An example:
python train_model.py -d mnist -m d2l -e 50 -b 128 -r 40
-d
: dataset in ['mnist', 'svhn', 'cifar-10', 'cifar-100']
-m
: model in ['ce', 'forward', 'backward', 'boot_hard', 'boot_soft', 'd2l']
-e
: epoch, -b
: batch size, -r
: noise rate in [0, 100]
for dataset in ['mnist']:
for noise_ratio in ['0', '20', '40', '60']:
args = parser.parse_args(['-d', dataset, '-m', 'd2l',
'-e', '50', '-b', '128',
'-r', noise_ratio])
main(args)
tensorflow, Keras, numpy, scipy, tqdm, sklearn, matplotlib