xgboost::linalg Namespace Reference

Copyright 2021-2023 by XGBoost Contributors. More...

Data Structures
class	Tensor
	A tensor storage. More...
class	TensorView
	A tensor view with static type and dimension. More...

Typedefs
template<typename T >
using	VectorView = TensorView< T, 1 >
	A view over a vector, specialization of Tensor.
template<typename T >
using	MatrixView = TensorView< T, 2 >
	A view over a matrix, specialization of Tensor.
template<typename T >
using	Matrix = Tensor< T, 2 >
template<typename T >
using	Vector = Tensor< T, 1 >

Enumerations
enum	Order : std::uint8_t { kC , kF }

Functions
constexpr detail::AllTag	All ()
	Specify all elements in the axis for slicing.
template<typename I >
constexpr detail::RangeTag< I >	Range (I beg, I end)
	Specify a range of elements in the axis for slicing.
template<typename Container , typename... S, std::enable_if_t<!common::detail::IsSpan< Container >::value &&!std::is_pointer_v< Container > > * = nullptr>
auto	MakeTensorView (Context const *ctx, Container &data, S &&...shape)
	Constructor for automatic type deduction.
template<typename T , typename... S>
LINALG_HD auto	MakeTensorView (std::int32_t device, common::Span< T > data, S &&...shape)
template<typename T , typename... S>
auto	MakeTensorView (Context const *ctx, common::Span< T > data, S &&...shape)
template<typename T , typename... S>
auto	MakeTensorView (Context const *ctx, HostDeviceVector< T > *data, S &&...shape)
template<typename T , typename... S>
auto	MakeTensorView (Context const *ctx, HostDeviceVector< T > const *data, S &&...shape)
template<size_t D>
LINALG_HD auto	UnravelIndex (size_t idx, common::Span< size_t const, D > shape)
	Turns linear index into multi-dimension index.
template<size_t D>
LINALG_HD auto	UnravelIndex (size_t idx, std::size_t const (&shape)[D])
template<typename... S>
LINALG_HD auto	UnravelIndex (std::size_t idx, S... shape)
template<typename T >
auto	MakeVec (T *ptr, size_t s, int32_t device=-1)
	Create a vector view from contigious memory.
template<typename T >
auto	MakeVec (HostDeviceVector< T > *data)
template<typename T >
auto	MakeVec (HostDeviceVector< T > const *data)
template<typename T , int32_t D>
Json	ArrayInterface (TensorView< T const, D > const &t)
	Array Interface defined by numpy.
template<typename T , int32_t D>
Json	ArrayInterface (TensorView< T, D > const &t)
	Same as const version, but returns non-readonly data pointer.
template<typename T , int32_t D>
auto	ArrayInterfaceStr (TensorView< T const, D > const &t)
	Return string representation of array interface.
template<typename T , int32_t D>
auto	ArrayInterfaceStr (TensorView< T, D > const &t)
template<typename T , typename... Index>
auto	Empty (Context const *ctx, Index &&...index)
	Create an array without initialization.
template<typename T , typename... Index>
auto	Constant (Context const *ctx, T v, Index &&...index)
	Create an array with value v.
template<typename T , typename... Index>
auto	Zeros (Context const *ctx, Index &&...index)
	Like np.zeros, return a new array of given shape and type, filled with zeros.
template<typename T , int32_t D>
void	Stack (Tensor< T, D > *l, Tensor< T, D > const &r)
template<typename T , int32_t D, typename Fn >
void	ElementWiseTransformHost (linalg::TensorView< T, D > t, int32_t n_threads, Fn &&fn)
template<typename T , int32_t D, typename Fn >
void	ElementWiseKernelHost (linalg::TensorView< T, D > t, int32_t n_threads, Fn &&fn)
template<typename T , int32_t D, typename Fn >
void	ElementWiseKernelDevice (linalg::TensorView< T, D >, Fn &&, void *=nullptr)
template<typename T , int32_t D, typename Fn >
void	ElementWiseTransformDevice (linalg::TensorView< T, D >, Fn &&, void *=nullptr)
template<typename T , int32_t D, typename Fn >
void	ElementWiseKernel (Context const *ctx, linalg::TensorView< T, D > t, Fn &&fn)
template<typename T , std::int32_t kDim>
auto	cbegin (TensorView< T, kDim > const &v)
template<typename T , std::int32_t kDim>
auto	cend (TensorView< T, kDim > const &v)
template<typename T , std::int32_t kDim>
auto	begin (TensorView< T, kDim > &v)
template<typename T , std::int32_t kDim>
auto	end (TensorView< T, kDim > &v)
auto	MakeMatrixFromTest (HostDeviceVector< float > *storage, std::size_t n_rows, std::size_t n_cols)
	TEST (Linalg, MatrixView)
	TEST (Linalg, VectorView)
	TEST (Linalg, TensorView)
	TEST (Linalg, Tensor)
	TEST (Linalg, Empty)
	TEST (Linalg, ArrayInterface)
	TEST (Linalg, Popc)
	TEST (Linalg, Stack)
	TEST (Linalg, FOrder)

Detailed Description

Copyright 2021-2023 by XGBoost Contributors.

Typedef Documentation

MatrixView

template<typename T >

using xgboost::linalg::MatrixView = typedef TensorView<T, 2>

A view over a matrix, specialization of Tensor.

Template Parameters

T	data type of matrix

VectorView

template<typename T >

using xgboost::linalg::VectorView = typedef TensorView<T, 1>

A view over a vector, specialization of Tensor.

Template Parameters

T	data type of vector

Function Documentation

ArrayInterface()

template<typename T , int32_t D>

Json xgboost::linalg::ArrayInterface

(

TensorView< T const, D > const &

t

)

Array Interface defined by numpy.

stream is optionally included when data is on CUDA device.

MakeVec()

template<typename T >

auto xgboost::linalg::MakeVec	(	T *	ptr,
		size_t	s,
		int32_t	device = -1
	)

Create a vector view from contigious memory.

Parameters

ptr	Pointer to the contigious memory.
s	Size of the vector.
device	(optional) Device ordinal, default to be host.

UnravelIndex()

template<size_t D>

LINALG_HD auto xgboost::linalg::UnravelIndex	(	size_t	idx,
		common::Span< size_t const, D >	shape
	)

Turns linear index into multi-dimension index.

Similar to numpy unravel.