mshadow Namespace Reference

namespace for mshadow More...

Namespaces
	expr
	namespace for abstract expressions and expressions template, have no dependecy on tensor.h, These data structure takes no charge in computations, they are only used to define operations and represent expression in a symbolic way
	op
	operations for algorithm
	red
	namespace for potential reducer operations
	sse2
	namespace to support sse2 vectorization
	sv
	namespace for savers
	utils
	namespace for helper utils of the project

Classes
struct	Shape
	shape of a tensor IMPORTANT NOTE: this shape is different from numpy.shape shape[0] gives the lowest dimension, shape[dimension-1] gives the highest dimension shape[k] corresponds to k-th dimension of tensor More...
struct	cpu
	device name CPU More...
struct	gpu
	device name CPU More...
struct	Tensor
	general tensor More...
struct	Tensor< Device, 1 >
class	TensorContainer
	tensor container that does memory allocation and resize like STL, use it to save the lines of FreeSpace in class. Do not abuse it, efficiency can come from pre-allocation and no re-allocation More...
struct	MapExpCPUEngine
struct	MapExpCPUEngine< false, SV, dim, E, etype >
struct	MapExpCPUEngine< true, SV, dim, E, etype >
class	Random
	random number generator More...
class	Random< cpu >
	CPU random number generator. More...

Typedefs
typedef float	real_t
	type that will be used for content
typedef unsigned	index_t
	type that will be used for index

Functions
MSHADOW_XINLINE Shape< 1 >	Shape1 (index_t s0)
	construct a one dimension shape, stride will equal s0 More...
MSHADOW_XINLINE Shape< 2 >	Shape2 (index_t s1, index_t s0)
	construct a two dimension shape, stride will equal s0 More...
MSHADOW_XINLINE Shape< 3 >	Shape3 (index_t s2, index_t s1, index_t s0)
	construct a three dimension shape, stride will equal s0 More...
MSHADOW_XINLINE Shape< 4 >	Shape4 (index_t s3, index_t s2, index_t s1, index_t s0)
	construct a four dimension shape, stride will equal s0 More...
void	InitTensorEngine (int device_id=0)
	initialize tensor engine, used to call intialization functions of dependent libs this function should be called before all GPU tensor operations, for using tensors in CPU, this call is actually not needed More...
void	ShutdownTensorEngine (void)
	Shutdown tensor engine, this function should be called after all GPU tensor operations, for using tensors in CPU, this call is actually not needed.
template<int dim>
void	AllocSpace (Tensor< cpu, dim > &obj, bool pad=MSHADOW_ALLOC_PAD)
	CPU/CPU: allocate space for CTensor, according to the shape in the obj this function is responsible to set the stride_ in each obj.shape. More...
template<int dim>
void	AllocSpace (Tensor< gpu, dim > &obj, bool pad=MSHADOW_ALLOC_PAD)
	refer to comment of cpu ver More...
template<int dim>
void	FreeSpace (Tensor< cpu, dim > &obj)
	CPU/GPU: free the space of tensor, will set obj.dptr to NULL. More...
template<int dim>
void	FreeSpace (Tensor< gpu, dim > &obj)
	refer to comment of cpu ver More...
template<typename Device , int dim>
Tensor< Device, dim >	NewTensor (const Shape< dim > &shape, real_t initv, bool pad=MSHADOW_ALLOC_PAD)
	CPU/GPU: short cut to allocate and initialize a Tensor. More...
template<int dim>
void	Copy (Tensor< cpu, dim > dst, const Tensor< cpu, dim > &src)
	copy data from one tensor to another, with same shape More...
template<int dim>
void	Copy (Tensor< cpu, dim > dst, const Tensor< gpu, dim > &src)
	refer to comment of cpu ver More...
template<int dim>
void	Copy (Tensor< gpu, dim > dst, const Tensor< cpu, dim > &src)
	refer to comment of cpu ver More...
template<int dim>
void	Copy (Tensor< gpu, dim > dst, const Tensor< gpu, dim > &src)
	refer to comment of cpu ver More...
void	Softmax (Tensor< cpu, 2 > dst, const Tensor< cpu, 2 > &energy)
	CPU/GPU: normalize softmax: dst[i][j] = exp( energy[i][j] ) /( sum_j exp( energy[i][j] ) ) More...
void	Softmax (Tensor< gpu, 2 > dst, const Tensor< gpu, 2 > &energy)
	refer to comment of cpu ver More...
template<typename Saver , int dim, typename E , int etype>
void	MapExp (Tensor< cpu, dim > dst, const expr::Exp< E, etype > &exp)
	CPU/GPU: map a expression to a tensor, this function calls MapPlan. More...
template<typename Saver , int dim, typename E , int etype>
void	MapExp (Tensor< gpu, dim > dst, const expr::Exp< E, etype > &exp)
	refer to comment of cpu ver More...
template<typename Saver , typename Reducer , typename E , int etype>
void	MapReduceKeepLowest (Tensor< cpu, 1 > dst, const expr::Exp< E, etype > &exp, real_t scale=1.0f)
	CPU/GPU: map a expression, do reduction to 1D Tensor in lowest dimension (dimension 0) More...
template<typename Saver , typename Reducer , typename E , int etype>
void	MapReduceKeepLowest (Tensor< gpu, 1 > dst, const expr::Exp< E, etype > &exp, real_t scale=1.0f)
	refer to comment of cpu ver More...
template<typename Saver , typename Reducer , int dimkeep, typename E , int etype>
void	MapReduceKeepHighDim (Tensor< cpu, 1 > dst, const expr::Exp< E, etype > &exp, real_t scale=1.0f)
	CPU/GPU: map a expression, do reduction to 1D Tensor in third dimension (dimension 2) More...
template<typename Saver , typename Reducer , int dimkeep, typename E , int etype>
void	MapReduceKeepHighDim (Tensor< gpu, 1 > dst, const expr::Exp< E, etype > &exp, real_t scale=1.0f)
	refer to comment of cpu ver More...
template<typename Saver , typename E , int dim>
void	MapPlan (Tensor< cpu, dim > _dst, const expr::Plan< E > &plan)
void	Softmax (Tensor< cpu, 1 > dst, const Tensor< cpu, 1 > &energy)
template<typename A , typename B , int dim>
void	Copy (Tensor< A, dim > _dst, Tensor< B, dim > _src, cudaMemcpyKind kind)
template<int dim, typename TStream >
void	SaveBinary (TStream &fo, const Tensor< cpu, dim > &src)
	CPU/GPU: save a tensor by binary format, for GPU version, a temp Tensor<cpu,dim> storage will be allocated. More...
template<int dim, typename TStream >
void	SaveBinary (TStream &fo, const Tensor< gpu, dim > &src)
	refer to comment of cpu ver More...
template<int dim, typename TStream >
void	LoadBinary (TStream &fi, Tensor< cpu, dim > &dst, bool pre_alloc)
	CPU/GPU: load a tensor by binary format, for GPU version, a temp Tensor<cpu,dim> storage will be allocated if pre_alloc is true , then space in dst is preallocated, and must have same shape of the tensor loaded if pre_alloc is false, then dst originally does not have space allocated, LoadBinary will allocate space for dst. More...
template<int dim, typename TStream >
void	LoadBinary (TStream &fi, Tensor< gpu, dim > &dst, bool pre_alloc)
	refer to comment of cpu ver More...
template<typename SV , typename E , int dim>
void	MapSSEPlan (Tensor< cpu, dim > _dst, const expr::SSEPlan< E > &plan)
	use SSEPlan to compute result

Variables
const unsigned	kRandBufferSize = 1000000
	buffer size for each random number generator
const float	kPi = 3.1415926f
	pi

Detailed Description

namespace for mshadow

Function Documentation

template<int dim>

void mshadow::AllocSpace ( Tensor< cpu, dim > &  obj, bool  pad = MSHADOW_ALLOC_PAD  )

inline

CPU/CPU: allocate space for CTensor, according to the shape in the obj this function is responsible to set the stride_ in each obj.shape.

Template Parameters

dim	specify the dim of tensor

Parameters

obj	the tensor object, with shape specified
pad	whether padding dimension 0, to make last dimension aligned, padding may help improve efficiency of matrix multiplications if true, will allocate space with stride_ that may not equals shape[0] if false, will allocate continuous space

template<int dim>

void mshadow::AllocSpace ( Tensor< gpu, dim > &  obj, bool  pad = MSHADOW_ALLOC_PAD  )

inline

refer to comment of cpu ver

See Also

AllocSpace

template<int dim>

void mshadow::Copy ( Tensor< cpu, dim >  dst, const Tensor< cpu, dim > &  src  )

inline

copy data from one tensor to another, with same shape

Template Parameters

dim	specify the dim of tensor

Parameters

dst	target tensor
src	source tensor

template<int dim>

void mshadow::Copy ( Tensor< cpu, dim >  dst, const Tensor< gpu, dim > &  src  )

inline

refer to comment of cpu ver

See Also

Copy

template<int dim>

void mshadow::Copy ( Tensor< gpu, dim >  dst, const Tensor< cpu, dim > &  src  )

inline

refer to comment of cpu ver

See Also

Copy

template<int dim>

void mshadow::Copy ( Tensor< gpu, dim >  dst, const Tensor< gpu, dim > &  src  )

inline

refer to comment of cpu ver

See Also

Copy

template<int dim>

void mshadow::FreeSpace ( Tensor< cpu, dim > &  obj )

inline

CPU/GPU: free the space of tensor, will set obj.dptr to NULL.

Template Parameters

dim	specify the dim of tensor

Parameters

obj	the tensor object

template<int dim>

void mshadow::FreeSpace ( Tensor< gpu, dim > &  obj )

inline

refer to comment of cpu ver

See Also

FreeSpace

void mshadow::InitTensorEngine ( int  device_id = 0 )

inline

initialize tensor engine, used to call intialization functions of dependent libs this function should be called before all GPU tensor operations, for using tensors in CPU, this call is actually not needed

Parameters

device_id

GPU device id to be choosed

template<int dim, typename TStream >

void mshadow::LoadBinary ( TStream &  fi, Tensor< cpu, dim > &  dst, bool  pre_alloc  )

inline

CPU/GPU: load a tensor by binary format, for GPU version, a temp Tensor<cpu,dim> storage will be allocated if pre_alloc is true , then space in dst is preallocated, and must have same shape of the tensor loaded if pre_alloc is false, then dst originally does not have space allocated, LoadBinary will allocate space for dst.

Parameters

fi	output binary stream
dst	destination file
pre_alloc	whether space is pre-allocated, if false, space allocation will happen

Template Parameters

dim	dimension of tensor
TStream	type of stream, need to support Read, Write, one example is utils::IStream.

template<int dim, typename TStream >

void mshadow::LoadBinary ( TStream &  fi, Tensor< gpu, dim > &  dst, bool  pre_alloc  )

inline

refer to comment of cpu ver

See Also

LoadBinary

template<typename Saver , int dim, typename E , int etype>

void mshadow::MapExp ( Tensor< cpu, dim >  dst, const expr::Exp< E, etype > &  exp  )

inline

CPU/GPU: map a expression to a tensor, this function calls MapPlan.

Template Parameters

Saver	specify storage method
dim	dim of the tensor, during usage, there is no need to specify this parameter
E	specifies the expression type, not need to specify this parameter during usage
etype	expression type

Parameters

dst	destination
exp	expression

See Also

namespace mshadow:sv, mshadow::op, mshadow::expr

template<typename Saver , int dim, typename E , int etype>

void mshadow::MapExp ( Tensor< gpu, dim >  dst, const expr::Exp< E, etype > &  exp  )

inline

refer to comment of cpu ver

See Also

MapExp

template<typename Saver , typename Reducer , int dimkeep, typename E , int etype>

void mshadow::MapReduceKeepHighDim ( Tensor< cpu, 1 >  dst, const expr::Exp< E, etype > &  exp, real_t  scale = 1.0f  )

inline

CPU/GPU: map a expression, do reduction to 1D Tensor in third dimension (dimension 2)

Template Parameters

Saver	specify storage method
Reducer	specify a reducer method
E	specifies the expression type, not need to specify this parameter during usage
dimkeep	the target dimension to be kept, should be larger than 0, for 0, use MapReduceKeepLowest
etype	expression type

Parameters

dst	destination
exp	expression
scale	scale the result before save

See Also

namespace mshadow:sv, mshadow::op, mshadow::red, mshadow::expr

template<typename Saver , typename Reducer , int dimkeep, typename E , int etype>

void mshadow::MapReduceKeepHighDim ( Tensor< gpu, 1 >  dst, const expr::Exp< E, etype > &  exp, real_t  scale = 1.0f  )

inline

refer to comment of cpu ver

See Also

MapReduceKeepHighDim

template<typename Saver , typename Reducer , typename E , int etype>

void mshadow::MapReduceKeepLowest ( Tensor< cpu, 1 >  dst, const expr::Exp< E, etype > &  exp, real_t  scale = 1.0f  )

inline

CPU/GPU: map a expression, do reduction to 1D Tensor in lowest dimension (dimension 0)

Template Parameters

Saver	specify storage method
Reducer	specify a reducer method
E	specifies the expression type, not need to specify this parameter during usage
etype	expression type

Parameters

dst	destination
exp	expression
scale	scale the result before save

See Also

namespace mshadow:sv, mshadow::op, mshadow::red, mshadow::expr

template<typename Saver , typename Reducer , typename E , int etype>

void mshadow::MapReduceKeepLowest ( Tensor< gpu, 1 >  dst, const expr::Exp< E, etype > &  exp, real_t  scale = 1.0f  )

inline

refer to comment of cpu ver

See Also

MapReduceKeepLowest

template<typename Device , int dim>

Tensor< Device, dim > mshadow::NewTensor ( const Shape< dim > &  shape, real_t  initv, bool  pad = MSHADOW_ALLOC_PAD  )

inline

CPU/GPU: short cut to allocate and initialize a Tensor.

Template Parameters

Device	device of tensor
dim	dimention of tensor

Parameters

shape	shape of tensor
initv	initialization value
pad	: padding option

See Also

AllocSpace

template<int dim, typename TStream >

void mshadow::SaveBinary ( TStream &  fo, const Tensor< cpu, dim > &  src  )

inline

CPU/GPU: save a tensor by binary format, for GPU version, a temp Tensor<cpu,dim> storage will be allocated.

Parameters

fo	output binary stream
src	source data file

Template Parameters

dim	dimension of tensor
TStream	type of stream, need to support Read, Write, one example is utils::IStream.

template<int dim, typename TStream >

void mshadow::SaveBinary ( TStream &  fo, const Tensor< gpu, dim > &  src  )

inline

refer to comment of cpu ver

See Also

SaveBinary

MSHADOW_XINLINE Shape<1> mshadow::Shape1

(

index_t

s0

)

construct a one dimension shape, stride will equal s0

Parameters

s0	size of dimension 0

Returns

the shape construction

MSHADOW_XINLINE Shape<2> mshadow::Shape2	(	index_t	s1,
		index_t	s0
	)

construct a two dimension shape, stride will equal s0

Parameters

s1	size of dimension 1
s0	size of dimension 0

Returns

the shape construction

MSHADOW_XINLINE Shape<3> mshadow::Shape3	(	index_t	s2,
		index_t	s1,
		index_t	s0
	)

construct a three dimension shape, stride will equal s0

Parameters

s2	size of dimension 2
s1	size of dimension 1
s0	size of dimension 0

Returns

the shape construction

MSHADOW_XINLINE Shape<4> mshadow::Shape4	(	index_t	s3,
		index_t	s2,
		index_t	s1,
		index_t	s0
	)

construct a four dimension shape, stride will equal s0

Parameters

s3	size of dimension 3
s2	size of dimension 2
s1	size of dimension 1
s0	size of dimension 0

Returns

the shape construction

void mshadow::Softmax ( Tensor< cpu, 2 >  dst, const Tensor< cpu, 2 > &  energy  )

inline

CPU/GPU: normalize softmax: dst[i][j] = exp( energy[i][j] ) /( sum_j exp( energy[i][j] ) )

Parameters

dst	destination
energy	input energy

void mshadow::Softmax ( Tensor< gpu, 2 >  dst, const Tensor< gpu, 2 > &  energy  )

inline

refer to comment of cpu ver

See Also

Softmax