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)
