Represents a Tensor- a multidimensional array that can represent a multilinear map. More...

#include <Tensor.hpp>

Inheritance diagram for sp::Tensor< T, R, Options >:

Public Types
using	Opts = Options

using	Base = MemTensorLike< Tensor< T, Rank, Options >, T, Rank, Options >

using	ValueType = sp::remove_cvref_t< sp::remove_addrspace_t< T > >

using	Type = T

using	PtrType = typename Base::PtrType

using	ConstTensor = Tensor< const T, R, Options >

using	ThisT = Tensor< T, R, Options >

template<typename NewT >
using	InValueType = Tensor< NewT, R, Options >

Public Types inherited from sp::MemTensorLike< Tensor< T, R, sp::DefaultTensorOptions >, T, R, sp::DefaultTensorOptions >
using	ThisType = MemTensorLike< Tensor< T, R, sp::DefaultTensorOptions >, T, TensorRank, sp::DefaultTensorOptions >

using	ValueType = sp::remove_cvref_t< sp::remove_addrspace_t< T > >

using	Type = T

using	Opts = sp::DefaultTensorOptions

using	Base = TensorLike< Tensor< T, R, sp::DefaultTensorOptions >, TensorRank >

using	InValueType = MemTensorLike< Tensor< T, R, sp::DefaultTensorOptions >, NewT, TensorRank, sp::DefaultTensorOptions >

using	PtrType = T *
	The type of the data pointer. More...

Public Member Functions
	operator ConstTensor () const

	Tensor (PtrType data, const Vec< int, Rank > &sizes)
	Create an R-dimensional packed `Tensor` of the given sizes. More...

	Tensor (PtrType data, const Vec< int, Rank > &sizes, const Vec< int, Rank > &strides)
	Create an R-dimensional `Tensor` with given strides and sizes. More...

template<typename U = T>
	Tensor (PtrType data, int size, typename std::enable_if< Rank==1 &&std::is_same< U, T >()>::type *=nullptr)
	Construct a 1D packed `Tensor` of given size. More...

template<typename U = T>
	Tensor (PtrType data, int size, int stride, typename std::enable_if< Rank==1 &&std::is_same< U, T >()>::type *=nullptr)
	Construct a 1D packed `Tensor` with given size and stride. More...

template<int Dummy = 0>
auto	row (int n)
	For a 2D tensor, get the nth row as a 1D tensor. More...

template<int Dummy = 0>
auto	rows (int start, int n)

template<int Dummy = 0>
auto	col (int n)

template<int Dummy = 0>
auto	cols (int start, int n)

Public Member Functions inherited from sp::MemTensorLike< Tensor< T, R, sp::DefaultTensorOptions >, T, R, sp::DefaultTensorOptions >
auto	getSizes () const

void	setSizes (sp::Vec< int, Rank > sz)

auto &	getSize (int n)

const auto &	getSize (int n) const

auto	getStrides () const

void	setStrides (sp::Vec< int, getNumStrides()> sz)

auto &	getStride (int n)

const auto &	getStride (int n) const

auto &	getTotalSize ()

const auto &	getTotalSize () const

auto &	sizeQuantisation ()

const auto &	sizeQuantisation () const

void	setDefaultSizeQuantisation ()

sp::Vec< int, Rank >	getDimsWithPadding ()

void	validateFields ()

void	computeStrides ()
	Compute strides in the default way. More...

int	totalSizeImpl () const
	Get the total memory occupied by the `Tensor`, in terms of elements. More...

sp::Vec< int, Rank >	stridesImpl () const
	Default implementation of the stride-getter. More...

sp::Vec< int, Rank >	strides () const

int	stride (int i) const

	MemTensorLike (PtrType ptr, const Vec< int, Rank > &sizes)
	Create a `Tensor`. More...

	MemTensorLike (PtrType ptr, const Vec< int, Rank > &sizes, const Vec< int, Rank > &strides)
	Create a `Tensor` with specified strides. More...

int	computeOffsetImpl (const Vec< int, Rank > &pos) const
	Calculate the offset from the start of the buffer that a particular element can be found at. More...

int	computeOffset (const Vec< int, Rank > &pos) const

const PtrType	ptr (const Vec< int, Rank > &pos) const
	Get a pointer to a particular element. More...

PtrType	ptr (const Vec< int, Rank > &pos)

const PtrType	ptr () const
	Get a pointer to the start of the underlying buffer. More...

PtrType	ptr ()

auto	begin () const

auto	end () const

auto	getViewImpl (const sp::Vec< int, Rank > &start, const sp::Vec< int, Rank > &size)
	Create a view into this Tensor using identical striding. More...

auto &	operator[] (int idx)
	Handy 1D subscript operator. More...

const auto &	operator[] (int idx) const

void	setSizeQuantisation (int x)
	Set the size quantisation for the bounds checks. More...

Public Member Functions inherited from sp::TensorLike< Subclass, TensorRank >
auto	dims () const

bool	boundsCheck (const Vec< int, Rank > &pos) const

template<int L, CacheMode Mode = CacheMode::DEFAULT>
auto	vectorRead (const Vec< int, Rank > &pos) const

template<int L, CacheMode Mode = CacheMode::DEFAULT>
auto	vectorOffsetRead (const Vec< int, Rank > &base, const Vec< int, Rank > &offset) const

template<int L, CacheMode Mode = CacheMode::DEFAULT>
auto	maskedVectorRead (const Vec< int, Rank > &pos) const

template<int L, CacheMode Mode = CacheMode::DEFAULT, typename T >
void	vectorWrite (const Vec< int, Rank > &pos, const Vec< T, L > &values)

template<int L, CacheMode Mode = CacheMode::DEFAULT, typename T >
void	maskedVectorWrite (const Vec< int, Rank > &pos, const Vec< T, L > &values)

int	sizeQuantisation () const

int	totalSize () const
	Get the total memory occupied by the `Tensor`, in terms of elements. More...

auto	getView (const sp::Vec< int, Rank > &start, const sp::Vec< int, Rank > &size)
	Get an object that represents (and aliases) a portion of this object. More...

int	dim (int d) const
	Behaviour common to all TensorLikes ///. More...

template<CacheMode Mode = CacheMode::DEFAULT>
auto	read (const Vec< int, Rank > &pos) const
	Get the element at a given position. More...

template<CacheMode Mode = CacheMode::DEFAULT, typename T >
void	write (const Vec< int, Rank > &pos, const T &value)
	Set a single element. More...

template<int Dummy = 0>
int	size () const

template<int L>
void	boundsCheckAccess (Vec< int, Rank > pos) const
	Bounds-check an L-element vector read at `pos`. More...

Static Public Attributes
static constexpr int	Rank = R

static constexpr int	MaxVectorSize = (Opts::Pitched && Opts::Packedness != PackMode::NONE) ? sp::getMaxGMemVectorSize<T>() : 1

Static Public Attributes inherited from sp::MemTensorLike< Tensor< T, R, sp::DefaultTensorOptions >, T, R, sp::DefaultTensorOptions >
static constexpr int	Rank

static constexpr bool	AllowVectorMemoryOps
	An overrideable flag to indicate if a concrete `MemTensorLike` subclass supports vector memory operations. More...

static constexpr int	NumStrides
	The number of strides to explicitly store. More...

static constexpr int	ImplicitStrides
	The number of strides that are not stored. More...

constexpr static bool	HasTotalSize

Static Public Attributes inherited from sp::TensorLike< Subclass, TensorRank >
constexpr static int	Rank = TensorRank

Additional Inherited Members
Static Public Member Functions inherited from sp::MemTensorLike< Tensor< T, R, sp::DefaultTensorOptions >, T, R, sp::DefaultTensorOptions >
static constexpr int	calculateNumStrides ()
	Compute the default value for `NumStrides`. More...

Public Attributes inherited from sp::MemTensorLike< Tensor< T, R, sp::DefaultTensorOptions >, T, R, sp::DefaultTensorOptions >
friend	Base

PtrType	dataPtr

sp::Vec< int, Rank+getNumStrides()+HasTotalSize+AssertionsEnabled >	variousIntegers

Protected Member Functions inherited from sp::MemTensorLike< Tensor< T, R, sp::DefaultTensorOptions >, T, R, sp::DefaultTensorOptions >
sp::Vec< int, Rank >	dimsImpl () const

int	sizeQuantisationImpl () const

Vec< ValueType, L >	vectorReadImpl (const Vec< int, Rank > &pos) const
	This will yield a vector load instruction if the alignment permits. More...

void	vectorWriteImpl (const Vec< int, Rank > &pos, const Vec< ValueType, L > &values)

Protected Member Functions inherited from sp::TensorLike< Subclass, TensorRank >
template<typename Dummy = void*>
auto	dimsImpl () const
	Get an `sp::Vec<int, X>` representing the dimensions of the object. More...

bool	boundsCheckImpl (const sp::Vec< int, Rank > &) const
	Return true iff the given coordinates are inside the object (Default implementation below) More...

int	sizeQuantisationImpl () const
	The last dimension is rounded up to the next multiple of this value for the purposes of bounds checks. More...

template<int L, CacheMode Mode = CacheMode::DEFAULT>
auto	vectorReadImpl (const Vec< int, Rank > &) const
	Read L elements, adjacent in the last dimension, starting at the given position. More...

template<int L, CacheMode Mode = CacheMode::DEFAULT>
auto	vectorOffsetReadImpl (const Vec< int, Rank > &base, const Vec< int, Rank > &offset) const
	Read L elements, adjacent in the last dimension, from position `base + offset`. More...

template<int L, CacheMode Mode = CacheMode::DEFAULT>
auto	maskedVectorReadImpl (const Vec< int, Rank > &pos) const
	Do a vectorRead that copes with the possibility of part of the vector being out of bounds. More...

template<int L, CacheMode Mode = CacheMode::DEFAULT, typename T >
void	maskedVectorWriteImpl (const Vec< int, Rank > &pos, const Vec< T, L > &values)
	Do a vectorWrite that copes with the possibility of part of the vector being out of bounds. More...

template<int L, CacheMode Mode, typename T >
void	vectorWriteImpl (const Vec< int, Rank > &pos, const Vec< T, L > &values)
	Write L elements, adjacent in the last dimension, starting at the given position. More...

auto	getViewImpl (const sp::Vec< int, Rank > &start, const sp::Vec< int, Rank > &size)
	The default implementation just makes a `TensorView`. Not hugely fast, but always works. More...

Detailed Description

template<typename T, int R, typename Options = sp::DefaultTensorOptions>
class sp::Tensor< T, R, Options >

Represents a Tensor- a multidimensional array that can represent a multilinear map.

Additionally carries optimization information- The default flags are the least optimising ones. Usually, users will run their arguments through sp::runSpecialised() at some point to have their Tensors replaced with the most optimised versions possible given their data layout. It is, however, more efficient (and saves binary size) if you explicitly set a more restrictive set of optimisation flags on your Tensor type right from the start, if you know that your input is guaranteed to satisfy the requirements.

Template Parameters

T	The type of each element in the `Tensor`.
R	How many dimensions the `Tensor` has.
Options	An instantiation of `sp::TensorProperties` providing optimisation flags.