    def add_args(parser):
        """Add model-specific arguments to the parser."""
        # fmt: off
        parser.add_argument('--dropout', type=float, metavar='D',
                            help='dropout probability')
        parser.add_argument('--encoder-embed-dim', type=int, metavar='N',
                            help='encoder embedding dimension')
        parser.add_argument('--encoder-layers', type=str, metavar='EXPR',
                            help='encoder layers [(dim, kernel_size), ...]')
        parser.add_argument('--decoder-embed-dim', type=int, metavar='N',
                            help='decoder embedding dimension')
        parser.add_argument('--decoder-layers', type=str, metavar='EXPR',
                            help='decoder layers [(dim, kernel_size), ...]')
        parser.add_argument('--decoder-out-embed-dim', type=int, metavar='N',
                            help='decoder output embedding dimension')
        parser.add_argument('--decoder-attention', type=str, metavar='EXPR',
                            help='decoder attention [True, ...]')
        parser.add_argument('--self-attention', type=str, metavar='EXPR',
                            help='decoder self-attention layers, ex: [True] + [False]*5')
        parser.add_argument('--multihead-attention-nheads', type=int,
                            help='Number of heads to use in attention')
        parser.add_argument('--multihead-self-attention-nheads', type=int,
                            help='Number of heads to use in self-attention')
        parser.add_argument('--encoder-attention', type=str, metavar='EXPR',
                            help='encoder attention [True, ...]')
        parser.add_argument('--encoder-attention-nheads', type=int,
                            help='Number of heads to use in encoder attention')
        parser.add_argument('--project-input', type=str, metavar='EXPR',
                            help='Use projections in self-attention [True, ...]')
        parser.add_argument('--gated-attention', type=str, metavar='EXPR',
                            help='Use GLU layers in self-attention projections [True, ...]')
        parser.add_argument('--downsample', type=str, metavar='EXPR',
                            help='Use downsampling in self-attention [True, ...]')
        parser.add_argument('--pretrained-checkpoint', metavar='DIR',
                            help='path to load checkpoint from pretrained model')
        parser.add_argument('--pretrained', type=str, metavar='EXPR',
                            help='use pretrained model when training [True, ...]')
Add model-specific arguments to the parser.
fairseq/models/fconv_self_att.py