class_docstr: Serializer for gym.spaces.Box.
  
  Assumes that the space is bounded. Internally rescales it to the [0, 1]
  interval and uses a fixed-precision encoding.
class_docstr_tok: ["Serializer","for","gym.spaces.Box",".","Assumes","that","the","space","is","bounded",".","Internally","rescales","it","to","the","[","0",",","1","]","interval","and","uses","a","fixed-precision","encoding","."]
code: def deserialize(self, representation):
      digits = representation
      batch_size = digits.shape[0]
      digits = np.reshape(digits, (batch_size, -1, self._precision))
      array = np.zeros(digits.shape[:-1])
      for digit_index_in_seq in range(self._precision):
          digit_index = -digit_index_in_seq - 1
          array += (
              self._vocab_size**digit_index
              * digits[..., digit_index_in_seq]
          )
      array = np.reshape(array, (batch_size,) + self._space.shape)
      return (
          array * (self._space.high - self._space.low) + self._space.low
      )
  
imports: import copy
  from absl import logging
  import gin
  import gym
  from jax import numpy
label_desc: Use image node_id 3 for calling the BoxSpaceSerializer obj's underlying member method code with example usage: obj.deserialize(representation) and returns: unknown