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.
docstr: Project the labels, the return value is the normalized (sum to 1) probs of label words.
  
  Args:
      logits (:obj:`torch.Tensor`): The original logits of label words.
  
  Returns:
      :obj:`torch.Tensor`: The normalized logits of label words
docstr_tok: ["Project","the","labels",",","the","return","value","is","the","normalized","(","sum","to","1",")","probs","of","label","words",".","Args",":","logits","(",":","obj",":","`","torch.Tensor","`",")",":","The","original","logits","of","label","words",".","Returns",":",":","obj",":","`","torch.Tensor","`",":","The","normalized","logits","of","label","words"]
code: def project(
      self,
      logits: torch.Tensor,
      **kwargs,
  ) -> torch.Tensor:
      r"""
      Project the labels, the return value is the normalized (sum to 1) probs of label words.
  
      Args:
          logits (:obj:`torch.Tensor`): The original logits of label words.
  
      Returns:
          :obj:`torch.Tensor`: The normalized logits of label words
      """
  
      label_words_logits = logits[:, self.label_words_ids]
      label_words_logits = self.handle_multi_token(
          label_words_logits, self.words_ids_mask
      )
      label_words_logits -= 10000 * (1 - self.label_words_mask)
      return label_words_logits
  
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 5 for calling the ManualVerbalizer obj's underlying member method code with example usage: obj.project(logits) and returns: label_words_logits