From de746df702b949160a3c41337b3b921fc01e8aad Mon Sep 17 00:00:00 2001 From: root <18013846960@189.cn> Date: Sat, 16 Apr 2022 16:22:16 +0800 Subject: [PATCH] * --- .../fusion_result.json | 1821 ----------------- .../{ => test}/train_full_1p.sh | 376 ++-- 2 files changed, 189 insertions(+), 2008 deletions(-) delete mode 100644 TensorFlow/contrib/cv/YOLOV5_ID0378_for_TensorFlow/fusion_result.json rename TensorFlow/contrib/cv/YOLOV5_ID0378_for_TensorFlow/{ => test}/train_full_1p.sh (83%) diff --git a/TensorFlow/contrib/cv/YOLOV5_ID0378_for_TensorFlow/fusion_result.json b/TensorFlow/contrib/cv/YOLOV5_ID0378_for_TensorFlow/fusion_result.json deleted file mode 100644 index bb2fbca3d..000000000 --- a/TensorFlow/contrib/cv/YOLOV5_ID0378_for_TensorFlow/fusion_result.json +++ /dev/null @@ -1,1821 +0,0 @@ -{ - "graph_fusion": { - "RefreshInt64ToInt32FusionPass": { - "effect_times": "1", - "match_times": "1" - } - }, - "session_and_graph_id": "0_1" -}{ - "graph_fusion": { - 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a/TensorFlow/contrib/cv/YOLOV5_ID0378_for_TensorFlow/train_full_1p.sh b/TensorFlow/contrib/cv/YOLOV5_ID0378_for_TensorFlow/test/train_full_1p.sh similarity index 83% rename from TensorFlow/contrib/cv/YOLOV5_ID0378_for_TensorFlow/train_full_1p.sh rename to TensorFlow/contrib/cv/YOLOV5_ID0378_for_TensorFlow/test/train_full_1p.sh index 27cfdbd7a..b19ccb843 100644 --- a/TensorFlow/contrib/cv/YOLOV5_ID0378_for_TensorFlow/train_full_1p.sh +++ b/TensorFlow/contrib/cv/YOLOV5_ID0378_for_TensorFlow/test/train_full_1p.sh @@ -1,187 +1,189 @@ -#!/bin/bash - -########################################################## -#########第3行 至 100行，请一定不要、不要、不要修改########## -#########第3行 至 100行，请一定不要、不要、不要修改########## -#########第3行 至 100行，请一定不要、不要、不要修改########## -########################################################## -# shell脚本所在路径 -cur_path=`echo $(cd $(dirname $0);pwd)` - -# 判断当前shell是否是performance -perf_flag=`echo $0 | grep performance | wc -l` - -# 当前执行网络的名称 -Network=`echo $(cd $(dirname $0);pwd) | awk -F"/" '{print $(NF-1)}'` - -export RANK_SIZE=1 -export RANK_ID=0 -export JOB_ID=10087 - -# 路径参数初始化 -data_path='' -output_path='' - -# 帮助信息，不需要修改 -if [[ $1 == --help || $1 == -h ]];then - echo"usage:./train_performance_1P.sh " - echo " " - echo "parameter explain: - --data_path # dataset of training - --output_path # output of training - --train_steps # max_step for training - --train_epochs # max_epoch for training - --batch_size # batch size - -h/--help show help message - " - exit 1 -fi - -# 参数校验，不需要修改 -for para in $* -do - if [[ $para == --data_path* ]];then - data_path=`echo ${para#*=}` - elif [[ $para == --output_path* ]];then - output_path=`echo ${para#*=}` - elif [[ $para == --train_steps* ]];then - train_steps=`echo ${para#*=}` - elif [[ $para == --train_epochs* ]];then - train_epochs=`echo ${para#*=}` - elif [[ $para == --batch_size* ]];then - batch_size=`echo ${para#*=}` - fi -done - -# 校验是否传入data_path,不需要修改 -if [[ $data_path == "" ]];then - echo "[Error] para \"data_path\" must be config" - exit 1 -fi - -# 校验是否传入output_path,不需要修改 -if [[ $output_path == "" ]];then - output_path="./test/output/${ASCEND_DEVICE_ID}" -fi - -# 设置打屏日志文件名，请保留，文件名为${print_log} -print_log="./test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log" -modelarts_flag=${MODELARTS_MODEL_PATH} -if [ x"${modelarts_flag}" != x ]; -then - echo "running without etp..." - print_log_name=`ls /home/ma-user/modelarts/log/ | grep proc-rank` - print_log="/home/ma-user/modelarts/log/${print_log_name}" -fi -echo "### get your log here : ${print_log}" - -CaseName="" -function get_casename() -{ - if [ x"${perf_flag}" = x1 ]; - then - CaseName=${Network}_bs${batch_size}_${RANK_SIZE}'p'_'perf' - else - CaseName=${Network}_bs${batch_size}_${RANK_SIZE}'p'_'acc' - fi -} - -# 跳转到code目录 -cd ${cur_path}/../ -rm -rf ./test/output/${ASCEND_DEVICE_ID} -mkdir -p ./test/output/${ASCEND_DEVICE_ID} - -# 训练开始时间记录，不需要修改 -start_time=$(date +%s) -########################################################## -#########第3行 至 100行，请一定不要、不要、不要修改########## -#########第3行 至 100行，请一定不要、不要、不要修改########## -#########第3行 至 100行，请一定不要、不要、不要修改########## -########################################################## - -#========================================================= -#========================================================= -#========训练执行命令，需要根据您的网络进行修改============== -#========================================================= -#========================================================= -# 基础参数，需要模型审视修改 -# 您的训练数据集在${data_path}路径下，请直接使用这个变量获取 -# 您的训练输出目录在${output_path}路径下，请直接使用这个变量获取 -# 您的其他基础参数，可以自定义增加，但是batch_size请保留，并且设置正确的值 -batch_size=128 - - -if [ x"${modelarts_flag}" != x ]; -then - python3.7 ./train.py - python3.7 ./get_map.py -else - python3.7 ./train.py 1>>${print_log} 2>&1 - python3.7 ./get_map.py 1>>${print_log} 2>&1 -fi - -# 性能相关数据计算 -StepTime=`grep "ms/step :" ${print_log} | tail -n 10 | awk '{print $NF}' | awk '{sum+=$1} END {print sum/NR}'` -FPS=`awk 'BEGIN{printf "%.2f\n", '${batch_size}'/'${StepTime}*1000'}'` - -# 精度相关数据计算 -train_accuracy=`grep "Final Accuracy accuracy" ${print_log} | awk '{print $NF}'` -# 提取所有loss打印信息 -grep "loss :" ${print_log} | awk -F ":" '{print $4}' | awk -F "-" '{print $1}' > ./test/output/${ASCEND_DEVICE_ID}/my_output_loss.txt - - -########################################################### -#########后面的所有内容请不要修改########################### -#########后面的所有内容请不要修改########################### -#########后面的所有内容请不要修改########################### -########################################################### - -# 判断本次执行是否正确使用Ascend NPU -use_npu_flag=`grep "The model has been compiled on the Ascend AI processor" ${print_log} | wc -l` -if [ x"${use_npu_flag}" == x0 ]; -then - echo "------------------ ERROR NOTICE START ------------------" - echo "ERROR, your task haven't used Ascend NPU, please check your npu Migration." - echo "------------------ ERROR NOTICE END------------------" -else - echo "------------------ INFO NOTICE START------------------" - echo "INFO, your task have used Ascend NPU, please check your result." - echo "------------------ INFO NOTICE END------------------" -fi - -# 获取最终的casename，请保留，case文件名为${CaseName} -get_casename - -# 重命名loss文件 -if [ -f ./test/output/${ASCEND_DEVICE_ID}/my_output_loss.txt ]; -then - mv ./test/output/${ASCEND_DEVICE_ID}/my_output_loss.txt ./test/output/${ASCEND_DEVICE_ID}/${CaseName}_loss.txt -fi - -# 训练端到端耗时 -end_time=$(date +%s) -e2e_time=$(( $end_time - $start_time )) - -echo "------------------ Final result ------------------" -# 输出性能FPS/单step耗时/端到端耗时 -echo "Final Performance images/sec : $FPS" -echo "Final Performance ms/step : $StepTime" -echo "E2E Training Duration sec : $e2e_time" - -# 输出训练精度 -echo "Final Train Accuracy : ${train_accuracy}" - -# 最后一个迭代loss值，不需要修改 -ActualLoss=(`awk 'END {print $NF}' $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}_loss.txt`) - -#关键信息打印到${CaseName}.log中，不需要修改 -echo "Network = ${Network}" > $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log -echo "RankSize = ${RANK_SIZE}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log -echo "BatchSize = ${batch_size}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log -echo "DeviceType = `uname -m`" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log -echo "CaseName = ${CaseName}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log -echo "ActualFPS = ${FPS}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log -echo "TrainingTime = ${StepTime}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log -echo "ActualLoss = ${ActualLoss}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log -echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log -echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log +#!/bin/bash + +########################################################## +#########第3行 至 100行，请一定不要、不要、不要修改########## +#########第3行 至 100行，请一定不要、不要、不要修改########## +#########第3行 至 100行，请一定不要、不要、不要修改########## +########################################################## +# shell脚本所在路径 +cur_path=`echo $(cd $(dirname $0);pwd)` + +# 判断当前shell是否是performance +perf_flag=`echo $0 | grep performance | wc -l` + +# 当前执行网络的名称 +Network=`echo $(cd $(dirname $0);pwd) | awk -F"/" '{print $(NF-1)}'` + +export RANK_SIZE=1 +export RANK_ID=0 +export JOB_ID=10087 + +# 路径参数初始化 +data_path="" +output_path="" + +# 帮助信息，不需要修改 +if [[ $1 == --help || $1 == -h ]];then + echo"usage:./train_performance_1P.sh " + echo " " + echo "parameter explain: + --data_path # dataset of training + --output_path # output of training + --train_steps # max_step for training + --train_epochs # max_epoch for training + --batch_size # batch size + -h/--help show help message + " + exit 1 +fi + +# 参数校验，不需要修改 +for para in $* +do + if [[ $para == --data_path* ]];then + data_path=`echo ${para#*=}` + elif [[ $para == --output_path* ]];then + output_path=`echo ${para#*=}` + elif [[ $para == --train_steps* ]];then + train_steps=`echo ${para#*=}` + elif [[ $para == --train_epochs* ]];then + train_epochs=`echo ${para#*=}` + elif [[ $para == --batch_size* ]];then + batch_size=`echo ${para#*=}` + fi +done + +# 校验是否传入data_path,不需要修改 +if [[ $data_path == "" ]];then + echo "[Error] para \"data_path\" must be config" + exit 1 +fi + +# 校验是否传入output_path,不需要修改 +if [[ $output_path == "" ]];then + output_path="./test/output/${ASCEND_DEVICE_ID}" +fi + +# 设置打屏日志文件名，请保留，文件名为${print_log} +print_log="./test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log" +modelarts_flag=${MODELARTS_MODEL_PATH} +if [ x"${modelarts_flag}" != x ]; +then + echo "running without etp..." + print_log_name=`ls /home/ma-user/modelarts/log/ | grep proc-rank` + print_log="/home/ma-user/modelarts/log/${print_log_name}" +fi +echo "### get your log here : ${print_log}" + +CaseName="" +function get_casename() +{ + if [ x"${perf_flag}" = x1 ]; + then + CaseName=${Network}_bs${batch_size}_${RANK_SIZE}'p'_'perf' + else + CaseName=${Network}_bs${batch_size}_${RANK_SIZE}'p'_'acc' + fi +} + +# 跳转到code目录 +cd ${cur_path}/../ +rm -rf ./test/output/${ASCEND_DEVICE_ID} +mkdir -p ./test/output/${ASCEND_DEVICE_ID} + +# 训练开始时间记录，不需要修改 +start_time=$(date +%s) +########################################################## +#########第3行 至 100行，请一定不要、不要、不要修改########## +#########第3行 至 100行，请一定不要、不要、不要修改########## +#########第3行 至 100行，请一定不要、不要、不要修改########## +########################################################## + +#========================================================= +#========================================================= +#========训练执行命令，需要根据您的网络进行修改============== +#========================================================= +#========================================================= +# 基础参数，需要模型审视修改 +# 您的训练数据集在${data_path}路径下，请直接使用这个变量获取 +# 您的训练输出目录在${output_path}路径下，请直接使用这个变量获取 +# 您的其他基础参数，可以自定义增加，但是batch_size请保留，并且设置正确的值 +batch_size=8 + +sed -i s#"/home/dingwei/yolov5"#"${data_path}"#g ./2007_train.txt +sed -i s#"/home/dingwei/yolov5"#"${data_path}"#g ./2007_val.txt + +if [ x"${modelarts_flag}" != x ]; +then + python3.7 ./train.py + python3.7 ./get_map.py --data_url=${data_path} +else + python3.7 ./train.py 1>${print_log} 2>&1 + python3.7 ./get_map.py --data_url=${data_path} 1>${print_log} 2>&1 +fi + +# 性能相关数据计算 +#StepTime=`grep "each step time" ${print_log} | tail -n 10 | awk '{print $NF}' | awk '{sum+=$1} END {print sum/NR}'` +#FPS=`awk 'BEGIN{printf "%.2f\n", '${batch_size}'/'${StepTime}'}'` + +# 精度相关数据计算 +train_accuracy=`grep "mAP =" ${print_log} | awk '{print $NF}'` +# 提取所有loss打印信息 +grep "loss:" ${print_log} | awk '{print $NF}' > ./test/output/${ASCEND_DEVICE_ID}/my_output_loss.txt + + +########################################################### +#########后面的所有内容请不要修改########################### +#########后面的所有内容请不要修改########################### +#########后面的所有内容请不要修改########################### +########################################################### + +# 判断本次执行是否正确使用Ascend NPU +use_npu_flag=`grep "The model has been compiled on the Ascend AI processor" ${print_log} | wc -l` +if [ x"${use_npu_flag}" == x0 ]; +then + echo "------------------ ERROR NOTICE START ------------------" + echo "ERROR, your task haven't used Ascend NPU, please check your npu Migration." + echo "------------------ ERROR NOTICE END------------------" +else + echo "------------------ INFO NOTICE START------------------" + echo "INFO, your task have used Ascend NPU, please check your result." + echo "------------------ INFO NOTICE END------------------" +fi + +# 获取最终的casename，请保留，case文件名为${CaseName} +get_casename + +# 重命名loss文件 +if [ -f ./test/output/${ASCEND_DEVICE_ID}/my_output_loss.txt ]; +then + mv ./test/output/${ASCEND_DEVICE_ID}/my_output_loss.txt ./test/output/${ASCEND_DEVICE_ID}/${CaseName}_loss.txt +fi + +# 训练端到端耗时 +end_time=$(date +%s) +e2e_time=$(( $end_time - $start_time )) + +echo "------------------ Final result ------------------" +# 输出性能FPS/单step耗时/端到端耗时 +#echo "Final Performance images/sec : $FPS" +#echo "Final Performance sec/step : $StepTime" +echo "E2E Training Duration sec : $e2e_time" + +# 输出训练精度 +echo "Final Train Accuracy : ${train_accuracy}" + +# 最后一个迭代loss值，不需要修改 +ActualLoss=(`awk 'END {print $NF}' $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}_loss.txt`) + +#关键信息打印到${CaseName}.log中，不需要修改 +echo "Network = ${Network}" > $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log +echo "RankSize = ${RANK_SIZE}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log +echo "BatchSize = ${batch_size}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log +echo "DeviceType = `uname -m`" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log +echo "CaseName = ${CaseName}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log +#echo "ActualFPS = ${FPS}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log +#echo "TrainingTime = ${StepTime}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log +#echo "ActualLoss = ${ActualLoss}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log +echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log +echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log -- Gitee