File size: 1,264 Bytes
178d33b | 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 | #!/bin/bash
# sh scripts/ood/react/cifar10_test_ood_react.sh
# GPU=1
# CPU=1
# node=36
# jobname=openood
PYTHONPATH='.':$PYTHONPATH \
#srun -p dsta --mpi=pmi2 --gres=gpu:${GPU} -n1 \
#--cpus-per-task=${CPU} --ntasks-per-node=${GPU} \
#--kill-on-bad-exit=1 --job-name=${jobname} -w SG-IDC1-10-51-2-${node} \
python main.py \
--config configs/datasets/cifar10/cifar10.yml \
configs/datasets/cifar10/cifar10_ood.yml \
configs/networks/react_net.yml \
configs/pipelines/test/test_ood.yml \
configs/preprocessors/base_preprocessor.yml \
configs/postprocessors/react.yml \
--network.pretrained False \
--network.backbone.name resnet18_32x32 \
--network.backbone.pretrained True \
--network.backbone.checkpoint 'results/cifar10_resnet18_32x32_base_e100_lr0.1_default/s0/best.ckpt' \
--num_workers 8 \
--mark fixed_0
############################################
# alternatively, we recommend using the
# new unified, easy-to-use evaluator with
# the example script scripts/eval_ood.py
# especially if you want to get results from
# multiple runs
python scripts/eval_ood.py \
--id-data cifar10 \
--root ./results/cifar10_resnet18_32x32_base_e100_lr0.1_default \
--postprocessor react \
--save-score --save-csv
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