MultiplyMerge< InputDataType, OutputDataType, CustomLayers > Class Template Reference

Implementation of the MultiplyMerge module class. More...

Public Member Functions

 MultiplyMerge (const bool model=false, const bool run=true)
 Create the MultiplyMerge object using the specified parameters. More...

 
 MultiplyMerge (const MultiplyMerge &layer)
 Copy Constructor. More...

 
 MultiplyMerge (MultiplyMerge &&layer)
 Move Constructor. More...

 
 ~MultiplyMerge ()
 Destructor to release allocated memory. More...

 
template<class LayerType , class... Args>
void Add (Args... args)
 
void Add (LayerTypes< CustomLayers... > layer)
 
template
<
typename
eT
>
void Backward (const arma::Mat< eT > &, const arma::Mat< eT > &gy, arma::Mat< eT > &g)
 Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backwards trough f, using the results from the feed forward pass. More...

 
OutputDataType const & Delta () const
 Get the delta. More...

 
OutputDataType & Delta ()
 Modify the delta. More...

 
template
<
typename
InputType
,
typename
OutputType
>
void Forward (const InputType &, OutputType &output)
 Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activity forward through f. More...

 
template
<
typename
eT
>
void Gradient (const arma::Mat< eT > &input, const arma::Mat< eT > &error, arma::Mat< eT > &gradient)
 
OutputDataType const & Gradient () const
 Get the gradient. More...

 
OutputDataType & Gradient ()
 Modify the gradient. More...

 
std::vector< LayerTypes< CustomLayers... > > & Model ()
 Return the model modules. More...

 
MultiplyMergeoperator= (const MultiplyMerge &layer)
 Copy assignment operator. More...

 
MultiplyMergeoperator= (MultiplyMerge &&layer)
 Move assignment operator. More...

 
OutputDataType const & OutputParameter () const
 Get the output parameter. More...

 
OutputDataType & OutputParameter ()
 Modify the output parameter. More...

 
OutputDataType const & Parameters () const
 Get the parameters. More...

 
OutputDataType & Parameters ()
 Modify the parameters. More...

 
template
<
typename
Archive
>
void serialize (Archive &ar, const uint32_t)
 Serialize the layer. More...

 
size_t WeightSize () const
 Get the size of the weights. More...

 

Detailed Description


template<typename InputDataType = arma::mat, typename OutputDataType = arma::mat, typename... CustomLayers>
class mlpack::ann::MultiplyMerge< InputDataType, OutputDataType, CustomLayers >

Implementation of the MultiplyMerge module class.

The MultiplyMerge class multiplies the output of various modules element-wise.

Template Parameters
InputDataTypeType of the input data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).
OutputDataTypeType of the output data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).
CustomLayersAdditional custom layers that can be added.

Definition at line 211 of file layer_types.hpp.

Constructor & Destructor Documentation

◆ MultiplyMerge() [1/3]

MultiplyMerge ( const bool  model = false,
const bool  run = true 
)

Create the MultiplyMerge object using the specified parameters.

Parameters
modelExpose all the network modules.
runCall the Forward/Backward method before the output is merged.

◆ MultiplyMerge() [2/3]

MultiplyMerge ( const MultiplyMerge< InputDataType, OutputDataType, CustomLayers > &  layer)

Copy Constructor.

◆ MultiplyMerge() [3/3]

MultiplyMerge ( MultiplyMerge< InputDataType, OutputDataType, CustomLayers > &&  layer)

Move Constructor.

◆ ~MultiplyMerge()

Destructor to release allocated memory.

Member Function Documentation

◆ Add() [1/2]

void Add ( Args...  args)
inline

Definition at line 110 of file multiply_merge.hpp.

◆ Add() [2/2]

void Add ( LayerTypes< CustomLayers... >  layer)
inline

Definition at line 117 of file multiply_merge.hpp.

◆ Backward()

void Backward ( const arma::Mat< eT > &  ,
const arma::Mat< eT > &  gy,
arma::Mat< eT > &  g 
)

Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backwards trough f, using the results from the feed forward pass.

Parameters
*(input) The propagated input activation.
gyThe backpropagated error.
gThe calculated gradient.

◆ Delta() [1/2]

OutputDataType const& Delta ( ) const
inline

Get the delta.

Definition at line 125 of file multiply_merge.hpp.

◆ Delta() [2/2]

OutputDataType& Delta ( )
inline

Modify the delta.

Definition at line 127 of file multiply_merge.hpp.

◆ Forward()

void Forward ( const InputType &  ,
OutputType &  output 
)

Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activity forward through f.

Parameters
*(input) Input data used for evaluating the specified function.
outputResulting output activation.

◆ Gradient() [1/3]

void Gradient ( const arma::Mat< eT > &  input,
const arma::Mat< eT > &  error,
arma::Mat< eT > &  gradient 
)

◆ Gradient() [2/3]

OutputDataType const& Gradient ( ) const
inline

Get the gradient.

Definition at line 130 of file multiply_merge.hpp.

◆ Gradient() [3/3]

OutputDataType& Gradient ( )
inline

Modify the gradient.

Definition at line 132 of file multiply_merge.hpp.

◆ Model()

std::vector<LayerTypes<CustomLayers...> >& Model ( )
inline

Return the model modules.

Definition at line 135 of file multiply_merge.hpp.

◆ operator=() [1/2]

MultiplyMerge& operator= ( const MultiplyMerge< InputDataType, OutputDataType, CustomLayers > &  layer)

Copy assignment operator.

◆ operator=() [2/2]

MultiplyMerge& operator= ( MultiplyMerge< InputDataType, OutputDataType, CustomLayers > &&  layer)

Move assignment operator.

◆ OutputParameter() [1/2]

OutputDataType const& OutputParameter ( ) const
inline

Get the output parameter.

Definition at line 120 of file multiply_merge.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )
inline

Modify the output parameter.

Definition at line 122 of file multiply_merge.hpp.

◆ Parameters() [1/2]

OutputDataType const& Parameters ( ) const
inline

Get the parameters.

Definition at line 146 of file multiply_merge.hpp.

◆ Parameters() [2/2]

OutputDataType& Parameters ( )
inline

Modify the parameters.

Definition at line 148 of file multiply_merge.hpp.

◆ serialize()

void serialize ( Archive &  ar,
const uint32_t   
)

◆ WeightSize()

size_t WeightSize ( ) const
inline

Get the size of the weights.

Definition at line 151 of file multiply_merge.hpp.

References MultiplyMerge< InputDataType, OutputDataType, CustomLayers >::serialize().


The documentation for this class was generated from the following files:
  • /home/jenkins-mlpack/mlpack.org/_src/mlpack-git/src/mlpack/methods/ann/layer/layer_types.hpp
  • /home/jenkins-mlpack/mlpack.org/_src/mlpack-git/src/mlpack/methods/ann/layer/multiply_merge.hpp