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sbatch_moco_train_local.sh
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/
sbatch_moco_train_local.sh
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#!/bin/bash
#SBATCH --partition=deep
#SBATCH --nodes=1
#SBATCH --cpus-per-task=4
#SBATCH --mem=32000
# only use the following on partition with GPUs
#SBATCH --gres=gpu:1
#SBATCH --job-name="densenet121"
#SBATCH --output=exp_logs/densenet121-%j.out
# only use the following if you want email notification
####SBATCH --mail-user=youremailaddress
####SBATCH --mail-type=ALL
# list out some useful information
echo "SLURM_JOBID="$SLURM_JOBID
echo "SLURM_JOB_NODELIST"=$SLURM_JOB_NODELIST
echo "SLURM_NNODES"=$SLURM_NNODES
echo "SLURMTMPDIR="$SLURMTMPDIR
echo "working directory = "$SLURM_SUBMIT_DIR
# sample job
NPROCS=`sbatch --nodes=${SLURM_NNODES} bash -c 'hostname' |wc -l`
echo NPROCS=$NPROCS
cd ../moco; python main_moco.py -a densenet121 \
--lr 1e-4 --batch-size 16 \
--world-size 1 --rank 0 \
--mlp --moco-t 0.2 \
--dist-url 'tcp://localhost:10001' --multiprocessing-distributed \
--aug-setting chexpert --rotate --maintain-ratio \
--train_data data/full_train \
--exp-name densenet121
# done
echo "Done"