Add an empty line

src/imitation/algorithms/sqil.py

@@ -3,6 +3,7 @@
 Trains a policy via DQN-style Q-learning,
 replacing half the buffer with expert demonstrations and adjusting the rewards.
 """
+
 from typing import Any, Dict, Iterable, Optional, Tuple, Type, Union
 
 import numpy as np