diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_8p.sh b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_8p.sh index 566ebe837d4957b8f12d30bb94e691d92fe4aeb4..3d86d6562e771b580f489c8f0506e50242de7ce6 100644 --- a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_8p.sh +++ b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_8p.sh @@ -68,7 +68,7 @@ python3 bootstrap.py --work_dir=$cur_path/estimator_working_dir --export_path=$c wait export ASCEND_DEVICE_ID=0 -export RANK_SIZE=8 +export RANK_SIZES=8 #export RANK_TABLE_FILE="${cur_path}/test/8p.json" export JOB_ID=10086 @@ -130,9 +130,9 @@ BatchSize=${batch_size} DeviceType=`uname -m` #用例名称,自动获取 if [[ $precision_mode == "must_keep_origin_dtype" ]];then - CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'fp32'_'perf' + CaseName=${Network}_bs${BatchSize}_${RankSize}'p'_'fp32'_'perf' else - CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'perf' + CaseName=${Network}_bs${BatchSize}_${RankSize}'p'_'perf' fi #获取性能 TrainingTime=`grep "tensorflow:global_step/sec" $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log|awk 'END {print $2}'`