    def add_args(parser):
        """Add model-specific arguments to the parser."""
        # Arguments related to dropout
        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(
            "--act-dropout",
            type=float,
            metavar="D",
            help="dropout probability after" " activation in FFN",
        )

        # Arguments related to hidden states and self-attention
        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",
        )

        # Arguments related to input and output embeddings
        parser.add_argument(
            "--encoder-embed-dim",
            type=int,
            metavar="N",
            help="encoder embedding dimension",
        )
        parser.add_argument(
            "--share-encoder-input-output-embed",
            action="store_true",
            help="share encoder input" " and output embeddings",
        )
        parser.add_argument(
            "--encoder-learned-pos",
            action="store_true",
            help="use learned positional embeddings in the encoder",
        )
        parser.add_argument(
            "--no-token-positional-embeddings",
            action="store_true",
            help="if set, disables positional embeddings" " (outside self attention)",
        )
        parser.add_argument(
            "--num-segment", type=int, metavar="N", help="num segment in the input"
        )
        parser.add_argument(
            "--max-positions", type=int, help="number of positional embeddings to learn"
        )

        # Arguments related to sentence level prediction
        parser.add_argument(
            "--sentence-class-num",
            type=int,
            metavar="N",
            help="number of classes for sentence task",
        )
        parser.add_argument(
            "--sent-loss",
            action="store_true",
            help="if set," " calculate sentence level predictions",
        )

        # Arguments related to parameter initialization
        parser.add_argument(
            "--apply-bert-init",
            action="store_true",
            help="use custom param initialization for BERT",
        )

        # misc params
        parser.add_argument(
            "--activation-fn",
            choices=utils.get_available_activation_fns(),
            help="activation function to use",
        )
        parser.add_argument(
            "--pooler-activation-fn",
            choices=utils.get_available_activation_fns(),
            help="Which activation function to use for pooler layer.",
        )
        parser.add_argument(
            "--encoder-normalize-before",
            action="store_true",
            help="apply layernorm before each encoder block",
        )
Add model-specific arguments to the parser.
fairseq/models/masked_lm.py