MiniBatchDiscrimination< InputDataType, OutputDataType > Class Template Reference

Implementation of the MiniBatchDiscrimination layer. More...

Public Member Functions

 MiniBatchDiscrimination ()
 Create the MiniBatchDiscrimination object. More...

 
 MiniBatchDiscrimination (const size_t inSize, const size_t outSize, const size_t features)
 Create the MiniBatchDiscrimination layer object using the specified number of units. More...

 
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 through f. More...

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

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

 
template
<
typename
eT
>
void Forward (const arma::Mat< eT > &input, arma::Mat< eT > &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 > &, arma::Mat< eT > &gradient)
 Calculate the gradient using the output delta and the input activation. More...

 
OutputDataType const & Gradient () const
 Get the gradient. More...

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

 
InputDataType const & InputParameter () const
 Get the input parameter. More...

 
InputDataType & InputParameter ()
 Modify the input parameter. More...

 
size_t InputShape () const
 Get the shape of the input. 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...

 
void Reset ()
 Reset the layer parameter. More...

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

 

Detailed Description


template
<
typename
InputDataType
=
arma::mat
,
typename
OutputDataType
=
arma::mat
>

class mlpack::ann::MiniBatchDiscrimination< InputDataType, OutputDataType >

Implementation of the MiniBatchDiscrimination layer.

MiniBatchDiscrimination is a layer of the discriminator that allows the discriminator to look at multiple data examples in combination and perform what is called as mini-batch discrimination. This helps prevent the collapse of the generator parameters to a setting where it emits the same point. This happens because normally a discriminator will process each example independently and there will be no mechanism to diversify the outputs of the generator.

For more information, see the following.

@article{Goodfellow2016,
author = {Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung,
Alec Radford, Xi Chen},
title = {Improved Techniques for Training GANs},
year = {2016},
url = {https://arxiv.org/abs/1606.03498},
}
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 118 of file layer_types.hpp.

Constructor & Destructor Documentation

◆ MiniBatchDiscrimination() [1/2]

◆ MiniBatchDiscrimination() [2/2]

MiniBatchDiscrimination ( const size_t  inSize,
const size_t  outSize,
const size_t  features 
)

Create the MiniBatchDiscrimination layer object using the specified number of units.

Parameters
inSizeThe number of input units.
outSizeThe number of output units.
featuresThe number of features to compute for each dimension.

Member Function Documentation

◆ 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 through 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 128 of file minibatch_discrimination.hpp.

◆ Delta() [2/2]

OutputDataType& Delta ( )
inline

Modify the delta.

Definition at line 130 of file minibatch_discrimination.hpp.

◆ Forward()

void Forward ( const arma::Mat< eT > &  input,
arma::Mat< eT > &  output 
)

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

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

◆ Gradient() [1/3]

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

Calculate the gradient using the output delta and the input activation.

Parameters
inputThe input parameter used for calculating the gradient.
*(error) The calculated error.
gradientThe calculated gradient.

◆ Gradient() [2/3]

OutputDataType const& Gradient ( ) const
inline

Get the gradient.

Definition at line 133 of file minibatch_discrimination.hpp.

◆ Gradient() [3/3]

OutputDataType& Gradient ( )
inline

Modify the gradient.

Definition at line 135 of file minibatch_discrimination.hpp.

◆ InputParameter() [1/2]

InputDataType const& InputParameter ( ) const
inline

Get the input parameter.

Definition at line 118 of file minibatch_discrimination.hpp.

◆ InputParameter() [2/2]

InputDataType& InputParameter ( )
inline

Modify the input parameter.

Definition at line 120 of file minibatch_discrimination.hpp.

◆ InputShape()

size_t InputShape ( ) const
inline

Get the shape of the input.

Definition at line 138 of file minibatch_discrimination.hpp.

References MiniBatchDiscrimination< InputDataType, OutputDataType >::serialize().

◆ OutputParameter() [1/2]

OutputDataType const& OutputParameter ( ) const
inline

Get the output parameter.

Definition at line 123 of file minibatch_discrimination.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )
inline

Modify the output parameter.

Definition at line 125 of file minibatch_discrimination.hpp.

◆ Parameters() [1/2]

OutputDataType const& Parameters ( ) const
inline

Get the parameters.

Definition at line 113 of file minibatch_discrimination.hpp.

◆ Parameters() [2/2]

OutputDataType& Parameters ( )
inline

Modify the parameters.

Definition at line 115 of file minibatch_discrimination.hpp.

◆ Reset()

void Reset ( )

Reset the layer parameter.

◆ serialize()

void serialize ( Archive &  ar,
const uint32_t   
)

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