def add_arguments(parser: argparse.ArgumentParser): add_glue_args(parser) add_glue_inference_args(parser) inference_args(parser) create_base_args( parser, model_types=TransformerSequenceClassifier.MODEL_CLASS.keys())
def add_arguments(parser: argparse.ArgumentParser): parser.add_argument( "--data_dir", default=None, type=str, required=True, help= "The input data dir. Should contain dataset files to be parsed " + "by the dataloaders.", ) train_args(parser, models_family=TransformerTokenClassifier.MODEL_CLASS.keys()) create_base_args( parser, model_types=TransformerTokenClassifier.MODEL_CLASS.keys()) parser.add_argument( "--train_file_name", type=str, default="train.txt", help="File name of the training dataset", ) parser.add_argument( "--ignore_token", type=str, default="", help="a token to ignore when processing the data", ) parser.add_argument( "--best_result_file", type=str, default="best_result.txt", help="file path for best evaluation output", )
def add_arguments(parser: argparse.ArgumentParser): parser.add_argument("--data_dir", default=None, type=str, required=True, help="The input data dir. Should contain dataset files to be parsed " + "by the dataloaders.") train_args(parser, models_family=TransformerTokenClassifier.MODEL_CLASS.keys()) create_base_args(parser, model_types=TransformerTokenClassifier.MODEL_CLASS.keys()) parser.add_argument('--train_file_name', type=str, default="train.txt", help='File name of the training dataset')
def add_arguments(parser: argparse.ArgumentParser): parser.add_argument("--data_file", default=None, type=str, required=True, help="The data file containing data for inference") inference_args(parser) create_base_args( parser, model_types=TransformerTokenClassifier.MODEL_CLASS.keys())