174 lines
7.7 KiB
Bash
174 lines
7.7 KiB
Bash
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#!/bin/bash
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FILENAME=$1
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source test_tipc/common_func.sh
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# MODE be one of ['whole_infer']
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MODE=$2
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dataline=$(cat ${FILENAME})
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# parser params
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IFS=$'\n'
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lines=(${dataline})
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# The training params
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model_name=$(func_parser_value "${lines[1]}")
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python=$(func_parser_value "${lines[2]}")
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gpu_list=$(func_parser_value "${lines[3]}")
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train_use_gpu_key=$(func_parser_key "${lines[4]}")
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train_use_gpu_value=$(func_parser_value "${lines[4]}")
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autocast_list=$(func_parser_value "${lines[5]}")
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autocast_key=$(func_parser_key "${lines[5]}")
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epoch_key=$(func_parser_key "${lines[6]}")
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epoch_num=$(func_parser_params "${lines[6]}")
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save_model_key=$(func_parser_key "${lines[7]}")
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train_batch_key=$(func_parser_key "${lines[8]}")
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train_batch_value=$(func_parser_value "${lines[8]}")
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pretrain_model_key=$(func_parser_key "${lines[9]}")
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pretrain_model_value=$(func_parser_value "${lines[9]}")
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train_model_name=$(func_parser_value "${lines[10]}")
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train_infer_img_dir=$(func_parser_value "${lines[11]}")
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train_param_key1=$(func_parser_key "${lines[12]}")
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train_param_value1=$(func_parser_value "${lines[12]}")
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trainer_list=$(func_parser_value "${lines[14]}")
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trainer_norm=$(func_parser_key "${lines[15]}")
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norm_trainer=$(func_parser_value "${lines[15]}")
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pact_key=$(func_parser_key "${lines[16]}")
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pact_trainer=$(func_parser_value "${lines[16]}")
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fpgm_key=$(func_parser_key "${lines[17]}")
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fpgm_trainer=$(func_parser_value "${lines[17]}")
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distill_key=$(func_parser_key "${lines[18]}")
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distill_trainer=$(func_parser_value "${lines[18]}")
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to_static_key=$(func_parser_key "${lines[19]}")
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to_static_trainer=$(func_parser_value "${lines[19]}")
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trainer_key2=$(func_parser_key "${lines[20]}")
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trainer_value2=$(func_parser_value "${lines[20]}")
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eval_py=$(func_parser_value "${lines[23]}")
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eval_key1=$(func_parser_key "${lines[24]}")
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eval_value1=$(func_parser_value "${lines[24]}")
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save_infer_key=$(func_parser_key "${lines[27]}")
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export_weight=$(func_parser_key "${lines[28]}")
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norm_export=$(func_parser_value "${lines[29]}")
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pact_export=$(func_parser_value "${lines[30]}")
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fpgm_export=$(func_parser_value "${lines[31]}")
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distill_export=$(func_parser_value "${lines[32]}")
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kl_quant_cmd_key=$(func_parser_key "${lines[33]}")
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kl_quant_cmd_value=$(func_parser_value "${lines[33]}")
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export_key2=$(func_parser_key "${lines[34]}")
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export_value2=$(func_parser_value "${lines[34]}")
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# parser inference model
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infer_model_dir_list=$(func_parser_value "${lines[36]}")
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infer_export_flag=$(func_parser_value "${lines[37]}")
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infer_is_quant=$(func_parser_value "${lines[38]}")
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# parser inference
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inference_py=$(func_parser_value "${lines[39]}")
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use_gpu_key=$(func_parser_key "${lines[40]}")
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use_gpu_list=$(func_parser_value "${lines[40]}")
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use_mkldnn_key=$(func_parser_key "${lines[41]}")
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use_mkldnn_list=$(func_parser_value "${lines[41]}")
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cpu_threads_key=$(func_parser_key "${lines[42]}")
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cpu_threads_list=$(func_parser_value "${lines[42]}")
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batch_size_key=$(func_parser_key "${lines[43]}")
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batch_size_list=$(func_parser_value "${lines[43]}")
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use_trt_key=$(func_parser_key "${lines[44]}")
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use_trt_list=$(func_parser_value "${lines[44]}")
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precision_key=$(func_parser_key "${lines[45]}")
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precision_list=$(func_parser_value "${lines[45]}")
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infer_model_key=$(func_parser_key "${lines[46]}")
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image_dir_key=$(func_parser_key "${lines[47]}")
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infer_img_dir=$(func_parser_value "${lines[47]}")
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save_log_key=$(func_parser_key "${lines[48]}")
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benchmark_key=$(func_parser_key "${lines[49]}")
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benchmark_value=$(func_parser_value "${lines[49]}")
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infer_key1=$(func_parser_key "${lines[50]}")
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infer_value1=$(func_parser_value "${lines[50]}")
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if [ ! $epoch_num ]; then
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epoch_num=2
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fi
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if [[ $MODE = 'benchmark_train' ]]; then
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epoch_num=1
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fi
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LOG_PATH="./test_tipc/output/${model_name}/${MODE}"
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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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for threads in ${cpu_threads_list[*]}; do
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for batch_size in ${batch_size_list[*]}; do
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_save_log_path="${_log_path}/infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_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_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}" "../${status_log}" "${model_name}"
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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 [ ${precision} = "True" ] && [ ${use_trt} = "False" ]; 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}/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}" "${_model_dir}")
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command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${set_tensorrt} ${set_precision} ${set_model_dir} ${set_batchsize} ${set_infer_data} ${set_benchmark} > ${_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}" "../${status_log}" "${model_name}"
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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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# for kl_quant
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if [ ${kl_quant_cmd_value} != "null" ] && [ ${kl_quant_cmd_value} != "False" ]; then
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echo "kl_quant"
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command="${python} ${kl_quant_cmd_value}"
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echo ${command}
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eval $command
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last_status=${PIPESTATUS[0]}
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status_check $last_status "${command}" "${status_log}" "${model_name}"
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cd ${infer_model_dir_list}/quant_post_static_model
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ln -s __model__ inference.pdmodel
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ln -s __params__ inference.pdiparams
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cd ../../deploy
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is_quant=True
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func_inference "${python}" "${inference_py}" "../${infer_model_dir_list}/quant_post_static_model" "../${LOG_PATH}" "${infer_img_dir}" ${is_quant}
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cd ..
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fi
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