parlai/tasks/light_dialog_wild/agents.py [209:257]:
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            help='type of target in light dialogues',
        )
        agent.add_argument('--light_use_cands', type=int, default=20)
        agent.add_argument('--light_use_clip_cands', type=int, default=10000)
        agent.add_argument('--light_use_speech_prefix', type='bool', default=False)
        agent.add_argument('--light_use_score_cutoff', type=int, default=1)
        agent.add_argument('--light_use_max_score_cutoff', type=int, default=-1)
        agent.add_argument(
            '--light_use_hard_score_cutoff',
            type='bool',
            default=False,
            help='Specify True to **only** include examples with the specified '
            'score cutoff. E.g., if `--light-use-score-cutoff 3`, will only '
            'supply dialogues with scores of 3.',
        )
        agent.add_argument(
            '--light-model-name',
            type=str,
            default=None,
            help='if specified, the model from which chats should be saved',
        )
        agent.add_argument(
            '--light-use-continue-type',
            type=str,
            default='all',
            choices=['all', 'continue', 'exit'],
            help='only use dialogues that had a specific continue outcome, default use all',
        )
        agent.add_argument(
            '--light-use-date-cutoff',
            type=str,
            default=None,
            help=(
                'If specified, only include hobbot conversations that were collected '
                'before this date. Format YYYY-MM-DD.'
            ),
        )
        agent.add_argument(
            '--light-use-person-names-prefix',
            type='bool',
            default=False,
            help="If specified, prefix text with character name",
        )
        agent.add_argument('--light_percent_train_exs', type=float, default=1.0)
        return parser

    def __init__(self, opt, shared=None):
        super().__init__(opt, shared)
        self.id += '_' + self.opt['light_label_type']
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parlai/tasks/light_dialog_wild/agents.py [313:361]:
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            help='type of target in light dialogues',
        )
        agent.add_argument('--light_use_cands', type=int, default=20)
        agent.add_argument('--light_use_clip_cands', type=int, default=10000)
        agent.add_argument('--light_use_speech_prefix', type='bool', default=False)
        agent.add_argument('--light_use_score_cutoff', type=int, default=1)
        agent.add_argument('--light_use_max_score_cutoff', type=int, default=-1)
        agent.add_argument(
            '--light_use_hard_score_cutoff',
            type='bool',
            default=False,
            help='Specify True to **only** include examples with the specified '
            'score cutoff. E.g., if `--light-use-score-cutoff 3`, will only '
            'supply dialogues with scores of 3.',
        )
        agent.add_argument(
            '--light-model-name',
            type=str,
            default=None,
            help='if specified, the model from which chats should be saved',
        )
        agent.add_argument(
            '--light-use-continue-type',
            type=str,
            default='all',
            choices=['all', 'continue', 'exit'],
            help='only use dialogues that had a specific continue outcome, default use all',
        )
        agent.add_argument(
            '--light-use-date-cutoff',
            type=str,
            default=None,
            help=(
                'If specified, only include hobbot conversations that were collected '
                'before this date. Format YYYY-MM-DD.'
            ),
        )
        agent.add_argument(
            '--light-use-person-names-prefix',
            type='bool',
            default=False,
            help="If specified, prefix text with character name",
        )
        agent.add_argument('--light_percent_train_exs', type=float, default=1.0)
        return parser

    def __init__(self, opt, shared=None):
        super().__init__(opt, shared)
        self.id += '_' + self.opt['light_label_type']
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