    def reorder_encoder_out(
        self, encoder_outs: Optional[List[Dict[str, List[Tensor]]]], new_order
    ):
        """
        Reorder encoder output according to *new_order*.

        Args:
            encoder_out: output from the ``forward()`` method
            new_order (LongTensor): desired order

        Returns:
            *encoder_out* rearranged according to *new_order*
        """
        new_outs: List[Dict[str, List[Tensor]]] = []
        if not self.has_encoder():
            return new_outs
        for i, model in enumerate(self.models):
            assert encoder_outs is not None
            new_outs.append(
                model.encoder.reorder_encoder_out(encoder_outs[i], new_order)
            )
        return new_outs
Reorder encoder output according to *new_order*.

Args:
encoder_out: output from the ``forward()`` method
new_order (LongTensor): desired order

Returns:
*encoder_out* rearranged according to *new_order*
fairseq/models/speech_dlm/sequence_generator/multichannel_sequence_generator.py