code: def bytes_to_unicode():
      r"""Returns list of utf-8 byte and a corresponding list of unicode strings.
      The reversible bpe codes work on unicode strings. This means you need a
      large number of unicode characters in your vocab if you want to avoid UNKs.
      When you're at something like a 10B token dataset you end up needing
      around 5K for decent coverage. This is a significant percentage of your
      normal, say, 32K bpe vocab. To avoid that, we want lookup tables between
      utf-8 bytes and unicode strings.
  
      Note that this function avoids the mapping to whitespace and control
      characters, which is designed specifically for GPT-2 BPE.
      """
      bs = (
          list(range(ord("!"), ord("~") + 1))
          + list(range(ord("¡"), ord("¬") + 1))
          + list(range(ord("®"), ord("ÿ") + 1))
      )
      cs = bs[:]
      n = 0
      for b in range(2**8):
          if b not in bs:
              bs.append(b)
              cs.append(2**8 + n)
              n += 1
      cs = [chr(n) for n in cs]
      return dict(zip(bs, cs))
  
label_desc: Use image node_id 1 for calling a global function with example usage: bytes_to_unicode() and returns: dict