forked from OSSInnovation/mindspore
!3816 If not set pretrained model,we should not be allowed to run training tasks
Merge pull request !3816 from zhouyuanshen/master
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commit
e01036f6ca
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@ -94,7 +94,7 @@ sh run_standalone_train.sh [PRETRAINED_MODEL]
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```
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> Rank_table.json which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
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> As for PRETRAINED_MODEL,if not set, the model will be trained from the very beginning.Ready-made pretrained_models are not available now. Stay tuned.
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> As for PRETRAINED_MODEL,it should be a ResNet50 checkpoint that trained over ImageNet2012. Ready-made pretrained_models are not available now. Stay tuned.
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#### Result
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@ -125,7 +125,7 @@ sh run_eval.sh [VALIDATION_JSON_FILE] [CHECKPOINT_PATH]
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#### Result
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Inference result will be stored in the example path, whose folder name is "infer". Under this, you can find result like the followings in log.
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Inference result will be stored in the example path, whose folder name is "eval". Under this, you can find result like the followings in log.
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```
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Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.360
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@ -14,7 +14,7 @@
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# limitations under the License.
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# ============================================================================
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if [ $# -lt 1 ] || [ $# -gt 2 ]
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if [ $# -ne 2 ]
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then
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echo "Usage: sh run_train.sh [RANK_TABLE_FILE] [PRETRAINED_PATH]"
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exit 1
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@ -37,15 +37,12 @@ then
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exit 1
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fi
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if [ $# == 2 ]
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then
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PATH2=$(get_real_path $2)
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echo $PATH2
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if [ ! -f $PATH2 ]
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then
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echo "error: PRETRAINED_PATH=$PATH2 is not a file"
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exit 1
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fi
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PATH2=$(get_real_path $2)
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echo $PATH2
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if [ ! -f $PATH2 ]
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then
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echo "error: PRETRAINED_PATH=$PATH2 is not a file"
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exit 1
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fi
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ulimit -u unlimited
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@ -65,11 +62,6 @@ do
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cd ./train_parallel$i || exit
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echo "start training for rank $RANK_ID, device $DEVICE_ID"
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env > env.log
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if [ $# == 2 ]
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then
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python train.py --do_train=True --device_id=$i --rank_id=$i --run_distribute=True --device_num=$DEVICE_NUM --pre_trained=$PATH2 &> log &
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else
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python train.py --do_train=True --device_id=$i --rank_id=$i --run_distribute=True --device_num=$DEVICE_NUM &> log &
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fi
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python train.py --do_train=True --device_id=$i --rank_id=$i --run_distribute=True --device_num=$DEVICE_NUM --pre_trained=$PATH2 &> log &
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cd ..
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done
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@ -14,7 +14,7 @@
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# limitations under the License.
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# ============================================================================
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if [ $# -gt 1 ]
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if [ $# -ne 1 ]
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then
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echo "Usage: sh run_standalone_train.sh [PRETRAINED_PATH]"
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exit 1
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@ -28,16 +28,13 @@ get_real_path(){
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fi
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}
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if [ $# == 1 ]
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then
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PATH1=$(get_real_path $1)
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echo $PATH1
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PATH1=$(get_real_path $1)
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echo $PATH1
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if [ ! -f $PATH1 ]
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then
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echo "error: PRETRAINED_PATH=$PATH1 is not a file"
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exit 1
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fi
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if [ ! -f $PATH1 ]
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then
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echo "error: PRETRAINED_PATH=$PATH1 is not a file"
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exit 1
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fi
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ulimit -u unlimited
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@ -57,10 +54,5 @@ cp -r ../src ./train
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cd ./train || exit
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echo "start training for device $DEVICE_ID"
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env > env.log
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if [ $# == 1 ]
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then
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python train.py --do_train=True --device_id=$DEVICE_ID --pre_trained=$PATH1 &> log &
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else
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python train.py --do_train=True --device_id=$DEVICE_ID &> log &
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fi
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python train.py --do_train=True --device_id=$DEVICE_ID --pre_trained=$PATH1 &> log &
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cd ..
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