#!/bin/bash source test_tipc/common_func.sh FILENAME=$1 # MODE be one of [''whole_infer'] MODE=$2 IFS=$'\n' # parser klquant_infer params dataline=$(awk 'NR==1, NR==17{print}' $FILENAME) lines=(${dataline}) model_name=$(func_parser_value "${lines[1]}") python=$(func_parser_value "${lines[2]}") export_weight=$(func_parser_key "${lines[3]}") save_infer_key=$(func_parser_key "${lines[4]}") # parser inference model infer_model_dir_list=$(func_parser_value "${lines[5]}") infer_export_list=$(func_parser_value "${lines[6]}") infer_is_quant=$(func_parser_value "${lines[7]}") # parser inference inference_py=$(func_parser_value "${lines[8]}") use_gpu_key=$(func_parser_key "${lines[9]}") use_gpu_list=$(func_parser_value "${lines[9]}") use_mkldnn_key=$(func_parser_key "${lines[10]}") use_mkldnn_list=$(func_parser_value "${lines[10]}") cpu_threads_key=$(func_parser_key "${lines[11]}") cpu_threads_list=$(func_parser_value "${lines[11]}") batch_size_key=$(func_parser_key "${lines[12]}") batch_size_list=$(func_parser_value "${lines[12]}") use_trt_key=$(func_parser_key "${lines[13]}") use_trt_list=$(func_parser_value "${lines[13]}") precision_key=$(func_parser_key "${lines[14]}") precision_list=$(func_parser_value "${lines[14]}") infer_model_key=$(func_parser_key "${lines[15]}") image_dir_key=$(func_parser_key "${lines[16]}") infer_img_dir=$(func_parser_value "${lines[16]}") save_log_key=$(func_parser_key "${lines[17]}") save_log_value=$(func_parser_value "${lines[17]}") benchmark_key=$(func_parser_key "${lines[18]}") benchmark_value=$(func_parser_value "${lines[18]}") infer_key1=$(func_parser_key "${lines[19]}") infer_value1=$(func_parser_value "${lines[19]}") LOG_PATH="./test_tipc/output/${model_name}/${MODE}" mkdir -p ${LOG_PATH} status_log="${LOG_PATH}/results_python.log" function func_inference(){ IFS='|' _python=$1 _script=$2 _model_dir=$3 _log_path=$4 _img_dir=$5 _flag_quant=$6 # inference for use_gpu in ${use_gpu_list[*]}; do if [ ${use_gpu} = "False" ] || [ ${use_gpu} = "cpu" ]; then for use_mkldnn in ${use_mkldnn_list[*]}; do for threads in ${cpu_threads_list[*]}; do for batch_size in ${batch_size_list[*]}; do for precision in ${precision_list[*]}; do if [ ${use_mkldnn} = "False" ] && [ ${precision} = "fp16" ]; then continue fi # skip when enable fp16 but disable mkldnn if [ ${_flag_quant} = "True" ] && [ ${precision} != "int8" ]; then continue fi # skip when quant model inference but precision is not int8 set_precision=$(func_set_params "${precision_key}" "${precision}") _save_log_path="${_log_path}/python_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log" set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}") set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}") set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}") set_mkldnn=$(func_set_params "${use_mkldnn_key}" "${use_mkldnn}") set_cpu_threads=$(func_set_params "${cpu_threads_key}" "${threads}") set_model_dir=$(func_set_params "${infer_model_key}" "${_model_dir}") set_infer_params0=$(func_set_params "${save_log_key}" "${save_log_value}") set_infer_params1=$(func_set_params "${infer_key1}" "${infer_value1}") command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${set_mkldnn} ${set_cpu_threads} ${set_model_dir} ${set_batchsize} ${set_infer_params0} ${set_infer_data} ${set_benchmark} ${set_precision} ${set_infer_params1} > ${_save_log_path} 2>&1 " eval $command last_status=${PIPESTATUS[0]} eval "cat ${_save_log_path}" status_check $last_status "${command}" "${status_log}" "${model_name}" done done done done elif [ ${use_gpu} = "True" ] || [ ${use_gpu} = "gpu" ]; then for use_trt in ${use_trt_list[*]}; do for precision in ${precision_list[*]}; do if [ ${_flag_quant} = "True" ] && [ ${precision} != "int8" ]; then continue fi # skip when quant model inference but precision is not int8 for batch_size in ${batch_size_list[*]}; do _save_log_path="${_log_path}/python_infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log" set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}") set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}") set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}") set_tensorrt=$(func_set_params "${use_trt_key}" "${use_trt}") set_precision=$(func_set_params "${precision_key}" "${precision}") set_model_dir=$(func_set_params "${infer_model_key}" "${_model_dir}") set_infer_params0=$(func_set_params "${save_log_key}" "${save_log_value}") set_infer_params1=$(func_set_params "${infer_key1}" "${infer_value1}") command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${set_tensorrt} ${set_precision} ${set_model_dir} ${set_batchsize} ${set_infer_data} ${set_benchmark} ${set_infer_params1} ${set_infer_params0} > ${_save_log_path} 2>&1 " eval $command last_status=${PIPESTATUS[0]} eval "cat ${_save_log_path}" status_check $last_status "${command}" "${status_log}" "${model_name}" done done done else echo "Does not support hardware other than CPU and GPU Currently!" fi done } if [ ${MODE} = "whole_infer" ]; then GPUID=$3 if [ ${#GPUID} -le 0 ];then env=" " else env="export CUDA_VISIBLE_DEVICES=${GPUID}" fi # set CUDA_VISIBLE_DEVICES eval $env export Count=0 IFS="|" infer_run_exports=(${infer_export_list}) infer_quant_flag=(${infer_is_quant}) for infer_model in ${infer_model_dir_list[*]}; do # run export if [ ${infer_run_exports[Count]} != "null" ];then save_infer_dir="${infer_model}_klquant" set_export_weight=$(func_set_params "${export_weight}" "${infer_model}") set_save_infer_key=$(func_set_params "${save_infer_key}" "${save_infer_dir}") export_cmd="${python} ${infer_run_exports[Count]} ${set_export_weight} ${set_save_infer_key}" echo ${infer_run_exports[Count]} echo $export_cmd eval $export_cmd status_export=$? status_check $status_export "${export_cmd}" "${status_log}" "${model_name}" else save_infer_dir=${infer_model} fi #run inference is_quant="True" func_inference "${python}" "${inference_py}" "${save_infer_dir}" "${LOG_PATH}" "${infer_img_dir}" ${is_quant} Count=$(($Count + 1)) done fi