keep model name and directory same

test_tipc/benchmark_train.sh

 #!/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

test_tipc/benchmark_trainv2.sh

-#!/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

test_tipc/configs/det_mv3_db_v2/train_benchmark.txt

-===========================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

test_tipc/configs/det_mv3_db_v2/train_infer_python.txt

-===========================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