Med-AL-SSL/code/check_logs.py at master · marrlab/Med-AL-SSL · GitHub

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from options.train_options import get_arguments
from utils import set_model_name
import os

root = '/home/ahmad/thesis/med_active_learning/logs_final'
arguments = get_arguments()
files = os.listdir(root)


def main(args):
    args.dataset = 'isic'
    seeds = ['9999', '5555', '2323', '6666']
    name = set_model_name(args)

    not_founds = []

    for seed in seeds:
        found = False

        for file in files:
            file = f"{file.split('-')[1]}-{file.split('-')[2]}"

            if file == f'{name}-seed:{seed}':
                found = True

        if not found:
            print(f'{name}-seed:{seed}')
            not_founds.append(f'{name}-seed:{seed}')


if __name__ == '__main__':
    states = [
        ('active_learning', 'entropy_based', None, None, False, None),
        ('active_learning', 'mc_dropout', None, None, False, None),
        ('active_learning', 'augmentations_based', None, None, False, None),
        ('active_learning', 'least_confidence', None, None, False, None),
        ('active_learning', 'margin_confidence', None, None, False, None),
        ('active_learning', 'learning_loss', None, None, False, None),
        ('random_sampling', None, None, None, False, None),
        ('semi_supervised', None, 'simclr', None, False, None),
        ('semi_supervised', None, 'simclr_with_al', 'augmentations_based', False, None),
        ('semi_supervised', None, 'simclr_with_al', 'entropy_based', False, None),
        ('semi_supervised', None, 'simclr_with_al', 'mc_dropout', False, None),
        ('semi_supervised', None, 'simclr_with_al', 'least_confidence', False, None),
        ('semi_supervised', None, 'simclr_with_al', 'margin_confidence', False, None),
        ('semi_supervised', None, 'simclr_with_al', 'learning_loss', False, None),
        ('semi_supervised', None, 'auto_encoder', None, False, None),
        ('semi_supervised', None, 'auto_encoder_with_al', 'augmentations_based', False, None),
        ('semi_supervised', None, 'auto_encoder_with_al', 'entropy_based', False, None),
        ('semi_supervised', None, 'auto_encoder_with_al', 'mc_dropout', False, None),
        ('semi_supervised', None, 'auto_encoder_with_al', 'least_confidence', False, None),
        ('semi_supervised', None, 'auto_encoder_with_al', 'margin_confidence', False, None),
        ('semi_supervised', None, 'auto_encoder_with_al', 'learning_loss', False, None),
        ('semi_supervised', None, 'fixmatch', None, False, None),
        ('semi_supervised', None, 'fixmatch_with_al', 'augmentations_based', False, None),
        ('semi_supervised', None, 'fixmatch_with_al', 'entropy_based', False, None),
        ('semi_supervised', None, 'fixmatch_with_al', 'mc_dropout', False, None),
        ('semi_supervised', None, 'fixmatch_with_al', 'least_confidence', False, None),
        ('semi_supervised', None, 'fixmatch_with_al', 'margin_confidence', False, None),
        ('semi_supervised', None, 'fixmatch_with_al', 'learning_loss', False, None),
        ('semi_supervised', None, 'pseudo_label', None, False, None),
        ('semi_supervised', None, 'pseudo_label_with_al', 'augmentations_based', False, None),
        ('semi_supervised', None, 'pseudo_label_with_al', 'entropy_based', False, None),
        ('semi_supervised', None, 'pseudo_label_with_al', 'mc_dropout', False, None),
        ('semi_supervised', None, 'pseudo_label_with_al', 'least_confidence', False, None),
        ('semi_supervised', None, 'pseudo_label_with_al', 'margin_confidence', False, None),
        ('semi_supervised', None, 'pseudo_label_with_al', 'learning_loss', False, None),
        ('active_learning', 'entropy_based', None, None, True, None),
        ('active_learning', 'mc_dropout', None, None, True, None),
        ('active_learning', 'augmentations_based', None, None, True, None),
        ('active_learning', 'least_confidence', None, None, True, None),
        ('active_learning', 'margin_confidence', None, None, True, None),
        ('active_learning', 'learning_loss', None, None, True, None),
        ('random_sampling', None, None, None, True, None),
        ('semi_supervised', None, 'fixmatch', None, True, 'pretrained'),
        ('semi_supervised', None, 'fixmatch_with_al', 'augmentations_based', True, 'pretrained'),
        ('semi_supervised', None, 'fixmatch_with_al', 'entropy_based', True, 'pretrained'),
        ('semi_supervised', None, 'fixmatch_with_al', 'mc_dropout', True, 'pretrained'),
        ('semi_supervised', None, 'fixmatch_with_al', 'least_confidence', True, 'pretrained'),
        ('semi_supervised', None, 'fixmatch_with_al', 'margin_confidence', True, 'pretrained'),
        ('semi_supervised', None, 'fixmatch_with_al', 'learning_loss', True, 'pretrained'),
        ('semi_supervised', None, 'fixmatch', None, True, 'simclr'),
        ('semi_supervised', None, 'fixmatch_with_al', 'augmentations_based', True, 'simclr'),
        ('semi_supervised', None, 'fixmatch_with_al', 'entropy_based', True, 'simclr'),
        ('semi_supervised', None, 'fixmatch_with_al', 'mc_dropout', True, 'simclr'),
        ('semi_supervised', None, 'fixmatch_with_al', 'least_confidence', True, 'simclr'),
        ('semi_supervised', None, 'fixmatch_with_al', 'margin_confidence', True, 'simclr'),
        ('semi_supervised', None, 'fixmatch_with_al', 'learning_loss', True, 'simclr'),
        ('semi_supervised', None, 'fixmatch', None, True, 'autoencoder'),
        ('semi_supervised', None, 'fixmatch_with_al', 'augmentations_based', True, 'autoencoder'),
        ('semi_supervised', None, 'fixmatch_with_al', 'entropy_based', True, 'autoencoder'),
        ('semi_supervised', None, 'fixmatch_with_al', 'mc_dropout', True, 'autoencoder'),
        ('semi_supervised', None, 'fixmatch_with_al', 'least_confidence', True, 'autoencoder'),
        ('semi_supervised', None, 'fixmatch_with_al', 'margin_confidence', True, 'autoencoder'),
        ('semi_supervised', None, 'fixmatch_with_al', 'learning_loss', True, 'autoencoder'),
        ('semi_supervised', None, 'pseudo_label', None, True, 'pretrained'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'augmentations_based', True, 'pretrained'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'entropy_based', True, 'pretrained'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'mc_dropout', True, 'pretrained'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'least_confidence', True, 'pretrained'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'margin_confidence', True, 'pretrained'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'learning_loss', True, 'pretrained'),
        ('semi_supervised', None, 'pseudo_label', None, True, 'simclr'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'augmentations_based', True, 'simclr'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'entropy_based', True, 'simclr'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'mc_dropout', True, 'simclr'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'least_confidence', True, 'simclr'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'margin_confidence', True, 'simclr'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'learning_loss', True, 'simclr'),
        ('semi_supervised', None, 'pseudo_label', None, True, 'autoencoder'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'augmentations_based', True, 'autoencoder'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'entropy_based', True, 'autoencoder'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'mc_dropout', True, 'autoencoder'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'least_confidence', True, 'autoencoder'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'margin_confidence', True, 'autoencoder'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'learning_loss', True, 'autoencoder'),
        ('active_learning', 'badge', None, None, False, None),
        ('semi_supervised', None, 'simclr_with_al', 'badge', False, None),
        ('semi_supervised', None, 'auto_encoder_with_al', 'badge', False, None),
        ('semi_supervised', None, 'fixmatch_with_al', 'badge', False, None),
        ('semi_supervised', None, 'pseudo_label_with_al', 'badge', False, None),
        ('active_learning', 'badge', None, None, True, None),
        ('semi_supervised', None, 'fixmatch_with_al', 'badge', True, 'pretrained'),
        ('semi_supervised', None, 'fixmatch_with_al', 'badge', True, 'simclr'),
        ('semi_supervised', None, 'fixmatch_with_al', 'badge', True, 'autoencoder'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'badge', True, 'pretrained'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'badge', True, 'simclr'),
        ('semi_supervised', None, 'pseudo_label_with_al', 'badge', True, 'autoencoder'),
    ]

    for (m, u, s, us, p, init) in states:
        arguments.weak_supervision_strategy = m
        arguments.uncertainty_sampling_method = u
        arguments.semi_supervised_method = s
        arguments.semi_supervised_uncertainty_method = us
        arguments.load_pretrained = p
        arguments.semi_supervised_init = init
        main(args=arguments)