code: def step(self, a):
      xposbefore = self.get_body_com("torso")[0]
      self.do_simulation(a, self.frame_skip)
      xposafter = self.get_body_com("torso")[0]
  
      forward_reward = (xposafter - xposbefore) / self.dt
      ctrl_cost = 0.5 * np.square(a).sum()
      contact_cost = (
          0.5
          * 1e-3
          * np.sum(np.square(np.clip(self.sim.data.cfrc_ext, -1, 1)))
      )
      survive_reward = 1.0
      reward = (
          forward_reward - ctrl_cost - contact_cost + survive_reward
      )
      state = self.state_vector()
      not_terminated = (
          np.isfinite(state).all()
          and state[2] >= 0.2
          and state[2] <= 1.0
      )
      terminated = not not_terminated
      ob = self._get_obs()
  
      if self.render_mode == "human":
          self.render()
      return (
          ob,
          reward,
          terminated,
          False,
          dict(
              reward_forward=forward_reward,
              reward_ctrl=-ctrl_cost,
              reward_contact=-contact_cost,
              reward_survive=survive_reward,
          ),
      )
  
file_path: gym/gym/envs/mujoco/ant.py
imports: import numpy
  from gym import utils
  from gym.envs.mujoco import MuJocoPyEnv
  from gym.spaces import Box
label_desc: Use image node_id 2 for calling the AntEnv obj's underlying member method code with example usage: obj.step(a) and returns: ob,  reward,  terminated,  False,  dict