docstr: Get the logits of label words.
  
  Args:
      batch (:obj:`Union[Dict, InputFeatures]`): The original batch
  
  Returns:
      :obj:`paddle.Tensor`: The logits of the label words (obtained by the current verbalizer).
docstr_tok: ["Get","the","logits","of","label","words",".","Args",":","batch","(",":","obj",":","`","Union","[","Dict",",","InputFeatures","]","`",")",":","The","original","batch","Returns",":",":","obj",":","`","paddle.Tensor","`",":","The","logits","of","the","label","words","(","obtained","by","the","current","verbalizer",")","."]
code: def forward(self, batch):
      r"""
      Get the logits of label words.
  
      Args:
          batch (:obj:`Union[Dict, InputFeatures]`): The original batch
  
      Returns:
          :obj:`paddle.Tensor`: The logits of the label words (obtained by the current verbalizer).
      """
      outputs = self.prompt_model(batch)
      outputs = self.verbalizer.gather_outputs(outputs)
  
      if isinstance(outputs, tuple):
          outputs_at_mask = [
              self.extract_at_mask(output, batch) for output in outputs
          ]
      else:
          outputs_at_mask = self.extract_at_mask(outputs, batch)
      label_words_logits = self.verbalizer.process_outputs(
          outputs_at_mask, batch=batch
      )
      return label_words_logits
  
imports: from typing import *
  from utils import round_list, signature
  import paddle
label_desc: Use image node_id 6 for calling the ErniePromptforClassification obj's underlying member method code with example usage: obj.forward(batch) and returns: label_words_logits