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run_moodcat.sh
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run_moodcat.sh
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#!/bin/bash
set -x
export CUBLAS_WORKSPACE_CONFIG=:16:8
PARAMS="--dataset CIFAR10 --parallel --batch_size 384 --which_best FID \
--num_D_steps 1 --G_lr 5e-5 --D_lr 2e-4 \
--D_B2 0.999 --G_B2 0.999 --G_attn 0 --D_attn 0 --G_ortho 0.0 \
--G_init ortho --D_init ortho --G_ch 32 --D_ch 32 --test_every 10000 \
--save_every 8000 --num_best_copies 0 --num_save_copies 0 --seed 99 \
--sample_every 8000 --G_eval_mode --id imagenet100_unet_noatt_cutmix_cons --gpus 0,1,2,3,4,5,6,7 \
--ema --use_ema --accumulate_stats --num_standing_accumulations 100 \
--unet_mixup --slow_mixup --full_batch_mixup --consistency_loss_and_augmentation --warmup_epochs 200 \
--base_root ./results --data_folder ./dataset"
# ################## TEST for all metric in benchmark ######################
# for DT in "LSUN" "SVHN" "CIFAR100" "Places365" "Texture" "Tiny_imagenet"; do
# for DET in "8 9 89"; do
# python -u mcoodcat_on_scood.py ${PARAMS} \
# --ood_dataset ${DT} --test_detector ${DET} --ind_dataset cifar10 \
# | tee -a results/cifar10_89.log
# done
# done
# for DT in "SVHN" "CIFAR10" "LSUN" "Places365" "Texture" "Tiny_imagenet"; do
# for DET in "8 9 89"; do
# python -u mcoodcat_on_scood.py ${PARAMS} \
# --ood_dataset ${DT} --test_detector ${DET} --ind_dataset cifar100 \
# | tee -a results/cifar100_89.log
# done
# done
#################### TEST for different mask style ######################
for MASK in "random" "high_fix" "low_fix" "board" "shuffle" "zero_mask" "board0.3"; do
for DET in "5 8"; do
for DT in "CIFAR100"; do
python -u mcoodcat_ablation.py ${PARAMS} --ood_dataset ${DT} \
--test_detector ${DET} --ind_dataset cifar10 \
--mask_method ${MASK} | tee -a results/cifar10_100_masking.log
done
done
done
#################### TEST for Overhead ############################
python -u mcoodcat_overhead.py ${PARAMS} --ood_dataset "CIFAR10" \
--test_detector 5 8 --ind_dataset cifar100 | tee -a results/overhead.log