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example train.sh
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11
src/train.sh
11
src/train.sh
@@ -3,8 +3,11 @@ export MXNET_CPU_WORKER_NTHREADS=24
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export MXNET_CUDNN_AUTOTUNE_DEFAULT=0
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export MXNET_ENGINE_TYPE=ThreadedEnginePerDevice
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DATA_DIR=/opt/jiaguo/faces_normed
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CUDA_VISIBLE_DEVICES='4,5,6,7' python -u train_softmax.py --data-dir $DATA_DIR --network 'm29' --patch '0_0_96_112_0' --loss-type 0 --lr 0.1 --prefix '../model/softmax' --verbose 2000 --per-batch-size 128 > sx_m29.log 2>&1 &
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#CUDA_VISIBLE_DEVICES='0,1,2,3' python -u train_softmax.py --data-dir $DATA_DIR --network 'm29' --patch '0_0_96_112_0' --loss-type 1 --lr 0.1 --prefix '../model/spherem' --verbose 2000 --per-batch-size 224 --lr-steps '60000,80000,90000' > spm_m29.log 2>&1 &
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DATA_DIR=/opt/jiaguo/faces_vgg_112x112
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JOB=softmax1e3
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MODELDIR="../model-$JOB"
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mkdir -p "$MODELDIR"
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PREFIX="$MODELDIR/model"
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LOGFILE="$MODELDIR/log"
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CUDA_VISIBLE_DEVICES='0,1,2,3' python -u train_softmax.py --data-dir $DATA_DIR --network 'r49' --loss-type 0 --lr 0.1 --prefix "$PREFIX" --per-batch-size 128 --image-size '112,112' --version-input 1 --version-output E --version-unit 3 > "$LOGFILE" 2>&1 &
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