forked from mindspore-Ecosystem/mindspore
solve maskrcnn_mobilenetv1 scripts problems
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@ -178,7 +178,6 @@ Usage: sh run_standalone_train.sh [PRETRAINED_MODEL]
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# random threshold in data augmentation
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"keep_ratio": True,
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"flip_ratio": 0.5,
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"photo_ratio": 0.5,
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"expand_ratio": 1.0,
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"max_instance_count": 128, # max number of bbox for each image
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@ -265,7 +264,6 @@ Usage: sh run_standalone_train.sh [PRETRAINED_MODEL]
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"test_max_per_img": 100, # max number of instance
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"test_batch_size": 2, # batch size
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"rpn_head_loss_type": "CrossEntropyLoss", # loss type in rpn
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"rpn_head_use_sigmoid": True, # whether use sigmoid or not in rpn
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"rpn_head_weight": 1.0, # rpn head weight in loss
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"mask_thr_binary": 0.5, # mask threshold for in rcnn
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@ -275,7 +273,6 @@ Usage: sh run_standalone_train.sh [PRETRAINED_MODEL]
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"base_step": 58633, # bsae step in lr generator
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"total_epoch": 13, # total epoch in lr generator
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"warmup_step": 500, # warmp up step in lr generator
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"warmup_mode": "linear", # warmp up mode
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"warmup_ratio": 1/3.0, # warpm up ratio
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"sgd_momentum": 0.9, # momentum in optimizer
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@ -14,9 +14,9 @@
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# limitations under the License.
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# ============================================================================
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if [ $# != 2 ]
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if [ $# != 2 ] && [ $# != 1 ]
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then
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echo "Usage: sh run_train.sh [RANK_TABLE_FILE] [PRETRAINED_PATH]"
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echo "Usage: sh run_distribute_train.sh [RANK_TABLE_FILE] [PRETRAINED_PATH](optional)"
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exit 1
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fi
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@ -31,7 +31,11 @@ PATH1=$(get_real_path $1)
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PATH2=$2
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echo $PATH1
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echo $PATH2
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if [ $# == 2 ]
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then
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echo $PATH2
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fi
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if [ ! -f $PATH1 ]
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then
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@ -67,7 +71,16 @@ do
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cd ./train_parallel$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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taskset -c $cmdopt python train.py --do_train=True --device_id=$i --rank_id=$i --run_distribute=True --device_num=$DEVICE_NUM \
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--pre_trained=$PATH2 &> log &
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if [ $# == 2 ]
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then
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taskset -c $cmdopt python train.py --do_train=True --device_id=$i --rank_id=$i --run_distribute=True --device_num=$DEVICE_NUM \
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--pre_trained=$PATH2 &> log &
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fi
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if [ $# == 1 ]
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then
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taskset -c $cmdopt python train.py --do_train=True --device_id=$i --rank_id=$i --run_distribute=True --device_num=$DEVICE_NUM &> log &
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fi
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cd ..
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done
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@ -14,9 +14,9 @@
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# limitations under the License.
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# ============================================================================
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if [ $# != 1 ]
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if [ $# != 1 ] && [ $# != 0 ]
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then
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echo "Usage: sh run_standalone_train.sh [PRETRAINED_PATH]"
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echo "Usage: sh run_standalone_train.sh [PRETRAINED_PATH](optional)"
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exit 1
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fi
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@ -27,13 +27,11 @@ get_real_path(){
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echo "$(realpath -m $PWD/$1)"
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fi
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}
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PATH1=$(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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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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fi
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ulimit -u unlimited
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@ -53,5 +51,14 @@ cp -r ../src ./train
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cd ./train || exit
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echo "start training for device $DEVICE_ID"
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env > env.log
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python train.py --do_train=True --device_id=$DEVICE_ID --pre_trained=$PATH1 &> 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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fi
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if [ $# == 0 ]
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then
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python train.py --do_train=True --device_id=$DEVICE_ID &> log &
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fi
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cd ..
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@ -22,7 +22,6 @@ config = ed({
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"img_height": 768,
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"keep_ratio": True,
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"flip_ratio": 0.5,
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"photo_ratio": 0.5,
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"expand_ratio": 1.0,
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"max_instance_count": 128,
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@ -109,7 +108,6 @@ config = ed({
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"test_max_per_img": 100,
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"test_batch_size": 2,
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"rpn_head_loss_type": "CrossEntropyLoss",
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"rpn_head_use_sigmoid": True,
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"rpn_head_weight": 1.0,
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"mask_thr_binary": 0.5,
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@ -119,7 +117,6 @@ config = ed({
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"base_step": 58633,
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"total_epoch": 13,
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"warmup_step": 500,
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"warmup_mode": "linear",
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"warmup_ratio": 1/3.0,
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"sgd_momentum": 0.9,
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@ -131,7 +128,7 @@ config = ed({
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"pretrain_epoch_size": 0,
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"epoch_size": 12,
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"save_checkpoint": True,
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"save_checkpoint_epochs": 1,
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"save_checkpoint_epochs": 12,
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"keep_checkpoint_max": 12,
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"save_checkpoint_path": "./",
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