def run_experiment(configpath: str, random_seed: int, noconfig: bool):
"""
Runs one experiment and saves results and plots
:param configpath: path to configfile
:param noconfig: whether to override config
:return: (train_csv_path, eval_csv_path)
"""
if configpath is not None and not noconfig:
if not os.path.exists(configpath):
write_default_config()
config = util.read_config(configpath)
else:
config = default_config()
time_str = str(time.time())
util.create_artefact_dirs(config.output_dir, random_seed)
logger = util.setup_logger("dqn_vs_random_defense-v4",
config.output_dir + "/results/logs/" +
str(random_seed) + "/",
time_str=time_str)
config.q_agent_config.save_dir = default_output_dir(
) + "/results/data/" + str(random_seed) + "/"
config.q_agent_config.video_dir = default_output_dir(
) + "/results/videos/" + str(random_seed) + "/"
config.q_agent_config.gif_dir = default_output_dir(
) + "/results/gifs/" + str(random_seed) + "/"
config.q_agent_config.dqn_config.tensorboard_dir = default_output_dir() + "/results/tensorboard/" \
+ str(random_seed) + "/"
config.logger = logger
config.q_agent_config.logger = logger
config.q_agent_config.random_seed = random_seed
config.random_seed = random_seed
config.q_agent_config.to_csv(config.output_dir +
"/results/hyperparameters/" +
str(random_seed) + "/" + time_str + ".csv")
train_result, eval_result = Runner.run(config)
train_csv_path = ""
eval_csv_path = ""
if len(train_result.avg_episode_steps) > 0 and len(
eval_result.avg_episode_steps) > 0:
train_csv_path = config.output_dir + "/results/data/" + str(
random_seed) + "/" + time_str + "_train" + ".csv"
train_result.to_csv(train_csv_path)
eval_csv_path = config.output_dir + "/results/data/" + str(
random_seed) + "/" + time_str + "_eval" + ".csv"
eval_result.to_csv(eval_csv_path)
plot_csv(config, eval_csv_path, train_csv_path, random_seed)
return train_csv_path, eval_csv_path
eval_csv_path = config.output_dir + "/results/data/" + str(
random_seed) + "/" + time_str + "_eval" + ".csv"
eval_result.to_csv(eval_csv_path)
plot_csv(config, eval_csv_path, train_csv_path, random_seed)
return train_csv_path, eval_csv_path
# Program entrypoint
if __name__ == '__main__':
args = util.parse_args(default_config_path())
experiment_title = "Q-learning vs Q-learning"
if args.configpath is not None and not args.noconfig:
if not os.path.exists(args.configpath):
write_default_config()
config = util.read_config(args.configpath)
else:
config = default_config()
if args.plotonly:
base_dir = default_output_dir() + "/results/data/"
train_csv_paths = []
eval_csv_paths = []
if config.run_many:
for seed in config.random_seeds:
train_csv_path = glob.glob(base_dir + str(seed) +
"/*_train.csv")[0]
eval_csv_path = glob.glob(base_dir + str(seed) +
"/*_eval.csv")[0]
attack_stats_csv_path = None
try:
attack_stats_csv_paths = glob.glob(base_dir + str(seed) +
