def add_args()

in fairseq/models/lightconv.py [0:0]

• 168 lines of code
• 1 McCabe index (conditional complexity)

    def add_args(parser):
        """Add model-specific arguments to the parser."""
        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(
            "--relu-dropout",
            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(
            "--encoder-embed-path",
            type=str,
            metavar="STR",
            help="path to pre-trained encoder embedding",
        )
        parser.add_argument(
            "--encoder-embed-dim",
            type=int,
            metavar="N",
            help="encoder embedding dimension",
        )
        parser.add_argument(
            "--encoder-conv-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 or LightConv/DynamicConv heads",
        )
        parser.add_argument(
            "--encoder-normalize-before",
            action="store_true",
            help="apply layernorm before each encoder block",
        )
        parser.add_argument(
            "--encoder-learned-pos",
            action="store_true",
            help="use learned positional embeddings in the encoder",
        )
        parser.add_argument(
            "--decoder-embed-path",
            type=str,
            metavar="STR",
            help="path to pre-trained decoder embedding",
        )
        parser.add_argument(
            "--decoder-embed-dim",
            type=int,
            metavar="N",
            help="decoder embedding dimension",
        )
        parser.add_argument(
            "--decoder-conv-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 or LightConv/DynamicConv heads",
        )
        parser.add_argument(
            "--decoder-learned-pos",
            action="store_true",
            help="use learned positional embeddings in the decoder",
        )
        parser.add_argument(
            "--decoder-normalize-before",
            action="store_true",
            help="apply layernorm before each decoder block",
        )
        parser.add_argument(
            "--share-decoder-input-output-embed",
            action="store_true",
            help="share decoder input and output embeddings",
        )
        parser.add_argument(
            "--share-all-embeddings",
            action="store_true",
            help="share encoder, decoder and output embeddings"
            " (requires shared dictionary and embed dim)",
        )
        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",
        )

        """LightConv and DynamicConv arguments"""
        parser.add_argument(
            "--encoder-kernel-size-list",
            type=lambda x: utils.eval_str_list(x, int),
            help='list of kernel size (default: "[3,7,15,31,31,31,31]")',
        )
        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(
            "--encoder-glu", type=utils.eval_bool, help="glu after in proj"
        )
        parser.add_argument(
            "--decoder-glu", type=utils.eval_bool, help="glu after in proj"
        )
        parser.add_argument(
            "--encoder-conv-type",
            default="dynamic",
            type=str,
            choices=["dynamic", "lightweight"],
            help="type of convolution",
        )
        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",
        )