def update(
        self, outputs: torch.Tensor, targets: torch.Tensor
    ) -> Tuple[float, float, float]:
        """
        Update statistics and return metrics intermediate results

        Args:
            outputs: predicted labels
            targets: target labels

        Returns:
            tuple of intermediate metrics: precision, recall, f1 score

        """
        tn, fp, fn, tp, support = super().update(outputs=outputs, targets=targets)
        precision_value, recall_value, f1_value = get_binary_metrics(
            tp=tp, fp=fp, fn=fn, zero_division=self.zero_division
        )
        return precision_value, recall_value, f1_value

        Update statistics and return metrics intermediate results

        Args:
            outputs: predicted labels
            targets: target labels

        Returns:
            tuple of intermediate metrics: precision, recall, f1 score

        
catalyst/metrics/_classification.py