mlpack 3.4.2
Public Member Functions | List of all members
Constant< InputDataType, OutputDataType > Class Template Reference

Implementation of the constant layer. More...

#include <constant.hpp>

Public Member Functions

 Constant (const size_t outSize=0, const double scalar=0.0)
 Create the Constant object that outputs a given constant scalar value given any input value. More...
 
template<typename DataType >
void Backward (const DataType &, const DataType &, DataType &g)
 Ordinary feed backward pass of a neural network. More...
 
OutputDataType & Delta ()
 Modify the delta. More...
 
OutputDataType & Delta () const
 Get the delta. More...
 
template<typename InputType , typename OutputType >
void Forward (const InputType &input, OutputType &output)
 Ordinary feed forward pass of a neural network. More...
 
OutputDataType & OutputParameter ()
 Modify the output parameter. More...
 
OutputDataType & OutputParameter () const
 Get the output parameter. More...
 
size_t OutSize () const
 Get the output size. More...
 
template<typename Archive >
void serialize (Archive &ar, const unsigned int)
 Serialize the layer. More...
 

Detailed Description

template<typename InputDataType = arma::mat, typename OutputDataType = arma::mat>
class mlpack::ann::Constant< InputDataType, OutputDataType >

Implementation of the constant layer.

The constant layer outputs a given constant value given any input value.

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).

Definition at line 34 of file constant.hpp.

Constructor & Destructor Documentation

◆ Constant()

Constant ( const size_t  outSize = 0,
const double  scalar = 0.0 
)

Create the Constant object that outputs a given constant scalar value given any input value.

Parameters
outSizeThe number of output units.
scalarThe constant value used to create the constant output.

Member Function Documentation

◆ Backward()

void Backward ( const DataType &  ,
const DataType &  ,
DataType &  g 
)

Ordinary feed backward pass of a neural network.

The backward pass of the constant layer is returns always a zero output error matrix.

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

◆ Delta() [1/2]

OutputDataType & Delta ( )
inline

Modify the delta.

Definition at line 77 of file constant.hpp.

◆ Delta() [2/2]

OutputDataType & Delta ( ) const
inline

Get the delta.

Definition at line 75 of file constant.hpp.

◆ Forward()

void Forward ( const InputType &  input,
OutputType &  output 
)

Ordinary feed forward pass of a neural network.

The forward pass fills the output with the specified constant parameter.

Parameters
inputInput data used for evaluating the specified function.
outputResulting output activation.

◆ OutputParameter() [1/2]

OutputDataType & OutputParameter ( )
inline

Modify the output parameter.

Definition at line 72 of file constant.hpp.

◆ OutputParameter() [2/2]

OutputDataType & OutputParameter ( ) const
inline

Get the output parameter.

Definition at line 70 of file constant.hpp.

◆ OutSize()

size_t OutSize ( ) const
inline

Get the output size.

Definition at line 80 of file constant.hpp.

◆ serialize()

void serialize ( Archive &  ar,
const unsigned int   
)

Serialize the layer.


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