    def __call__(
        self, predictions: torch.Tensor, gold_labels: torch.Tensor, mask: Optional[torch.BoolTensor]
    ):
        """
        # Parameters

        predictions : `torch.Tensor`, required.
            A tensor of predictions.
        gold_labels : `torch.Tensor`, required.
            A tensor corresponding to some gold label to evaluate against.
        mask : `torch.BoolTensor`, optional (default = `None`).
            A mask can be passed, in order to deal with metrics which are
            computed over potentially padded elements, such as sequence labels.
        """
        raise NotImplementedError
# Parameters

predictions : `torch.Tensor`, required.
A tensor of predictions.
gold_labels : `torch.Tensor`, required.
A tensor corresponding to some gold label to evaluate against.
mask : `torch.BoolTensor`, optional (default = `None`).
A mask can be passed, in order to deal with metrics which are
computed over potentially padded elements, such as sequence labels.
allennlp/training/metrics/metric.py