BatchNorm2DT< T, num_filters_t, num_features_t, affine > Class Template Reference

Static batch normalization layer. More...

Public Member Functions
	BatchNorm2DT ()
std::string	getName () const noexcept
	Returns the name of this layer. More...
constexpr bool	isActivation () const noexcept
	Returns false since batch-norm is not an activation layer. More...
RTNEURAL_REALTIME void	reset ()
	Resets the layer state. More...
template<bool isAffine = affine>
RTNEURAL_REALTIME std::enable_if< isAffine, void >::type	forward (const T(&ins)[in_size]) noexcept
	Performs forward propagation for this layer. More...
template<bool isAffine = affine>
RTNEURAL_REALTIME std::enable_if<!isAffine, void >::type	forward (const T(&ins)[in_size]) noexcept
	Performs forward propagation for this layer. More...
template<bool isAffine = affine>
RTNEURAL_REALTIME std::enable_if< isAffine, void >::type	setGamma (const std::vector< T > &gammaVals)
	Sets the layer "gamma" values. More...
template<bool isAffine = affine>
RTNEURAL_REALTIME std::enable_if<!isAffine, void >::type	setGamma (const std::vector< T > &)
	Sets the layer "gamma" values. More...
template<bool isAffine = affine>
RTNEURAL_REALTIME std::enable_if< isAffine, void >::type	setBeta (const std::vector< T > &betaVals)
	Sets the layer "beta" values. More...
template<bool isAffine = affine>
RTNEURAL_REALTIME std::enable_if<!isAffine, void >::type	setBeta (const std::vector< T > &)
	Sets the layer "beta" values. More...
RTNEURAL_REALTIME void	setRunningMean (const std::vector< T > &runningMean)
	Sets the layer's trained running mean. More...
RTNEURAL_REALTIME void	setRunningVariance (const std::vector< T > &runningVar)
	Set's the layer's trained running variance. More...
RTNEURAL_REALTIME void	setEpsilon (T epsilon)
	Set's the layer "epsilon" value. More...

Public Attributes
T	outs [out_size]

Static Public Attributes
static constexpr auto	in_size = num_filters_t * num_features_t
static constexpr auto	out_size = num_filters_t * num_features_t
static constexpr auto	num_filters = num_filters_t
static constexpr auto	num_features = num_features_t
static constexpr bool	is_affine = affine

Detailed Description

template<typename T, int num_filters_t, int num_features_t, bool affine = true>
class RTNEURAL_NAMESPACE::BatchNorm2DT< T, num_filters_t, num_features_t, affine >

Static batch normalization layer.

Constructor & Destructor Documentation

BatchNorm2DT()

BatchNorm2DT

(

)

Member Function Documentation

getName()

std::string getName ( ) const

noexcept

Returns the name of this layer.

isActivation()

constexpr bool isActivation ( ) const

constexprnoexcept

Returns false since batch-norm is not an activation layer.

reset()

RTNEURAL_REALTIME void reset

(

)

Resets the layer state.

forward() [1/2]

RTNEURAL_REALTIME std::enable_if<isAffine, void>::type forward ( const T(&)  ins[in_size] )

noexcept

Performs forward propagation for this layer.

References BatchNorm2DT< T, num_filters_t, num_features_t, affine >::num_features, BatchNorm2DT< T, num_filters_t, num_features_t, affine >::num_filters, and BatchNorm2DT< T, num_filters_t, num_features_t, affine >::outs.

forward() [2/2]

RTNEURAL_REALTIME std::enable_if<!isAffine, void>::type forward ( const T(&)  ins[in_size] )

noexcept

Performs forward propagation for this layer.

References BatchNorm2DT< T, num_filters_t, num_features_t, affine >::num_features, BatchNorm2DT< T, num_filters_t, num_features_t, affine >::num_filters, and BatchNorm2DT< T, num_filters_t, num_features_t, affine >::outs.

setGamma() [1/2]

RTNEURAL_REALTIME std::enable_if<isAffine, void>::type setGamma

(

const std::vector< T > &

gammaVals

)

Sets the layer "gamma" values.

setGamma() [2/2]

RTNEURAL_REALTIME std::enable_if<!isAffine, void>::type setGamma

(

const std::vector< T > &

)

Sets the layer "gamma" values.

setBeta() [1/2]

RTNEURAL_REALTIME std::enable_if<isAffine, void>::type setBeta

(

const std::vector< T > &

betaVals

)

Sets the layer "beta" values.

setBeta() [2/2]

RTNEURAL_REALTIME std::enable_if<!isAffine, void>::type setBeta

(

const std::vector< T > &

)

Sets the layer "beta" values.

setRunningMean()

RTNEURAL_REALTIME void setRunningMean

(

const std::vector< T > &

runningMean

)

Sets the layer's trained running mean.

setRunningVariance()

RTNEURAL_REALTIME void setRunningVariance

(

const std::vector< T > &

runningVar

)

Set's the layer's trained running variance.

setEpsilon()

RTNEURAL_REALTIME void setEpsilon

(

T

epsilon

)

Set's the layer "epsilon" value.

Member Data Documentation

in_size

constexpr auto in_size = num_filters_t * num_features_t

staticconstexpr

out_size

constexpr auto out_size = num_filters_t * num_features_t

staticconstexpr

num_filters

constexpr auto num_filters = num_filters_t

staticconstexpr

Referenced by BatchNorm2DT< T, num_filters_t, num_features_t, affine >::forward().

num_features

constexpr auto num_features = num_features_t

staticconstexpr

Referenced by BatchNorm2DT< T, num_filters_t, num_features_t, affine >::forward().

is_affine

constexpr bool is_affine = affine

staticconstexpr

outs

T outs[out_size]

Referenced by BatchNorm2DT< T, num_filters_t, num_features_t, affine >::forward().

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

• batchnorm2d.h