diff --git a/TensorFlow/built-in/nlp/Transformer_ID0004_for_TensorFlow/test/train_full_1p.sh b/TensorFlow/built-in/nlp/Transformer_ID0004_for_TensorFlow/test/train_full_1p.sh
index a7ff6ecf74bc5020bd089c651a368d6b0cc76d27..b3a21a5cfea3241b94c1626c509e81300acd281e 100644
--- a/TensorFlow/built-in/nlp/Transformer_ID0004_for_TensorFlow/test/train_full_1p.sh
+++ b/TensorFlow/built-in/nlp/Transformer_ID0004_for_TensorFlow/test/train_full_1p.sh
@@ -195,12 +195,16 @@ 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
-FPS=`grep TimeHistory  $cur_path/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log|awk 'END {print $6}'`
+FPS=`grep "INFO:tensorflow:" $cur_path/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log|grep 'words/sec'|tr -d 'k'|awk 'END {print 8*1000*$NF}'`
 #打印，不需要修改
 echo "Final Performance images/sec : $FPS"
 
 #输出训练精度,需要模型审视修改
-train_accuracy=`grep train_accuracy $cur_path/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log|awk 'END {print $8}'|cut -c 1-5`
+bash inference.sh
+bash scripts/process_output.sh ${data_path}/newstest2014.tok.de ${data_path}/output-0603 ${data_path}/vocab.share
+perl ${data_path}/multi-bleu.perl ${data_path}/newstest2014.tok.de.forbleu < ${data_path}/output-0603.forbleu > result_bleu.txt
+cat result_bleu.txt >> $cur_path/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log
+train_accuracy=`grep "BLEU" $cur_path/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log|awk 'END {print $3}'|tr -d ','`
 #打印，不需要修改
 echo "Final Train Accuracy : ${train_accuracy}"
 echo "E2E Training Duration sec : $e2e_time"
@@ -209,7 +213,7 @@ echo "E2E Training Duration sec : $e2e_time"
 #训练用例信息，不需要修改
 BatchSize=${batch_size}
 DeviceType=`uname -m`
-CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'acc'
+CaseName=${Network}${name_bind}_bs${BatchSize}_${RANK_SIZE}'p'_'acc'
 
 ##获取性能数据
 #吞吐量，不需要修改
@@ -218,7 +222,7 @@ ActualFPS=${FPS}
 TrainingTime=`awk 'BEGIN{printf "%.2f\n",'${BatchSize}'*'${RANK_SIZE}'*1000/'${FPS}'}'`
 
 #从train_$ASCEND_DEVICE_ID.log提取Loss到train_${CaseName}_loss.txt中，需要根据模型审视
-grep train_loss $cur_path/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log|grep -v BatchTimestamp|awk '{print $10}'|sed 's/,//g'|sed '/^$/d' >> $cur_path/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt
+grep "INFO:tensorflow:" $cur_path/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log|grep 'loss'|awk '{print $3}'|sed 's/,//g'|sed '/^$/d' >> $cur_path/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt
 
 #最后一个迭代loss值，不需要修改
 ActualLoss=`awk 'END {print}' $cur_path/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt`