def add_args(parser):
        """Add model-specific arguments to the parser."""
        # encoder 1: S2TTransformerEncoder for speech
        parser.add_argument(
            "--conv-kernel-sizes",
            type=str,
            metavar="N",
            help="kernel sizes of Conv1d subsampling layers",
        )
        parser.add_argument(
            "--conv-channels",
            type=int,
            metavar="N",
            help="# of channels in Conv1d subsampling layers",
        )
        parser.add_argument(
            "--enc-output-dim",
            type=int,
            metavar="N",
            help="""
                encoder output dimension, can be None. If specified, projecting the
                transformer output to the specified dimension""",
        )
        # standard Transformer
        parser.add_argument(
            "--activation-fn",
            type=str,
            default="relu",
            choices=utils.get_available_activation_fns(),
            help="activation function to use",
        )
        parser.add_argument(
            "--dropout", type=float, metavar="D", help="dropout probability"
        )
        parser.add_argument(
            "--attention-dropout",
            type=float,
            metavar="D",
            help="dropout probability for attention weights",
        )
        parser.add_argument(
            "--activation-dropout",
            "--relu-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-text-embed-dim",
            type=int,
            metavar="N",
            help="encoder text embedding dimension",
        )
        parser.add_argument(
            "--encoder-ffn-embed-dim",
            type=int,
            metavar="N",
            help="encoder embedding dimension for FFN",
        )
        parser.add_argument(
            "--encoder-attention-heads",
            type=int,
            metavar="N",
            help="num encoder attention heads",
        )
        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(
            "--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",
        )
        # non-standard transformer parameters
        parser.add_argument(
            "--speech-encoder-layers",
            type=int,
            metavar="N",
            help="num speech encoder layers",
        )
        parser.add_argument(
            "--text-encoder-layers",
            type=int,
            metavar="N",
            help="num text encoder layers",
        )
        parser.add_argument(
            "--encoder-shared-layers",
            type=int,
            metavar="N",
            help="num shared encoder layers",
        )
        parser.add_argument(
            "--encoder-shared-layer-level",
            type=int,
            metavar="N",
            default=0,
            choices=[0, 1, 2],
            help="share layer level 0: all share 1: all share with separate model 2: share weight but not bias and layernorm",
        )

        parser.add_argument(
            "--decoder-shared-layer-level",
            default=0,
            choices=[0, 1, 2],
            type=int,
            metavar="N",
            help="0: share everything; 1: share everything with different model 2: no share layer_norm and bias",
        )
        ###
        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(
            "--init-scale",
            type=float,
            default=1.0,
            metavar="V",
            help="scale the initial weight by given factor",
        )
        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(
            "--load-pretrain-encoder",
            type=str,
            default="",
            metavar="EXPR",
            help=""" path to the pretrained encoder """,
        )
        parser.add_argument(
            "--load-pretrain-speech-encoder",
            type=str,
            default="",
            metavar="EXPR",
            help=""" path to the pretrained speech encoder """,
        )
        parser.add_argument(
            "--load-pretrain-text-encoder",
            type=str,
            default="",
            metavar="EXPR",
            help=""" path to the pretrained text encoder """,
        )
        parser.add_argument(
            "--load-pretrain-text-encoder-last",
            type=str,
            default="",
            metavar="EXPR",
            help=""" path to the pretrained text encoder """,
        )
        parser.add_argument(
            "--load-pretrain-decoder",
            type=str,
            metavar="EXPR",
            default="",
            help=""" path to the pretrained encoder """,
        )
        parser.add_argument(
            "--add-speech-eos",
            action="store_true",
            help="add eos token at the end of input feature",
        )
        parser.add_argument(
            "--speech-encoder-adapter-type",
            type=str,
            metavar="EXPR",
            default="None",
            choices=["None", "Linear", "MLP"],
            help="add speech encoder adapter",
        )
Add model-specific arguments to the parser.
structured_prompting/fairseq-version/fairseq/examples/speech_text_joint_to_text/models/s2t_dualinputtransformer.py