#!/bin/bash source test_tipc/utils_func.sh FILENAME=$1 MODE="cpp_infer" # parser model_name dataline=$(cat ${FILENAME}) IFS=$'\n' lines=(${dataline}) model_name=$(func_parser_value "${lines[1]}") echo "ppdet cpp_infer: ${model_name}" python=$(func_parser_value "${lines[2]}") filename_key=$(func_parser_key "${lines[3]}") filename_value=$(func_parser_value "${lines[3]}") # export params save_export_key=$(func_parser_key "${lines[5]}") save_export_value=$(func_parser_value "${lines[5]}") export_weight_key=$(func_parser_key "${lines[6]}") export_weight_value=$(func_parser_value "${lines[6]}") norm_export=$(func_parser_value "${lines[7]}") pact_export=$(func_parser_value "${lines[8]}") fpgm_export=$(func_parser_value "${lines[9]}") distill_export=$(func_parser_value "${lines[10]}") export_key1=$(func_parser_key "${lines[11]}") export_value1=$(func_parser_value "${lines[11]}") export_key2=$(func_parser_key "${lines[12]}") export_value2=$(func_parser_value "${lines[12]}") kl_quant_export=$(func_parser_value "${lines[13]}") # parser cpp inference model opencv_dir=$(func_parser_value "${lines[15]}") cpp_infer_mode_list=$(func_parser_value "${lines[16]}") cpp_infer_is_quant_list=$(func_parser_value "${lines[17]}") # parser cpp inference inference_cmd=$(func_parser_value "${lines[18]}") cpp_use_gpu_key=$(func_parser_key "${lines[19]}") cpp_use_gpu_list=$(func_parser_value "${lines[19]}") cpp_use_mkldnn_key=$(func_parser_key "${lines[20]}") cpp_use_mkldnn_list=$(func_parser_value "${lines[20]}") cpp_cpu_threads_key=$(func_parser_key "${lines[21]}") cpp_cpu_threads_list=$(func_parser_value "${lines[21]}") cpp_batch_size_key=$(func_parser_key "${lines[22]}") cpp_batch_size_list=$(func_parser_value "${lines[22]}") cpp_use_trt_key=$(func_parser_key "${lines[23]}") cpp_use_trt_list=$(func_parser_value "${lines[23]}") cpp_precision_key=$(func_parser_key "${lines[24]}") cpp_precision_list=$(func_parser_value "${lines[24]}") cpp_infer_model_key=$(func_parser_key "${lines[25]}") cpp_image_dir_key=$(func_parser_key "${lines[26]}") cpp_infer_img_dir=$(func_parser_value "${lines[26]}") cpp_benchmark_key=$(func_parser_key "${lines[27]}") cpp_benchmark_value=$(func_parser_value "${lines[27]}") cpp_infer_key1=$(func_parser_key "${lines[28]}") cpp_infer_value1=$(func_parser_value "${lines[28]}") LOG_PATH="./test_tipc/output/${model_name}/${MODE}" mkdir -p ${LOG_PATH} status_log="${LOG_PATH}/results_cpp.log" function func_cpp_inference(){ IFS='|' _script=$1 _model_dir=$2 _log_path=$3 _img_dir=$4 _flag_quant=$5 # inference for use_gpu in ${cpp_use_gpu_list[*]}; do if [ ${use_gpu} = "False" ] || [ ${use_gpu} = "cpu" ]; then for use_mkldnn in ${cpp_use_mkldnn_list[*]}; do if [ ${use_mkldnn} = "False" ] && [ ${_flag_quant} = "True" ]; then continue fi for threads in ${cpp_cpu_threads_list[*]}; do for batch_size in ${cpp_batch_size_list[*]}; do _save_log_path="${_log_path}/cpp_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_mode_paddle_batchsize_${batch_size}.log" set_infer_data=$(func_set_params "${cpp_image_dir_key}" "${_img_dir}") set_benchmark=$(func_set_params "${cpp_benchmark_key}" "${cpp_benchmark_value}") set_batchsize=$(func_set_params "${cpp_batch_size_key}" "${batch_size}") set_cpu_threads=$(func_set_params "${cpp_cpu_threads_key}" "${threads}") set_model_dir=$(func_set_params "${cpp_infer_model_key}" "${_model_dir}") set_infer_params1=$(func_set_params "${cpp_infer_key1}" "${cpp_infer_value1}") command="${_script} ${cpp_use_gpu_key}=${use_gpu} ${cpp_use_mkldnn_key}=${use_mkldnn} ${set_cpu_threads} ${set_model_dir} ${set_batchsize} ${set_infer_data} ${set_benchmark} ${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}" "${_save_log_path}" done done done elif [ ${use_gpu} = "True" ] || [ ${use_gpu} = "gpu" ]; then for precision in ${cpp_precision_list[*]}; do if [[ ${precision} != "paddle" ]]; then if [[ ${_flag_quant} = "False" ]] && [[ ${precision} = "trt_int8" ]]; then continue fi if [[ ${_flag_quant} = "True" ]] && [[ ${precision} != "trt_int8" ]]; then continue fi fi for batch_size in ${cpp_batch_size_list[*]}; do _save_log_path="${_log_path}/cpp_infer_gpu_mode_${precision}_batchsize_${batch_size}.log" set_infer_data=$(func_set_params "${cpp_image_dir_key}" "${_img_dir}") set_benchmark=$(func_set_params "${cpp_benchmark_key}" "${cpp_benchmark_value}") set_batchsize=$(func_set_params "${cpp_batch_size_key}" "${batch_size}") set_precision=$(func_set_params "${cpp_precision_key}" "${precision}") set_model_dir=$(func_set_params "${cpp_infer_model_key}" "${_model_dir}") set_infer_params1=$(func_set_params "${cpp_infer_key1}" "${cpp_infer_value1}") command="${_script} ${cpp_use_gpu_key}=${use_gpu} ${set_precision} ${set_model_dir} ${set_batchsize} ${set_infer_data} ${set_benchmark} ${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}" "${_save_log_path}" done done else echo "Does not support hardware other than CPU and GPU Currently!" fi done } cd ./deploy/cpp # set OPENCV_DIR if [ ${opencv_dir} = "default" ] || [ ${opencv_dir} = "null" ]; then OPENCV_DIR=$(pwd)/deps/opencv-3.4.16_gcc8.2_ffmpeg else OPENCV_DIR=${opencv_dir} fi # build program # TODO: set PADDLE_INFER_DIR and TENSORRT_ROOT if [ -z $PADDLE_INFER_DIR ]; then Paddle_Infer_Link=$2 if [ "" = "$Paddle_Infer_Link" ];then wget -nc https://paddle-inference-lib.bj.bcebos.com/2.2.2/cxx_c/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddle_inference.tgz --no-check-certificate tar zxf paddle_inference.tgz PADDLE_INFER_DIR=$(pwd)/paddle_inference else wget -nc $Paddle_Infer_Link --no-check-certificate tar zxf paddle_inference.tgz PADDLE_INFER_DIR=$(pwd)/paddle_inference if [ ! -d "paddle_inference" ]; then PADDLE_INFER_DIR=$(pwd)/paddle_inference_install_dir fi fi fi if [ -z $TENSORRT_ROOT ]; then TENSORRT_ROOT=/usr/local/TensorRT6-cuda10.1-cudnn7 fi CUDA_LIB=$(dirname `find /usr -name libcudart.so`) CUDNN_LIB=$(dirname `find /usr -name libcudnn.so`) TENSORRT_LIB_DIR="${TENSORRT_ROOT}/lib" TENSORRT_INC_DIR="${TENSORRT_ROOT}/include" rm -rf build mkdir -p build cd ./build cmake .. \ -DWITH_GPU=ON \ -DWITH_MKL=ON \ -DWITH_TENSORRT=OFF \ -DPADDLE_LIB_NAME=libpaddle_inference \ -DPADDLE_DIR=${PADDLE_INFER_DIR} \ -DCUDA_LIB=${CUDA_LIB} \ -DCUDNN_LIB=${CUDNN_LIB} \ -DTENSORRT_LIB_DIR=${TENSORRT_LIB_DIR} \ -DTENSORRT_INC_DIR=${TENSORRT_INC_DIR} \ -DOPENCV_DIR=${OPENCV_DIR} \ -DWITH_KEYPOINT=ON \ -DWITH_MOT=ON make -j8 cd ../../../ echo "################### build finished! ###################" # set cuda device GPUID=$3 if [ ${#GPUID} -le 0 ];then env=" " else env="export CUDA_VISIBLE_DEVICES=${GPUID}" fi eval $env # run cpp infer Count=0 IFS="|" infer_quant_flag=(${cpp_infer_is_quant_list}) for infer_mode in ${cpp_infer_mode_list[*]}; do if [ ${infer_mode} != "null" ]; then # run export case ${infer_mode} in norm) run_export=${norm_export} ;; quant) run_export=${pact_export} ;; fpgm) run_export=${fpgm_export} ;; distill) run_export=${distill_export} ;; kl_quant) run_export=${kl_quant_export} ;; *) echo "Undefined infer_mode!"; exit 1; esac set_export_weight=$(func_set_params "${export_weight_key}" "${export_weight_value}") set_save_export_dir=$(func_set_params "${save_export_key}" "${save_export_value}") set_filename=$(func_set_params "${filename_key}" "${model_name}") export_log_path="${LOG_PATH}/export.log" export_cmd="${python} ${run_export} ${set_export_weight} ${set_filename} ${set_save_export_dir} " echo $export_cmd eval "${export_cmd} > ${export_log_path} 2>&1" status_export=$? cat ${export_log_path} status_check $status_export "${export_cmd}" "${status_log}" "${model_name}" "${export_log_path}" fi #run inference save_export_model_dir="${save_export_value}/${model_name}" is_quant=${infer_quant_flag[Count]} func_cpp_inference "${inference_cmd}" "${save_export_model_dir}" "${LOG_PATH}" "${cpp_infer_img_dir}" ${is_quant} Count=$(($Count + 1)) done eval "unset CUDA_VISIBLE_DEVICES"