    def add_args(parser):
        """Add task-specific arguments to the parser."""
        parser.add_argument(
            "data",
            help="colon separated path to data directories list, \
                            will be iterated upon during epochs in round-robin manner",
        )
        parser.add_argument(
            "--sample-break-mode",
            default="complete",
            choices=["none", "complete", "complete_doc", "eos"],
            help='If omitted or "none", fills each sample with tokens-per-sample '
            'tokens. If set to "complete", splits samples only at the end '
            "of sentence, but may include multiple sentences per sample. "
            '"complete_doc" is similar but respects doc boundaries. '
            'If set to "eos", includes only one sentence per sample.',
        )
        parser.add_argument(
            "--tokens-per-sample",
            default=512,
            type=int,
            help="max number of total tokens over all segments "
            "per sample for BERT dataset",
        )
        parser.add_argument(
            "--mask-prob",
            default=0.15,
            type=float,
            help="probability of replacing a token with mask",
        )
        parser.add_argument(
            "--leave-unmasked-prob",
            default=0.1,
            type=float,
            help="probability that a masked token is unmasked",
        )
        parser.add_argument(
            "--random-token-prob",
            default=0.1,
            type=float,
            help="probability of replacing a token with a random token",
        )
        parser.add_argument(
            "--freq-weighted-replacement",
            action="store_true",
            help="sample random replacement words based on word frequencies",
        )
        parser.add_argument(
            "--mask-whole-words",
            default=False,
            action="store_true",
            help="mask whole words; you may also want to set --bpe",
        )
        parser.add_argument(
            "--multilang-sampling-alpha",
            type=float,
            default=1.0,
            help="smoothing alpha for sample rations across multiple datasets",
        )
Add task-specific arguments to the parser.
fairseq/tasks/multilingual_masked_lm.py