class_docstr: Base class for all the templates.
  Most of methods are abstract, with some exceptions to hold the common methods for all template, such as ``loss_ids``, ``save``, ``load``.
  
  Args:
      tokenizer (:obj:`PreTrainedTokenizer`): A tokenizer to appoint the vocabulary and the tokenization strategy.
      placeholder_mapping (:obj:`dict`): A place holder to represent the original input text.
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docstr: Post processing the outputs of language models according
  to the need of template. Most templates don't need post processing,
  The template like SoftTemplate, which appends soft template as a module
  (rather than a sequence of input tokens) to the input,
  should remove the outputs on these positions to keep the seq_len the same
docstr_tok: ["Post","processing","the","outputs","of","language","models","according","to","the","need","of","template",".","Most","templates","do","n't","need","post","processing",",","The","template","like","SoftTemplate",",","which","appends","soft","template","as","a","module","(","rather","than","a","sequence","of","input","tokens",")","to","the","input",",","should","remove","the","outputs","on","these","positions","to","keep","the","seq_len","the","same"]
code: def post_processing_outputs(self, outputs):
      r"""Post processing the outputs of language models according
      to the need of template. Most templates don't need post processing,
      The template like SoftTemplate, which appends soft template as a module
      (rather than a sequence of input tokens) to the input,
      should remove the outputs on these positions to keep the seq_len the same
      """
      return outputs
  
imports: from abc import abstractmethod
  from typing import *
  import paddle
  from data_utils import InputExample
label_desc: Use image node_id 10 for calling the ErnieManualTemplate obj's underlying member method code with example usage: obj.post_processing_outputs(outputs) and returns: outputs