mshadow::Random< cpu > Class Template Reference

CPU random number generator. More...

#include <tensor_random.h>

Public Member Functions
	Random ()
	constructor of random engine using default seed
	Random (int seed)
	constructor of random engine More...
void	Seed (int seed)
	seed random number generator using this seed More...
template<int dim>
void	SampleBinary (Tensor< cpu, dim > &src)
template<int dim>
void	SampleBinary (Tensor< cpu, dim > &dst, Tensor< cpu, dim > &src)
	generate binary data according to a probability matrix More...
template<int dim>
void	SampleUniform (Tensor< cpu, dim > &dst, real_t a=0.0f, real_t b=1.0f)
	generate data from uniform [a,b) More...
template<int dim>
void	SampleGaussian (Tensor< cpu, dim > &dst, real_t mu=0.0f, real_t sigma=1.0f)
	generate data from standard gaussian More...
template<int dim>
expr::ReshapeExp< Tensor< cpu, 1 > , dim, 1 >	gaussian (Shape< dim > shape)
	return a temporal expression storing standard gaussian random variables the temporal tensor is only valid before next call of gaussian or uniform can be used as part of expression Caution: this means expression such as A = gaussian(s1) * gaussian(s2) will give invalid result, since second call of gaussian(s2) makes gaussian(s1) invalid A = gaussian(s1)*B+C; is correct; use one gaussian/uniform in each expression More...
template<int dim>
expr::ReshapeExp< Tensor< cpu, 1 > , dim, 1 >	uniform (Shape< dim > shape)
	return a temporal expression storing standard uniform [0,1) the temporal tensor is only valid before next call of gaussian or uniform can be used as part of expression Caution: this means expression such as A = gaussian(s1) * gaussian(s2) will give invalid result, since second call of gaussian(s2) makes gaussian(s1) invalid A = gaussian(s1)*B+C; is correct; use one gaussian/uniform in each expression More...

Detailed Description

template<>
class mshadow::Random< cpu >

CPU random number generator.

Constructor & Destructor Documentation

mshadow::Random< cpu >::Random ( int  seed )

inline

constructor of random engine

Parameters

seed	random number seed

Member Function Documentation

template<int dim>

expr::ReshapeExp<Tensor<cpu,1>,dim,1> mshadow::Random< cpu >::gaussian ( Shape< dim >  shape )

inline

return a temporal expression storing standard gaussian random variables the temporal tensor is only valid before next call of gaussian or uniform can be used as part of expression Caution: this means expression such as A = gaussian(s1) * gaussian(s2) will give invalid result, since second call of gaussian(s2) makes gaussian(s1) invalid A = gaussian(s1)*B+C; is correct; use one gaussian/uniform in each expression

Parameters

shape

shape of the tensor

Template Parameters

dim	dimension of tensor

template<int dim>

void mshadow::Random< cpu >::SampleBinary ( Tensor< cpu, dim > &  dst, Tensor< cpu, dim > &  src  )

inline

generate binary data according to a probability matrix

Parameters

src	source
dst	destination
a	lower bound of uniform
b	upper bound of uniform

Template Parameters

dim	dimension of tensor

template<int dim>

void mshadow::Random< cpu >::SampleGaussian ( Tensor< cpu, dim > &  dst, real_t  mu = 0.0f, real_t  sigma = 1.0f  )

inline

generate data from standard gaussian

Parameters

dst	destination
mu	mean variable
sigma	standard deviation

Template Parameters

dim	dimension of tensor

template<int dim>

void mshadow::Random< cpu >::SampleUniform ( Tensor< cpu, dim > &  dst, real_t  a = 0.0f, real_t  b = 1.0f  )

inline

generate data from uniform [a,b)

Parameters

dst	destination
a	lower bound of uniform
b	upper bound of uniform

Template Parameters

dim	dimension of tensor

void mshadow::Random< cpu >::Seed ( int  seed )

inline

seed random number generator using this seed

Parameters

seed	seed of prng

template<int dim>

expr::ReshapeExp<Tensor<cpu,1>,dim,1> mshadow::Random< cpu >::uniform ( Shape< dim >  shape )

inline

return a temporal expression storing standard uniform [0,1) the temporal tensor is only valid before next call of gaussian or uniform can be used as part of expression Caution: this means expression such as A = gaussian(s1) * gaussian(s2) will give invalid result, since second call of gaussian(s2) makes gaussian(s1) invalid A = gaussian(s1)*B+C; is correct; use one gaussian/uniform in each expression

Parameters

shape

shape of the tensor

Template Parameters

dim	dimension of tensor

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

• /home/wangwei/program/asf/release-0.1/apache-singa-incubating-0.1.0-RC1/include/mshadow/tensor_random.h