BMIP/scripts/maple/base2new_test_maple2.sh at main · LAMDA-NeSy/BMIP · GitHub

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#!/bin/bash

#cd ../..

# custom config
DATA="/home/lvsl/DATA/Data"
TRAINER=MaPLe

DATASET=$1
SEED=$2
DEVICE=$3
BEST=$4

CFG=vit_b16_c2_ep3_ctx1_dp9TT_warmup2_BZ2_V3
SHOTS=16
LOADEP=10
SUB=new


COMMON_DIR=${DATASET}/shots_${SHOTS}/${TRAINER}/${CFG}/seed${SEED}
MODEL_DIR=output/base2new/train_base/${COMMON_DIR}
DIR=output/base2new/test_${SUB}/${COMMON_DIR}
if [ -d "$DIR" ]; then
    echo "Evaluating model"
    echo "Results are available in ${DIR}. Resuming..."

    python train.py \
    --root ${DATA} \
    --seed ${SEED} \
    --trainer ${TRAINER} \
    --dataset-config-file configs/datasets/${DATASET}.yaml \
    --config-file configs/trainers/${TRAINER}/${CFG}.yaml \
    --output-dir ${DIR} \
    --model-dir ${MODEL_DIR} \
    --load-epoch ${LOADEP} \
    --device ${DEVICE} \
    --eval-only \
    DATASET.NUM_SHOTS ${SHOTS} \
    DATASET.SUBSAMPLE_CLASSES ${SUB}

else
    echo "Evaluating model"
    echo "Runing the first phase job and save the output to ${DIR}"

    python train.py \
    --root ${DATA} \
    --seed ${SEED} \
    --trainer ${TRAINER} \
    --dataset-config-file configs/datasets/${DATASET}.yaml \
    --config-file configs/trainers/${TRAINER}/${CFG}.yaml \
    --output-dir ${DIR} \
    --model-dir ${MODEL_DIR} \
    --load-epoch ${LOADEP} \
    --device ${DEVICE} \
    --eval-only \
    DATASET.NUM_SHOTS ${SHOTS} \
    DATASET.SUBSAMPLE_CLASSES ${SUB}
fi