experiments/slurm/run_pred_cls3.sh

#!/bin/bash
# Action Prediction Round 3: 8 coarse classes + prev action label + hidden_dim=128
# Transition baseline: acc=0.31 F1w=0.25 — target: beat this with sensor+prev_action
# Total: 9 jobs

PYTHON=python
BASEDIR=${PULSE_ROOT}
TRAIN_SCRIPT=${BASEDIR}/experiments/tasks/train_pred_cls.py
OUTDIR=${BASEDIR}/results/pred_cls3
LOGDIR=${OUTDIR}/slurm_logs
mkdir -p $LOGDIR

COMMON="--coarse --use_prev_action --epochs 80 --batch_size 32 --lr 1e-3 --weight_decay 1e-4 --hidden_dim 128 --downsample 5 --patience 20 --seed 42 --augment --noise_std 0.1 --time_mask_ratio 0.1 --label_smoothing 0.1 --output_dir $OUTDIR --window_sec 15.0"

MODS=("imu" "emg" "mocap" "emg,imu" "mocap,imu" "mocap,emg,imu" "mocap,emg,eyetrack" "mocap,emg,eyetrack,imu" "mocap,emg,eyetrack,imu,pressure")

for mods in "${MODS[@]}"; do
    mod_tag=$(echo $mods | tr ',' '-')
    sbatch \
        -J "pcls3_${mod_tag}" \
        -p gpuA800 \
        --gres=gpu:1 \
        -N 1 -n 1 \
        --cpus-per-task=4 \
        --mem=32G \
        -t 2:00:00 \
        -o "${LOGDIR}/${mod_tag}_%j.out" \
        -e "${LOGDIR}/${mod_tag}_%j.err" \
        --export=ALL \
        --wrap="export PYTHONUNBUFFERED=1; cd ${BASEDIR}; $PYTHON $TRAIN_SCRIPT --modalities $mods $COMMON"
    echo "Submitted: $mods"
done

echo ""
echo "Total: 9 jobs | 8 coarse + prev_action | hidden_dim=128"
echo "Baseline to beat: majority transition F1w=0.25"
echo "Results: $OUTDIR"