def main():
parser = argparse.ArgumentParser()
subparsers = parser.add_subparsers(dest="cmd")
subparsers.required = True
train_parser = subparsers.add_parser(
"train", help="Submit a ElasticDL distributed training job"
)
train_parser.set_defaults(func=train)
add_common_params(train_parser)
add_train_params(train_parser)
evaluate_parser = subparsers.add_parser(
"evaluate", help="Submit a ElasticDL distributed evaluation job"
)
evaluate_parser.set_defaults(func=evaluate)
add_common_params(evaluate_parser)
add_evaluate_params(evaluate_parser)
predict_parser = subparsers.add_parser(
"predict", help="Submit a ElasticDL distributed prediction job"
)
predict_parser.set_defaults(func=predict)
add_common_params(predict_parser)
add_predict_params(predict_parser)
args, _ = parser.parse_known_args()
args.func(args)
def main():
parser = argparse.ArgumentParser(
usage="""elasticdl <command> [<args>]
Below is the list of supported commands:
train Submit a ElasticDL distributed training job.
evaluate Submit a ElasticDL distributed evaluation job.
predict Submit a ElasticDL distributed prediction job.
"""
)
subparsers = parser.add_subparsers()
train_parser = subparsers.add_parser("train", help="elasticdl train -h")
train_parser.set_defaults(func=train)
add_common_params(train_parser)
add_train_params(train_parser)
evaluate_parser = subparsers.add_parser(
"evaluate", help="elasticdl evaluate -h"
)
evaluate_parser.set_defaults(func=evaluate)
add_common_params(evaluate_parser)
add_evaluate_params(evaluate_parser)
predict_parser = subparsers.add_parser(
"predict", help="elasticdl predict -h"
)
predict_parser.set_defaults(func=predict)
add_common_params(predict_parser)
add_predict_params(predict_parser)
args, _ = parser.parse_known_args()
args.func(args)
def parse_args():
parser = argparse.ArgumentParser(description="ElasticDL Master")
parser.add_argument(
"--port",
default=50001,
type=pos_int,
help="The listening port of master",
)
parser.add_argument("--worker_image",
help="Docker image for workers",
default=None)
parser.add_argument("--worker_pod_priority",
help="Priority requested by workers")
parser.add_argument(
"--prediction_data_dir",
help="Prediction data directory. Files should be in RecordIO format",
default="",
)
parser.add_argument(
"--log_level",
choices=["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"],
type=str.upper,
default="INFO",
help="The logging level. Default to WARNING",
)
add_common_params(parser)
add_train_params(parser)
args = parser.parse_args()
print_args(args, groups=ALL_ARGS_GROUPS)
if all(v == "" or v is None for v in [
args.training_data_dir,
args.evaluation_data_dir,
args.prediction_data_dir,
]):
raise ValueError(
"At least one of the data directories needs to be provided")
if args.prediction_data_dir and (args.training_data_dir
or args.evaluation_data_dir):
raise ValueError(
"Running prediction together with training or evaluation "
"is not supported")
if args.prediction_data_dir and not args.checkpoint_filename_for_init:
raise ValueError(
"checkpoint_filename_for_init is required for running "
"prediction job")
return args