model-selection

#!/bin/bash

VALIDATION_RESULT=0
BEST=0
VAL_KEY=val_acc
# Uncomment the following lines for regression tasks (i.e, esol)
# BEST=10000
# VAL_KEY=val_error

mkdir runs/$1 2> /dev/null
touch runs/$1/best

for LR in 0.005 0.001 0.0005 0.0001
do
    for BS in 20 60 120
    do
        for HS in 32 64 128 256
        do
            SEED=$RANDOM
            EXPERIMENT="ADAM_LR_${LR}_BS_${BS}_HS_${HS}"
            echo "lr: ${LR} hidden_size: ${HS} batch_size: ${BS} seed: ${SEED}"
            python train_dgn.py $1 $EXPERIMENT --lr $LR --hidden-size $HS --batch-size $BS --dropout 0.1 --epochs 100 --seed $SEED


            VALIDATION_RESULT=`cat runs/$1/$EXPERIMENT/best_result.json | python3 -c "import sys, json; print(json.load(sys.stdin)['$VAL_KEY'])"`

            echo $VALIDATION_RESULT
            # Uncomment the following line for regression tasks
            # if echo $VALIDATION_RESULT $BEST | awk '{exit !( $1 < $2)}'; then
            if echo $VALIDATION_RESULT $BEST | awk '{exit !( $1 > $2)}'; then

                echo "NEW BEST"
                BEST=$VALIDATION_RESULT
                echo $EXPERIMENT > runs/$1/best
            fi

            echo "--------------------DONE------------------------"
        done
    done
done