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: Use weight to aggregate the logits of label words.
  
  Args:
      label_words_logits(:obj:`torch.Tensor`): The logits of the label words.
  
  Returns:
      :obj:`torch.Tensor`: The aggregated logits from the label words.
docstr_tok: ["Use","weight","to","aggregate","the","logits","of","label","words",".","Args",":","label_words_logits","(",":","obj",":","`","torch.Tensor","`",")",":","The","logits","of","the","label","words",".","Returns",":",":","obj",":","`","torch.Tensor","`",":","The","aggregated","logits","from","the","label","words","."]
code: def aggregate(self, label_words_logits: torch.Tensor) -> torch.Tensor:
      r"""Use weight to aggregate the logits of label words.
  
      Args:
          label_words_logits(:obj:`torch.Tensor`): The logits of the label words.
  
      Returns:
          :obj:`torch.Tensor`: The aggregated logits from the label words.
      """
      label_words_logits = (
          label_words_logits * self.label_words_mask
      ).sum(-1) / self.label_words_mask.sum(-1)
      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 8 for calling the ManualVerbalizer obj's underlying member method code with example usage: obj.aggregate(label_words_logits) and returns: label_words_logits