def METHOD_NAME(self, value: torch.Tensor) -> 'ReIDDataSample':
    """Set score of ``gt_label``."""
    assert isinstance(value, torch.Tensor), \
        f'The value should be a torch.Tensor but got {type(value)}.'
    assert value.ndim == 1, \
        f'The dims of value should be 1, but got {value.ndim}.'
    if 'num_classes' in self:
        assert value.size(0) == self.num_classes, \
            f"The length of value ({value.size(0)}) doesn't "\
            f'match the num_classes ({self.num_classes}).'
        metainfo = {'num_classes': self.num_classes}
    else:
        metainfo = {'num_classes': value.size(0)}
    if 'gt_label' in self:  # setting for the second time
        self.gt_label.score = value
    else:  # setting for the first time
        self.gt_label = LabelData(score=value, metainfo=metainfo)
    return self