class_docstr: The basic manually defined verbalizer class, this class is inherited from the :obj:`Verbalizer` class.
  
  Args:
      tokenizer (:obj:`PreTrainedTokenizer`): The tokenizer of the current pre-trained model to point out the vocabulary.
      classes (:obj:`List[Any]`): The classes (or labels) of the current task.
      label_words (:obj:`Union[List[str], List[List[str]], Dict[List[str]]]`, optional): The label words that are projected by the labels.
      prefix (:obj:`str`, optional): The prefix string of the verbalizer (used in PLMs like RoBERTa, which is sensitive to prefix space)
      multi_token_handler (:obj:`str`, optional): The handling strategy for multiple tokens produced by the tokenizer.
      post_log_softmax (:obj:`bool`, optional): Whether to apply log softmax post processing on label_logits. Default to True.
code: def __init__(
      self,
      tokenizer: PreTrainedTokenizer,
      classes: Optional[List] = None,
      num_classes: Optional[Sequence[str]] = None,
      label_words: Optional[
          Union[Sequence[str], Mapping[str, str]]
      ] = None,
      prefix: Optional[str] = " ",
      multi_token_handler: Optional[str] = "first",
      post_log_softmax: Optional[bool] = True,
  ):
      super().__init__(
          tokenizer=tokenizer, num_classes=num_classes, classes=classes
      )
      self.prefix = prefix
      self.multi_token_handler = multi_token_handler
      self.label_words = label_words
      self.post_log_softmax = post_log_softmax
  
imports: import json
  from transformers.tokenization_utils import PreTrainedTokenizer
  from yacs.config import CfgNode
  from openprompt.data_utils import InputFeatures
  import re
  from openprompt import Verbalizer
  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 ManualVerbalizer object from inherited base classes: Verbalizer with example: obj = ManualVerbalizer(tokenizer, classes, num_classes, label_words, prefix, multi_token_handler, post_log_softmax)