def parse_args(parser: argparse, config: Config):
"""Parse the programme arguments
:param config:
:param parser:
:return: arguments
"""
location_help = r"""location specifying the start point to scan to recursively hash files.
May also be a single file.
"""
report_location_help = r"""location specifying the csv report file in which to write results. """
parser.add_argument('scan_location',
help=location_help)
parser.add_argument('-report', '--report',
default=config.report,
required=False,
help=report_location_help)
args = parser.parse_args()
logging.debug(str(args))
return args
def add_parser_option(parser: argparse,
short_name: str = '',
full_name: str = '',
**kwargs):
"""
Add a new option to the Parser.
This function allows us to add a new option to the argument parser. This
allows for every module with an entry point to set up its own set of
arguments for multi-module startup.
Args:
parser (argparse): The parser we are adding the new option to.
short_name (str): The short name of the command line flag. e.g. '-f'.
full_name (str): The fully descriptive command line flag e.g. '--foo'.
**kwargs: The optional parameters that will be added to the parser.
see cref: https://github.com/python/cpython/blob/3.7/Lib/argparse.py.
"""
if short_name and full_name:
parser.add_argument(short_name, full_name, **kwargs)
else:
parser.add_argument(full_name, **kwargs)
def aws_parser_arguments(aws_parser: argparse) -> argparse:
aws_parser.add_argument("--access_key",
type=str,
required=False,
help="Access key of the AWS account")
aws_parser.add_argument("--secret_key",
type=str,
required=False,
help="Secret key of the AWS account")
aws_parser.add_argument("--account_id",
type=str,
required=False,
help="Account ID of the AWS account")
aws_parser.add_argument("--region",
type=str,
required=False,
help="Region of the AWS account")
return aws_parser
def add_parser(self, parser: argparse):
# pylint: disable=protected-access
parser.add_argument('archive_file',
type=str,
help='path to an archived trained model')
parser.add_argument(
'input_file',
type=str,
help='path to the file containing the evaluation data')
parser.add_argument('--output-file',
type=str,
help='path to output file')
parser.add_argument(
'--weights-file',
type=str,
help='a path that overrides which weights file to use')
cuda_device = parser.add_mutually_exclusive_group(required=False)
cuda_device.add_argument('--cuda-device',
type=int,
default=-1,
help='id of GPU to use (if any)')
parser.add_argument(
'-t',
'--thresholds',
type=str,
default="0",
help=
'A comma (,) or underscore (_) separated list of temperature thresholds to consider'
)
parser.add_argument(
'-o',
'--overrides',
type=str,
default="",
help=
'a JSON structure used to override the experiment configuration')
parser.add_argument(
'--batch-weight-key',
type=str,
default="",
help=
'If non-empty, name of metric used to weight the loss on a per-batch basis.'
)
parser.add_argument(
'--extend-vocab',
action='store_true',
default=False,
help=
'if specified, we will use the instances in your new dataset to '
'extend your vocabulary. If pretrained-file was used to initialize '
'embedding layers, you may also need to pass --embedding-sources-mapping.'
)
parser.add_argument(
'--embedding-sources-mapping',
type=str,
default="",
help=
'a JSON dict defining mapping from embedding module path to embedding'
'pretrained-file used during training. If not passed, and embedding needs to be '
'extended, we will try to use the original file paths used during training. If '
'they are not available we will use random vectors for embedding extension.'
)
parser.add_argument('--include-package',
type=str,
action='append',
default=[],
help='additional packages to include')
parser.set_defaults(func=evaluate_from_args)