linalg.h File Reference

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

#include <dmlc/endian.h>
#include <xgboost/base.h>
#include <xgboost/context.h>
#include <xgboost/host_device_vector.h>
#include <xgboost/json.h>
#include <xgboost/span.h>
#include <algorithm>
#include <cassert>
#include <cinttypes>
#include <cstddef>
#include <limits>
#include <string>
#include <tuple>
#include <type_traits>
#include <utility>
#include <vector>

Go to the source code of this file.

Data Structures
struct	xgboost::linalg::detail::ArrayInterfaceHandler
struct	xgboost::linalg::detail::AllTag
struct	xgboost::linalg::detail::IntTag
struct	xgboost::linalg::detail::RangeTag< I >
struct	xgboost::linalg::detail::Conjunction<... >
	C++ 17 conjunction. More...
struct	xgboost::linalg::detail::Conjunction< B1 >
struct	xgboost::linalg::detail::Conjunction< B1, Bn... >
class	xgboost::linalg::TensorView< T, kDim >
	A tensor view with static type and dimension. More...
class	xgboost::linalg::Tensor< T, kDim >
	A tensor storage. More...

Namespaces
namespace	xgboost
	namespace of xgboost
namespace	xgboost::linalg
	Copyright 2021-2023 by XGBoost Contributors.

Typedefs
template<typename S >
using	xgboost::linalg::detail::RemoveCRType = std::remove_const_t< std::remove_reference_t< S > >
template<typename S >
using	xgboost::linalg::detail::IndexToTag = std::conditional_t< std::is_integral< RemoveCRType< S > >::value, IntTag, S >
template<typename... Index>
using	xgboost::linalg::detail::IsAllIntegral = Conjunction< std::is_integral< std::remove_reference_t< Index > >... >
template<typename... Index>
using	xgboost::linalg::detail::EnableIfIntegral = std::enable_if_t< IsAllIntegral< Index... >::value >
template<typename T >
using	xgboost::linalg::VectorView = TensorView< T, 1 >
	A view over a vector, specialization of Tensor.
template<typename T >
using	xgboost::linalg::MatrixView = TensorView< T, 2 >
	A view over a matrix, specialization of Tensor.
template<typename T >
using	xgboost::linalg::Matrix = Tensor< T, 2 >
template<typename T >
using	xgboost::linalg::Vector = Tensor< T, 1 >

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

Functions
template<size_t dim, typename S , typename Head , size_t D>
constexpr size_t	xgboost::linalg::detail::Offset (S(&strides)[D], size_t n, Head head)
template<size_t dim, typename S , size_t D, typename Head , typename... Tail>
constexpr std::enable_if_t< sizeof...(Tail) !=0, size_t >	xgboost::linalg::detail::Offset (S(&strides)[D], size_t n, Head head, Tail &&...rest)
template<int32_t D, bool f_array = false>
constexpr void	xgboost::linalg::detail::CalcStride (size_t const (&shape)[D], size_t(&stride)[D])
template<typename T >
constexpr int32_t	xgboost::linalg::detail::CalcSliceDim ()
	Calculate the dimension of sliced tensor.
template<typename T , typename... S>
constexpr std::enable_if_t< sizeof...(S) !=0, int32_t >	xgboost::linalg::detail::CalcSliceDim ()
template<int32_t D>
constexpr size_t	xgboost::linalg::detail::CalcSize (size_t(&shape)[D])
template<int32_t n, typename Fn >
LINALG_HD constexpr auto	xgboost::linalg::detail::UnrollLoop (Fn fn)
template<typename T >
int32_t	xgboost::linalg::detail::NativePopc (T v)
LINALG_HD int	xgboost::linalg::detail::Popc (uint32_t v)
LINALG_HD int	xgboost::linalg::detail::Popc (uint64_t v)
template<std::size_t D, typename Head >
LINALG_HD void	xgboost::linalg::detail::IndexToArr (std::size_t(&arr)[D], Head head)
template<std::size_t D, typename Head , typename... Rest>
LINALG_HD void	xgboost::linalg::detail::IndexToArr (std::size_t(&arr)[D], Head head, Rest &&...index)
	Convert index from parameter pack to C-style array.
template<class T , std::size_t N, std::size_t... Idx>
constexpr auto	xgboost::linalg::detail::ArrToTuple (T(&arr)[N], std::index_sequence< Idx... >)
template<class T , std::size_t N>
constexpr auto	xgboost::linalg::detail::ArrToTuple (T(&arr)[N])
	Convert C-styple array to std::tuple.
template<typename I , int32_t D>
LINALG_HD auto	xgboost::linalg::detail::UnravelImpl (I idx, common::Span< size_t const, D > shape)
template<size_t dim, typename I , int32_t D>
void	xgboost::linalg::detail::ReshapeImpl (size_t(&out_shape)[D], I s)
template<size_t dim, int32_t D, typename... S, typename I , std::enable_if_t< sizeof...(S) !=0 > * = nullptr>
void	xgboost::linalg::detail::ReshapeImpl (size_t(&out_shape)[D], I &&s, S &&...rest)
template<typename Fn , typename Tup , size_t... I>
LINALG_HD decltype(auto) constexpr	xgboost::linalg::detail::Apply (Fn &&f, Tup &&t, std::index_sequence< I... >)
template<typename Fn , typename Tup >
LINALG_HD decltype(auto) constexpr	xgboost::linalg::detail::Apply (Fn &&f, Tup &&t)
	C++ 17 style apply.
constexpr detail::AllTag	xgboost::linalg::All ()
	Specify all elements in the axis for slicing.
template<typename I >
constexpr detail::RangeTag< I >	xgboost::linalg::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	xgboost::linalg::MakeTensorView (Context const *ctx, Container &data, S &&...shape)
	Constructor for automatic type deduction.
template<typename T , typename... S>
LINALG_HD auto	xgboost::linalg::MakeTensorView (std::int32_t device, common::Span< T > data, S &&...shape)
template<typename T , typename... S>
auto	xgboost::linalg::MakeTensorView (Context const *ctx, common::Span< T > data, S &&...shape)
template<typename T , typename... S>
auto	xgboost::linalg::MakeTensorView (Context const *ctx, HostDeviceVector< T > *data, S &&...shape)
template<typename T , typename... S>
auto	xgboost::linalg::MakeTensorView (Context const *ctx, HostDeviceVector< T > const *data, S &&...shape)
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.
template<size_t D>
LINALG_HD auto	xgboost::linalg::UnravelIndex (size_t idx, std::size_t const (&shape)[D])
template<typename... S>
LINALG_HD auto	xgboost::linalg::UnravelIndex (std::size_t idx, S... shape)
template<typename T >
auto	xgboost::linalg::MakeVec (T *ptr, size_t s, int32_t device=-1)
	Create a vector view from contigious memory.
template<typename T >
auto	xgboost::linalg::MakeVec (HostDeviceVector< T > *data)
template<typename T >
auto	xgboost::linalg::MakeVec (HostDeviceVector< T > const *data)
template<typename T , int32_t D>
Json	xgboost::linalg::ArrayInterface (TensorView< T const, D > const &t)
	Array Interface defined by numpy.
template<typename T , int32_t D>
Json	xgboost::linalg::ArrayInterface (TensorView< T, D > const &t)
	Same as const version, but returns non-readonly data pointer.
template<typename T , int32_t D>
auto	xgboost::linalg::ArrayInterfaceStr (TensorView< T const, D > const &t)
	Return string representation of array interface.
template<typename T , int32_t D>
auto	xgboost::linalg::ArrayInterfaceStr (TensorView< T, D > const &t)
template<typename T , typename... Index>
auto	xgboost::linalg::Empty (Context const *ctx, Index &&...index)
	Create an array without initialization.
template<typename T , typename... Index>
auto	xgboost::linalg::Constant (Context const *ctx, T v, Index &&...index)
	Create an array with value v.
template<typename T , typename... Index>
auto	xgboost::linalg::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	xgboost::linalg::Stack (Tensor< T, D > *l, Tensor< T, D > const &r)

Detailed Description

Copyright 2021-2023 by XGBoost Contributors.

Linear algebra related utilities.

Function Documentation

Apply()

template<typename Fn , typename Tup >

LINALG_HD decltype(auto) constexpr xgboost::linalg::detail::Apply ( Fn &&  f, Tup &&  t  )

constexpr

C++ 17 style apply.

Parameters

f	function to apply
t	tuple of arguments