diff --git a/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_16p.sh b/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_16p.sh
index 7cf2b07c3235f8216094dd362441b46eea734aa1..e78001b025701f36d760552bc1e7fd54868c94f8 100644
--- a/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_16p.sh
+++ b/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_16p.sh
@@ -130,7 +130,7 @@ e2e_time=$(( $end_time - $start_time ))
 # 结果打印，不需要修改
 echo "------------------ Final result ------------------"
 # 输出性能FPS，需要模型审视修改
-step_time=`grep "Epoch" ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log | awk -F "Time " '{print $2}' | awk -F " " '{print $1}' | tail -n 20 | awk '{a+=$1} END {if (NR != 0) printf("%.3f",a/NR)}'`
+step_time=`grep "Epoch" ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log | awk -F "Time " '{print $2}' | awk -F " " '{print $2}' |awk -F " " '{print $3}' | awk -F ")" '{print $1}' | tail -n 1`
 FPS=`echo "${batch_size} / ${step_time}"|bc`
 # 打印，不需要修改
 echo "Final Performance images/sec : $FPS"
diff --git a/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_1p.sh b/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_1p.sh
index ecbdb30c869f37de9ccf5bd8963057c07afa799e..236e3f55930cde45141c23b2317e18708030258f 100644
--- a/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_1p.sh
+++ b/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_1p.sh
@@ -1,22 +1,22 @@
 #!/bin/bash
 
-################�������ò�������Ҫģ�������޸�##################
-# ��ѡ�ֶ�(�����ڴ˴�����IJ���): Network batch_size RANK_SIZE
-# �������ƣ�ͬĿ¼����
+################基础配置参数，需要模型审视修改##################
+# 必选字段(必须在此处定义的参数): Network batch_size RANK_SIZE
+# 网络名称，同目录名称
 Network="ResNet50_ID4149_for_PyTorch"
-# ѵ��batch_size
+# 训练batch_size
 batch_size=512
-# ѵ��ʹ�õ�npu����
+# 训练使用的npu卡数
 export RANK_SIZE=1
-# ���ݼ�·��,����Ϊ��,����Ҫ�޸�
+# 数据集路径,保持为空,不需要修改
 data_path=""
 
-# ѵ��epoch 90
+# 训练epoch 1
 train_epochs=1
-# �������ݽ�����
+# 加载数据进程数
 workers=64
 device_id=0
-# ����У�飬data_pathΪ�ش�������������������ɾ��ģ�������������˴������������������ж��岢��ֵ
+# 参数校验，data_path为必传参数，其他参数的增删由模型自身决定；此处新增参数需在上面有定义并赋值
 for para in $*
 do
     if [[ $para == --data_path* ]];then
@@ -34,14 +34,14 @@ do
     fi
 done
 
-# У���Ƿ���data_path,����Ҫ�޸�
+# 校验是否传入data_path,不需要修改
 if [[ $data_path == "" ]];then
     echo "[Error] para \"data_path\" must be confing"
     exit 1
 fi
 
-###############ָ��ѵ���ű�ִ��·��###############
-# cd����test�ļ���ͬ�㼶Ŀ¼��ִ�нű�����߼����ԣ�test_path_dirΪ����test�ļ��е�·��
+###############指定训练脚本执行路径###############
+# cd到与test文件夹同层级目录下执行脚本，提高兼容性；test_path_dir为包含test文件夹的路径
 cur_path=`pwd`
 cur_path_last_dirname=${cur_path##*/}
 if [ x"${cur_path_last_dirname}" == x"test" ];then
@@ -52,10 +52,10 @@ else
     test_path_dir=${cur_path}/test
 fi
 
-# У���Ƿ�ָ����device_id,�ֶ�̬����device_id���ֶ�ָ��device_id,�˴�����Ҫ�޸�
+# 校验是否指定了device_id,分动态分配device_id与手动指定device_id,此处不需要修改
 if [ $ASCEND_DEVICE_ID ];then
     echo "device id is ${ASCEND_DEVICE_ID}"
-    # ƽ̨�����������ݼ�·��
+    # 平台运行软链数据集路径
 elif [ ${device_id} ];then
     export ASCEND_DEVICE_ID=${device_id}
     echo "device id is ${ASCEND_DEVICE_ID}"
@@ -64,7 +64,7 @@ else
     exit 1
 fi
 
-#################������־���Ŀ¼������Ҫ�޸�#################
+#################创建日志输出目录，不需要修改#################
 if [ -d ${test_path_dir}/output/${ASCEND_DEVICE_ID} ];then
     rm -rf ${test_path_dir}/output/${ASCEND_DEVICE_ID}
     mkdir -p ${test_path_dir}/output/$ASCEND_DEVICE_ID
@@ -73,10 +73,10 @@ else
 fi
 
 
-#################����ѵ���ű�#################
-# ѵ����ʼʱ�䣬����Ҫ�޸�
+#################启动训练脚本#################
+# 训练开始时间，不需要修改
 start_time=$(date +%s)
-# ��ƽ̨����ʱsource ��������
+# 非平台场景时source 环境变量
 check_etp_flag=`env | grep etp_running_flag`
 etp_flag=`echo ${check_etp_flag#*=}`
 if [ x"${etp_flag}" != x"true" ];then
@@ -97,43 +97,41 @@ nohup python3 main.py \
 wait
 
 
-##################��ȡѵ������################
-# ѵ������ʱ�䣬����Ҫ�޸�
+##################获取训练数据################
+# 训练结束时间，不需要修改
 end_time=$(date +%s)
 e2e_time=$(( $end_time - $start_time ))
 
-# �����ӡ������Ҫ�޸�
+# 结果打印，不需要修改
 echo "------------------ Final result ------------------"
-# �������FPS����Ҫģ�������޸�
-step_time=`grep "Epoch" ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log | awk -F "Time " '{print $2}' | awk -F " " '{print $1}' | tail -n 100 | awk '{a+=$1} END {if (NR != 0) printf("%.3f",a/NR)}'`
+# 输出性能FPS，需要模型审视修改
+step_time=`grep "Epoch" ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log | awk -F "Time " '{print $2}' | awk -F " " '{print $2}' |awk -F " " '{print $3}' | awk -F ")" '{print $1}' | tail -n 1`
 FPS=`echo "${batch_size} / ${step_time}"|bc`
-# ��ӡ������Ҫ�޸�
+# 打印，不需要修改
 echo "Final Performance images/sec : $FPS"
 
-CompileTime=`grep step_time ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log| head -2 |awk -F "step_time = " '{print $2}' | awk '{sum+=$1} END {print"",sum}' |sed s/[[:space:]]//g`
-
-# ���ѵ������,��Ҫģ�������޸�
+# 输出训练精度,需要模型审视修改
 train_accuracy=`grep -a '*   Acc@1'  ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log|awk 'END {print}'|awk -F "Acc@1 " '{print $NF}'|awk -F " " '{print $1}'`
-# ��ӡ������Ҫ�޸�
+# 打印，不需要修改
 echo "Final Train Accuracy : ${train_accuracy}"
 echo "E2E Training Duration sec : $e2e_time"
 
-# ѵ��������Ϣ������Ҫ�޸�
+# 训练用例信息，不需要修改
 BatchSize=${batch_size}
 DeviceType=`uname -m`
-CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'perf'
-# ������
+CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'acc'
+# 吞吐量
 ActualFPS=${FPS}
-# ������ѵ��ʱ��
+# 单迭代训练时长
 TrainingTime=`awk 'BEGIN{printf "%.2f\n", '${batch_size}'*1000/'${FPS}'}'`
 
-# ��train_$ASCEND_DEVICE_ID.log��ȡLoss��train_${CaseName}_loss.txt�У���Ҫ����ģ������
+# 从train_$ASCEND_DEVICE_ID.log提取Loss到train_${CaseName}_loss.txt中，需要根据模型审视
 grep Epoch: ${test_path_dir}/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log|grep -v Test|awk -F "Loss " '{print $NF}' | awk -F " " '{print $1}' >>  ${test_path_dir}/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt
 
-# ���һ������lossֵ������Ҫ�޸�
+# 最后一个迭代loss值，不需要修改
 ActualLoss=`awk 'END {print}'  ${test_path_dir}/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt`
 
-# �ؼ���Ϣ��ӡ��${CaseName}.log�У�����Ҫ�޸�
+# 关键信息打印到${CaseName}.log中，不需要修改
 echo "Network = ${Network}" >  ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "RankSize = ${RANK_SIZE}" >>  ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "BatchSize = ${BatchSize}" >>  ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
@@ -144,4 +142,3 @@ echo "TrainingTime = ${TrainingTime}" >>  ${test_path_dir}/output/$ASCEND_DEVICE
 echo "TrainAccuracy = ${train_accuracy}" >> ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >>  ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "E2ETrainingTime = ${e2e_time}" >>  ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "CompileTime = ${CompileTime}" >> ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
diff --git a/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_8p.sh b/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_8p.sh
index 5244b07e1047c9c54494653ef55c006771ad6b70..8c81e7fa18b34c98a09db99e373498231233f88d 100644
--- a/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_8p.sh
+++ b/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_8p.sh
@@ -1,4 +1,4 @@
-#!/bin/bash
+    #!/bin/bash
 
 ################基础配置参数，需要模型审视修改##################
 # 必选字段(必须在此处定义的参数): Network batch_size RANK_SIZE
@@ -130,7 +130,7 @@ e2e_time=$(( $end_time - $start_time ))
 # 结果打印，不需要修改
 echo "------------------ Final result ------------------"
 # 输出性能FPS，需要模型审视修改
-step_time=`grep "Epoch" ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log | awk -F "Time " '{print $2}' | awk -F " " '{print $1}' | tail -n 20 | awk '{a+=$1} END {if (NR != 0) printf("%.3f",a/NR)}'`
+step_time=`grep "Epoch" ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log | awk -F "Time " '{print $2}' | awk -F " " '{print $2}' |awk -F " " '{print $3}' | awk -F ")" '{print $1}' | tail -n 1`
 FPS=`echo "${batch_size} / ${step_time}"|bc`
 # 打印，不需要修改
 echo "Final Performance images/sec : $FPS"