[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

lerobot/common/envs/configs.py

@@ -202,12 +202,11 @@ class EnvWrapperConfig:
     ee_action_space_params: Optional[EEActionSpaceConfig] = None
     use_gripper: bool = False
     gripper_quantization_threshold: float | None = 0.8
-    gripper_penalty: float = 0.0 
+    gripper_penalty: float = 0.0
     gripper_penalty_in_reward: bool = False
     open_gripper_on_reset: bool = False
 
 
-
 @EnvConfig.register_subclass(name="gym_manipulator")
 @dataclass
 class HILSerlRobotEnvConfig(EnvConfig):

lerobot/scripts/server/gym_manipulator.py

@@ -718,7 +718,7 @@ class ResetWrapper(gym.Wrapper):
         env: HILSerlRobotEnv,
         reset_pose: np.ndarray | None = None,
         reset_time_s: float = 5,
-        open_gripper_on_reset: bool = False
+        open_gripper_on_reset: bool = False,
     ):
         super().__init__(env)
         self.reset_time_s = reset_time_s
@@ -727,8 +727,6 @@ class ResetWrapper(gym.Wrapper):
         self.open_gripper_on_reset = open_gripper_on_reset
 
     def reset(self, *, seed=None, options=None):
-
-
         if self.reset_pose is not None:
             start_time = time.perf_counter()
             log_say("Reset the environment.", play_sounds=True)
@@ -777,12 +775,11 @@ class GripperPenaltyWrapper(gym.RewardWrapper):
         self.penalty = penalty
         self.gripper_penalty_in_reward = gripper_penalty_in_reward
         self.last_gripper_state = None
-        
 
     def reward(self, reward, action):
         gripper_state_normalized = self.last_gripper_state / MAX_GRIPPER_COMMAND
 
-        action_normalized = action - 1.0 #action / MAX_GRIPPER_COMMAND
+        action_normalized = action - 1.0  # action / MAX_GRIPPER_COMMAND
 
         gripper_penalty_bool = (gripper_state_normalized < 0.5 and action_normalized > 0.5) or (
             gripper_state_normalized > 0.75 and action_normalized < -0.5
@@ -803,7 +800,7 @@ class GripperPenaltyWrapper(gym.RewardWrapper):
             reward += gripper_penalty
         else:
             info["gripper_penalty"] = gripper_penalty
-            
+
         return obs, reward, terminated, truncated, info
 
     def reset(self, **kwargs):
@@ -813,6 +810,7 @@ class GripperPenaltyWrapper(gym.RewardWrapper):
             info["gripper_penalty"] = 0.0
         return obs, info
 
+
 class GripperActionWrapper(gym.ActionWrapper):
     def __init__(self, env, quantization_threshold: float = 0.2):
         super().__init__(env)
@@ -1189,11 +1187,13 @@ def make_robot_env(cfg) -> gym.vector.VectorEnv:
     # env = RewardWrapper(env=env, reward_classifier=reward_classifier, device=cfg.device)
     env = TimeLimitWrapper(env=env, control_time_s=cfg.wrapper.control_time_s, fps=cfg.fps)
     if cfg.wrapper.use_gripper:
-        env = GripperActionWrapper(
-            env=env, quantization_threshold=cfg.wrapper.gripper_quantization_threshold
-        )
+        env = GripperActionWrapper(env=env, quantization_threshold=cfg.wrapper.gripper_quantization_threshold)
         if cfg.wrapper.gripper_penalty is not None:
-            env = GripperPenaltyWrapper(env=env, penalty=cfg.wrapper.gripper_penalty, gripper_penalty_in_reward=cfg.wrapper.gripper_penalty_in_reward)
+            env = GripperPenaltyWrapper(
+                env=env,
+                penalty=cfg.wrapper.gripper_penalty,
+                gripper_penalty_in_reward=cfg.wrapper.gripper_penalty_in_reward,
+            )
 
     if cfg.wrapper.ee_action_space_params is not None:
         env = EEActionWrapper(
@@ -1218,7 +1218,7 @@ def make_robot_env(cfg) -> gym.vector.VectorEnv:
         env=env,
         reset_pose=cfg.wrapper.fixed_reset_joint_positions,
         reset_time_s=cfg.wrapper.reset_time_s,
-        open_gripper_on_reset=cfg.wrapper.open_gripper_on_reset
+        open_gripper_on_reset=cfg.wrapper.open_gripper_on_reset,
     )
     if cfg.wrapper.ee_action_space_params is None and cfg.wrapper.joint_masking_action_space is not None:
         env = JointMaskingActionSpace(env=env, mask=cfg.wrapper.joint_masking_action_space)

lerobot/scripts/server/learner_server.py

@@ -406,7 +406,7 @@ def add_actor_information_and_train(
                 "next_state": next_observations,
                 "done": done,
                 "observation_feature": observation_features,
-                "next_observation_feature": next_observation_features, 
+                "next_observation_feature": next_observation_features,
                 "complementary_info": batch["complementary_info"],
             }