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