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run_uq_baselines.sh
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run_uq_baselines.sh
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#!/bin/bash
# -------------------------
# R-MNIST
# -------------------------
for seed in 6 12 13 523 972394; do
python uq.py --data_root ~/Datasets --benchmark R-MNIST --model LeNet --models_root models --method map --model_seed $seed
python uq.py --data_root ~/Datasets --benchmark R-MNIST --model LeNet --models_root models --method ensemble --nr_components 5 --model_seed $seed
python uq.py --data_root ~/Datasets --benchmark R-MNIST --model LeNet-BBB-flipout --models_root models/bbb/flipout --method bbb --model_seed $seed
python uq.py --data_root ~/Datasets --benchmark R-MNIST --model LeNet-CSGHMC --models_root models/csghmc --method csghmc --model_seed $seed
done
# -------------------------
# CIFAR-10-C
# -------------------------
for seed in 6 12 13 523 972394; do
python uq.py --data_root ~/Datasets/alt --benchmark CIFAR-10-C --model WRN16-4 --models_root models/wrn16_4_cifar10 --method map --model_seed $seed
python uq.py --data_root ~/Datasets/alt --benchmark CIFAR-10-C --model WRN16-4 --models_root models/wrn16_4_cifar10 --method ensemble --nr_components 5 --model_seed $seed
python uq.py --data_root ~/Datasets/alt --benchmark CIFAR-10-C --model WRN16-4-BBB-flipout --models_root models/bbb/flipout --method bbb --model_seed $seed
python uq.py --data_root ~/Datasets/alt --benchmark CIFAR-10-C --model WRN16-4-CSGHMC --models_root models/csghmc --method csghmc --model_seed $seed
done
#-------------------------
# MNIST OOD DETECTION
#-------------------------
for seed in 6 12 13 523 972394; do
python uq.py --data_root ~/Datasets --benchmark MNIST-OOD --model LeNet --models_root models --method map --model_seed $seed
python uq.py --data_root ~/Datasets --benchmark MNIST-OOD --model LeNet --models_root models --method ensemble --nr_components 5 --model_seed $seed
python uq.py --data_root ~/Datasets --benchmark MNIST-OOD --model LeNet-BBB-flipout --models_root models/bbb/flipout --method bbb --model_seed $seed
python uq.py --data_root ~/Datasets --benchmark MNIST-OOD --model LeNet-CSGHMC --models_root models/csghmc --method csghmc --model_seed $seed
done
#-------------------------
# CIFAR-10 OOD DETECTION
#-------------------------
for seed in 6 12 13 523 972394; do
python uq.py --data_root ~/Datasets --benchmark CIFAR-10-OOD --model WRN16-4 --models_root models --method map --model_seed $seed
python uq.py --data_root ~/Datasets --benchmark CIFAR-10-OOD --model WRN16-4 --models_root models --method ensemble --nr_components 5 --model_seed $seed
python uq.py --data_root ~/Datasets --benchmark CIFAR-10-OOD --model WRN16-4-BBB-flipout --models_root models/bbb/flipout --method bbb --model_seed $seed
python uq.py --data_root ~/Datasets --benchmark CIFAR-10-OOD --model WRN16-4-CSGHMC --models_root models/csghmc --method csghmc --model_seed $seed
done
#-------------------------
# SWAG
#-------------------------
python uq.py --data_root ~/Datasets --benchmark MNIST-OOD --model LeNet --models_root models --method swag --n_samples 30 --seed 711 --model_seed 6
python uq.py --data_root ~/Datasets --benchmark CIFAR-10-OOD --model WRN16-4 --models_root models --method swag --n_samples 30 --seed 711 --model_seed 6