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04c2975 | 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 | #!/bin/bash
#SBATCH --job-name=refit-seed-array
#SBATCH --partition=dgx-b200
#SBATCH --gpus=1
#SBATCH --cpus-per-task=10
#SBATCH --mem=100G
#SBATCH --time=12:00:00
#SBATCH --output=%x_%A_%a.out
#SBATCH --array=0-4 # 5 seeds → indices 0..4
HOME_LOC=~/
SCRIPT_LOC=$HOME_LOC/PeptiVerse/training_classifiers
DATA_LOC=$HOME_LOC/PeptiVerse/training_data_cleaned
# ── Configure per submission ──────────────────────────────────────────
OBJECTIVE='permeability_pampa' # nf / solubility / hemolysis / permeability_penetrance/ permeability_pampa / permeability_caco2
WT='chemberta' # wt / smiles / chemberta / peptideclm
MODEL_TYPE='mlp' # mlp / cnn / transformer
DATA_FILE="hemo_${WT}_with_embeddings_unpooled" # nf / sol/ hemo / perm / pampa/ caco2
# Points to the directory where Optuna already saved best_model.pt
BASE_OUT_DIR="${SCRIPT_LOC}/${OBJECTIVE}/${MODEL_TYPE}_${WT}"
DATASET_PATH="${DATA_LOC}/permeability_${WT}/${DATA_FILE}"
# ────────────────────────────────────────────────────────────────────────────
SEEDS=(1986 42 0 123 12345)
SEED=${SEEDS[$SLURM_ARRAY_TASK_ID]}
LOG_LOC=$SCRIPT_LOC/src_bash/logs
mkdir -p $LOG_LOC
DATE=$(date +%m_%d)
cd $SCRIPT_LOC
echo "Running seed=$SEED model=$MODEL_TYPE objective=$OBJECTIVE wt=$WT"
START_TIME=$(date +%s%N)
python -u refit_nn_seed.py \
--dataset_path "${DATASET_PATH}" \
--base_out_dir "${BASE_OUT_DIR}" \
--model "${MODEL_TYPE}" \
--seed "${SEED}" \
> "${LOG_LOC}/${DATE}_refit_${MODEL_TYPE}_${OBJECTIVE}_${WT}_seed${SEED}.log" 2>&1
END_TIME=$(date +%s%N)
ELAPSED_S=$(( (END_TIME - START_TIME) / 1000000000 ))
echo "Seed $SEED done at $(date) — wall clock: ${ELAPSED_S}s"
echo "{\"model\": \"${MODEL_TYPE}\", \"objective\": \"${OBJECTIVE}\", \"wt\": \"${WT}\", \"seed\": ${SEED}, \"wall_s\": ${ELAPSED_S}}" \
>> "${LOG_LOC}/${DATE}_wall_clock_refit.jsonl"
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