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 b3d8d0e87c2e8ae15c584ef62a571776a4525931..73da94968b8204ed880971525603e959f749d0aa 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
 
-################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
+################鍩虹閰嶇疆鍙傛暟锛岄渶瑕佹ā鍨嬪瑙嗕慨鏀�##################
+# 蹇呴�夊瓧娈�(蹇呴』鍦ㄦ澶勫畾涔夌殑鍙傛暟): Network batch_size RANK_SIZE
+# 缃戠粶鍚嶇О锛屽悓鐩綍鍚嶇О
 Network="ResNet50_ID4149_for_PyTorch"
-# 训练batch_size
+# 璁粌batch_size
 batch_size=512
-# 训练使用的npu卡数
+# 璁粌浣跨敤鐨刵pu鍗℃暟
 export RANK_SIZE=1
-# 数据集路径,保持为空,不需要修改
+# 鏁版嵁闆嗚矾寰�,淇濇寔涓虹┖,涓嶉渶瑕佷慨鏀�
 data_path=""
 
-# 训练epoch 90
+# 璁粌epoch 90
 train_epochs=1
-# 加载数据进程数
-workers=64
+# 鍔犺浇鏁版嵁杩涚▼鏁�
+workers=24
 device_id=0
-# 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
+# 鍙傛暟鏍￠獙锛宒ata_path涓哄繀浼犲弬鏁帮紝鍏朵粬鍙傛暟鐨勫鍒犵敱妯″瀷鑷韩鍐冲畾锛涙澶勬柊澧炲弬鏁伴渶鍦ㄤ笂闈㈡湁瀹氫箟骞惰祴鍊�
 for para in $*
 do
     if [[ $para == --data_path* ]];then
@@ -28,14 +28,14 @@ do
     fi
 done
 
-# 校验是否传入data_path,不需要修改
+# 鏍￠獙鏄惁浼犲叆data_path,涓嶉渶瑕佷慨鏀�
 if [[ $data_path == "" ]];then
     echo "[Error] para \"data_path\" must be confing"
     exit 1
 fi
 
-###############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
+###############鎸囧畾璁粌鑴氭湰鎵ц璺緞###############
+# cd鍒颁笌test鏂囦欢澶瑰悓灞傜骇鐩綍涓嬫墽琛岃剼鏈紝鎻愰珮鍏煎鎬э紱test_path_dir涓哄寘鍚玹est鏂囦欢澶圭殑璺緞
 cur_path=`pwd`
 cur_path_last_dirname=${cur_path##*/}
 if [ x"${cur_path_last_dirname}" == x"test" ];then
@@ -46,10 +46,10 @@ else
     test_path_dir=${cur_path}/test
 fi
 
-# 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
+# 鏍￠獙鏄惁鎸囧畾浜哾evice_id,鍒嗗姩鎬佸垎閰峝evice_id涓庢墜鍔ㄦ寚瀹歞evice_id,姝ゅ涓嶉渶瑕佷慨鏀�
 if [ $ASCEND_DEVICE_ID ];then
     echo "device id is ${ASCEND_DEVICE_ID}"
-    # 平台运行软链数据集路径
+    # 骞冲彴杩愯杞摼鏁版嵁闆嗚矾寰�
 elif [ ${device_id} ];then
     export ASCEND_DEVICE_ID=${device_id}
     echo "device id is ${ASCEND_DEVICE_ID}"
@@ -58,7 +58,7 @@ else
     exit 1
 fi
 
-#################创建日志输出目录，不需要修改#################
+#################鍒涘缓鏃ュ織杈撳嚭鐩綍锛屼笉闇�瑕佷慨鏀�#################
 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
@@ -67,10 +67,10 @@ else
 fi
 
 
-#################启动训练脚本#################
-# 训练开始时间，不需要修改
+#################鍚姩璁粌鑴氭湰#################
+# 璁粌寮�濮嬫椂闂达紝涓嶉渶瑕佷慨鏀�
 start_time=$(date +%s)
-# 非平台场景时source 环境变量
+# 闈炲钩鍙板満鏅椂source 鐜鍙橀噺
 check_etp_flag=`env | grep etp_running_flag`
 etp_flag=`echo ${check_etp_flag#*=}`
 if [ x"${etp_flag}" != x"true" ];then
@@ -78,56 +78,56 @@ if [ x"${etp_flag}" != x"true" ];then
 fi
 
 nohup python3.7 main.py \
-    --data $data_path \
-    --amp \
-    --world-size 1 \
-    --seed 60 \
-    -a resnet50 \
-    -j $workers \
-    -b $batch_size \
-    --lr 0.2 \
-    --epochs $train_epochs \
-    --gpu $device_id > ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+          --data $data_path \
+          --amp \
+          --world-size 1 \
+          --seed 60 \
+          -a resnet50 \
+          -j $workers \
+          -b $batch_size  \
+          --lr 0.2 \
+          --epochs $train_epochs \
+          --gpu $device_id  > ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
 wait
 
 
-##################获取训练数据################
-# 训练结束时间，不需要修改
+##################鑾峰彇璁粌鏁版嵁################
+# 璁粌缁撴潫鏃堕棿锛屼笉闇�瑕佷慨鏀�
 end_time=$(date +%s)
 e2e_time=$(( $end_time - $start_time ))
 
-# 结果打印，不需要修改
+# 缁撴灉鎵撳嵃锛屼笉闇�瑕佷慨鏀�
 echo "------------------ Final result ------------------"
-# 输出性能FPS，需要模型审视修改
+# 杈撳嚭鎬ц兘FPS锛岄渶瑕佹ā鍨嬪瑙嗕慨鏀�
 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+=$1} END {if (NR != 0) printf("%.3f",a/NR)}'`
 FPS=`echo "${batch_size} / ${step_time}"|bc`
-# 打印，不需要修改
+# 鎵撳嵃锛屼笉闇�瑕佷慨鏀�
 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`
 
-# 输出训练精度,需要模型审视修改
+# 杈撳嚭璁粌绮惧害,闇�瑕佹ā鍨嬪瑙嗕慨鏀�
 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}'`
-# 打印，不需要修改
+# 鎵撳嵃锛屼笉闇�瑕佷慨鏀�
 echo "Final Train Accuracy : ${train_accuracy}"
 echo "E2E Training Duration sec : $e2e_time"
 
-# 训练用例信息，不需要修改
+# 璁粌鐢ㄤ緥淇℃伅锛屼笉闇�瑕佷慨鏀�
 BatchSize=${batch_size}
 DeviceType=`uname -m`
 CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'perf'
-# 吞吐量
+# 鍚炲悙閲�
 ActualFPS=${FPS}
-# 单迭代训练时长
+# 鍗曡凯浠ｈ缁冩椂闀�
 TrainingTime=`awk 'BEGIN{printf "%.2f\n", '${batch_size}'*1000/'${FPS}'}'`
 
-# 从train_$ASCEND_DEVICE_ID.log提取Loss到train_${CaseName}_loss.txt中，需要根据模型审视
+# 浠巘rain_$ASCEND_DEVICE_ID.log鎻愬彇Loss鍒皌rain_${CaseName}_loss.txt涓紝闇�瑕佹牴鎹ā鍨嬪瑙�
 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
 
-# 最后一个迭代loss值，不需要修改
+# 鏈�鍚庝竴涓凯浠oss鍊硷紝涓嶉渶瑕佷慨鏀�
 ActualLoss=`awk 'END {print}'  ${test_path_dir}/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt`
 
-# 关键信息打印到${CaseName}.log中，不需要修改
+# 鍏抽敭淇℃伅鎵撳嵃鍒�${CaseName}.log涓紝涓嶉渶瑕佷慨鏀�
 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
diff --git a/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_2p.sh b/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_2p.sh
new file mode 100644
index 0000000000000000000000000000000000000000..9cc73a28df082b4d024f837e8bad7c2689507fb3
--- /dev/null
+++ b/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_2p.sh
@@ -0,0 +1,168 @@
+#!/bin/bash
+
+################鍩虹閰嶇疆鍙傛暟锛岄渶瑕佹ā鍨嬪瑙嗕慨鏀�##################
+# 蹇呴�夊瓧娈�(蹇呴』鍦ㄦ澶勫畾涔夌殑鍙傛暟): Network batch_size RANK_SIZE
+# 缃戠粶鍚嶇О锛屽悓鐩綍鍚嶇О
+Network="ResNet50_ID4149_for_PyTorch"
+# 璁粌batch_size
+batch_size=1024
+# 璁粌浣跨敤鐨刵pu鍗℃暟
+export RANK_SIZE=2
+# 鏁版嵁闆嗚矾寰�,淇濇寔涓虹┖,涓嶉渶瑕佷慨鏀�
+data_path=""
+
+# 璁粌epoch 90
+train_epochs=2
+# 鍔犺浇鏁版嵁杩涚▼鏁�
+workers=48
+device_id=0
+# 鍙傛暟鏍￠獙锛宒ata_path涓哄繀浼犲弬鏁帮紝鍏朵粬鍙傛暟鐨勫鍒犵敱妯″瀷鑷韩鍐冲畾锛涙澶勬柊澧炲弬鏁伴渶鍦ㄤ笂闈㈡湁瀹氫箟骞惰祴鍊�
+for para in $*
+do
+    if [[ $para == --data_path* ]];then
+        data_path=`echo ${para#*=}`
+    elif [[ $para == --batch_size* ]];then
+        batch_size=`echo ${para#*=}`
+    elif [[ $para == --device_id* ]];then
+        device_id=`echo ${para#*=}`
+    fi
+done
+
+# 鏍￠獙鏄惁浼犲叆data_path,涓嶉渶瑕佷慨鏀�
+if [[ $data_path == "" ]];then
+    echo "[Error] para \"data_path\" must be confing"
+    exit 1
+fi
+
+###############鎸囧畾璁粌鑴氭湰鎵ц璺緞###############
+# cd鍒颁笌test鏂囦欢澶瑰悓灞傜骇鐩綍涓嬫墽琛岃剼鏈紝鎻愰珮鍏煎鎬э紱test_path_dir涓哄寘鍚玹est鏂囦欢澶圭殑璺緞
+cur_path=`pwd`
+cur_path_last_dirname=${cur_path##*/}
+if [ x"${cur_path_last_dirname}" == x"test" ];then
+    test_path_dir=${cur_path}
+    cd ..
+    cur_path=`pwd`
+else
+    test_path_dir=${cur_path}/test
+fi
+
+# 鏍￠獙鏄惁鎸囧畾浜哾evice_id,鍒嗗姩鎬佸垎閰峝evice_id涓庢墜鍔ㄦ寚瀹歞evice_id,姝ゅ涓嶉渶瑕佷慨鏀�
+if [ $ASCEND_DEVICE_ID ];then
+    echo "device id is ${ASCEND_DEVICE_ID}"
+    # 骞冲彴杩愯杞摼鏁版嵁闆嗚矾寰�
+elif [ ${device_id} ];then
+    export ASCEND_DEVICE_ID=${device_id}
+    echo "device id is ${ASCEND_DEVICE_ID}"
+else
+    "[Error] device id must be config"
+    exit 1
+fi
+
+#################鍒涘缓鏃ュ織杈撳嚭鐩綍锛屼笉闇�瑕佷慨鏀�#################
+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
+else
+    mkdir -p ${test_path_dir}/output/$ASCEND_DEVICE_ID
+fi
+
+
+#################鍚姩璁粌鑴氭湰#################
+# 璁粌寮�濮嬫椂闂达紝涓嶉渶瑕佷慨鏀�
+start_time=$(date +%s)
+# 闈炲钩鍙板満鏅椂source 鐜鍙橀噺
+check_etp_flag=`env | grep etp_running_flag`
+etp_flag=`echo ${check_etp_flag#*=}`
+if [ x"${etp_flag}" != x"true" ];then
+    source ${test_path_dir}/env_npu.sh
+fi
+
+KERNEL_NUM=$(($(nproc)/2))
+for((RANK_ID=0;RANK_ID<2;RANK_ID++));
+do
+    export RANK_SIZE=2
+    export RANK_ID=$RANK_ID
+    if [ $(uname -m) = 'aarch64' ]
+    then
+        PID_START=$((KERNEL_NUM * RANK_ID))
+        PID_END=$((PID_START + KERNEL_NUM - 1))
+        nohup taskset -c $PID_START-$PID_END python3.7 main.py \
+            --data $data_path \
+            --amp \
+            --world-size 1 \
+            --seed 60 \
+            -a resnet50 \
+            -j $workers \
+            -b $batch_size  \
+            --lr 1.6 \
+            --epochs $train_epochs \
+            --gpu ${RANK_ID} \
+            --rank 0 \
+            --multiprocessing-distributed > ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+    else
+        nohup python3.7 main.py \
+            --data $data_path \
+            --amp \
+            --world-size 1 \
+            --seed 60 \
+            -a resnet50 \
+            -j $workers \
+            -b $batch_size  \
+            --lr 1.6 \
+            --epochs $train_epochs \
+            --gpu ${RANK_ID} \
+            --rank 0 \
+            --multiprocessing-distributed > ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+    fi
+done
+wait
+
+
+##################鑾峰彇璁粌鏁版嵁################
+# 璁粌缁撴潫鏃堕棿锛屼笉闇�瑕佷慨鏀�
+end_time=$(date +%s)
+e2e_time=$(( $end_time - $start_time ))
+
+# 缁撴灉鎵撳嵃锛屼笉闇�瑕佷慨鏀�
+echo "------------------ Final result ------------------"
+# 杈撳嚭鎬ц兘FPS锛岄渶瑕佹ā鍨嬪瑙嗕慨鏀�
+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+=$1} END {if (NR != 0) printf("%.3f",a/NR)}'`
+FPS=`echo "${batch_size} / ${step_time}"|bc`
+# 鎵撳嵃锛屼笉闇�瑕佷慨鏀�
+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`
+
+# 杈撳嚭璁粌绮惧害,闇�瑕佹ā鍨嬪瑙嗕慨鏀�
+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}'`
+# 鎵撳嵃锛屼笉闇�瑕佷慨鏀�
+echo "Final Train Accuracy : ${train_accuracy}"
+echo "E2E Training Duration sec : $e2e_time"
+
+# 璁粌鐢ㄤ緥淇℃伅锛屼笉闇�瑕佷慨鏀�
+BatchSize=${batch_size}
+DeviceType=`uname -m`
+CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'perf'
+# 鍚炲悙閲�
+ActualFPS=${FPS}
+# 鍗曡凯浠ｈ缁冩椂闀�
+TrainingTime=`awk 'BEGIN{printf "%.2f\n", '${batch_size}'*1000/'${FPS}'}'`
+
+# 浠巘rain_$ASCEND_DEVICE_ID.log鎻愬彇Loss鍒皌rain_${CaseName}_loss.txt涓紝闇�瑕佹牴鎹ā鍨嬪瑙�
+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
+
+# 鏈�鍚庝竴涓凯浠oss鍊硷紝涓嶉渶瑕佷慨鏀�
+ActualLoss=`awk 'END {print}'  ${test_path_dir}/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt`
+
+# 鍏抽敭淇℃伅鎵撳嵃鍒�${CaseName}.log涓紝涓嶉渶瑕佷慨鏀�
+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
+echo "DeviceType = ${DeviceType}" >>  ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "CaseName = ${CaseName}" >>  ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "ActualFPS = ${ActualFPS}" >>  ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "TrainingTime = ${TrainingTime}" >>  ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
+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_4p.sh b/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_4p.sh
new file mode 100644
index 0000000000000000000000000000000000000000..8893c4be3a710b7b73fbf017f9ec12d10db485ed
--- /dev/null
+++ b/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/test/train_performance_4p.sh
@@ -0,0 +1,168 @@
+#!/bin/bash
+
+################鍩虹閰嶇疆鍙傛暟锛岄渶瑕佹ā鍨嬪瑙嗕慨鏀�##################
+# 蹇呴�夊瓧娈�(蹇呴』鍦ㄦ澶勫畾涔夌殑鍙傛暟): Network batch_size RANK_SIZE
+# 缃戠粶鍚嶇О锛屽悓鐩綍鍚嶇О
+Network="ResNet50_ID4149_for_PyTorch"
+# 璁粌batch_size
+batch_size=2048
+# 璁粌浣跨敤鐨刵pu鍗℃暟
+export RANK_SIZE=4
+# 鏁版嵁闆嗚矾寰�,淇濇寔涓虹┖,涓嶉渶瑕佷慨鏀�
+data_path=""
+
+# 璁粌epoch 90
+train_epochs=2
+# 鍔犺浇鏁版嵁杩涚▼鏁�
+workers=96
+device_id=0
+# 鍙傛暟鏍￠獙锛宒ata_path涓哄繀浼犲弬鏁帮紝鍏朵粬鍙傛暟鐨勫鍒犵敱妯″瀷鑷韩鍐冲畾锛涙澶勬柊澧炲弬鏁伴渶鍦ㄤ笂闈㈡湁瀹氫箟骞惰祴鍊�
+for para in $*
+do
+    if [[ $para == --data_path* ]];then
+        data_path=`echo ${para#*=}`
+    elif [[ $para == --batch_size* ]];then
+        batch_size=`echo ${para#*=}`
+    elif [[ $para == --device_id* ]];then
+        device_id=`echo ${para#*=}`
+    fi
+done
+
+# 鏍￠獙鏄惁浼犲叆data_path,涓嶉渶瑕佷慨鏀�
+if [[ $data_path == "" ]];then
+    echo "[Error] para \"data_path\" must be confing"
+    exit 1
+fi
+
+###############鎸囧畾璁粌鑴氭湰鎵ц璺緞###############
+# cd鍒颁笌test鏂囦欢澶瑰悓灞傜骇鐩綍涓嬫墽琛岃剼鏈紝鎻愰珮鍏煎鎬э紱test_path_dir涓哄寘鍚玹est鏂囦欢澶圭殑璺緞
+cur_path=`pwd`
+cur_path_last_dirname=${cur_path##*/}
+if [ x"${cur_path_last_dirname}" == x"test" ];then
+    test_path_dir=${cur_path}
+    cd ..
+    cur_path=`pwd`
+else
+    test_path_dir=${cur_path}/test
+fi
+
+# 鏍￠獙鏄惁鎸囧畾浜哾evice_id,鍒嗗姩鎬佸垎閰峝evice_id涓庢墜鍔ㄦ寚瀹歞evice_id,姝ゅ涓嶉渶瑕佷慨鏀�
+if [ $ASCEND_DEVICE_ID ];then
+    echo "device id is ${ASCEND_DEVICE_ID}"
+    # 骞冲彴杩愯杞摼鏁版嵁闆嗚矾寰�
+elif [ ${device_id} ];then
+    export ASCEND_DEVICE_ID=${device_id}
+    echo "device id is ${ASCEND_DEVICE_ID}"
+else
+    "[Error] device id must be config"
+    exit 1
+fi
+
+#################鍒涘缓鏃ュ織杈撳嚭鐩綍锛屼笉闇�瑕佷慨鏀�#################
+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
+else
+    mkdir -p ${test_path_dir}/output/$ASCEND_DEVICE_ID
+fi
+
+
+#################鍚姩璁粌鑴氭湰#################
+# 璁粌寮�濮嬫椂闂达紝涓嶉渶瑕佷慨鏀�
+start_time=$(date +%s)
+# 闈炲钩鍙板満鏅椂source 鐜鍙橀噺
+check_etp_flag=`env | grep etp_running_flag`
+etp_flag=`echo ${check_etp_flag#*=}`
+if [ x"${etp_flag}" != x"true" ];then
+    source ${test_path_dir}/env_npu.sh
+fi
+
+KERNEL_NUM=$(($(nproc)/4))
+for((RANK_ID=0;RANK_ID<4;RANK_ID++));
+do
+    export RANK_SIZE=4
+    export RANK_ID=$RANK_ID
+    if [ $(uname -m) = 'aarch64' ]
+    then
+        PID_START=$((KERNEL_NUM * RANK_ID))
+        PID_END=$((PID_START + KERNEL_NUM - 1))
+        nohup taskset -c $PID_START-$PID_END python3.7 main.py \
+            --data $data_path \
+            --amp \
+            --world-size 1 \
+            --seed 60 \
+            -a resnet50 \
+            -j $workers \
+            -b $batch_size  \
+            --lr 1.6 \
+            --epochs $train_epochs \
+            --gpu ${RANK_ID} \
+            --rank 0 \
+            --multiprocessing-distributed > ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+    else
+        nohup python3.7 main.py \
+            --data $data_path \
+            --amp \
+            --world-size 1 \
+            --seed 60 \
+            -a resnet50 \
+            -j $workers \
+            -b $batch_size  \
+            --lr 1.6 \
+            --epochs $train_epochs \
+            --gpu ${RANK_ID} \
+            --rank 0 \
+            --multiprocessing-distributed > ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+    fi
+done
+wait
+
+
+##################鑾峰彇璁粌鏁版嵁################
+# 璁粌缁撴潫鏃堕棿锛屼笉闇�瑕佷慨鏀�
+end_time=$(date +%s)
+e2e_time=$(( $end_time - $start_time ))
+
+# 缁撴灉鎵撳嵃锛屼笉闇�瑕佷慨鏀�
+echo "------------------ Final result ------------------"
+# 杈撳嚭鎬ц兘FPS锛岄渶瑕佹ā鍨嬪瑙嗕慨鏀�
+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+=$1} END {if (NR != 0) printf("%.3f",a/NR)}'`
+FPS=`echo "${batch_size} / ${step_time}"|bc`
+# 鎵撳嵃锛屼笉闇�瑕佷慨鏀�
+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`
+
+# 杈撳嚭璁粌绮惧害,闇�瑕佹ā鍨嬪瑙嗕慨鏀�
+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}'`
+# 鎵撳嵃锛屼笉闇�瑕佷慨鏀�
+echo "Final Train Accuracy : ${train_accuracy}"
+echo "E2E Training Duration sec : $e2e_time"
+
+# 璁粌鐢ㄤ緥淇℃伅锛屼笉闇�瑕佷慨鏀�
+BatchSize=${batch_size}
+DeviceType=`uname -m`
+CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'perf'
+# 鍚炲悙閲�
+ActualFPS=${FPS}
+# 鍗曡凯浠ｈ缁冩椂闀�
+TrainingTime=`awk 'BEGIN{printf "%.2f\n", '${batch_size}'*1000/'${FPS}'}'`
+
+# 浠巘rain_$ASCEND_DEVICE_ID.log鎻愬彇Loss鍒皌rain_${CaseName}_loss.txt涓紝闇�瑕佹牴鎹ā鍨嬪瑙�
+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
+
+# 鏈�鍚庝竴涓凯浠oss鍊硷紝涓嶉渶瑕佷慨鏀�
+ActualLoss=`awk 'END {print}'  ${test_path_dir}/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt`
+
+# 鍏抽敭淇℃伅鎵撳嵃鍒�${CaseName}.log涓紝涓嶉渶瑕佷慨鏀�
+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
+echo "DeviceType = ${DeviceType}" >>  ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "CaseName = ${CaseName}" >>  ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "ActualFPS = ${ActualFPS}" >>  ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "TrainingTime = ${TrainingTime}" >>  ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
+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 d21159916e2bb9cfa7c7ad36a5234f1a48ac621c..0f259328c8890b63bac05668ee50b5d5de78a1c7 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
@@ -14,7 +14,7 @@ data_path=""
 # 璁粌epoch 90
 train_epochs=2
 # 鍔犺浇鏁版嵁杩涚▼鏁�
-workers=256
+workers=192
 device_id=0
 # 鍙傛暟鏍￠獙锛宒ata_path涓哄繀浼犲弬鏁帮紝鍏朵粬鍙傛暟鐨勫鍒犵敱妯″瀷鑷韩鍐冲畾锛涙澶勬柊澧炲弬鏁伴渶鍦ㄤ笂闈㈡湁瀹氫箟骞惰祴鍊�
 for para in $*