    def add_args(parser):
        """Add model-specific arguments to the parser."""
        parser.add_argument(
            "--input-feat-per-channel",
            type=int,
            metavar="N",
            help="encoder input dimension per input channel",
        )
        parser.add_argument(
            "--activation-fn",
            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-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(
            "--decoder-output-dim",
            type=int,
            metavar="N",
            help="decoder output dimension (extra linear layer if different from decoder embed dim)",
        )
        parser.add_argument(
            "--share-decoder-input-output-embed",
            action="store_true",
            help="share decoder input and output embeddings",
        )
        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-encoder-from",
            type=str,
            metavar="STR",
            help="model to take encoder weights from (for initialization)",
        )
        parser.add_argument(
            "--load-pretrained-decoder-from",
            type=str,
            metavar="STR",
            help="model to take decoder weights from (for initialization)",
        )
        parser.add_argument(
            "--conv-out-channels",
            type=int,
            metavar="INT",
            help="the number of output channels of conv layer",
        )
Add model-specific arguments to the parser.
fairseq/models/speech_to_text/convtransformer.py