docstr: Hack to hopefully support generate_stream for the maximum number of tokenizers
docstr_tok: ["Hack","to","hopefully","support","generate_stream","for","the","maximum","number","of","tokenizers"]
code: def decode_token(
      self,
      all_input_ids: List[int],
      prefix_offset: int = 0,
      read_offset: int = 0,
      skip_special_tokens: bool = False,
  ) -> Tuple[str, int, int]:
      """Hack to hopefully support generate_stream for the maximum number of tokenizers"""
  
      # The prefix text is necessary only to defeat cleanup algorithms in the decode
      # which decide to add a space or not depending on the surrounding ids.
      prefix_text = self.tokenizer.decode(
          all_input_ids[prefix_offset:read_offset],
          skip_special_tokens=skip_special_tokens,
      )
      new_text = self.tokenizer.decode(
          all_input_ids[prefix_offset:],
          skip_special_tokens=skip_special_tokens,
      )
  
      if len(new_text) > len(prefix_text) and not new_text.endswith(
          "�"
      ):
          # utf-8 char at the end means it's a potential unfinished byte sequence
          # from byte fallback tokenization.
          # If it's in the middle, it's probably a real invalid id generated
          # by the model
          new_text = new_text[len(prefix_text) :]
          return new_text, read_offset, len(all_input_ids)
      else:
          return "", prefix_offset, read_offset
  
file_path: text-generation-inference/server/text_generation_server/models/model.py
imports: import inspect
  import torch
  from abc import ABC, abstractmethod
  from typing import List, Tuple, Optional, TypeVar, Type
  from transformers import PreTrainedTokenizerBase, PretrainedConfig
  from text_generation_server.models.types import Batch, Generation
  from text_generation_server.utils.speculate import get_speculate
  from text_generation_server.pb.generate_pb2 import InfoResponse
label_desc: Use image node_id 6 for calling the Model obj's underlying member method code with example usage: obj.decode_token(all_input_ids, prefix_offset, read_offset, skip_special_tokens) and returns: new_text,  read_offset,  len, str,  prefix_offset,  read_offset