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., type=float, metavar='D',
                            help='dropout probability for attention weights')
        parser.add_argument('--relu-dropout', default=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: options.eval_str_list(x, int),
                            help='list of kernel size (default: "[3,7,15,31,31,31]")')
        parser.add_argument('--decoder-glu', type=options.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=options.eval_bool)
        parser.add_argument('--weight-dropout', type=float, metavar='D',
                            help='dropout probability for conv weights')
Add model-specific arguments to the parser.
infoxlm/fairseq/fairseq/models/lightconv_lm.py