# Copyright (c) 2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX-License-Identifier: MPL-2.0
# This file is part of L2RPN Baselines, L2RPN Baselines a repository to host baselines for l2rpn competitions.
import argparse
[docs]def cli_train():
"""some default command line arguments (cli) for training the baselines. Can be reused in some baselines here."""
parser = argparse.ArgumentParser(description="Train baseline DDQN")
parser.add_argument("--num_train_steps", required=False,
default=1024, type=int,
help="Number of training iterations")
parser.add_argument("--save_path", required=False,
help="Path where the model should be saved.")
parser.add_argument("--name", required=False,
help="Name given to your model.")
parser.add_argument("--nb_env", required=False, default=1, type=int,
help="Number of process to use when training your Agent. If > 1 then MultiEnv will be used. "
"NB: not all models are compatible. NB it does not work on windows at the moment. "
"NB: experimental at the moment.")
parser.add_argument("--load_path", required=False,
help="Path from which to reload your model from (by default ``None`` to NOT reload anything)")
parser.add_argument("--env_name", required=False, default="l2rpn_case14_sandbox",
help="Name of the environment to load (default \"l2rpn_case14_sandbox\"")
parser.add_argument("--logs_dir", required=False, default=None,
help="Where to output the training logs (usually tensorboard logs)")
return parser