(self)
return
Updates the current episode length depending on the number of environment steps taken so far.
Updates the current episode length depending on the number of environment steps taken so far.
Updates the current episode length depending on the number of environment steps taken so far .
def _update_time_limit(self):
    """Updates the current episode length depending on the number of environment steps taken so far."""
    t = float(self._total_step_count) / self._curriculum_steps
    t = np.clip(t, 0.0, 1.0)
    t = np.power(t, 3.0)
    new_steps = int((1.0 - t) * self._episode_length_start +
                       t * self._episode_length_end)
    self._max_episode_steps = new_steps
    return
def _update_time_limit ( self ) : t = float ( self . _total_step_count ) / self . _curriculum_steps t = np . clip ( t , 0.0 , 1.0 ) t = np . power ( t , 3.0 ) new_steps = int ( ( 1.0 - t ) * self . _episode_length_start + t * self . _episode_length_end ) self . _max_episode_steps = new_steps return