class_docstr: This is the implementation of knowledeagble verbalizer, which uses external knowledge to expand the set of label words.
  This class inherit the ``ManualVerbalizer`` class.
  
  Args:
      tokenizer (:obj:`PreTrainedTokenizer`): The tokenizer of the current pre-trained model to point out the vocabulary.
      classes (:obj:`classes`): The classes (or labels) of the current task.
      prefix (:obj:`str`, optional): The prefix string of the verbalizer.
      multi_token_handler (:obj:`str`, optional): The handling strategy for multiple tokens produced by the tokenizer.
      max_token_split (:obj:`int`, optional):
      verbalizer_lr (:obj:`float`, optional): The learning rate of the verbalizer optimization.
      candidate_frac (:obj:`float`, optional):
code: def __init__(
      self,
      tokenizer: PreTrainedTokenizer = None,
      classes: Sequence[str] = None,
      prefix: Optional[str] = " ",
      multi_token_handler: Optional[str] = "first",
      max_token_split: Optional[int] = -1,
      verbalizer_lr: Optional[float] = 5e-2,
      candidate_frac: Optional[float] = 0.5,
      pred_temp: Optional[float] = 1.0,
      **kwargs,
  ):
      super().__init__(
          classes=classes,
          prefix=prefix,
          multi_token_handler=multi_token_handler,
          tokenizer=tokenizer,
          **kwargs,
      )
      self.max_token_split = max_token_split
      self.verbalizer_lr = verbalizer_lr
      self.candidate_frac = candidate_frac
      self.pred_temp = pred_temp
  
imports: import os
  from openprompt.prompts.manual_template import ManualTemplate
  from transformers.tokenization_utils import PreTrainedTokenizer
  from transformers.utils.dummy_pt_objects import PreTrainedModel
  from openprompt.data_utils import InputFeatures
  import re
  from openprompt.prompts.manual_verbalizer import ManualVerbalizer
  from typing import *
  import torch
  import torch.nn
  import torch.nn.functional
  from openprompt.utils.logging import logger
label_desc: Use image node_id 1 to create a new KnowledgeableVerbalizer object from inherited base classes: ManualVerbalizer with example: obj = KnowledgeableVerbalizer(tokenizer, classes, prefix, multi_token_handler, max_token_split, verbalizer_lr, candidate_frac, pred_temp)