docstr: Stub functions for adding application specific constraint checks on
  the candidates being generated during beam search. This and the below
  stub functions can be implemented in a child class without needing to
  touch the actual beam search code
docstr_tok: ["Stub","functions","for","adding","application","specific","constraint","checks","on","the","candidates","being","generated","during","beam","search",".","This","and","the","below","stub","functions","can","be","implemented","in","a","child","class","without","needing","to","touch","the","actual","beam","search","code"]
code: def _build_constraints(self, src_tokens, beam_size):
      """
      Stub functions for adding application specific constraint checks on
      the candidates being generated during beam search. This and the below
      stub functions can be implemented in a child class without needing to
      touch the actual beam search code
      """
      pass
  
imports: import math
  from typing import List, Tuple
  import torch
  from fairseq import search, utils
  from fairseq.models import FairseqIncrementalDecoder
  from pytorch_translate import utils
  from torch import Tensor
label_desc: Use image node_id 6 for calling the SequenceGenerator obj's underlying member method code with example usage: obj._build_constraints(src_tokens, beam_size) without return types