ML::HDBSCAN::detail::Utils Namespace Reference

Functions
template<typename value_idx , typename value_t , typename CUBReduceFunc >
void	cub_segmented_reduce (const value_t *in, value_t *out, int n_segments, const value_idx *offsets, cudaStream_t stream, CUBReduceFunc cub_reduce_func)
template<typename value_idx , typename value_t >
Common::CondensedHierarchy< value_idx, value_t >	make_cluster_tree (const raft::handle_t &handle, Common::CondensedHierarchy< value_idx, value_t > &condensed_tree)
template<typename value_idx , typename value_t >
void	parent_csr (const raft::handle_t &handle, Common::CondensedHierarchy< value_idx, value_t > &condensed_tree, value_idx *sorted_parents, value_idx *indptr)
template<typename value_idx , typename value_t >
void	normalize (value_t *data, value_idx n, size_t m, cudaStream_t stream)
template<typename value_idx , typename value_t >
void	softmax (const raft::handle_t &handle, value_t *data, value_idx n, size_t m)

Function Documentation

cub_segmented_reduce()

template<typename value_idx , typename value_t , typename CUBReduceFunc >

void ML::HDBSCAN::detail::Utils::cub_segmented_reduce	(	const value_t *	in,
		value_t *	out,
		int	n_segments,
		const value_idx *	offsets,
		cudaStream_t	stream,
		CUBReduceFunc	cub_reduce_func
	)

Invokes a cub segmented reduce function over a CSR data array using the indptr as segment offsets

Template Parameters

value_idx
value_t
CUBReduceFunc

Parameters

[in]	in	data array (size offsets[n_segments]+1)
[out]	out	output data array (size offsets[n_segmented]+1)
[in]	n_segments	number of segments in offsets array
[in]	offsets	array of segment offsets (size n_segments+1)
[in]	stream	cuda stream for ordering operations
[in]	cub_reduce_func	segmented reduction function

make_cluster_tree()

template<typename value_idx , typename value_t >

Common::CondensedHierarchy<value_idx, value_t> ML::HDBSCAN::detail::Utils::make_cluster_tree	(	const raft::handle_t &	handle,
		Common::CondensedHierarchy< value_idx, value_t > &	condensed_tree
	)

Constructs a cluster tree from a CondensedHierarchy by filtering for only entries with cluster size > 1

Template Parameters

value_idx
value_t

Parameters

[in]	handle	raft handle for resource reuse
[in]	condensed_tree	condensed hierarchy (size n_leaves + n_clusters)

Returns

a new condensed hierarchy with only entries of size > 1

normalize()

template<typename value_idx , typename value_t >

void ML::HDBSCAN::detail::Utils::normalize	(	value_t *	data,
		value_idx	n,
		size_t	m,
		cudaStream_t	stream
	)

parent_csr()

template<typename value_idx , typename value_t >

void ML::HDBSCAN::detail::Utils::parent_csr	(	const raft::handle_t &	handle,
		Common::CondensedHierarchy< value_idx, value_t > &	condensed_tree,
		value_idx *	sorted_parents,
		value_idx *	indptr
	)

Computes a CSR index of sorted parents of condensed tree.

Template Parameters

value_idx
value_t

Parameters

[in]	handle	raft handle for resource reuse
[in,out]	condensed_tree	cluster tree (condensed hierarchy with all nodes of size > 1)
[in]	sorted_parents	parents array sorted
[out]	indptr	CSR indptr of parents array after sort

softmax()

template<typename value_idx , typename value_t >

void ML::HDBSCAN::detail::Utils::softmax	(	const raft::handle_t &	handle,
		value_t *	data,
		value_idx	n,
		size_t	m
	)

Computes softmax (unnormalized). The input is modified in-place. For numerical stability, the maximum value of a row is subtracted from the exponent.

Template Parameters

value_idx
value_t

Parameters

[in]	handle	raft handle for resource reuse
[in]	data	input matrix (size m * n)
[in]	n	number of columns
[out]	m	number of rows