def update_distances(self, cluster_centers: list[int]) -> None:
        """Update minimum distances given cluster centers.

        Args:
            cluster_centers (list[int]): Indices of cluster centers.
        """
        if cluster_centers:
            centers = self.features[cluster_centers]

            distance = F.pairwise_distance(self.features, centers, p=2).reshape(-1, 1)

            if self.min_distances is None:
                self.min_distances = distance
            else:
                self.min_distances = torch.minimum(self.min_distances, distance)
Update minimum distances given cluster centers.

        Args:
            cluster_centers (list[int]): Indices of cluster centers.
        
src/anomalib/models/components/sampling/k_center_greedy.py