Detailed implementation of `clustered_sparse_dot_product`

[HanielF]

Could you explain the detailed implementation of clustered_sparse_dot_product in _topk_attention function of ImprovedClusteredAttention class.
I feel a little confused about how to compute QK with the below code snippet

class ImprovedClusteredAttention(Module):
    ......

    def _topk_attention(self, Q, K, V,
                        clusters, counts,
                        topk, topk_values,
                        A_bottomk, softmax_temp,
                        query_lengths):
        N, H, L, E = Q.shape
        _, _, S, _ = K.shape
        _, _, C, k = topk.shape

        # We need to pass the output tensor to initialize to 0
        QK = clustered_sparse_dot_product(
            Q, K, topk,
            clusters, counts,
            query_lengths._lengths.int()
        )
      
      ......