def load_network()

in classification/model.py [0:0]

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

def load_network(opt, model, which_epoch, save_dir=''):
    if which_epoch > 0:
        if opt.network_arch == 'mlp':
            save_filename = '%s_classifier.pth' % (which_epoch)
        else:
            save_filename = '%s_linear_classifier.pth' % (which_epoch)
        if not save_dir:
            save_dir = opt.save_dir
    else:
        if opt.network_arch == 'mlp':
            save_filename = get_model_list(save_dir, 'classifier')
        else:
            save_filename = get_model_list(save_dir, 'linear_classifier')

    if not save_filename:
        print("file does not exist")
        exit()
    save_path = os.path.join(save_dir, save_filename)

    if not os.path.isfile(save_path):
        print('%s not exists yet!' % save_path)
        exit()
    else:
        try:
            model.load_state_dict(torch.load(save_path))
        except:
            print("cannot load pretrained model")
            exit()

    if which_epoch > 0:
        print('Resume from iteration %d' % which_epoch)
        return which_epoch
    else:
        iterations = int(save_filename.split('_')[0])
        print('Resume from iteration %d' % iterations)
        return iterations