    def update_constraints(self, active_hypos: Tensor):
        """
        Updates the constraint states by selecting the beam items that are retained.
        This is called at each time step of sequence_generator._generate() when
        the set of 2 * {beam_size} candidate hypotheses are reduced to the beam size.

        Args:
            active_hypos: (batch size, beam size)
              list of integers denoting, for each sentence, which beam candidate items
              should be kept.
        """
        pass
Updates the constraint states by selecting the beam items that are retained.
This is called at each time step of sequence_generator._generate() when
the set of 2 * {beam_size} candidate hypotheses are reduced to the beam size.

Args:
active_hypos: (batch size, beam size)
list of integers denoting, for each sentence, which beam candidate items
should be kept.
fairseq/models/speech_dlm/sequence_generator/multichannel_search.py