class_docstr: Beta Torch probability distribution.
  
  :param logits: the logits for both mean and standard deviation.
  :param action_space: the underlying gym.spaces action space.
code: def _un_squash(self, values: torch.Tensor) -> torch.Tensor:
      return (values - self.low) / (self.high - self.low)
  
imports: import math
  from typing import Sequence
  import numpy
  import gym
  import torch
  from gym import spaces
  from torch.distributions import Beta, kl_divergence
  from maze.core.annotations import override
  from maze.distributions.torch_dist import TorchProbabilityDistribution
  from maze.distributions.utils import EPSILON
  from maze.perception.perception_utils import convert_to_torch
label_desc: Use image node_id 9 for calling the BetaProbabilityDistribution obj's underlying member method code with example usage: obj._un_squash(values) and returns: unknown