class_docstr: Tokenizing strategy for Reflection prompts.
class_docstr_tok: ["Tokenizing","strategy","for","Reflection","prompts","."]
code: def _tokenize(
      self, prompt, add_eos_token=True, strip_bos_token=False
  ):
      result = self.tokenizer(
          prompt,
          truncation=True,
          max_length=self.sequence_len,
          padding=False,
          return_tensors=None,
      )
      if (
          result["input_ids"][-1] != self.tokenizer.eos_token_id
          and len(result["input_ids"]) < self.sequence_len
          and add_eos_token
      ):
          result["input_ids"].append(self.tokenizer.eos_token_id)
          result["attention_mask"].append(1)
  
      result["labels"] = result["input_ids"].copy()
      return result
  
imports: import abc
  import copy
  import logging
  from typing import Dict, List, Tuple, Union
  from fastchat.conversation import Conversation
  from transformers import BatchEncoding, PreTrainedTokenizer
  from axolotl.monkeypatch.fastchat_conversation_turns import add_get_turns_to_conversation
  from axolotl.prompters import IGNORE_TOKEN_ID
label_desc: Use image node_id 4 for calling the ReflectionPromptTokenizingStrategy obj's underlying member method code with example usage: obj._tokenize(prompt, add_eos_token, strip_bos_token) and returns: result