in train_procgen/graph.py [0:0]
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--distribution_mode', type=str, default='easy', help="Environment distribution_mode ('easy' or 'hard')")
parser.add_argument('--normalize_and_reduce', dest='normalize_and_reduce', action='store_true')
parser.add_argument('--restrict_training_set', dest='restrict_training_set', action='store_true')
parser.add_argument('--save', dest='save', action='store_true')
args = parser.parse_args()
run_directory_prefix = main_pcg_sample_entry(args.distribution_mode, args.normalize_and_reduce, args.restrict_training_set)
plt.tight_layout()
if args.save:
suffix = '-mean' if args.normalize_and_reduce else ''
plt.savefig(f'results/{run_directory_prefix}{suffix}.pdf')
else:
plt.show()