From 44ea4d8698cfe028c7e47de0c05008e3b8947744 Mon Sep 17 00:00:00 2001 From: LDOUBLEV Date: Tue, 8 Feb 2022 02:29:33 +0000 Subject: [PATCH] keep model name and directory same --- test_tipc/benchmark_train.sh | 299 ++++++++++-------- test_tipc/benchmark_trainv2.sh | 258 --------------- .../configs/det_mv3_db_v2/train_benchmark.txt | 40 --- .../det_mv3_db_v2/train_infer_python.txt | 57 ---- 4 files changed, 171 insertions(+), 483 deletions(-) delete mode 100644 test_tipc/benchmark_trainv2.sh delete mode 100644 test_tipc/configs/det_mv3_db_v2/train_benchmark.txt delete mode 100644 test_tipc/configs/det_mv3_db_v2/train_infer_python.txt diff --git a/test_tipc/benchmark_train.sh b/test_tipc/benchmark_train.sh index 7b7833ff..bd3e8de4 100644 --- a/test_tipc/benchmark_train.sh +++ b/test_tipc/benchmark_train.sh @@ -1,9 +1,19 @@ #!/bin/bash source test_tipc/common_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 @@ -55,30 +65,15 @@ function get_repo_name(){ } FILENAME=$1 -# MODE be one of ['benchmark_train'] +# 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=$3 -# bash test_tipc/benchmark_train.sh test_tipc/configs/det_mv3_db_v2.0/train_benchmark.txt benchmark_train dynamic_bs8_null_SingleP_DP_N1C1 -IFS="\n" - -# parser params from input: modeltype_bs${bs_item}_${fp_item}_${run_process_type}_${run_mode}_${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_process_type=${params_list[3]} -run_mode=${params_list[4]} -device_num=${params_list[5]} -device_num_copy=$device_num -IFS=";" - - -# sed batchsize and precision -func_sed_params "$FILENAME" "6" "$precision" -func_sed_params "$FILENAME" "9" "$batch_size" - +PARAMS=$3 +# bash test_tipc/benchmark_train.sh test_tipc/configs/det_mv3_db_v2_0/train_benchmark.txt benchmark_train dynamic_bs8_null_SingleP_DP_N1C1 +IFS=$'\n' # parser params from train_benchmark.txt dataline=`cat $FILENAME` # parser params @@ -87,31 +82,22 @@ lines=(${dataline}) model_name=$(func_parser_value "${lines[1]}") # 获取benchmark_params所在的行数 -line_num=`grep -n "benchmark_params" $FILENAME | cut -d ":" -f 1` +line_num=`grep -n "train_benchmark_params" $FILENAME | cut -d ":" -f 1` # for train log parser -line_num=`expr $line_num + 3` -speed_unit_value=$(func_parser_value "${lines[line_num]}") - +batch_size=$(func_parser_value "${lines[line_num]}") line_num=`expr $line_num + 1` -skip_steps_value=$(func_parser_value "${lines[line_num]}") - +fp_items=$(func_parser_value "${lines[line_num]}") line_num=`expr $line_num + 1` -keyword_value=$(func_parser_value "${lines[line_num]}") -echo $keyword_value +epoch=$(func_parser_value "${lines[line_num]}") line_num=`expr $line_num + 1` -convergence_key_value=$(func_parser_value "${lines[line_num]}") +profile_option_key=$(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 "${lines[line_num]}") - -gpu_id=$(set_gpu_id $device_num) -repo_name=$(get_repo_name ) - -SAVE_LOG=${BENCHMARK_LOG_DIR:-$(pwd)} # */benchmark_log -status_log="${SAVE_LOG}/benchmark_log/results.log" - -# set export +# set flags IFS=";" flags_list=(${flags_value}) for _flag in ${flags_list[*]}; do @@ -119,97 +105,154 @@ for _flag in ${flags_list[*]}; do eval $cmd done -if [ ${precision} = "null" ];then - precision="fp32" -fi - -# set env -export model_branch=`git symbolic-ref HEAD 2>/dev/null | cut -d"/" -f 3` -export model_commit=$(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=$(echo `python -c "import paddle;print(paddle.version.commit)"`) +# set log_name +repo_name=$(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 -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_process_type}_${run_mode}_${device_num}_profiling" - func_sed_params "$FILENAME" "4" "0" # sed used gpu_id - 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_process_type}_${run_mode}_${device_num}_log" - speed_log_name="${repo_name}_${model_name}_bs${batch_size}_${precision}_${run_process_type}_${run_mode}_${device_num}_speed" - func_sed_params "$FILENAME" "13" "null" # sed used gpu_id - 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_process_type}_${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} \ - --run_process_type ${run_process_type} \ - --fp_item ${precision} \ - --keyword ${keyword_value}: \ - --skip_steps ${skip_steps_value} \ - --device_num ${device_num} \ - --speed_unit ${speed_unit_value} \ - --convergence_key ${convergence_key_value}: " - echo $cmd - eval $cmd - last_status=${PIPESTATUS[0]} - status_check $last_status "${cmd}" "${status_log}" +func_sed_params "$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=(${fp_items}) + device_num_list=(N1C4) + run_mode="DP" else - log_path="$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_process_type}_${run_mode}_${device_num}_log" - speed_log_name="${repo_name}_${model_name}_bs${batch_size}_${precision}_${run_process_type}_${run_mode}_${device_num}_speed" - func_sed_params "$FILENAME" "4" "$gpu_id" # sed used gpu_id - func_sed_params "$FILENAME" "13" "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_process_type}_${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} \ - --run_process_type ${run_process_type} \ - --fp_item ${precision} \ - --keyword ${keyword_value}: \ - --skip_steps ${skip_steps_value} \ - --device_num ${device_num} \ - --speed_unit ${speed_unit_value} \ - --convergence_key ${convergence_key_value}: " - echo $cmd - eval $cmd - last_status=${PIPESTATUS[0]} - status_check $last_status "${cmd}" "${status_log}" + # parser params from input: modeltype_bs${bs_item}_${fp_item}_${run_process_type}_${run_mode}_${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_process_type=${params_list[3]} + run_mode=${params_list[4]} + device_num=${params_list[5]} + 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 [ ${#gpu_id} -le 1 ];then + run_process_type="SingleP" + log_path="$SAVE_LOG/profiling_log" + mkdir -p $log_path + log_name="${repo_name}_${model_name}_bs${batch_size}_${precision}_${run_process_type}_${run_mode}_${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_process_type}_${run_mode}_${device_num}_log" + speed_log_name="${repo_name}_${model_name}_bs${batch_size}_${precision}_${run_process_type}_${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_process_type}_${run_mode}" + cmd="${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} \ + --run_process_type ${run_process_type} \ + --fp_item ${precision} \ + --keyword ips: \ + --skip_steps 2 \ + --device_num ${device_num} \ + --speed_unit samples/s \ + --convergence_key loss: " + echo $cmd + eval $cmd + last_status=${PIPESTATUS[0]} + status_check $last_status "${cmd}" "${status_log}" + else + IFS=";" + unset_env=`unset CUDA_VISIBLE_DEVICES` + run_process_type="MultiP" + log_path="$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_process_type}_${run_mode}_${device_num}_log" + speed_log_name="${repo_name}_${model_name}_bs${batch_size}_${precision}_${run_process_type}_${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_process_type}_${run_mode}" + + cmd="${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} \ + --run_process_type ${run_process_type} \ + --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}" "${status_log}" + fi + done + done +done \ No newline at end of file diff --git a/test_tipc/benchmark_trainv2.sh b/test_tipc/benchmark_trainv2.sh deleted file mode 100644 index da205071..00000000 --- a/test_tipc/benchmark_trainv2.sh +++ /dev/null @@ -1,258 +0,0 @@ -#!/bin/bash -source test_tipc/common_func.sh - -# set env -python=python3.7 -export model_branch=`git symbolic-ref HEAD 2>/dev/null | cut -d"/" -f 3` -export model_commit=$(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=${array[0]} - value=${array[1]} - if [[ $value =~ 'benchmark_train' ]];then - IFS='=' - _val=(${value}) - param_value="${_val[0]}=${param_value}" - fi - 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=$3 -# bash test_tipc/benchmark_train.sh test_tipc/configs/det_mv3_db_v2.0/train_benchmark.txt benchmark_train dynamic_bs8_null_SingleP_DP_N1C1 -IFS=$'\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 "${lines[line_num]}") -# set flags -IFS=";" -flags_list=(${flags_value}) -for _flag in ${flags_list[*]}; do - cmd="export ${_flag}" - eval $cmd -done - -# set log_name -repo_name=$(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}_${run_process_type}_${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_process_type=${params_list[3]} - run_mode=${params_list[4]} - device_num=${params_list[5]} - 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 [ ${#gpu_id} -le 1 ];then - run_process_type="SingleP" - log_path="$SAVE_LOG/profiling_log" - mkdir -p $log_path - log_name="${repo_name}_${model_name}_bs${batch_size}_${precision}_${run_process_type}_${run_mode}_${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_process_type}_${run_mode}_${device_num}_log" - speed_log_name="${repo_name}_${model_name}_bs${batch_size}_${precision}_${run_process_type}_${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_process_type}_${run_mode}" - cmd="${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} \ - --run_process_type ${run_process_type} \ - --fp_item ${precision} \ - --keyword ips: \ - --skip_steps 2 \ - --device_num ${device_num} \ - --speed_unit samples/s \ - --convergence_key loss: " - echo $cmd - eval $cmd - last_status=${PIPESTATUS[0]} - status_check $last_status "${cmd}" "${status_log}" - else - IFS=";" - unset_env=`unset CUDA_VISIBLE_DEVICES` - run_process_type="MultiP" - log_path="$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_process_type}_${run_mode}_${device_num}_log" - speed_log_name="${repo_name}_${model_name}_bs${batch_size}_${precision}_${run_process_type}_${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_process_type}_${run_mode}" - - cmd="${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} \ - --run_process_type ${run_process_type} \ - --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 \ No newline at end of file diff --git a/test_tipc/configs/det_mv3_db_v2/train_benchmark.txt b/test_tipc/configs/det_mv3_db_v2/train_benchmark.txt deleted file mode 100644 index 4f9a1b64..00000000 --- a/test_tipc/configs/det_mv3_db_v2/train_benchmark.txt +++ /dev/null @@ -1,40 +0,0 @@ -===========================train_params=========================== -model_name:det_mv3_db_v2 -python:python -gpu_list:0 -Global.use_gpu:True -Global.auto_cast:null -Global.epoch_num:benchmark_train=2 -Global.save_model_dir:./output/ -Train.loader.batch_size_per_card:benchmark_train=16 -Global.pretrained_model:null -train_model_name:latest -train_infer_img_dir:null ---profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile -## -trainer:norm_train -norm_train:tools/train.py -c configs/det/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained -pact_train:null -fpgm_train:null -distill_train:null -null:null -null:null -## -===========================eval_params=========================== -eval:null -null:null -## -===========================infer_params=========================== -Global.save_inference_dir:./output/ -Global.checkpoints: -norm_export:null -===========================benchmark_params========================== -device_num:N1C1|N1C8|N4C32 -run_process_type:MultiP -run_mode:DP|DP1-MP1-PP1|DP2-MP2-PP2 -speed_unit:images/s -skip_steps:2 -keyword:ips: -convergence_key:loss: -flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096 -null:null diff --git a/test_tipc/configs/det_mv3_db_v2/train_infer_python.txt b/test_tipc/configs/det_mv3_db_v2/train_infer_python.txt deleted file mode 100644 index 04bdeec4..00000000 --- a/test_tipc/configs/det_mv3_db_v2/train_infer_python.txt +++ /dev/null @@ -1,57 +0,0 @@ -===========================train_params=========================== -model_name:det_mv3_db_v2_0 -python:python3.7 -gpu_list:0|0,1 -Global.use_gpu:True|True -Global.auto_cast:null -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=300 -Global.save_model_dir:./output/ -Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4 -Global.pretrained_model:null -train_model_name:latest -train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ -null:null -## -trainer:norm_train -norm_train:tools/train.py -c configs/det/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained -pact_train:null -fpgm_train:null -distill_train:null -null:null -null:null -## -===========================eval_params=========================== -eval:null -null:null -## -===========================infer_params=========================== -Global.save_inference_dir:./output/ -Global.checkpoints: -norm_export:tools/export_model.py -c configs/det/det_mv3_db.yml -o -quant_export:null -fpgm_export:null -distill_export:null -export1:null -export2:null -inference_dir:null -train_model:./inference/det_mv3_db_v2.0_train/best_accuracy -infer_export:tools/export_model.py -c configs/det/det_mv3_db.yml -o -infer_quant:False -inference:tools/infer/predict_det.py ---use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 ---rec_batch_num:1 ---use_tensorrt:False|True ---precision:fp32|fp16|int8 ---det_model_dir: ---image_dir:./inference/ch_det_data_50/all-sum-510/ -null:null ---benchmark:True -null:null -===========================train_benchmark_params========================== -batch_size:8|16 -fp_items:fp32|fp16 -epoch:2 ---profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile -flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096 \ No newline at end of file -- GitLab