="${python} ${web_service_py} & "
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eval ${web_service_cmd}
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last_status=${PIPESTATUS[0]}
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status_check $last_status "${web_service_cmd}" "${status_log}" "${model_name}"
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sleep 10s
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for pipeline in ${pipeline_py[*]}; do
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_save_log_path="${LOG_PATH}/server_infer_gpu_${pipeline%_client*}_batchsize_1.log"
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pipeline_cmd="${python} ${pipeline} > ${_save_log_path} 2>&1"
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eval ${pipeline_cmd}
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last_status=${PIPESTATUS[0]}
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eval "cat ${_save_log_path}"
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status_check $last_status "${pipeline_cmd}" "${status_log}" "${model_name}"
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sleep 10s
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done
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eval "${python_} -m paddle_serving_server.serve stop"
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else
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echo "Does not support hardware [${use_gpu}] other than CPU and GPU Currently!"
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fi
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done
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}
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# set cuda device
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GPUID=$3
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if [ ${#GPUID} -le 0 ];then
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env="export CUDA_VISIBLE_DEVICES=0"
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else
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env="export CUDA_VISIBLE_DEVICES=${GPUID}"
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fi
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set CUDA_VISIBLE_DEVICES
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eval ${env}
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echo "################### run test ###################"
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export Count=0
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IFS="|"
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if [[ ${model_name} = "PPShiTu" ]]; then
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func_serving_rec
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else
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func_serving_cls
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fi
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