class_docstr: Base class for all the verbalizers.
  
  Args:
      tokenizer (:obj:`PreTrainedTokenizer`): A tokenizer to appoint the vocabulary and the tokenization strategy.
      classes (:obj:`Sequence[str]`): A sequence of classes that need to be projected.
class_docstr_tok: ["Base","class","for","all","the","verbalizers",".","Args",":","tokenizer","(",":","obj",":","`","PreTrainedTokenizer","`",")",":","A","tokenizer","to","appoint","the","vocabulary","and","the","tokenization","strategy",".","classes","(",":","obj",":","`","Sequence","[","str","]","`",")",":","A","sequence","of","classes","that","need","to","be","projected","."]
docstr: This method receives input logits of shape ``[batch_size, vocab_size]``, and use the
  parameters of this verbalizer to project the logits over entire vocab into the
  logits of labels words.
  
  Args:
      logits (:obj:`Tensor`): The logits over entire vocab generated by the pre-trained language model with shape [``batch_size``, ``max_seq_length``, ``vocab_size``]
  
  Returns:
      :obj:`Tensor`: The normalized probs (sum to 1) of each label .
code: def project(self, logits: torch.Tensor, **kwargs) -> torch.Tensor:
      r"""This method receives input logits of shape ``[batch_size, vocab_size]``, and use the
      parameters of this verbalizer to project the logits over entire vocab into the
      logits of labels words.
  
      Args:
          logits (:obj:`Tensor`): The logits over entire vocab generated by the pre-trained language model with shape [``batch_size``, ``max_seq_length``, ``vocab_size``]
  
      Returns:
          :obj:`Tensor`: The normalized probs (sum to 1) of each label .
      """
      raise NotImplementedError
  
imports: from abc import abstractmethod
  import json
  from transformers.file_utils import ModelOutput
  from openprompt.config import convert_cfg_to_dict
  from transformers.utils.dummy_pt_objects import PreTrainedModel
  from openprompt.utils.utils import signature
  from yacs.config import CfgNode
  from openprompt.data_utils import InputFeatures, InputExample
  import torch
  import torch.nn
  from typing import *
  from transformers.tokenization_utils import PreTrainedTokenizer
  from openprompt.utils.logging import logger
  import numpy
  import torch.nn.functional
label_desc: Use image node_id 15 for calling the Verbalizer obj's underlying member method code with example usage: obj.project(logits) without return types