def create_save_path()

in train.py [0:0]

• 28 lines of code
• 8 McCabe index (conditional complexity)

def create_save_path(args, _mkdir=True):
    # mkdirs:
    decay_str = args.decay
    if args.decay == 'multisteps':
        decay_str += '-'.join(map(str, args.decay_epochs)) 
    opt_str = args.opt 
    if args.opt == 'sgd':
        opt_str += '-m%s' % args.momentum
    opt_str = 'e%d-b%d-%s-lr%s-wd%s-%s' % (args.epochs, args.batch_size, opt_str, args.lr, args.wd, decay_str)
    reweighting_fn_str = 'sign' 
    loss_str = '%s-Lambda%s-Lambda2%s-T%s-%s' % \
                (args.ood_metric + '-' + args.aux_prior_type + '-' + args.aux_ood_loss, 
                 args.Lambda, args.Lambda2, args.T, reweighting_fn_str)
    if args.imbalance_ratio < 1:
        if args.logit_adjust > 0:
            lt_method = 'LA%s' % args.logit_adjust
        else:
            lt_method = 'none'
        loss_str = lt_method + '-' + loss_str
    loss_str += '-k%s'% (args.k)
    exp_str = '%s_%s' % (opt_str, loss_str)
    if args.timestamp:
        exp_str += '_%s' % datetime.datetime.now().strftime("%Y%m%d%H%M%S")
    dataset_str = '%s-%s-OOD%d' % (args.dataset, args.imbalance_ratio, args.num_ood_samples) if 'imagenet' not in args.dataset else '%s%d-lt' % (args.dataset, args.id_class_number)
    save_dir = osp.join(args.save_root_path, dataset_str, args.model, exp_str)
    if _mkdir:
        create_dir(save_dir)
        print('Saving to %s' % save_dir)

    return save_dir