Namespaces
	internal

Classes
struct	AnyConvr
	Implementation of optimization converter that represents any node. More...

struct	BuilderArg
	FuncArg equivalent for optimizer's IR of functor. More...

struct	Constant
	Constant implementation of Eigen leaf tensor. More...

struct	ConstantNode
	Constant's node wrapper. More...

struct	ConverterBuilder
	Optimization builder's implementation for building ETEQ nodes. More...

struct	CoordMap
	Eigen transformation wrapper implementation of iCoordMap. More...

struct	EADLoader
	PBM Unmarshaller implementation for loading ETEQ Nodes. More...

struct	EADSaver
	PBM Marshaller implementation for saving ETEQ Nodes. More...

struct	EigenMatOp
	Implementation of iEigen that assigns Matrix operator to Matrix object. More...

struct	EigenTensOp
	Implementation of iEigen that assigns Tensor operator to Tensor object. More...

struct	FuncArg
	Eigen node version of teq::FuncArg. More...

struct	FuncConvr
	Implementation of optimization converter that represents and builds functors. More...

struct	Functor
	Functor implementation of operable functor of Eigen operators. More...

struct	FunctorNode
	Functor's node wrapper. More...

struct	GradientBuilder
	ETEQ implementation of TEQ's Backward Propagation Builder. More...

struct	GroupConvr
	Implementation of optimization converter that represents and builds subgraphs of specific types. More...

struct	iEigen
	Interface of generic Eigen data wrapper. More...

struct	iLeaf
	iLeaf extension of TEQ iLeaf containing Eigen data objects More...

struct	iNode
	Interface node for wrapping typed tensor. More...

struct	iSession
	Session interface that tracks and rapidly updates subgraphs. More...

struct	NodeConverters
	Node registry of tensor types and tensor to node function. More...

struct	OpArg
	Raw data, shape, and transformation argument struct. More...

struct	ScalarConvr
	Implementation of optimization converter that represents and builds scalar constants. More...

struct	Session

struct	ShapedArr
	Shaped array wraps around a vector and shape. More...

struct	Variable
	Leaf node implementation containing mutable Eigen data. More...

struct	VariableNode
	Variable's node wrapper. More...

Typedefs
using	CoordptrT = std::shared_ptr< CoordMap >
	Type of iCoordMap smartpointer. More...

using	DimensionsT = std::array< Eigen::Index, 8 >
	Eigen shape. More...

template<typename T >
using	MatrixT = Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor >
	Eigen Matrix. More...

template<typename T >
using	MatMapT = Eigen::Map< MatrixT< T > >
	Eigen Matrix Map (reference) More...

template<typename T >
using	TensorT = Eigen::Tensor< T, 8 >
	Eigen Tensor. More...

template<typename T >
using	TensMapT = Eigen::TensorMap< TensorT< T > >
	Eigen Tensor Map (reference) More...

template<typename T >
using	EigenptrT = std::shared_ptr< iEigen< T > >
	Smart point of generic Eigen data object. More...

template<typename T >
using	ArgsT = std::vector< FuncArg< T > >
	Type of typed functor arguments. More...

template<typename T >
using	NodeptrT = std::shared_ptr< iNode< T > >
	Smart pointer of node. More...

template<typename T >
using	NodesT = std::vector< NodeptrT< T > >
	Vector of nodes. More...

template<typename T >
using	NodeBuilderF = std::function< NodeptrT< T >(teq::TensptrT)>
	Function for building a node from tensor. More...

template<typename OP , size_t N, typename T >
using	ReduceOutT = Eigen::TensorReductionOp< OP, const std::array< teq::RankT, N >, const TensMapT< T > >
	Generic Eigen reduction operator. More...

using	BuilderArgsT = std::vector< BuilderArg >
	Vector of FuncArg. More...

using	EngineT = std::default_random_engine
	RNG engine used. More...

template<typename T >
using	GenF = std::function< T()>
	Function that returns a generated number. More...

template<typename T >
using	VarptrT = std::shared_ptr< VariableNode< T > >
	Smart pointer of variable nodes to preserve assign functions. More...

Functions
template<typename T >
NodeptrT< T >	make_constant_scalar (T scalar, teq::Shape shape)
	Return constant node given scalar and shape. More...

template<typename T >
NodeptrT< T >	make_constant (T *data, teq::Shape shape)
	Return constant node given raw array and shape. More...

CoordptrT	reduce (std::vector< teq::RankT > red_dims)
	Return CoordMap wrapper of reduction dimensions. More...

CoordptrT	extend (teq::RankT rank, std::vector< teq::DimT > ext)
	Return CoordMap wrapper of extension parameters. More...

CoordptrT	permute (std::vector< teq::RankT > dims)
	Return CoordMap wrapper of permute indices. More...

template<typename T >
MatMapT< T >	tens_to_matmap (TensorT< T > &tens)
	Return Matrix Map given Tensor. More...

template<typename T >
MatMapT< T >	mat_to_matmap (MatrixT< T > &mat)
	Return Map of Matrix. More...

template<typename T >
MatMapT< T >	tensmap_to_matmap (TensMapT< T > &tens)
	Return Matrix Map of Tensor Map. More...

template<typename T >
TensMapT< T >	mat_to_tensmap (MatrixT< T > &mat)
	Return Tensor Map of Matrix. More...

template<typename T >
TensMapT< T >	tens_to_tensmap (TensorT< T > &tens)
	Return Tensor Map of Tensor. More...

template<typename T , typename EigenSource , typename EigenArgs >
EigenptrT< T >	make_eigentensor (DimensionsT dims, std::function< EigenSource(EigenArgs &)> make_base, EigenArgs args)

template<typename T , typename EigenSource , typename EigenArgs >
EigenptrT< T >	make_eigenmatrix (DimensionsT dims, std::function< EigenSource(EigenArgs &)> make_base, EigenArgs args)

template<typename T >
TensorT< T >	make_tensor (const teq::Shape &shape)
	Return Eigen Tensor filled with 0s given teq Shape. More...

template<typename T >
MatMapT< T >	make_matmap (T *data, const teq::Shape &shape)
	Return Eigen Matrix given raw data and teq Shape. More...

template<typename T >
TensMapT< T >	make_tensmap (T *data, const teq::Shape &shape)
	Return Eigen Tensor given raw data and teq Shape. More...

template<typename T >
teq::Shape	get_shape (const TensorT< T > &tens)
	Return the teq Shape representation of Eigen Tensor. More...

template<typename T >
teq::Shape	get_shape (const TensMapT< T > &tens)
	Return the teq Shape representation of Eigen Tensor Map. More...

DimensionsT	shape_convert (teq::Shape shape)
	Return Eigen shape of teq Shape. More...

template<typename T >
FuncArg< T >	identity_map (NodeptrT< T > node)
	Return FuncArg<T> that identity maps input tensor. More...

template<typename T >
FuncArg< T >	reduce_map (NodeptrT< T > node, teq::RankT offset, teq::RankT ndims)

template<typename T >
FuncArg< T >	extend_map (NodeptrT< T > node, teq::RankT rank, std::vector< teq::DimT > ext)

template<typename T >
FuncArg< T >	permute_map (NodeptrT< T > node, std::vector< teq::RankT > order)

template<typename T >
FuncArg< T >	slice_map (NodeptrT< T > node, teq::RankT offset, teq::RankT extent, teq::RankT dimension)

template<typename T >
FuncArg< T >	pad_map (NodeptrT< T > node, const std::pair< teq::DimT, teq::DimT > &padding, teq::RankT dimension)

template<typename T >
FuncArg< T >	stride_map (NodeptrT< T > node, const std::vector< teq::DimT > &incrs)

template<typename T >
NodeptrT< T >	make_functor (teq::Opcode opcode, ArgsT< T > args)
	Return functor node given opcode and node arguments. More...

template<typename T >
NodeptrT< T >	reduce_grad (const teq::FuncArg &child, NodeptrT< T > bwd, size_t idx)
	Return reduction operator gradient of reduced functor node (bwd) More...

template<typename T >
NodeptrT< T >	permute_grad (teq::iFunctor *fwd, NodeptrT< T > bwd, size_t idx)
	Return permutation gradient of permuted functor node (bwd) More...

template<typename T >
NodeptrT< T >	extend_grad (teq::iFunctor *fwd, NodeptrT< T > bwd, size_t idx)
	Return extension gradient of extended functor node (bwd) More...

template<typename T >
NodeptrT< T >	derive (NodeptrT< T > root, NodeptrT< T > target)
	Derive root with respect to target and optimized. More...

template<typename TensType , typename T >
bool	register_builder (NodeBuilderF< T > builder)

static bool	is_2d (teq::Shape shape)

template<typename T >
EigenptrT< T >	reduce_sum (teq::Shape &outshape, const OpArg< T > &in) template< typename T > EigenptrT< T > reduce_prod(teq
	Return Eigen data object representing reduction where aggregation is sum. More...

template<typename T >
EigenptrT< T >	permute (teq::Shape &outshape, const OpArg< T > &in)
	Return Eigen data object representing transpose and permutation. More...

template<typename T >
EigenptrT< T >	slice (teq::Shape &outshape, const OpArg< T > &in)
	Return Eigen data object representing data slicing of dimensions. More...

template<typename T >
EigenptrT< T >	pad (teq::Shape &outshape, const OpArg< T > &in)
	Return Eigen data object representing data zero padding. More...

template<typename T >
EigenptrT< T >	stride (teq::Shape &outshape, const OpArg< T > &in)
	Return Eigen data object representing strided view of in. More...

template<typename T >
EigenptrT< T >	abs (teq::Shape &outshape, const OpArg< T > &in)

template<typename T >
EigenptrT< T >	neg (teq::Shape &outshape, const OpArg< T > &in)

template<typename T >
EigenptrT< T >	sin (teq::Shape &outshape, const OpArg< T > &in)

template<typename T >
EigenptrT< T >	cos (teq::Shape &outshape, const OpArg< T > &in)

template<typename T >
EigenptrT< T >	tan (teq::Shape &outshape, const OpArg< T > &in)

template<typename T >
EigenptrT< T >	exp (teq::Shape &outshape, const OpArg< T > &in)

template<typename T >
EigenptrT< T >	log (teq::Shape &outshape, const OpArg< T > &in)

template<typename T >
EigenptrT< T >	sqrt (teq::Shape &outshape, const OpArg< T > &in)

template<typename T >
EigenptrT< T >	round (teq::Shape &outshape, const OpArg< T > &in)

template<typename T >
EigenptrT< T >	sigmoid (teq::Shape &outshape, const OpArg< T > &in)

template<typename T >
EigenptrT< T >	sigmoid_grad (teq::Shape &outshape, const OpArg< T > &in)

template<typename T >
EigenptrT< T >	tanh (teq::Shape &outshape, const OpArg< T > &in)

template<typename T >
EigenptrT< T >	square (teq::Shape &outshape, const OpArg< T > &in)

template<typename T >
EigenptrT< T >	cube (teq::Shape &outshape, const OpArg< T > &in)

template<typename T >
EigenptrT< T >	pow (teq::Shape &outshape, const OpArg< T > &a, const OpArg< T > &b)

template<typename T >
EigenptrT< T >	add (teq::Shape &outshape, const OpArg< T > &a, const OpArg< T > &b)

template<typename T >
EigenptrT< T >	sub (teq::Shape &outshape, const OpArg< T > &a, const OpArg< T > &b)

template<typename T >
EigenptrT< T >	mul (teq::Shape &outshape, const OpArg< T > &a, const OpArg< T > &b)

template<typename T >
EigenptrT< T >	div (teq::Shape &outshape, const OpArg< T > &a, const OpArg< T > &b)

template<typename T >
EigenptrT< T >	eq (teq::Shape &outshape, const OpArg< T > &a, const OpArg< T > &b)

template<typename T >
EigenptrT< T >	neq (teq::Shape &outshape, const OpArg< T > &a, const OpArg< T > &b)

template<typename T >
EigenptrT< T >	lt (teq::Shape &outshape, const OpArg< T > &a, const OpArg< T > &b)

template<typename T >
EigenptrT< T >	gt (teq::Shape &outshape, const OpArg< T > &a, const OpArg< T > &b)

template<typename T >
EigenptrT< T >	min (teq::Shape &outshape, const OpArg< T > &a, const OpArg< T > &b)

template<typename T >
EigenptrT< T >	max (teq::Shape &outshape, const OpArg< T > &a, const OpArg< T > &b)

template<typename T >
EigenptrT< T >	rand_uniform (teq::Shape &outshape, const OpArg< T > &a, const OpArg< T > &b)

template<typename T >
EigenptrT< T >	select (teq::Shape &outshape, const OpArg< T > &condition, const OpArg< T > &then, const OpArg< T > &otherwise)

template<typename T >
EigenptrT< T >	matmul (teq::Shape &outshape, const OpArg< T > &a, const OpArg< T > &b)

template<typename T >
EigenptrT< T >	convolution (teq::Shape &outshape, const OpArg< T > &input, const OpArg< T > &kernel)
	Apply convolution of kernel across input. More...

template<typename T >
EigenptrT< T >	convolution_image_grad (teq::Shape &imageshape, const OpArg< T > &kernel, const OpArg< T > &super_composite)
	Applies the gradient of convolution with respect to image. More...

template<typename T >
EigenptrT< T >	convolution_kernel_grad (teq::Shape &kernelshape, const OpArg< T > &image, const OpArg< T > &super_composite)
	Applies the gradient of convolution with respect to kernel. More...

static std::vector< double >	vectorize (::NumList *list)

static CoordptrT	coorderize (::NumList *list)

template<typename T >
opt::OptCtx	parse (std::string content)
	Return optimization rules tied to ETEQ Builder specified in content. More...

template<typename T >
opt::OptCtx	parse_file (std::string filename)
	Return optimization rules tied to ETEQ Builder specified in file. More...

EngineT &	get_engine (void)
	Return global random generator. More...

template<typename T , typename std::enable_if< std::is_integral< T >::value >::type * = nullptr>
T	unif (const T &a, const T &b)
	Return uniformly generated number between a and b (integers only) More...

template<typename T , typename std::enable_if< std::is_integral< T >::value >::type * = nullptr>
GenF< T >	unif_gen (const T &a, const T &b)
	Return uniformly generator function that produces numbers between a and b (integers only) More...

template<typename T , typename std::enable_if<!std::is_integral< T >::value >::type * = nullptr>
GenF< T >	unif_gen (T a, T b)
	Return uniformly generator function that produces numbers between a and b (decimals only) More...

template<typename T , typename std::enable_if<!std::is_integral< T >::value >::type * = nullptr>
GenF< T >	norm_gen (T mean, T stdev)
	Return normally generator function that produces numbers with mean and stdev (decimals only) More...

static bool	is_big_endian (void)

template<typename T >
NodeptrT< T >	convert_to_node (VarptrT< T > var)
	Return Node smart pointer of Variable smart pointer. More...

template<typename T >
VarptrT< T >	make_variable_scalar (T scalar, teq::Shape shape, std::string label="")
	Return variable node given scalar and shape. More...

template<typename T >
VarptrT< T >	make_variable (teq::Shape shape, std::string label="")
	Return zero-initialized variable node of specified shape. More...

template<typename T >
VarptrT< T >	make_variable (T *data, teq::Shape shape, std::string label="")
	Return variable node given raw array and shape. More...

Variables
static const size_t	label_limit = 5

static std::unordered_set< size_t >	non_bijectives

Detailed Description

constant.hpp eteq

Purpose: Implement constant leaf tensor

coord.hpp eteq

Purpose: Define Eigen transformation argument wrapper

eigen.hpp eteq

Purpose: Define Eigen tensor and matrix transformation functions

funcarg.hpp eteq

Purpose: Typed Eigen node version of teq::FuncArg

functor.hpp eteq

Purpose: Eigen functor implementation of operable func

grader.hpp eteq

Purpose: Implement eteq gradient definition for supported operations

ileaf.hpp eteq

Purpose: Define interfaces and building blocks for an equation graph

inode.hpp eteq

Purpose: Define node interface and registration and conversion objects

operator.hpp eteq

Purpose: Define functions manipulating tensor data values No function in this file makes any attempt to check for nullptrs

parse.hpp eteq

Purpose: Extend optimization module by defining ETEQ node parsing

random.hpp eteq

Purpose: Define randomization functions used in Eigen operators

serialize.hpp eteq

Purpose: Define functions for marshal and unmarshal data sources

session.hpp eteq

Purpose: Define and implement session that tracks subgraphs and rapidly updates the tracked graph or a portion of tracked graph

shaped_arr.hpp eteq

Purpose: Define a data-shape representation to feed in to the variable

variable.hpp eteq

Purpose: Define data structures for owning, and passing generalized and type-specific data

Typedef Documentation

◆ ArgsT

template<typename T >

using eteq::ArgsT = typedef std::vector<FuncArg<T> >

Type of typed functor arguments.

◆ BuilderArgsT

using eteq::BuilderArgsT = typedef std::vector<BuilderArg>

Vector of FuncArg.

◆ CoordptrT

using eteq::CoordptrT = typedef std::shared_ptr<CoordMap>

Type of iCoordMap smartpointer.

◆ DimensionsT

using eteq::DimensionsT = typedef std::array<Eigen::Index,8>

Eigen shape.

◆ EigenptrT

template<typename T >

using eteq::EigenptrT = typedef std::shared_ptr<iEigen<T> >

Smart point of generic Eigen data object.

◆ EngineT

using eteq::EngineT = typedef std::default_random_engine

RNG engine used.

◆ GenF

template<typename T >

using eteq::GenF = typedef std::function<T()>

Function that returns a generated number.

◆ MatMapT

template<typename T >

using eteq::MatMapT = typedef Eigen::Map<MatrixT<T> >

Eigen Matrix Map (reference)

◆ MatrixT

template<typename T >

using eteq::MatrixT = typedef Eigen::Matrix<T,Eigen::Dynamic,Eigen::Dynamic,Eigen::RowMajor>

Eigen Matrix.

◆ NodeBuilderF

template<typename T >

using eteq::NodeBuilderF = typedef std::function<NodeptrT<T>(teq::TensptrT)>

Function for building a node from tensor.

◆ NodeptrT

template<typename T >

using eteq::NodeptrT = typedef std::shared_ptr<iNode<T> >

Smart pointer of node.

◆ NodesT

template<typename T >

using eteq::NodesT = typedef std::vector<NodeptrT<T> >

Vector of nodes.

◆ ReduceOutT

template<typename OP , size_t N, typename T >

using eteq::ReduceOutT = typedef Eigen::TensorReductionOp<OP, const std::array<teq::RankT,N>,const TensMapT<T> >

Generic Eigen reduction operator.

◆ TensMapT

template<typename T >

using eteq::TensMapT = typedef Eigen::TensorMap<TensorT<T> >

Eigen Tensor Map (reference)

◆ TensorT

template<typename T >

using eteq::TensorT = typedef Eigen::Tensor<T,8>

Eigen Tensor.

◆ VarptrT

template<typename T >

using eteq::VarptrT = typedef std::shared_ptr<VariableNode<T> >

Smart pointer of variable nodes to preserve assign functions.

Function Documentation

◆ abs()

template<typename T >

EigenptrT<T> eteq::abs	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

Given reference to output array, and input vector ref, make output elements take absolute value of inputs

◆ add()

template<typename T >

EigenptrT<T> eteq::add	(	teq::Shape &	outshape,
		const OpArg< T > &	a,
		const OpArg< T > &	b
	)

◆ convert_to_node()

template<typename T >

NodeptrT<T> eteq::convert_to_node ( VarptrT< T > var )

Return Node smart pointer of Variable smart pointer.

◆ convolution()

template<typename T >

EigenptrT<T> eteq::convolution	(	teq::Shape &	outshape,
		const OpArg< T > &	input,
		const OpArg< T > &	kernel
	)

Apply convolution of kernel across input.

◆ convolution_image_grad()

template<typename T >

EigenptrT<T> eteq::convolution_image_grad	(	teq::Shape &	imageshape,
		const OpArg< T > &	kernel,
		const OpArg< T > &	super_composite
	)

Applies the gradient of convolution with respect to image.

◆ convolution_kernel_grad()

template<typename T >

EigenptrT<T> eteq::convolution_kernel_grad	(	teq::Shape &	kernelshape,
		const OpArg< T > &	image,
		const OpArg< T > &	super_composite
	)

Applies the gradient of convolution with respect to kernel.

◆ coorderize()

static CoordptrT eteq::coorderize ( ::NumList * list )

static

◆ cos()

template<typename T >

EigenptrT<T> eteq::cos	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

Given reference to output array, and input vector ref, make output elements take cosine of inputs

◆ cube()

template<typename T >

EigenptrT<T> eteq::cube	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

◆ derive()

template<typename T >

NodeptrT<T> eteq::derive	(	NodeptrT< T >	root,
		NodeptrT< T >	target
	)

Derive root with respect to target and optimized.

◆ div()

template<typename T >

EigenptrT<T> eteq::div	(	teq::Shape &	outshape,
		const OpArg< T > &	a,
		const OpArg< T > &	b
	)

Given arguments a, and b, for every pair of mapped elements sharing the same index divide Only accept 2 arguments

◆ eq()

template<typename T >

EigenptrT<T> eteq::eq	(	teq::Shape &	outshape,
		const OpArg< T > &	a,
		const OpArg< T > &	b
	)

Given arguments a, and b, for every pair of mapped elements sharing the same index apply == operator Only accept 2 arguments

◆ exp()

template<typename T >

EigenptrT<T> eteq::exp	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

Given reference to output array, and input vector ref, make output elements take exponent of inputs

◆ extend()

CoordptrT eteq::extend	(	teq::RankT	rank,
		std::vector< teq::DimT >	ext
	)

Return CoordMap wrapper of extension parameters.

◆ extend_grad()

template<typename T >

NodeptrT<T> eteq::extend_grad	(	teq::iFunctor *	fwd,
		NodeptrT< T >	bwd,
		size_t	idx
	)

Return extension gradient of extended functor node (bwd)

◆ extend_map()

template<typename T >

FuncArg<T> eteq::extend_map	(	NodeptrT< T >	node,
		teq::RankT	rank,
		std::vector< teq::DimT >	ext
	)

Return FuncArg<T> that extends input tensor by rank and extension vector E.g.: tensor w/ shape [2, 1, 1], rank = 1, ext = [3, 4] gets mapped to [2, 3, 4]

◆ get_engine()

EngineT& eteq::get_engine ( void )

Return global random generator.

◆ get_shape() [1/2]

template<typename T >

teq::Shape eteq::get_shape ( const TensorT< T > & tens )

Return the teq Shape representation of Eigen Tensor.

◆ get_shape() [2/2]

template<typename T >

teq::Shape eteq::get_shape ( const TensMapT< T > & tens )

Return the teq Shape representation of Eigen Tensor Map.

◆ gt()

template<typename T >

EigenptrT<T> eteq::gt	(	teq::Shape &	outshape,
		const OpArg< T > &	a,
		const OpArg< T > &	b
	)

Given arguments a, and b, for every pair of mapped elements sharing the same index apply > operator Only accept 2 arguments

◆ identity_map()

template<typename T >

FuncArg<T> eteq::identity_map ( NodeptrT< T > node )

Return FuncArg<T> that identity maps input tensor.

◆ is_2d()

static bool eteq::is_2d ( teq::Shape shape )

inlinestatic

◆ is_big_endian()

static bool eteq::is_big_endian ( void )

static

◆ log()

template<typename T >

EigenptrT<T> eteq::log	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

Given reference to output array, and input vector ref, make output elements take natural log of inputs

◆ lt()

template<typename T >

EigenptrT<T> eteq::lt	(	teq::Shape &	outshape,
		const OpArg< T > &	a,
		const OpArg< T > &	b
	)

Given arguments a, and b, for every pair of mapped elements sharing the same index apply < operator Only accept 2 arguments

◆ make_constant()

template<typename T >

NodeptrT<T> eteq::make_constant	(	T *	data,
		teq::Shape	shape
	)

Return constant node given raw array and shape.

◆ make_constant_scalar()

template<typename T >

NodeptrT<T> eteq::make_constant_scalar	(	T	scalar,
		teq::Shape	shape
	)

Return constant node given scalar and shape.

◆ make_eigenmatrix()

template<typename T , typename EigenSource , typename EigenArgs >

EigenptrT<T> eteq::make_eigenmatrix	(	DimensionsT	dims,
		std::function< EigenSource(EigenArgs &)>	make_base,
		EigenArgs	args
	)

inline

Return Eigen Matrix wrapper given output shape, and Eigen operator creation and arguments

◆ make_eigentensor()

template<typename T , typename EigenSource , typename EigenArgs >

EigenptrT<T> eteq::make_eigentensor	(	DimensionsT	dims,
		std::function< EigenSource(EigenArgs &)>	make_base,
		EigenArgs	args
	)

inline

Return Eigen Tensor wrapper given output shape, and Eigen operator creation and arguments

◆ make_functor()

template<typename T >

NodeptrT<T> eteq::make_functor	(	teq::Opcode	opcode,
		ArgsT< T >	args
	)

Return functor node given opcode and node arguments.

◆ make_matmap()

template<typename T >

MatMapT<T> eteq::make_matmap	(	T *	data,
		const teq::Shape &	shape
	)

inline

Return Eigen Matrix given raw data and teq Shape.

◆ make_tensmap()

template<typename T >

TensMapT<T> eteq::make_tensmap	(	T *	data,
		const teq::Shape &	shape
	)

inline

Return Eigen Tensor given raw data and teq Shape.

◆ make_tensor()

template<typename T >

TensorT<T> eteq::make_tensor ( const teq::Shape & shape )

inline

Return Eigen Tensor filled with 0s given teq Shape.

◆ make_variable() [1/2]

template<typename T >

VarptrT<T> eteq::make_variable	(	teq::Shape	shape,
		std::string	label = `""`
	)

Return zero-initialized variable node of specified shape.

◆ make_variable() [2/2]

template<typename T >

VarptrT<T> eteq::make_variable	(	T *	data,
		teq::Shape	shape,
		std::string	label = `""`
	)

Return variable node given raw array and shape.

◆ make_variable_scalar()

template<typename T >

VarptrT<T> eteq::make_variable_scalar	(	T	scalar,
		teq::Shape	shape,
		std::string	label = `""`
	)

Return variable node given scalar and shape.

◆ mat_to_matmap()

template<typename T >

MatMapT<T> eteq::mat_to_matmap ( MatrixT< T > & mat )

inline

Return Map of Matrix.

◆ mat_to_tensmap()

template<typename T >

TensMapT<T> eteq::mat_to_tensmap ( MatrixT< T > & mat )

inline

Return Tensor Map of Matrix.

◆ matmul()

template<typename T >

EigenptrT<T> eteq::matmul	(	teq::Shape &	outshape,
		const OpArg< T > &	a,
		const OpArg< T > &	b
	)

Only applies to 2-d tensors Apply matrix multiplication of a and b

◆ max()

template<typename T >

EigenptrT<T> eteq::max	(	teq::Shape &	outshape,
		const OpArg< T > &	a,
		const OpArg< T > &	b
	)

Given arguments, for every mapped index i in range [0:max_nelems], take the maximum all elements for all arguments

◆ min()

template<typename T >

EigenptrT<T> eteq::min	(	teq::Shape &	outshape,
		const OpArg< T > &	a,
		const OpArg< T > &	b
	)

Given arguments, for every mapped index i in range [0:max_nelems], take the minimum all elements for all arguments

◆ mul()

template<typename T >

EigenptrT<T> eteq::mul	(	teq::Shape &	outshape,
		const OpArg< T > &	a,
		const OpArg< T > &	b
	)

◆ neg()

template<typename T >

EigenptrT<T> eteq::neg	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

Given reference to output array, and input vector ref, make output elements take negatives of inputs

◆ neq()

template<typename T >

EigenptrT<T> eteq::neq	(	teq::Shape &	outshape,
		const OpArg< T > &	a,
		const OpArg< T > &	b
	)

Given arguments a, and b, for every pair of mapped elements sharing the same index apply != operator Only accept 2 arguments

◆ norm_gen()

template<typename T , typename std::enable_if<!std::is_integral< T >::value >::type * = nullptr>

GenF<T> eteq::norm_gen	(	T	mean,
		T	stdev
	)

Return normally generator function that produces numbers with mean and stdev (decimals only)

◆ pad()

template<typename T >

EigenptrT<T> eteq::pad	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

Return Eigen data object representing data zero padding.

◆ pad_map()

template<typename T >

FuncArg<T> eteq::pad_map	(	NodeptrT< T >	node,
		const std::pair< teq::DimT, teq::DimT > &	padding,
		teq::RankT	dimension
	)

Return FuncArg<T> that pads tensor with 0s across specified dimension E.g.: tensor w/ shape [2, 3, 4], padding = {2,1}, dimension = 0 gets mapped to [5, 3, 4] where [0,:,:] and [3:5,:,:] are 0 (first, fourth, and fifth slices of the 1st dimension are 0)

◆ parse()

template<typename T >

opt::OptCtx eteq::parse ( std::string content )

Return optimization rules tied to ETEQ Builder specified in content.

◆ parse_file()

template<typename T >

opt::OptCtx eteq::parse_file ( std::string filename )

Return optimization rules tied to ETEQ Builder specified in file.

◆ permute() [1/2]

CoordptrT eteq::permute ( std::vector< teq::RankT > dims )

Return CoordMap wrapper of permute indices.

◆ permute() [2/2]

template<typename T >

EigenptrT<T> eteq::permute	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

Return Eigen data object representing transpose and permutation.

◆ permute_grad()

template<typename T >

NodeptrT<T> eteq::permute_grad	(	teq::iFunctor *	fwd,
		NodeptrT< T >	bwd,
		size_t	idx
	)

Return permutation gradient of permuted functor node (bwd)

◆ permute_map()

template<typename T >

FuncArg<T> eteq::permute_map	(	NodeptrT< T >	node,
		std::vector< teq::RankT >	order
	)

Return FuncArg<T> that permutes input tensor by order E.g.: tensor w/ shape [2, 3, 4], order = [1, 2, 0] gets mapped to [3, 4, 2]

◆ pow()

template<typename T >

EigenptrT<T> eteq::pow	(	teq::Shape &	outshape,
		const OpArg< T > &	a,
		const OpArg< T > &	b
	)

Given arguments a, and b, for every pair of mapped elements sharing the same index apply std::pow operator Only accept 2 arguments

◆ rand_uniform()

template<typename T >

EigenptrT<T> eteq::rand_uniform	(	teq::Shape &	outshape,
		const OpArg< T > &	a,
		const OpArg< T > &	b
	)

Given arguments a, and b, for every pair of mapped elements sharing the same index apply std::uniform_distributon function Only accept 2 arguments

◆ reduce()

CoordptrT eteq::reduce ( std::vector< teq::RankT > red_dims )

Return CoordMap wrapper of reduction dimensions.

◆ reduce_grad()

template<typename T >

NodeptrT<T> eteq::reduce_grad	(	const teq::FuncArg &	child,
		NodeptrT< T >	bwd,
		size_t	idx
	)

Return reduction operator gradient of reduced functor node (bwd)

◆ reduce_map()

template<typename T >

FuncArg<T> eteq::reduce_map	(	NodeptrT< T >	node,
		teq::RankT	offset,
		teq::RankT	ndims
	)

Return FuncArg<T> that reduces input tensor by units in reduction vector after specified rank E.g.: tensor w/ shape [2, 3, 4], offset = 1, ndims = 2 gets mapped to [2, 1, 1]

◆ reduce_sum()

template<typename T >

EigenptrT<T> eteq::reduce_sum	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

Return Eigen data object representing reduction where aggregation is sum.

Return Eigen data object representing reduction where aggregation is prod

◆ register_builder()

template<typename TensType , typename T >

bool eteq::register_builder ( NodeBuilderF< T > builder )

Return true if tensor type successfully registers and maps to node builder, otherwise false

◆ round()

template<typename T >

EigenptrT<T> eteq::round	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

Given reference to output array, and input vector ref, make output elements take rounded values of inputs

◆ select()

template<typename T >

EigenptrT<T> eteq::select	(	teq::Shape &	outshape,
		const OpArg< T > &	condition,
		const OpArg< T > &	then,
		const OpArg< T > &	otherwise
	)

Given a condition, then values and otherwise apply corresponding then value if condition is non-zero otherwise apply otherwise value

◆ shape_convert()

DimensionsT eteq::shape_convert ( teq::Shape shape )

Return Eigen shape of teq Shape.

◆ sigmoid()

template<typename T >

EigenptrT<T> eteq::sigmoid	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

◆ sigmoid_grad()

template<typename T >

EigenptrT<T> eteq::sigmoid_grad	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

◆ sin()

template<typename T >

EigenptrT<T> eteq::sin	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

Given reference to output array, and input vector ref, make output elements take sine of inputs

◆ slice()

template<typename T >

EigenptrT<T> eteq::slice	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

Return Eigen data object representing data slicing of dimensions.

◆ slice_map()

template<typename T >

FuncArg<T> eteq::slice_map	(	NodeptrT< T >	node,
		teq::RankT	offset,
		teq::RankT	extent,
		teq::RankT	dimension
	)

Return FuncArg<T> that takes specific slice of tensor E.g.: tensor w/ shape [2, 3, 4], offset = 1, extent = 2, and dimension = 2 gets mapped to [3, 4, 2] that references [:,:,1:3] (second and third slices of the 3rd dimension)

◆ sqrt()

template<typename T >

EigenptrT<T> eteq::sqrt	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

Given reference to output array, and input vector ref, make output elements take square root of inputs

◆ square()

template<typename T >

EigenptrT<T> eteq::square	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

◆ stride()

template<typename T >

EigenptrT<T> eteq::stride	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

Return Eigen data object representing strided view of in.

◆ stride_map()

template<typename T >

FuncArg<T> eteq::stride_map	(	NodeptrT< T >	node,
		const std::vector< teq::DimT > &	incrs
	)

Return FuncArg<T> that takes elements of specific increments across dimensions starting from 0 E.g.: tensor w/ shape [2, 3, 4], incrs = {1, 2, 2} gets mapped to [2, 2, 2] where output[:,0,0] takes on input[:,0,0] output[:,1,0] takes on input[:,2,0] output[:,0,1] takes on input[:,0,2] output[:,1,1] takes on input[:,2,2]

◆ sub()

template<typename T >

EigenptrT<T> eteq::sub	(	teq::Shape &	outshape,
		const OpArg< T > &	a,
		const OpArg< T > &	b
	)

Given arguments a, and b, for every pair of mapped elements sharing the same index subtract Only accept 2 arguments

◆ tan()

template<typename T >

EigenptrT<T> eteq::tan	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

Given reference to output array, and input vector ref, make output elements take tangent of inputs

◆ tanh()

template<typename T >

EigenptrT<T> eteq::tanh	(	teq::Shape &	outshape,
		const OpArg< T > &	in
	)

◆ tens_to_matmap()

template<typename T >

MatMapT<T> eteq::tens_to_matmap ( TensorT< T > & tens )

inline

Return Matrix Map given Tensor.

◆ tens_to_tensmap()

template<typename T >

TensMapT<T> eteq::tens_to_tensmap ( TensorT< T > & tens )

inline

Return Tensor Map of Tensor.

◆ tensmap_to_matmap()

template<typename T >

MatMapT<T> eteq::tensmap_to_matmap ( TensMapT< T > & tens )

inline

Return Matrix Map of Tensor Map.

◆ unif()

template<typename T , typename std::enable_if< std::is_integral< T >::value >::type * = nullptr>

T eteq::unif	(	const T &	a,
		const T &	b
	)

Return uniformly generated number between a and b (integers only)

Return uniformly generate number between a and b (decimals only)

◆ unif_gen() [1/2]

template<typename T , typename std::enable_if< std::is_integral< T >::value >::type * = nullptr>

GenF<T> eteq::unif_gen	(	const T &	a,
		const T &	b
	)

Return uniformly generator function that produces numbers between a and b (integers only)

◆ unif_gen() [2/2]

template<typename T , typename std::enable_if<!std::is_integral< T >::value >::type * = nullptr>

GenF<T> eteq::unif_gen	(	T	a,
		T	b
	)

Return uniformly generator function that produces numbers between a and b (decimals only)

◆ vectorize()

static std::vector<double> eteq::vectorize ( ::NumList * list )

static

Variable Documentation

◆ label_limit

const size_t eteq::label_limit = 5

static

◆ non_bijectives

std::unordered_set<size_t> eteq::non_bijectives

static

Initial value:

=
{
    egen::REDUCE_SUM,
    egen::REDUCE_PROD,
    egen::REDUCE_MIN,
    egen::REDUCE_MAX,
    egen::EXTEND,
}

Namespaces

Classes

Typedefs

Functions

Variables

Detailed Description

Typedef Documentation

◆ ArgsT

◆ BuilderArgsT

◆ CoordptrT

◆ DimensionsT

◆ EigenptrT

◆ EngineT

◆ GenF

◆ MatMapT

◆ MatrixT

◆ NodeBuilderF

◆ NodeptrT

◆ NodesT

◆ ReduceOutT

◆ TensMapT

◆ TensorT

◆ VarptrT

Function Documentation

◆ abs()

◆ add()

◆ convert_to_node()

◆ convolution()

◆ convolution_image_grad()

◆ convolution_kernel_grad()

◆ coorderize()

◆ cos()

◆ cube()

◆ derive()

◆ div()

◆ eq()

◆ exp()

◆ extend()

◆ extend_grad()

◆ extend_map()

◆ get_engine()

◆ get_shape() [1/2]

◆ get_shape() [2/2]

◆ gt()

◆ identity_map()

◆ is_2d()

◆ is_big_endian()

◆ log()

◆ lt()

◆ make_constant()

◆ make_constant_scalar()

◆ make_eigenmatrix()

◆ make_eigentensor()

◆ make_functor()

◆ make_matmap()

◆ make_tensmap()

◆ make_tensor()

◆ make_variable() [1/2]

◆ make_variable() [2/2]

◆ make_variable_scalar()

◆ mat_to_matmap()

◆ mat_to_tensmap()

◆ matmul()

◆ max()

◆ min()

◆ mul()

◆ neg()

◆ neq()

◆ norm_gen()

◆ pad()

◆ pad_map()

◆ parse()

◆ parse_file()

◆ permute() [1/2]

◆ permute() [2/2]

◆ permute_grad()

◆ permute_map()

◆ pow()

◆ rand_uniform()

◆ reduce()