if args.cfg_file is not None: cfg_from_file(args.cfg_file) if args.gpu_id != -1: cfg.GPU_ID = args.gpu_id print('Using config:') pprint.pprint(cfg) now = datetime.datetime.now(dateutil.tz.tzlocal()) timestamp = now.strftime('%Y_%m_%d_%H_%M_%S') # datadir = 'Data/%s' % cfg.DATASET_NAME datadir = cfg.DATASET_NAME dataset = TextDataset(datadir, cfg.EMBEDDING_TYPE, 4) filename_test = datadir # dataset.test = dataset.get_data(filename_test) dataset.test = dataset.get_data(cfg.DATASET_NAME) if cfg.TRAIN.FLAG: filename_train = datadir # dataset.train = dataset.get_data(filename_train) dataset.train = dataset.get_data(cfg.DATASET_NAME) ckt_logs_dir = "ckt_logs/%s/%s_%s" % \ (cfg.DATASET_NAME, cfg.CONFIG_NAME, timestamp) mkdir_p(ckt_logs_dir) else: s_tmp = cfg.TRAIN.PRETRAINED_MODEL ckt_logs_dir = s_tmp[:s_tmp.find('.ckpt')] model = CondGAN(lr_imsize=int(dataset.image_shape[0] / dataset.hr_lr_ratio), hr_lr_ratio=dataset.hr_lr_ratio)
if __name__ == "__main__": args = parse_args() if args.cfg_file is not None: cfg_from_file(args.cfg_file) if args.gpu_id != -1: cfg.GPU_ID = args.gpu_id print('Using config:') pprint.pprint(cfg) now = datetime.datetime.now(dateutil.tz.tzlocal()) timestamp = now.strftime('%Y_%m_%d_%H_%M_%S') datadir = 'Data/%s' % cfg.DATASET_NAME dataset = TextDataset(datadir, cfg.EMBEDDING_TYPE, 1) filename_test = '%s/test' % (datadir) dataset.test = dataset.get_data(filename_test) if cfg.TRAIN.FLAG: filename_train = '%s/train' % (datadir) dataset.train = dataset.get_data(filename_train) ckt_logs_dir = "ckt_logs/%s/%s_%s" % (cfg.DATASET_NAME, cfg.CONFIG_NAME, timestamp) mkdir_p(ckt_logs_dir) else: s_tmp = cfg.TRAIN.PRETRAINED_MODEL ckt_logs_dir = s_tmp[:s_tmp.find('.ckpt')] model = CondGAN(image_shape=dataset.image_shape) algo = CondGANTrainer(model=model, dataset=dataset, ckt_logs_dir=ckt_logs_dir) if cfg.TRAIN.FLAG:
if __name__ == "__main__": args = parse_args() if args.cfg_file is not None: cfg_from_file(args.cfg_file) if args.gpu_id != -1: cfg.GPU_ID = args.gpu_id print('Using config:') pprint.pprint(cfg) now = datetime.datetime.now(dateutil.tz.tzlocal()) timestamp = now.strftime('%Y_%m_%d_%H_%M_%S') datadir = 'Data/%s' % cfg.DATASET_NAME dataset = TextDataset(datadir, cfg.EMBEDDING_TYPE, 1) filename_test = '%s/test' % (datadir) dataset.test = dataset.get_data(filename_test) if cfg.TRAIN.FLAG: filename_train = '%s/train' % (datadir) dataset.train = dataset.get_data(filename_train) ckt_logs_dir = "ckt_logs/%s/%s_%s" % \ (cfg.DATASET_NAME, cfg.CONFIG_NAME, timestamp) mkdir_p(ckt_logs_dir) else: s_tmp = cfg.TRAIN.PRETRAINED_MODEL ckt_logs_dir = s_tmp[:s_tmp.find('.ckpt')] model = CondGAN( image_shape=dataset.image_shape )