Cleaning configs

lerobot/common/envs/configs.py

@@ -230,55 +230,6 @@ class HILSerlRobotEnvConfig(EnvConfig):
         return {}
 
 
-@EnvConfig.register_subclass("maniskill_push")
-@dataclass
-class ManiskillEnvConfig(EnvConfig):
-    """Configuration for the ManiSkill environment."""
-
-    name: str = "maniskill/pushcube"
-    task: str = "PushCube-v1"
-    image_size: int = 64
-    control_mode: str = "pd_ee_delta_pose"
-    state_dim: int = 25
-    action_dim: int = 7
-    fps: int = 200
-    episode_length: int = 50
-    obs_type: str = "rgb"
-    render_mode: str = "rgb_array"
-    render_size: int = 64
-    device: str = "cuda"
-    robot: str = "so100"  # This is a hack to make the robot config work
-    video_record: VideoRecordConfig = field(default_factory=VideoRecordConfig)
-    wrapper: WrapperConfig = field(default_factory=WrapperConfig)
-    mock_gripper: bool = False
-    features: dict[str, PolicyFeature] = field(
-        default_factory=lambda: {
-            "action": PolicyFeature(type=FeatureType.ACTION, shape=(7,)),
-            "observation.image": PolicyFeature(type=FeatureType.VISUAL, shape=(3, 64, 64)),
-            "observation.state": PolicyFeature(type=FeatureType.STATE, shape=(25,)),
-        }
-    )
-    features_map: dict[str, str] = field(
-        default_factory=lambda: {
-            "action": ACTION,
-            "observation.image": OBS_IMAGE,
-            "observation.state": OBS_ROBOT,
-        }
-    )
-    reward_classifier_pretrained_path: Optional[str] = None
-
-    @property
-    def gym_kwargs(self) -> dict:
-        return {
-            "obs_type": self.obs_type,
-            "render_mode": self.render_mode,
-            "max_episode_steps": self.episode_length,
-            "control_mode": self.control_mode,
-            "sensor_configs": {"width": self.image_size, "height": self.image_size},
-            "num_envs": 1,
-        }
-
-
 @EnvConfig.register_subclass("hil")
 @dataclass
 class HILEnvConfig(EnvConfig):