(self,
      gym_env,
      episode_length_start=1000,
      episode_length_end=1000,
      curriculum_steps=0,
      num_parallel_envs=1)
return
Initialzes the wrapped env.

    Args:
      gym_env: An instance of LocomotionGymEnv.
Initialzes the wrapped env.
Initialzes the wrapped env .
def __init__(self,
      gym_env,
      episode_length_start=1000,
      episode_length_end=1000,
      curriculum_steps=0,
      num_parallel_envs=1):
    """Initialzes the wrapped env.

    Args:
      gym_env: An instance of LocomotionGymEnv.
    """
    self._gym_env = gym_env
    self.observation_space = self._build_observation_space()

    self._episode_length_start = episode_length_start
    self._episode_length_end = episode_length_end
    self._curriculum_steps = int(np.ceil(curriculum_steps / num_parallel_envs))
    self._total_step_count = 0

    if self._enable_curriculum():
      self._update_time_limit()

    self.seed()
    return
def __init__ ( self , gym_env , episode_length_start = 1000 , episode_length_end = 1000 , curriculum_steps = 0 , num_parallel_envs = 1 ) : self . _gym_env = gym_env self . observation_space = self . _build_observation_space ( ) self . _episode_length_start = episode_length_start self . _episode_length_end = episode_length_end self . _curriculum_steps = int ( np . ceil ( curriculum_steps / num_parallel_envs ) ) self . _total_step_count = 0 if self . _enable_curriculum ( ) : self . _update_time_limit ( ) self . seed ( ) return