in basic_pitch/data/commandline.py [0:0]
def add_default(parser: argparse.ArgumentParser, dataset_name: str = "") -> None:
default_source = str(Path.home() / "mir_datasets" / dataset_name)
default_destination = str(Path.home() / "data" / "basic_pitch" / dataset_name)
parser.add_argument(
"--source",
default=default_source,
type=str,
help=f"Source directory for mir data. Defaults to {default_source}",
)
parser.add_argument(
"--destination",
default=default_destination,
type=str,
help=f"Output directory to write results to. Defaults to {default_destination}",
)
parser.add_argument(
"--runner",
choices=["DataflowRunner", "DirectRunner", "PortableRunner"],
default="DirectRunner",
help="Whether to run the download and process locally or on GCP Dataflow",
)
parser.add_argument(
"--timestamped",
default=False,
action="store_true",
help="If passed, the dataset will be put into a timestamp directory instead of 'splits'",
)
parser.add_argument("--batch-size", default=5, type=int, help="Number of examples per tfrecord")
parser.add_argument(
"--sdk_container_image",
default="",
help="Container image to run dataset generation job with. \
Required due to non-python dependencies.",
)
parser.add_argument("--job_endpoint", default="embed", help="")