A tensor view with static type and dimension. It implements indexing and slicing. More...

#include <linalg.h>

Collaboration diagram for xgboost::linalg::TensorView< T, kDim >:

Public Types
using	ShapeT = std::size_t[kDim]

using	StrideT = ShapeT

using	element_type = T

using	value_type = std::remove_cv_t< T >

Public Member Functions
template<typename I , std::int32_t D>
LINALG_HD	TensorView (common::Span< T > data, I const (&shape)[D], DeviceOrd device)
	Create a tensor with data and shape. More...

template<typename I , int32_t D>
LINALG_HD	TensorView (common::Span< T > data, I const (&shape)[D], DeviceOrd device, Order order)

template<typename I , std::int32_t D>
LINALG_HD	TensorView (common::Span< T > data, I const (&shape)[D], I const (&stride)[D], DeviceOrd device)
	Create a tensor with data, shape and strides. Don't use this constructor if stride can be calculated from shape. More...

template<typename U , std::enable_if_t< common::detail::IsAllowedElementTypeConversion< U, T >::value > * = nullptr>
LINALG_HD	TensorView (TensorView< U, kDim > const &that)

template<typename... Index, detail::EnableIfIntegral< Index... > * = nullptr>
LINALG_HD T &	operator() (Index &&...index)
	Index the tensor to obtain a scalar value. More...

template<typename... Index, detail::EnableIfIntegral< Index... > * = nullptr>
LINALG_HD T const &	operator() (Index &&...index) const
	Index the tensor to obtain a scalar value. More...

template<typename... S>
LINALG_HD auto	Slice (S &&...slices) const
	Slice the tensor. The returned tensor has inferred dim and shape. Scalar result is not supported. More...

LINALG_HD auto	Shape () const

LINALG_HD auto	Shape (size_t i) const

LINALG_HD auto	Stride () const

LINALG_HD auto	Stride (size_t i) const

LINALG_HD std::size_t	Size () const
	Number of items in the tensor. More...

bool	Empty () const

LINALG_HD bool	Contiguous () const
	Whether this is a contiguous array, both C and F contiguous returns true. More...

LINALG_HD bool	CContiguous () const
	Whether it's a c-contiguous array. More...

LINALG_HD bool	FContiguous () const
	Whether it's a f-contiguous array. More...

LINALG_HD auto	Values () const -> decltype(data_) const &
	Obtain a reference to the raw data. More...

LINALG_HD auto	Device () const
	Obtain the CUDA device ordinal. More...

Static Public Attributes
constexpr static size_t	kValueSize = sizeof(T)

constexpr static size_t	kDimension = kDim

Detailed Description

template<typename T, int32_t kDim>
class xgboost::linalg::TensorView< T, kDim >

A tensor view with static type and dimension. It implements indexing and slicing.

Most of the algorithms in XGBoost are implemented for both CPU and GPU without using much linear algebra routines, this class is a helper intended to ease some high level operations like indexing into prediction tensor or gradient matrix. It can be passed into CUDA kernel as normal argument for GPU algorithms.

Ideally we should add a template parameter bool on_host so that the compiler can prevent passing/accessing the wrong view, but inheritance is heavily used in XGBoost so some functions expect data types that can be used in everywhere (update prediction cache for example).

Member Typedef Documentation

◆ element_type

template<typename T , int32_t kDim>

using xgboost::linalg::TensorView< T, kDim >::element_type = T

◆ ShapeT

template<typename T , int32_t kDim>

using xgboost::linalg::TensorView< T, kDim >::ShapeT = std::size_t[kDim]

◆ StrideT

template<typename T , int32_t kDim>

using xgboost::linalg::TensorView< T, kDim >::StrideT = ShapeT

◆ value_type

template<typename T , int32_t kDim>

using xgboost::linalg::TensorView< T, kDim >::value_type = std::remove_cv_t<T>

Constructor & Destructor Documentation

◆ TensorView() [1/4]

template<typename T , int32_t kDim>

template<typename I , std::int32_t D>

LINALG_HD xgboost::linalg::TensorView< T, kDim >::TensorView	(	common::Span< T >	data,
		I const (&)	shape[D],
		DeviceOrd	device
	)

inline

Create a tensor with data and shape.

Template Parameters

I	Type of the shape array element.
D	Size of the shape array, can be lesser than or equal to tensor dimension.

Parameters

data	Raw data input, can be const if this tensor has const type in its template parameter.
shape	shape of the tensor
device	Device ordinal

◆ TensorView() [2/4]

template<typename T , int32_t kDim>

template<typename I , int32_t D>

LINALG_HD xgboost::linalg::TensorView< T, kDim >::TensorView	(	common::Span< T >	data,
		I const (&)	shape[D],
		DeviceOrd	device,
		Order	order
	)

inline

◆ TensorView() [3/4]

template<typename T , int32_t kDim>

template<typename I , std::int32_t D>

LINALG_HD xgboost::linalg::TensorView< T, kDim >::TensorView	(	common::Span< T >	data,
		I const (&)	shape[D],
		I const (&)	stride[D],
		DeviceOrd	device
	)

inline

Create a tensor with data, shape and strides. Don't use this constructor if stride can be calculated from shape.

◆ TensorView() [4/4]

template<typename T , int32_t kDim>

template<typename U , std::enable_if_t< common::detail::IsAllowedElementTypeConversion< U, T >::value > * = nullptr>

LINALG_HD xgboost::linalg::TensorView< T, kDim >::TensorView ( TensorView< U, kDim > const & that )

inline

Member Function Documentation

◆ CContiguous()

template<typename T , int32_t kDim>

LINALG_HD bool xgboost::linalg::TensorView< T, kDim >::CContiguous ( ) const

inline

Whether it's a c-contiguous array.

◆ Contiguous()

template<typename T , int32_t kDim>

LINALG_HD bool xgboost::linalg::TensorView< T, kDim >::Contiguous ( ) const

inline

Whether this is a contiguous array, both C and F contiguous returns true.

◆ Device()

template<typename T , int32_t kDim>

LINALG_HD auto xgboost::linalg::TensorView< T, kDim >::Device ( ) const

inline

Obtain the CUDA device ordinal.

◆ Empty()

template<typename T , int32_t kDim>

bool xgboost::linalg::TensorView< T, kDim >::Empty ( ) const

inline

◆ FContiguous()

template<typename T , int32_t kDim>

LINALG_HD bool xgboost::linalg::TensorView< T, kDim >::FContiguous ( ) const

inline

Whether it's a f-contiguous array.

◆ operator()() [1/2]

template<typename T , int32_t kDim>

template<typename... Index, detail::EnableIfIntegral< Index... > * = nullptr>

LINALG_HD T& xgboost::linalg::TensorView< T, kDim >::operator() ( Index &&... index )

inline

Index the tensor to obtain a scalar value.

// Create a 3-dim tensor.
Tensor<float, 3> t {data, shape, 0};
float pi = 3.14159;
t(1, 2, 3) = pi;
ASSERT_EQ(t(1, 2, 3), pi);

◆ operator()() [2/2]

template<typename T , int32_t kDim>

template<typename... Index, detail::EnableIfIntegral< Index... > * = nullptr>

LINALG_HD T const& xgboost::linalg::TensorView< T, kDim >::operator() ( Index &&... index ) const

inline

Index the tensor to obtain a scalar value.

◆ Shape() [1/2]

template<typename T , int32_t kDim>

LINALG_HD auto xgboost::linalg::TensorView< T, kDim >::Shape ( ) const

inline

◆ Shape() [2/2]

template<typename T , int32_t kDim>

LINALG_HD auto xgboost::linalg::TensorView< T, kDim >::Shape ( size_t i ) const

inline

Get the shape for i^th dimension

◆ Size()

template<typename T , int32_t kDim>

LINALG_HD std::size_t xgboost::linalg::TensorView< T, kDim >::Size ( ) const

inline

Number of items in the tensor.

◆ Slice()

template<typename T , int32_t kDim>

template<typename... S>

LINALG_HD auto xgboost::linalg::TensorView< T, kDim >::Slice ( S &&... slices ) const

inline

Slice the tensor. The returned tensor has inferred dim and shape. Scalar result is not supported.

// Create a 3-dim tensor.
Tensor<float, 3> t {data, shape, 0};
// s has 2 dimensions (matrix)
auto s = t.Slice(1, All(), All());

◆ Stride() [1/2]

template<typename T , int32_t kDim>

LINALG_HD auto xgboost::linalg::TensorView< T, kDim >::Stride ( ) const

inline

◆ Stride() [2/2]

template<typename T , int32_t kDim>

LINALG_HD auto xgboost::linalg::TensorView< T, kDim >::Stride ( size_t i ) const

inline

Get the stride for i^th dimension, stride is specified as number of items instead of bytes.

◆ Values()

template<typename T , int32_t kDim>

LINALG_HD auto xgboost::linalg::TensorView< T, kDim >::Values ( ) const -> decltype(data_) const &

inline

Obtain a reference to the raw data.

Member Data Documentation

◆ kDimension

template<typename T , int32_t kDim>

constexpr static size_t xgboost::linalg::TensorView< T, kDim >::kDimension = kDim

staticconstexpr

◆ kValueSize

template<typename T , int32_t kDim>

constexpr static size_t xgboost::linalg::TensorView< T, kDim >::kValueSize = sizeof(T)

staticconstexpr

The documentation for this class was generated from the following file:

/home/docs/checkouts/readthedocs.org/user_builds/xgboost/checkouts/stable/include/xgboost/linalg.h

Public Types

Public Member Functions

Static Public Attributes

Detailed Description

template<typename T, int32_t kDim> class xgboost::linalg::TensorView< T, kDim >

Member Typedef Documentation

◆ element_type

◆ ShapeT

◆ StrideT

◆ value_type

Constructor & Destructor Documentation

◆ TensorView() [1/4]

◆ TensorView() [2/4]

◆ TensorView() [3/4]

◆ TensorView() [4/4]

Member Function Documentation

◆ CContiguous()

◆ Contiguous()

◆ Device()

◆ Empty()

◆ FContiguous()

◆ operator()() [1/2]

◆ operator()() [2/2]

◆ Shape() [1/2]

◆ Shape() [2/2]

◆ Size()

◆ Slice()

◆ Stride() [1/2]

◆ Stride() [2/2]

◆ Values()

Member Data Documentation

◆ kDimension

◆ kValueSize

template<typename T, int32_t kDim>
class xgboost::linalg::TensorView< T, kDim >