def seg_train(args): if not DatasetHandler.is_readable(args.training_file): logging.error("path '%s' open failed !" % (args.training_file)) logging.error('Exit!') exit(1) if not DatasetHandler.is_readable(args.developing_file): logging.error("path '%s' open failed !" % (args.developing_file)) logging.error("Exit!") exit(1) if not DatasetHandler.is_writeable(args.model_saving): logging.error("path '%s' open failed !" % (args.model_saving)) logging.error('Exit!') exit(1) segmentor = Segmentor() segmentor.train(args.training_file, args.developing_file, args.model_saving, args.max_iter)
def seg_predict(args): if not DatasetHandler.is_readable(args.predict_file): logging.error("path '%s' open failed !" % (args.predict_file)) logging.error('Exit!') exit(1) if not DatasetHandler.is_readable(args.model_loading): logging.error("path '%s' open failed ! Model load Error ." % (args.model_loading)) logging.error("Exit!") exit(1) if not DatasetHandler.is_writeable( args.output_path) and args.output_path != "stdout": logging.error("path '%s' open failed !" % (args.output_path)) logging.error('Exit!') exit(1) segmentor = Segmentor() segmentor.predict(args.model_loading, args.predict_file, args.output_path)