def add_args(parser):
        """Add model-specific arguments to the parser."""
        # wav2vec encoder
        Wav2VecEncoderWithAdaptor.add_args(parser)
        # add_decoder_args(parser)
        # mbart Transformer
        parser.add_argument(
            "--activation-fn",
            type=str,
            default="relu",
            choices=utils.get_available_activation_fns(),
            help="activation function to use",
        )

        parser.add_argument(
            "--mbart-dropout", type=float, metavar="D", help="dropout probability"
        )
        parser.add_argument(
            "--mbart-attention-dropout",
            type=float,
            metavar="D",
            help="dropout probability for attention weights",
        )
        parser.add_argument(
            "--mbart-activation-dropout",
            type=float,
            metavar="D",
            help="dropout probability after activation in FFN.",
        )

        parser.add_argument(
            "--encoder-embed-dim",
            type=int,
            metavar="N",
            help="encoder embedding dimension",
        )
        parser.add_argument(
            "--encoder-ffn-embed-dim",
            type=int,
            metavar="N",
            help="encoder embedding dimension for FFN",
        )
        parser.add_argument(
            "--encoder-layers", type=int, metavar="N", help="num encoder layers"
        )
        parser.add_argument(
            "--encoder-attention-heads",
            type=int,
            metavar="N",
            help="num encoder attention heads",
        )
        parser.add_argument(
            "--encoder-normalize-before",
            action="store_true",
            help="apply layernorm before each encoder block",
        )

        parser.add_argument(
            "--decoder-embed-dim",
            type=int,
            metavar="N",
            help="decoder embedding dimension",
        )
        parser.add_argument(
            "--decoder-ffn-embed-dim",
            type=int,
            metavar="N",
            help="decoder embedding dimension for FFN",
        )
        parser.add_argument(
            "--decoder-layers", type=int, metavar="N", help="num decoder layers"
        )
        parser.add_argument(
            "--decoder-attention-heads",
            type=int,
            metavar="N",
            help="num decoder attention heads",
        )
        parser.add_argument(
            "--decoder-normalize-before",
            action="store_true",
            help="apply layernorm before each decoder block",
        )
        parser.add_argument(
            "--layernorm-embedding",
            action="store_true",
            help="add layernorm to embedding",
        )
        parser.add_argument(
            "--no-scale-embedding",
            action="store_true",
            help="if True, dont scale embeddings",
        )
        parser.add_argument(
            "--load-pretrained-mbart-from",
            type=str,
            metavar="STR",
            help="model to take text encoder decoder weights from (for initialization)",
        )
        # parser.add_argument("--finetune-w2v-params", type=str, metavar="STR",
        #                    help="comma-separated param strings to finetune.")
        parser.add_argument(
            "--finetune-mbart-decoder-params",
            type=str,
            metavar="STR",
            help="comma-separated param strings to finetune.",
        )
        parser.add_argument(
            "--finetune-mbart-encoder-params",
            type=str,
            metavar="STR",
            help="comma-separated param strings to finetune.",
        )
        parser.add_argument(
            "--skip-encoder-projection",
            action="store_true",
            help="skip the projection layer in encoder",
        )

        parser.add_argument(
            "--enc-grad-mult",
            type=float,
            metavar="V",
            default=1.0,
            help="multiply enc1 and enc2 gradient by V",
        )
        parser.add_argument(
            "--enc2-along-grad-mult",
            type=float,
            metavar="V",
            default=1.0,
            help="multiply enc2 gradient by V if only enc2 is used",
        )
        parser.add_argument(
            "--text-input-cost-ratio",
            type=float,
            default=1.0,
            metavar="V",
            help="text input cost ratio relative to speech input cost",
        )
        parser.add_argument(
            "--stack-w2v-mbart-encoder",
            action="store_true",
            help="stack w2v and mbart encoder",
        )
        parser.add_argument(
            "--stack-w2v-mbart-nonorm-encoder",
            action="store_true",
            help="stack w2v and mbart encoder",
        )
        parser.add_argument(
            "--no-final-norm-decoder", action="store_true", help="no layer norm"
        )
        parser.add_argument(
            "--drop-w2v-layers",
            type=int,
            default=0,
            metavar="N",
            help="drop w2v encoder layers",
        )

        parser.add_argument(
            "--share-w2v-text-encoder",
            action="store_true",
            help="share w2v encoder layers with text encoder",
        )
        parser.add_argument(
            "--shared-w2v-layers",
            type=int,
            default=0,
            metavar="N",
            help="shared encoder layers from w2v encoder",
        )
Add model-specific arguments to the parser.
understand_icl/fairseq/examples/speech_text_joint_to_text/models/s2t_dualinputxmtransformer.py