def run(title, data_seed, **kwargs): print('run title: %s', title) ngpu = 1 main.args = parse_dict_args(**kwargs) context = RunContext(__file__, kwargs['consistency'], kwargs['epochs'], kwargs['labels']) main.main(context)
def run(title, base_batch_size, base_labeled_batch_size, base_lr, n_labels, data_seed, **kwargs): LOG.info('run title: %s, data seed: %d', title, data_seed) ngpu = torch.cuda.device_count() assert ngpu > 0, "Expecting at least one GPU, found none." adapted_args = { 'batch_size': base_batch_size * ngpu, 'labeled_batch_size': base_labeled_batch_size * ngpu, 'lr': base_lr * ngpu, 'labels': 'data-local/labels/cifar10/{}_balanced_labels/{:02d}.txt'.format( n_labels, data_seed), 'data_seed': data_seed, } context = RunContext(__file__, "{}_{}".format(n_labels, data_seed)) logfile = "{}/{}.log".format(context.result_dir, 'output') fh = logging.FileHandler(logfile) LOG.addHandler(fh) LOG.info('run title: %s, data seed: %d', title, data_seed) main.args = parse_dict_args(LOG, **adapted_args, **kwargs) main.main(context, LOG) LOG.info('Run finished, closing logfile.') LOG.removeHandler(fh)
def run(title, base_batch_size, base_labeled_batch_size, base_lr, data_seed, **kwargs): LOG.info('run title: %s', title) ngpu = 1 main.args = parse_dict_args(**kwargs) context = RunContext(__file__, args.consistency, args.epochs, args.labels) main.main(context)
def parse_parameters(title, base_batch_size, base_labeled_batch_size, base_lr, n_labels, data_seed, **kwargs): ngpu = torch.cuda.device_count() adapted_args = { 'batch_size': base_batch_size * ngpu, 'labeled_batch_size': base_labeled_batch_size * ngpu, 'lr': base_lr * ngpu, 'labels': 'data-local/labels/cifar10/{}_balanced_labels/{:02d}.txt'.format(n_labels, data_seed), } # print(adapted_args) args = parse_dict_args(**adapted_args, **kwargs) return args
def run(title, base_batch_size, base_labeled_batch_size, base_lr, n_labels, data_seed, **kwargs): LOG.info('run title: %s', title) ngpu = torch.cuda.device_count() adapted_args = { 'batch_size': base_batch_size * ngpu, 'labeled_batch_size': base_labeled_batch_size * ngpu, 'lr': base_lr * ngpu, 'labels': 'data-local/labels/cifar100/{}_balanced_labels/{:02d}.txt'.format(n_labels, data_seed), } context = RunContext(__file__, "{}_{}".format(n_labels, data_seed)) main.args = parse_dict_args(**adapted_args, **kwargs) main.main(context)
def run(title, base_batch_size, base_labeled_batch_size, base_lr, n_labels, data_seed, **kwargs): LOG.info('run title: %s, data seed: %d', title, data_seed) ngpu = torch.cuda.device_count() assert ngpu > 0, "Expecting at least one GPU, found none." adapted_args = { 'batch_size': base_batch_size * ngpu, 'labeled_batch_size': base_labeled_batch_size * ngpu, 'lr': base_lr * ngpu, 'labels': 'data-local/labels/cifar10/{}_balanced_labels/{:02d}.txt'.format(n_labels, data_seed), } context = RunContext(__file__, "{}_{}".format(n_labels, data_seed)) main_cnn_multi_label.args = parse_dict_args(**adapted_args, **kwargs) main_cnn_multi_label.main(context)
def run(title, base_batch_size, base_labeled_batch_size, base_lr, n_labels, data_seed, **kwargs): LOG.info('run title: %s, data seed: %d', title, data_seed) ngpu = torch.cuda.device_count() assert ngpu > 0, "Expecting at least one GPU, found none." adapted_args = { 'batch_size': base_batch_size * ngpu, 'labeled_batch_size': base_labeled_batch_size * ngpu, 'lr': base_lr * ngpu, 'labels': 'data-local/labels/cifar10/{}_balanced_labels/{:02d}.txt'.format(n_labels, data_seed), } context = RunContext(__file__, "{}_{}".format(n_labels, data_seed)) main.args = parse_dict_args(**adapted_args, **kwargs) main.main(context)
def run(title, base_batch_size, base_labeled_batch_size, base_lr, data_seed, **kwargs): LOG.info('run title: %s', title) ngpu = torch.cuda.device_count() adapted_args = { 'batch_size': base_batch_size * ngpu, 'labeled_batch_size': base_labeled_batch_size * ngpu, 'lr': base_lr * ngpu, 'labels': 'data-local/labels/ilsvrc2012/128000_balanced_labels/{:02d}.txt'. format(data_seed), } context = RunContext(__file__, data_seed) main_cifar.args = parse_dict_args(**adapted_args, **kwargs) main_cifar.main(context)
def run(title, data_seed, **kwargs): LOG.info('run title: %s', title) context = RunContext('/scratch/jtb470/ssl_j/', __file__, "{}".format(data_seed)) main.args = parse_dict_args(**kwargs) main.main(context)