class_docstr: Convert between text-label and text-index 
class_docstr_tok: ["Convert","between","text-label","and","text-index"]
code: def __init__(self, character):
      # character (str): set of the possible characters.
      # [GO] for the start token of the attention decoder. [s] for end-of-sentence token.
      list_token = ["[GO]", "[s]"]  # ['[s]','[UNK]','[PAD]','[GO]']
      list_character = list(character)
      self.character = list_token + list_character
  
      self.dict = {}
      for i, char in enumerate(self.character):
          # print(i, char)
          self.dict[char] = i
  
imports: import torch
  import pickle
  import numpy
label_desc: Use image node_id 1 to create a new AttnLabelConverter object from inherited base classes: object with example: obj = AttnLabelConverter(character)