code: def __init__(
      self,
      tokenizer,
      context: str,
      max_len: int = 2048,
      censored_words: List[str] = [],
  ):
      self.tokenizer = tokenizer
      self.context = context
      self.max_len = max_len
      self.censored_words = set(
          [word.lower() for word in censored_words]
      )
      # These will be initialized after the first call of preprocess_prompt()
      self.context_len: Optional[int] = None
      self.dialogue_placeholder_len: Optional[int] = None
  
imports: import json
  import re
  from threading import Lock
  from typing import Any, Callable, Generator, List, Optional
  import jieba
  import torch
  import torch.distributed
  import torch.nn
  from pydantic import BaseModel, Field
label_desc: Use image node_id 1 to create a new ChatPromptProcessor object  with example: obj = ChatPromptProcessor(tokenizer, context, max_len, censored_words)