def _split_encoder_out(self, encoder_out, incremental_state):
        """Split and transpose encoder outputs.

        This is cached when doing incremental inference.
        """
        cached_result = utils.get_incremental_state(
            self, incremental_state, "encoder_out"
        )
        if cached_result is not None:
            return cached_result

        # transpose only once to speed up attention layers
        encoder_a, encoder_b = encoder_out
        encoder_a = encoder_a.transpose(1, 2).contiguous()
        result = (encoder_a, encoder_b)

        if incremental_state is not None:
            utils.set_incremental_state(self, incremental_state, "encoder_out", result)
        return result
Split and transpose encoder outputs.

        This is cached when doing incremental inference.
        
understand_icl/fairseq/fairseq/models/fconv.py