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- #!/bin/bash
- source test_tipc/utils_func.sh
- # set env
- python=python
- export model_branch=`git symbolic-ref HEAD 2>/dev/null | cut -d"/" -f 3`
- export model_commit=$(git log|head -n1|awk '{print $2}')
- export str_tmp=$(echo `pip list|grep paddlepaddle-gpu|awk -F ' ' '{print $2}'`)
- export frame_version=${str_tmp%%.post*}
- export frame_commit=$(echo `${python} -c "import paddle;print(paddle.version.commit)"`)
- # run benchmark sh
- # Usage:
- # bash run_benchmark_train.sh config.txt params
- # or
- # bash run_benchmark_train.sh config.txt
- function func_parser_params(){
- strs=$1
- IFS="="
- array=(${strs})
- tmp=${array[1]}
- echo ${tmp}
- }
- function func_sed_params(){
- filename=$1
- line=$2
- param_value=$3
- params=`sed -n "${line}p" $filename`
- IFS=":"
- array=(${params})
- key=${array[0]}
- new_params="${key}:${param_value}"
- IFS=";"
- cmd="sed -i '${line}s/.*/${new_params}/' '${filename}'"
- eval $cmd
- }
- function set_gpu_id(){
- string=$1
- _str=${string:1:6}
- IFS="C"
- arr=(${_str})
- M=${arr[0]}
- P=${arr[1]}
- gn=`expr $P - 1`
- gpu_num=`expr $gn / $M`
- seq=`seq -s "," 0 $gpu_num`
- echo $seq
- }
- function get_repo_name(){
- IFS=";"
- cur_dir=$(pwd)
- IFS="/"
- arr=(${cur_dir})
- echo ${arr[-1]}
- }
- FILENAME=$1
- # copy FILENAME as new
- new_filename="./test_tipc/benchmark_train.txt"
- cmd=`yes|cp $FILENAME $new_filename`
- FILENAME=$new_filename
- # MODE must be one of ['benchmark_train']
- MODE=$2
- PARAMS=$3
- # bash test_tipc/benchmark_train.sh test_tipc/configs/det_mv3_db_v2_0/train_benchmark.txt benchmark_train dynamic_bs8_null_DP_N1C1
- IFS=$'\n'
- # parser params from train_benchmark.txt
- dataline=`cat $FILENAME`
- # parser params
- IFS=$'\n'
- lines=(${dataline})
- model_name=$(func_parser_value "${lines[1]}")
- # 获取benchmark_params所在的行数
- line_num=`grep -n "train_benchmark_params" $FILENAME | cut -d ":" -f 1`
- # for train log parser
- batch_size=$(func_parser_value "${lines[line_num]}")
- line_num=`expr $line_num + 1`
- fp_items=$(func_parser_value "${lines[line_num]}")
- line_num=`expr $line_num + 1`
- epoch=$(func_parser_value "${lines[line_num]}")
- line_num=`expr $line_num + 1`
- profile_option_key=$(func_parser_key "${lines[line_num]}")
- profile_option_params=$(func_parser_value "${lines[line_num]}")
- profile_option="${profile_option_key}:${profile_option_params}"
- line_num=`expr $line_num + 1`
- flags_value=$(func_parser_value "${lines[line_num]}")
- if [ ${flags_value} != "null" ];then
- # set flags
- IFS=";"
- flags_list=(${flags_value})
- for _flag in ${flags_list[*]}; do
- cmd="export ${_flag}"
- eval $cmd
- done
- fi
- # set log_name
- repo_name=$(get_repo_name )
- SAVE_LOG=${BENCHMARK_LOG_DIR:-$(pwd)} # */benchmark_log
- mkdir -p "${SAVE_LOG}/benchmark_log/"
- status_log="${SAVE_LOG}/benchmark_log/results.log"
- # The number of lines in which train params can be replaced.
- line_python=3
- line_gpuid=4
- line_precision=6
- line_epoch=7
- line_batchsize=9
- line_profile=13
- line_eval_py=24
- line_export_py=30
- func_sed_params "$FILENAME" "${line_eval_py}" "null"
- func_sed_params "$FILENAME" "${line_export_py}" "null"
- func_sed_params "$FILENAME" "${line_python}" "${python}"
- # if params
- if [ ! -n "$PARAMS" ] ;then
- # PARAMS input is not a word.
- IFS="|"
- batch_size_list=(${batch_size})
- fp_items_list=(${fp_items})
- device_num_list=(N1C4)
- run_mode="DP"
- else
- # parser params from input: modeltype_bs${bs_item}_${fp_item}_${run_mode}_${device_num}
- IFS="_"
- params_list=(${PARAMS})
- model_type=${params_list[0]}
- batch_size=${params_list[1]}
- batch_size=`echo ${batch_size} | tr -cd "[0-9]" `
- precision=${params_list[2]}
- run_mode=${params_list[3]}
- device_num=${params_list[4]}
- IFS=";"
- if [ ${precision} = "null" ];then
- precision="fp32"
- fi
- fp_items_list=($precision)
- batch_size_list=($batch_size)
- device_num_list=($device_num)
- fi
- IFS="|"
- for batch_size in ${batch_size_list[*]}; do
- for precision in ${fp_items_list[*]}; do
- for device_num in ${device_num_list[*]}; do
- # sed batchsize and precision
- func_sed_params "$FILENAME" "${line_precision}" "$precision"
- func_sed_params "$FILENAME" "${line_batchsize}" "$MODE=$batch_size"
- func_sed_params "$FILENAME" "${line_epoch}" "$MODE=$epoch"
- gpu_id=$(set_gpu_id $device_num)
- if [ ${#gpu_id} -le 1 ];then
- log_path="$SAVE_LOG/profiling_log"
- mkdir -p $log_path
- log_name="${repo_name}_${model_name}_bs${batch_size}_${precision}_${run_mode}_${device_num}_profiling"
- func_sed_params "$FILENAME" "${line_gpuid}" "0" # sed used gpu_id
- # set profile_option params
- tmp=`sed -i "${line_profile}s/.*/${profile_option}/" "${FILENAME}"`
- # run test_train_inference_python.sh
- cmd="bash test_tipc/test_train_inference_python.sh ${FILENAME} benchmark_train > ${log_path}/${log_name} 2>&1 "
- echo $cmd
- eval $cmd
- eval "cat ${log_path}/${log_name}"
- # without profile
- log_path="$SAVE_LOG/train_log"
- speed_log_path="$SAVE_LOG/index"
- mkdir -p $log_path
- mkdir -p $speed_log_path
- log_name="${repo_name}_${model_name}_bs${batch_size}_${precision}_${run_mode}_${device_num}_log"
- speed_log_name="${repo_name}_${model_name}_bs${batch_size}_${precision}_${run_mode}_${device_num}_speed"
- func_sed_params "$FILENAME" "${line_profile}" "null" # sed profile_id as null
- cmd="bash test_tipc/test_train_inference_python.sh ${FILENAME} benchmark_train > ${log_path}/${log_name} 2>&1 "
- echo $cmd
- job_bt=`date '+%Y%m%d%H%M%S'`
- eval $cmd
- job_et=`date '+%Y%m%d%H%M%S'`
- export model_run_time=$((${job_et}-${job_bt}))
- eval "cat ${log_path}/${log_name}"
- # parser log
- _model_name="${model_name}_bs${batch_size}_${precision}_${run_mode}"
- cmd="${python} ${BENCHMARK_ROOT}/scripts/analysis.py --filename ${log_path}/${log_name} \
- --speed_log_file '${speed_log_path}/${speed_log_name}' \
- --model_name ${_model_name} \
- --base_batch_size ${batch_size} \
- --run_mode ${run_mode} \
- --fp_item ${precision} \
- --keyword ips: \
- --skip_steps 2 \
- --device_num ${device_num} \
- --speed_unit images/s \
- --convergence_key loss: "
- echo $cmd
- eval $cmd
- last_status=${PIPESTATUS[0]}
- status_check $last_status "${cmd}" "${status_log}"
- else
- IFS=";"
- unset_env=`unset CUDA_VISIBLE_DEVICES`
- log_path="$SAVE_LOG/train_log"
- speed_log_path="$SAVE_LOG/index"
- mkdir -p $log_path
- mkdir -p $speed_log_path
- log_name="${repo_name}_${model_name}_bs${batch_size}_${precision}_${run_mode}_${device_num}_log"
- speed_log_name="${repo_name}_${model_name}_bs${batch_size}_${precision}_${run_mode}_${device_num}_speed"
- func_sed_params "$FILENAME" "${line_gpuid}" "$gpu_id" # sed used gpu_id
- func_sed_params "$FILENAME" "${line_profile}" "null" # sed --profile_option as null
- cmd="bash test_tipc/test_train_inference_python.sh ${FILENAME} benchmark_train > ${log_path}/${log_name} 2>&1 "
- echo $cmd
- job_bt=`date '+%Y%m%d%H%M%S'`
- eval $cmd
- job_et=`date '+%Y%m%d%H%M%S'`
- export model_run_time=$((${job_et}-${job_bt}))
- eval "cat ${log_path}/${log_name}"
- # parser log
- _model_name="${model_name}_bs${batch_size}_${precision}_${run_mode}"
- cmd="${python} ${BENCHMARK_ROOT}/scripts/analysis.py --filename ${log_path}/${log_name} \
- --speed_log_file '${speed_log_path}/${speed_log_name}' \
- --model_name ${_model_name} \
- --base_batch_size ${batch_size} \
- --run_mode ${run_mode} \
- --fp_item ${precision} \
- --keyword ips: \
- --skip_steps 2 \
- --device_num ${device_num} \
- --speed_unit images/s \
- --convergence_key loss: "
- echo $cmd
- eval $cmd
- last_status=${PIPESTATUS[0]}
- status_check $last_status "${cmd}" "${status_log}"
- fi
- done
- done
- done
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