File size: 1,667 Bytes
0161e74 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 | #!/bin/sh
#SBATCH --time=8:00:00
#SBATCH --cpus-per-task=8
#SBATCH --array=1,2,4,5,7,8
#SBATCH --mem=48G
#SBATCH --qos=nopreemption
#SBATCH -p cpu
QUERY_PATH="query_list.txt"
query_name=$(sed -n "${SLURM_ARRAY_TASK_ID}p" $QUERY_PATH)
echo "processing ${query_name}"
DATASET="/scratch/ssd004/datasets/cellxgene/scb_strict/${query_name}/all_counts"
VOCAB_PATH="/scratch/ssd004/datasets/cellxgene/scFormer/scformer/tokenizer/default_census_vocab.json"
bash ~/.bashrc
NPROC=$SLURM_GPUS_ON_NODE
JOB_NAME="cellxgene_census_${QUERY_NAME}"
LOG_INTERVAL=2000
VALID_SIZE_OR_RATIO=0.03
MAX_LENGTH=1200
per_proc_batch_size=32
LAYERS=12
MODEL_SCALE=8
SAVE_DIR="/scratch/ssd004/datasets/cellxgene/profile_tmp"
# others, pancreas, lung, kidney, heart, blood
alias python_=~/.cache/pypoetry/virtualenvs/scformer-9yG_XnDJ-py3.9/bin/python
python_ -c "import torch; print(torch.version.cuda)"
python_ process_allcounts.py \
--data-source $DATASET \
--save-dir ${SAVE_DIR}/${JOB_NAME}-$(date +%b%d-%H-%M-%Y) \
--vocab-path ${VOCAB_PATH} \
--valid-size-or-ratio $VALID_SIZE_OR_RATIO \
--max-seq-len $MAX_LENGTH \
--batch-size $per_proc_batch_size \
--eval-batch-size $(($per_proc_batch_size * 2)) \
--nlayers $LAYERS \
--nheads 8 \
--embsize $((MODEL_SCALE * 64)) \
--d-hid $((MODEL_SCALE * 64)) \
--grad-accu-steps $((128 / $per_proc_batch_size)) \
--epochs 2 \
--lr 0.0001 \
--warmup-ratio-or-step 10000 \
--log-interval $LOG_INTERVAL \
--save-interval $(($LOG_INTERVAL * 3)) \
--trunc-by-sample \
--no-cls \
--no-cce \
--fp16 |
awk '{ print strftime("[%Y-%m-%d %H:%M:%S]"), $0; fflush(); }'
|