class_docstr: This is the automatic label word search implementation in `LM-BFF <https://arxiv.org/pdf/2012.15723.pdf>`_.
  
  Args:
      model (:obj:`PretrainedModel`): A pre-trained model for label word generation.
      tokenizer (:obj:`PretrainedTokenizer`): The corresponding tokenize.
      candidate_num (:obj:`Optional[int]`): The number of label word combinations to generate. Validation will then be performed on each combination. Defaults to 100.
      label_word_num_per_class (:obj:`Optional[int]`): The number of candidate label words per class. Defaults to 100.
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code: def _show_verbalizer(self):
      logger.info("Verbalizer is {}".format(self.label_words))
  
imports: from abc import abstractmethod
  from builtins import ValueError
  from typing import List, Optional, Dict, Union
  from tokenizers import Tokenizer
  import json
  import torch
  import torch.nn.functional
  from yacs.config import CfgNode
  from openprompt.data_utils.utils import InputExample, InputFeatures
  from openprompt.pipeline_base import PromptDataLoader, PromptModel
  from openprompt.prompt_base import Template, Verbalizer
  from openprompt.prompts import ManualTemplate, ManualVerbalizer
  from ..utils import logger
  from transformers import T5Tokenizer, T5ForConditionalGeneration, BertForMaskedLM, RobertaForMaskedLM, RobertaTokenizer, PreTrainedModel, PreTrainedTokenizer
  from tqdm import tqdm
  from typing import List, Optional, Dict
  import itertools
  import numpy
  from ..utils import signature
  from ..config import convert_cfg_to_dict
  from torch.nn.parallel import DataParallel
label_desc: Use image node_id 5 for calling the VerbalizerGenerator obj's underlying member method code with example usage: obj._show_verbalizer() without return types