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split jeston inference
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LDOUBLEV
parent
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commit
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===========================train_params===========================
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===========================infer_params===========================
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model_name:ocr_det
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python:python
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gpu_list:null
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Global.use_gpu:null
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Global.auto_cast:null
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Global.epoch_num:null
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Global.save_model_dir:null
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Train.loader.batch_size_per_card:null
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Global.pretrained_model:null
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train_model_name:latest
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train_infer_img_dir:null
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null:null
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##
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trainer:null
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norm_train:null
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pact_train:null
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fpgm_train:null
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distill_train:null
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null:null
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null:null
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##
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===========================eval_params===========================
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eval:null
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null:null
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##
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===========================infer_params===========================
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Global.save_inference_dir:./output/
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Global.pretrained_model:null
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norm_export:null
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quant_export:null
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fpgm_export:null
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distill_export:null
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export1:null
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export2:null
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inference_dir:null
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train_model:./inference/ch_ppocr_mobile_v2.0_det_infer
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infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer
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infer_export:null
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infer_quant:False
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inference:tools/infer/predict_det.py
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165
test_tipc/test_inference_jeston.sh
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165
test_tipc/test_inference_jeston.sh
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#!/bin/bash
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source test_tipc/common_func.sh
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FILENAME=$1
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# MODE be one of ['whole_infer']
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MODE=$2
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dataline=$(awk 'NR==1, NR==17{print}' $FILENAME)
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# parser params
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IFS=$'\n'
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lines=(${dataline})
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model_name=$(func_parser_value "${lines[1]}")
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python=$(func_parser_value "${lines[2]}")
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infer_model_dir_list=$(func_parser_value "${lines[3]}")
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infer_export_list=$(func_parser_value "${lines[4]}")
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infer_is_quant=$(func_parser_value "${lines[5]}")
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# parser inference
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inference_py=$(func_parser_value "${lines[6]}")
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use_gpu_key=$(func_parser_key "${lines[7]}")
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use_gpu_list=$(func_parser_value "${lines[7]}")
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use_mkldnn_key=$(func_parser_key "${lines[8]}")
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use_mkldnn_list=$(func_parser_value "${lines[8]}")
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cpu_threads_key=$(func_parser_key "${lines[9]}")
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cpu_threads_list=$(func_parser_value "${lines[9]}")
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batch_size_key=$(func_parser_key "${lines[10]}")
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batch_size_list=$(func_parser_value "${lines[10]}")
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use_trt_key=$(func_parser_key "${lines[11]}")
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use_trt_list=$(func_parser_value "${lines[11]}")
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precision_key=$(func_parser_key "${lines[12]}")
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precision_list=$(func_parser_value "${lines[12]}")
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infer_model_key=$(func_parser_key "${lines[13]}")
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image_dir_key=$(func_parser_key "${lines[14]}")
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infer_img_dir=$(func_parser_value "${lines[14]}")
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save_log_key=$(func_parser_key "${lines[15]}")
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benchmark_key=$(func_parser_key "${lines[16]}")
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benchmark_value=$(func_parser_value "${lines[16]}")
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infer_key1=$(func_parser_key "${lines[17]}")
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infer_value1=$(func_parser_value "${lines[17]}")
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LOG_PATH="./test_tipc/output"
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mkdir -p ${LOG_PATH}
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status_log="${LOG_PATH}/results_python.log"
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function func_inference(){
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IFS='|'
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_python=$1
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_script=$2
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_model_dir=$3
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_log_path=$4
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_img_dir=$5
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_flag_quant=$6
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# inference
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for use_gpu in ${use_gpu_list[*]}; do
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if [ ${use_gpu} = "False" ] || [ ${use_gpu} = "cpu" ]; then
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for use_mkldnn in ${use_mkldnn_list[*]}; do
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if [ ${use_mkldnn} = "False" ] && [ ${_flag_quant} = "True" ]; then
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continue
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fi
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for threads in ${cpu_threads_list[*]}; do
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for batch_size in ${batch_size_list[*]}; do
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for precision in ${precision_list[*]}; do
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if [ ${use_mkldnn} = "False" ] && [ ${precision} = "fp16" ]; then
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continue
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fi # skip when enable fp16 but disable mkldnn
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if [ ${_flag_quant} = "True" ] && [ ${precision} != "int8" ]; then
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continue
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fi # skip when quant model inference but precision is not int8
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set_precision=$(func_set_params "${precision_key}" "${precision}")
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_save_log_path="${_log_path}/python_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log"
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set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}")
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set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}")
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set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}")
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set_cpu_threads=$(func_set_params "${cpu_threads_key}" "${threads}")
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set_model_dir=$(func_set_params "${infer_model_key}" "${_model_dir}")
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set_infer_params1=$(func_set_params "${infer_key1}" "${infer_value1}")
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command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_mkldnn_key}=${use_mkldnn} ${set_cpu_threads} ${set_model_dir} ${set_batchsize} ${set_infer_data} ${set_benchmark} ${set_precision} ${set_infer_params1} > ${_save_log_path} 2>&1 "
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eval $command
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last_status=${PIPESTATUS[0]}
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eval "cat ${_save_log_path}"
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status_check $last_status "${command}" "${status_log}"
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done
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done
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done
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done
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elif [ ${use_gpu} = "True" ] || [ ${use_gpu} = "gpu" ]; then
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for use_trt in ${use_trt_list[*]}; do
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for precision in ${precision_list[*]}; do
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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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for batch_size in ${batch_size_list[*]}; do
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_save_log_path="${_log_path}/python_infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
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set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}")
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set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}")
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set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}")
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set_tensorrt=$(func_set_params "${use_trt_key}" "${use_trt}")
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set_precision=$(func_set_params "${precision_key}" "${precision}")
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set_model_dir=$(func_set_params "${infer_model_key}" "${_model_dir}")
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set_infer_params1=$(func_set_params "${infer_key1}" "${infer_value1}")
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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} > ${_save_log_path} 2>&1 "
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eval $command
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last_status=${PIPESTATUS[0]}
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eval "cat ${_save_log_path}"
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status_check $last_status "${command}" "${status_log}"
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done
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done
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done
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else
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echo "Does not support hardware other than CPU and GPU Currently!"
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fi
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done
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}
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if [ ${MODE} = "klquant_whole_infer" ]; then
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GPUID=$3
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if [ ${#GPUID} -le 0 ];then
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env=" "
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else
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env="export CUDA_VISIBLE_DEVICES=${GPUID}"
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fi
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# set CUDA_VISIBLE_DEVICES
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eval $env
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export Count=0
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IFS="|"
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infer_run_exports=(${infer_export_list})
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infer_quant_flag=(${infer_is_quant})
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for infer_model in ${infer_model_dir_list[*]}; do
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# run export
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if [ ${infer_run_exports[Count]} != "null" ];then
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save_infer_dir=$(dirname $infer_model)
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set_export_weight=$(func_set_params "${export_weight}" "${infer_model}")
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set_save_infer_key=$(func_set_params "${save_infer_key}" "${save_infer_dir}")
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export_cmd="${python} ${infer_run_exports[Count]} ${set_export_weight} ${set_save_infer_key}"
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echo ${infer_run_exports[Count]}
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echo $export_cmd
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eval $export_cmd
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status_export=$?
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status_check $status_export "${export_cmd}" "${status_log}"
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else
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save_infer_dir=${infer_model}
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fi
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#run inference
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is_quant=${infer_quant_flag[Count]}
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if [ ${MODE} = "klquant_infer" ]; then
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is_quant="True"
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fi
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func_inference "${python}" "${inference_py}" "${save_infer_dir}" "${LOG_PATH}" "${infer_img_dir}" ${is_quant}
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Count=$(($Count + 1))
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done
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fi
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