Lint

lihuoran · lihuoran · commit abbebbaa203a · 2023-03-20T10:08:22.000+08:00
diff --git a/maro/rl/workflows/main.py b/maro/rl/workflows/main.py
@@ -247,7 +247,7 @@ def evaluate_only_workflow(rl_component_bundle: RLComponentBundle, env_attr: Wor
     args = _get_args()
     if args.seed is not None:
         set_seeds(seed=args.seed)
-    
+
     scenario_path = get_env("SCENARIO_PATH")
     scenario_path = os.path.normpath(scenario_path)
     sys.path.insert(0, os.path.dirname(scenario_path))
diff --git a/tests/rl/tasks/ddpg/__init__.py b/tests/rl/tasks/ddpg/__init__.py
@@ -41,11 +41,11 @@
 
 class MyContinuousDDPGNet(ContinuousDDPGNet):
     def __init__(
-        self, 
-        state_dim: int, 
-        action_dim: int, 
-        action_limit: float, 
-        action_space: spaces.Space, 
+        self,
+        state_dim: int,
+        action_dim: int,
+        action_limit: float,
+        action_space: spaces.Space,
         noise_scale: float = 0.1,
     ) -> None:
         super(MyContinuousDDPGNet, self).__init__(state_dim=state_dim, action_dim=action_dim)
@@ -75,6 +75,7 @@ def _get_random_actions_impl(self, states: torch.Tensor) -> torch.Tensor:
             [ndarray_to_tensor(self._action_space.sample(), device=self._device) for _ in range(states.shape[0])],
         )
 
+
 class MyQCriticNet(QNet):
     def __init__(self, state_dim: int, action_dim: int) -> None:
         super(MyQCriticNet, self).__init__(state_dim=state_dim, action_dim=action_dim)
