diff --git a/model_zoo/official/cv/deeplabv3/README.md b/model_zoo/official/cv/deeplabv3/README.md index 179793a3f7..0f897d6524 100644 --- a/model_zoo/official/cv/deeplabv3/README.md +++ b/model_zoo/official/cv/deeplabv3/README.md @@ -5,8 +5,7 @@ This is an example of training DeepLabV3 with PASCAL VOC 2012 dataset in MindSpo ## Requirements - Install [MindSpore](https://www.mindspore.cn/install/en). -- Download the VOC 2012 dataset for training. -- We need to run `./src/remove_gt_colormap.py` to remove the label colormap. +- Download the VOC 2012 dataset for training. ``` bash python remove_gt_colormap.py --original_gt_folder GT_FOLDER --output_dir OUTPUT_DIR diff --git a/model_zoo/official/cv/deeplabv3/scripts/run_distribute_train.sh b/model_zoo/official/cv/deeplabv3/scripts/run_distribute_train.sh index 4dcd8d9768..0d746c795c 100644 --- a/model_zoo/official/cv/deeplabv3/scripts/run_distribute_train.sh +++ b/model_zoo/official/cv/deeplabv3/scripts/run_distribute_train.sh @@ -26,6 +26,7 @@ DATA_DIR=$2 export MINDSPORE_HCCL_CONFIG_PATH=$1 export RANK_TABLE_FILE=$1 export RANK_SIZE=8 +export DEVICE_NUM=8 PATH_CHECKPOINT="" if [ $# == 3 ] then @@ -37,11 +38,13 @@ avg_core_per_rank=`expr $cores \/ $RANK_SIZE` core_gap=`expr $avg_core_per_rank \- 1` echo "avg_core_per_rank" $avg_core_per_rank echo "core_gap" $core_gap -for((i=0;i