File size: 2,608 Bytes
b4b2877 | 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 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 | #!/bin/bash
# Scene Recognition (Exp1 v3) - Train 14 vols / Test 4 vols (no val)
# v23,v24 moved from val to train; v3 stays in test
# Part 1: 9 modality combos × 3 backbones = 27 jobs (early fusion)
# Part 2: 7 fusion methods × transformer × (3-core + all-5) = 14 jobs
# Total: 41 jobs
PYTHON=python
BASEDIR=${PULSE_ROOT}
SCRIPT=${BASEDIR}/experiments/train_exp1.py
OUTDIR=${BASEDIR}/results/exp1_v3
LOGDIR=${OUTDIR}/slurm_logs
mkdir -p $LOGDIR
COMMON="--epochs 100 --batch_size 16 --lr 1e-3 --weight_decay 1e-4 --hidden_dim 128 --downsample 5 --patience 15 --seed 42 --output_dir $OUTDIR"
MODS=("mocap" "emg" "eyetrack" "imu" "pressure" "mocap,emg,eyetrack" "mocap,emg,eyetrack,imu" "mocap,emg,eyetrack,pressure" "mocap,emg,eyetrack,imu,pressure")
MODELS=("cnn" "lstm" "transformer")
# Part 1: Modality ablation × 3 backbones
echo "=== Part 1: Modality Ablation (27 jobs) ==="
for mods in "${MODS[@]}"; do
mod_tag=$(echo $mods | tr ',' '-')
for model in "${MODELS[@]}"; do
sbatch \
-J "e1v3_${model}_${mod_tag}" \
-p gpuA800 \
--gres=gpu:1 \
-N 1 -n 1 \
--cpus-per-task=4 \
--mem=32G \
-t 2:00:00 \
-o "${LOGDIR}/${model}_${mod_tag}_early_%j.out" \
-e "${LOGDIR}/${model}_${mod_tag}_early_%j.err" \
--export=ALL \
--wrap="export PYTHONUNBUFFERED=1; cd ${BASEDIR}; $PYTHON $SCRIPT --model $model --modalities $mods --fusion early $COMMON"
echo " $model / $mods / early"
done
done
# Part 2: Fusion methods × transformer
FUSIONS=("late" "attention" "weighted_late" "gated_late" "stacking" "product" "moe")
FUSION_MODS=("mocap,emg,eyetrack" "mocap,emg,eyetrack,imu,pressure")
echo ""
echo "=== Part 2: Fusion Ablation (14 jobs) ==="
for fmods in "${FUSION_MODS[@]}"; do
fmod_tag=$(echo $fmods | tr ',' '-')
for fusion in "${FUSIONS[@]}"; do
sbatch \
-J "e1v3_tf_${fusion}" \
-p gpuA800 \
--gres=gpu:1 \
-N 1 -n 1 \
--cpus-per-task=4 \
--mem=32G \
-t 2:00:00 \
-o "${LOGDIR}/transformer_${fmod_tag}_${fusion}_%j.out" \
-e "${LOGDIR}/transformer_${fmod_tag}_${fusion}_%j.err" \
--export=ALL \
--wrap="export PYTHONUNBUFFERED=1; cd ${BASEDIR}; $PYTHON $SCRIPT --model transformer --modalities $fmods --fusion $fusion $COMMON"
echo " transformer / $fmods / $fusion"
done
done
echo ""
echo "Total: 41 jobs | Scene Recognition v3 | Train=14vols, Test=4vols"
echo "Results: $OUTDIR"
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