cue_docker_gpu.slrm

#!/bin/bash
#$ -cwd
#$ -S /bin/bash
#SBATCH -p k40                                             
#SBATCH --gres=gpu:k40:1
#SBATCH --error=/scratch.global/neis/bakeoff/logs/%x_%A_%a.e
#SBATCH --output=/scratch.global/neis/bakeoff/logs/%x_%A_%a.o
#SBATCH --mail-type=FAIL
#SBATCH --mail-user=neis@umn.edu
#SBATCH --time=4:00:00
#SBATCH -n 1
#SBATCH -N 1
#SBATCH --mem 60G


set -e

# keep track of the last executed command
trap 'last_command=$current_command; current_command=$BASH_COMMAND' DEBUG
# echo an error message before exiting
trap 'echo "\"${last_command}\" command filed with exit code $?."' EXIT
SECONDS=0

refDir=/home/pankrat2/public/bin/ref/
cramDir=/scratch.global/neis/bakeoff/${GROUP}/cram/
outDir=/scratch.global/neis/bakeoff/cue/${SAMPLE}/
mkdir -p $outDir
cd $outDir

# generate data config file
echo -e "bam: \"${cramDir}${SAMPLE}.recab.cram\"\n\
fai: \"${refDir}GRCh38_full_analysis_set_plus_decoy_hla.fai\"\n\
chr_names: null\n\
logging_level: \"INFO\"" > call_data.yaml

# generate model config file
echo -e "model_path: \"/app/cue/data/models/cue.v2.pt\"\n\
gpu_ids: [0]\n\
n_jobs_per_gpu: 1024\n\
n_cpus: 10\n\
report_interval: 100\n\
batch_size: 16" > call_model.yaml

echo "Running Cue on sample ${SAMPLE} starting at $(date)"
singularity run --pwd "${outDir}" \
--bind "$refDir" \
--bind "$cramDir" \
--bind "$outDir" \
--tmpdir="/scratch.global/neis/tmp" \
"docker://ghcr.io/pankratzlab/cue:master" \
python3 /app/cue/engine/call.py --data_config call_data.yaml --model_config call_model.yaml

ELAPSED="Elapsed: $(($SECONDS / 3600))hrs $((($SECONDS / 60) % 60))min $(($SECONDS % 60))sec"
echo $ELAPSED