    def add_args(parser):
        """Add model-specific arguments to the parser."""
        parser.add_argument(
            "--dropout",
            default=0.1,
            type=float,
            metavar="D",
            help="dropout probability",
        )
        parser.add_argument(
            "--attention-dropout",
            default=0.0,
            type=float,
            metavar="D",
            help="dropout probability for attention weights",
        )
        parser.add_argument(
            "--relu-dropout",
            default=0.0,
            type=float,
            metavar="D",
            help="dropout probability after ReLU in FFN",
        )
        parser.add_argument(
            "--input-dropout",
            type=float,
            metavar="D",
            help="dropout probability of the inputs",
        )
        parser.add_argument(
            "--decoder-embed-dim",
            type=int,
            metavar="N",
            help="decoder embedding dimension",
        )
        parser.add_argument(
            "--decoder-output-dim",
            type=int,
            metavar="N",
            help="decoder output dimension",
        )
        parser.add_argument(
            "--decoder-input-dim", type=int, metavar="N", help="decoder input 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 or LightConv/DynamicConv heads",
        )
        parser.add_argument(
            "--decoder-normalize-before",
            default=False,
            action="store_true",
            help="apply layernorm before each decoder block",
        )
        parser.add_argument(
            "--adaptive-softmax-cutoff",
            metavar="EXPR",
            help="comma separated list of adaptive softmax cutoff points. "
            "Must be used with adaptive_loss criterion",
        )
        parser.add_argument(
            "--adaptive-softmax-dropout",
            type=float,
            metavar="D",
            help="sets adaptive softmax dropout for the tail projections",
        )
        parser.add_argument(
            "--adaptive-softmax-factor",
            type=float,
            metavar="N",
            help="adaptive input factor",
        )
        parser.add_argument(
            "--no-token-positional-embeddings",
            default=False,
            action="store_true",
            help="if set, disables positional embeddings (outside self attention)",
        )
        parser.add_argument(
            "--share-decoder-input-output-embed",
            default=False,
            action="store_true",
            help="share decoder input and output embeddings",
        )
        parser.add_argument(
            "--character-embeddings",
            default=False,
            action="store_true",
            help="if set, uses character embedding convolutions to produce token embeddings",
        )
        parser.add_argument(
            "--character-filters",
            type=str,
            metavar="LIST",
            default="[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]",
            help="size of character embeddings",
        )
        parser.add_argument(
            "--character-embedding-dim",
            type=int,
            metavar="N",
            default=4,
            help="size of character embeddings",
        )
        parser.add_argument(
            "--char-embedder-highway-layers",
            type=int,
            metavar="N",
            default=2,
            help="number of highway layers for character token embeddder",
        )
        parser.add_argument(
            "--adaptive-input",
            default=False,
            action="store_true",
            help="if set, uses adaptive input",
        )
        parser.add_argument(
            "--adaptive-input-factor",
            type=float,
            metavar="N",
            help="adaptive input factor",
        )
        parser.add_argument(
            "--adaptive-input-cutoff",
            metavar="EXPR",
            help="comma separated list of adaptive input cutoff points.",
        )
        parser.add_argument(
            "--tie-adaptive-weights",
            action="store_true",
            help="if set, ties the weights of adaptive softmax and adaptive input",
        )
        parser.add_argument(
            "--tie-adaptive-proj",
            action="store_true",
            help="if set, ties the projection weights of adaptive softmax and adaptive input",
        )
        parser.add_argument(
            "--decoder-learned-pos",
            action="store_true",
            help="use learned positional embeddings in the decoder",
        )

        """LightConv and DynamicConv arguments"""
        parser.add_argument(
            "--decoder-kernel-size-list",
            type=lambda x: utils.eval_str_list(x, int),
            help='list of kernel size (default: "[3,7,15,31,31,31]")',
        )
        parser.add_argument(
            "--decoder-glu", type=utils.eval_bool, help="glu after in proj"
        )
        parser.add_argument(
            "--decoder-conv-type",
            default="dynamic",
            type=str,
            choices=["dynamic", "lightweight"],
            help="type of convolution",
        )
        parser.add_argument("--weight-softmax", default=True, type=utils.eval_bool)
        parser.add_argument(
            "--weight-dropout",
            type=float,
            metavar="D",
            help="dropout probability for conv weights",
        )
Add model-specific arguments to the parser.
fairseq/models/lightconv_lm.py