import os import os.path as osp import logging import yaml from utils.util import OrderedYaml Loader, Dumper = OrderedYaml() def parse(opt_path, is_train=True): with open(opt_path, mode='r') as f: opt = yaml.load(f, Loader=Loader) opt['is_train'] = is_train # datasets if 'datasets' in opt.keys(): for phase, dataset in opt['datasets'].items(): phase = phase.split('_')[0] dataset['phase'] = phase is_lmdb = False ''' LMDB is not supported at this point with the mods I've been making. if dataset.get('dataroot_GT', None) is not None: dataset['dataroot_GT'] = osp.expanduser(dataset['dataroot_GT']) if dataset['dataroot_GT'].endswith('lmdb'): is_lmdb = True if dataset.get('dataroot_LQ', None) is not None: dataset['dataroot_LQ'] = osp.expanduser(dataset['dataroot_LQ']) if dataset['dataroot_LQ'].endswith('lmdb'): is_lmdb = True ''' dataset['data_type'] = 'lmdb' if is_lmdb else 'img' if dataset['mode'].endswith('mc'): # for memcached dataset['data_type'] = 'mc' dataset['mode'] = dataset['mode'].replace('_mc', '') # path if 'path' in opt.keys(): for key, path in opt['path'].items(): if path and key in opt['path'] and key != 'strict_load': opt['path'][key] = osp.expanduser(path) else: opt['path'] = {} opt['path']['root'] = osp.abspath(osp.join(__file__, osp.pardir, osp.pardir, osp.pardir)) if is_train: experiments_root = osp.join(opt['path']['root'], 'experiments', opt['name']) opt['path']['experiments_root'] = experiments_root opt['path']['models'] = osp.join(experiments_root, 'models') opt['path']['training_state'] = osp.join(experiments_root, 'training_state') opt['path']['log'] = experiments_root opt['path']['val_images'] = osp.join(experiments_root, 'val_images') # change some options for debug mode if 'debug' in opt['name']: opt['train']['val_freq'] = 8 opt['logger']['print_freq'] = 1 opt['logger']['save_checkpoint_freq'] = 8 else: # test results_root = osp.join(opt['path']['root'], 'results', opt['name']) opt['path']['results_root'] = results_root opt['path']['log'] = results_root return opt def dict2str(opt, indent_l=1): '''dict to string for logger''' msg = '' for k, v in opt.items(): if isinstance(v, dict): msg += ' ' * (indent_l * 2) + k + ':[\n' msg += dict2str(v, indent_l + 1) msg += ' ' * (indent_l * 2) + ']\n' else: msg += ' ' * (indent_l * 2) + k + ': ' + str(v) + '\n' return msg class NoneDict(dict): def __missing__(self, key): return None # convert to NoneDict, which return None for missing key. def dict_to_nonedict(opt): if isinstance(opt, dict): new_opt = dict() for key, sub_opt in opt.items(): new_opt[key] = dict_to_nonedict(sub_opt) return NoneDict(**new_opt) elif isinstance(opt, list): return [dict_to_nonedict(sub_opt) for sub_opt in opt] else: return opt def check_resume(opt, resume_iter): '''Check resume states and pretrain_model paths''' logger = logging.getLogger('base') if opt['path']['resume_state']: if opt['path'].get('pretrain_model_G', None) is not None or opt['path'].get( 'pretrain_model_D', None) is not None: logger.warning('pretrain_model path will be ignored when resuming training.') # Automatically fill in the network paths for a given resume iteration. for k in opt['networks'].keys(): pt_key = 'pretrain_model_%s' % (k,) if pt_key in opt['path'].keys(): # This is a dicey, error prone situation that has bitten me in both ways it can be handled. Opt for # a big, verbose error message. print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!") print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!") print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!") print("!!!!!!!!!!!!!!WARNING!! YOU SPECIFIED A PRETRAINED MODEL PATH!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!") print("!!!!!!!!!!!!!!!!!!!!!!!!AND A RESUME STATE PATH. THERE IS NO!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!") print("!!!!!!!!!!!!!!!!!!!!!!!!GOOD WAY TO HANDLE THIS SO WE JUST IGNORE!!!!!!!!!!!!!!!!!!!!!!!!!!!") print("!!!!!!!!!!!!!!!!!!!!!!!!THE MODEL PATH!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!") print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!") print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!") print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!") else: opt['path'][pt_key] = osp.join(opt['path']['models'], '{}_{}.pth'.format(resume_iter, k)) logger.info('Set model [%s] to %s' % (k, opt['path'][pt_key]))