#!/bin/bash metrics="GDE" # "AC DoC IM GDE ATC-MC ATC-NE COT COTT-MC" data_path="./data/CIFAR-10" dataset="CIFAR-10" corruption_path="./data/CIFAR-10-C" n_test_samples=-1 n_val_samples=10000 batch_size=200 arch=resnet18 pretrained="False" model_seed=$1 ckpt_epoch=300 corruptions="brightness defocus_blur elastic_transform fog frost gaussian_blur gaussian_noise glass_blur impulse_noise jpeg_compression motion_blur pixelate saturate shot_noise snow spatter speckle_noise zoom_blur contrast" echo ${corruptions} for metric in ${metrics} do if [[ ${pretrained} == 'True' ]] then echo "pretrained model used" python run_estimation.py --pretrained --dataset ${dataset} --corruption clean --severity 0 --model_seed ${model_seed} --ckpt_epoch ${ckpt_epoch} --n_test_samples ${n_test_samples} --batch_size ${batch_size} --arch ${arch} --metric ${metric} --data_path ${data_path} --corruption_path ${corruption_path} python run_estimation.py --pretrained --dataset ${dataset} --corruption collection --subpopulation natural --severity 0 --model_seed ${model_seed} --ckpt_epoch ${ckpt_epoch} --n_test_samples ${n_test_samples} --batch_size ${batch_size} --arch ${arch} --metric ${metric} --data_path ${data_path} --corruption_path ${corruption_path} else echo "scratch model used" python run_estimation.py --dataset ${dataset} --corruption clean --severity 0 --model_seed ${model_seed} --ckpt_epoch ${ckpt_epoch} --n_test_samples ${n_test_samples} --batch_size ${batch_size} --arch ${arch} --metric ${metric} --data_path ${data_path} --corruption_path ${corruption_path} python run_estimation.py --dataset ${dataset} --corruption collection --subpopulation natural --severity 0 --model_seed ${model_seed} --ckpt_epoch ${ckpt_epoch} --n_test_samples ${n_test_samples} --batch_size ${batch_size} --arch ${arch} --metric ${metric} --data_path ${data_path} --corruption_path ${corruption_path} fi for corruption in ${corruptions} do for level in {1..5} do echo ${corruption} ${level} if [[ ${pretrained} == 'True' ]] then python run_estimation.py --pretrained --dataset ${dataset} --corruption ${corruption} --severity ${level} --model_seed ${model_seed} --ckpt_epoch ${ckpt_epoch} --n_test_samples ${n_test_samples} --batch_size ${batch_size} --arch ${arch} --metric ${metric} --data_path ${data_path} --corruption_path ${corruption_path} else python run_estimation.py --dataset ${dataset} --corruption ${corruption} --severity ${level} --model_seed ${model_seed} --ckpt_epoch ${ckpt_epoch} --n_test_samples ${n_test_samples} --batch_size ${batch_size} --arch ${arch} --metric ${metric} --data_path ${data_path} --corruption_path ${corruption_path} fi done done done