34 lines
1.1 KiB
Bash
34 lines
1.1 KiB
Bash
#!/usr/bin/env bash
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set -e
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set -x
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PARTITION=$1
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JOB_NAME=$2
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CFG=$3 # use cfgs under "configs/benchmarks/classification/imagenet/imagenet_*percent/"
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PRETRAIN=$4 # pretrained model
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PY_ARGS=${@:5}
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GPUS=${GPUS:-4} # in the standard setting, GPUS=4
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GPUS_PER_NODE=${GPUS_PER_NODE:-4}
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CPUS_PER_TASK=${CPUS_PER_TASK:-5}
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PORT=${PORT:-29500}
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SRUN_ARGS=${SRUN_ARGS:-""}
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# set work_dir according to config path and pretrained model to distinguish different models
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WORK_DIR="$(echo ${CFG%.*} | sed -e "s/configs/work_dirs/g")/$(echo $PRETRAIN | rev | cut -d/ -f 1 | rev)"
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PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \
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srun -p ${PARTITION} \
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--job-name=${JOB_NAME} \
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--gres=gpu:${GPUS_PER_NODE} \
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--ntasks=${GPUS} \
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--ntasks-per-node=${GPUS_PER_NODE} \
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--cpus-per-task=${CPUS_PER_TASK} \
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--kill-on-bad-exit=1 \
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${SRUN_ARGS} \
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python -u tools/train.py $CFG \
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--cfg-options model.backbone.init_cfg.type=Pretrained \
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model.backbone.init_cfg.checkpoint=$PRETRAIN \
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dist_params.port=$PORT \
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--work-dir $WORK_DIR --seed 0 --launcher="slurm" ${PY_ARGS}
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