def forward(
        self,
        src_tokens,
        src_lengths,
        prev_output_tokens,
        return_all_hiddens: bool = True,
        features_only: bool = False,
        alignment_layer: Optional[int] = None,
        alignment_heads: Optional[int] = None,
    ):
        """
        Run the forward pass for an encoder-decoder model.

        Copied from the base class, but without ``**kwargs``,
        which are not supported by TorchScript.
        """
        encoder_out = self.encoder(
            src_tokens, src_lengths=src_lengths, return_all_hiddens=return_all_hiddens
        )
        decoder_out = self.decoder(
            prev_output_tokens,
            encoder_out=encoder_out,
            features_only=features_only,
            alignment_layer=alignment_layer,
            alignment_heads=alignment_heads,
            src_lengths=src_lengths,
            return_all_hiddens=return_all_hiddens,
        )
        return decoder_out

        Run the forward pass for an encoder-decoder model.

        Copied from the base class, but without ``**kwargs``,
        which are not supported by TorchScript.
        
understand_icl/fairseq/fairseq/models/transformer/transformer_base.py