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())
