diff --git a/TensorFlow/contrib/cv/FQ-GAN_ID1117_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/contrib/cv/FQ-GAN_ID1117_for_TensorFlow/test/train_performance_1p.sh
new file mode 100644
index 0000000000000000000000000000000000000000..1fc6c1b610cb4df0eab41530748ffc1d3ff94e1d
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+++ b/TensorFlow/contrib/cv/FQ-GAN_ID1117_for_TensorFlow/test/train_performance_1p.sh
@@ -0,0 +1,181 @@
+#!/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 <args>"
+    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=1
+
+if [ x"${modelarts_flag}" != x ];
+then
+    python3.7 main.py \
+        --dataset=${data_path}/dataset/selfie2anime \
+        --phase='train' \
+        --test_train=True \
+        --quant=True \
+        --epoch=100 \
+        --iteration=10000 >${print_log} 2>&1
+
+else
+    python3.7 main.py \
+        --dataset=${data_path}/dataset/selfie2anime \
+        --phase='train' \
+        --test_train=True \
+        --quant=True \
+        --checkpoint_dir=${output_path}/checkpoint \
+        --result_dir=${output_path}/results \
+        --log_dir=${output_path}/logs \
+        --sample_dir=${output_path}/samples \
+        --epoch=1 \
+        --iteration=10000 >${print_log} 2>&1
+fi
+
+# 性能相关数据计算
+Time1=`grep "time:" ${print_log} | awk '{print $7}' | head -n 1`
+Time2=`grep "time:" ${print_log} | awk '{print $7}' | awk '{sum+=$1} END {print sum}'`
+TrainingTime=`awk 'BEGIN{printf "%.2f\n", '\(${Time2}-${Time1}\)'/'10000'}'`
+FPS=`awk 'BEGIN{printf "%.2f\n", '${batch_size}'/'${TrainingTime}'}'`
+
+# 精度相关数据计算
+train_accuracy=`grep "d_loss:" ${print_log} | tail -n +2 | awk '{print $9}' | tr -d "," | awk '{sum+=$1} END {print sum/NR}'`
+# 提取所有loss打印信息
+grep "d_loss:" ${print_log} | tail -n +2 | awk '{print $9}' | tr -d "," > ./test/output/${ASCEND_DEVICE_ID}/my_output_loss.txt
+
+#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 : $TrainingTime"
+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 = ${TrainingTime}" >> $cur_path/output/$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
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