Dropout< InputDataType, OutputDataType > Class Template Reference

The dropout layer is a regularizer that randomly with probability 'ratio' sets input values to zero and scales the remaining elements by factor 1 / (1 - ratio) rather than during test time so as to keep the expected sum same. More...

Public Member Functions
	Dropout (const double ratio=0.5)
	Create the Dropout object using the specified ratio parameter. More...
template
void	Backward (const arma::Mat< eT > &, const arma::Mat< eT > &gy, arma::Mat< eT > &g)
	Ordinary feed backward pass of the dropout layer. More...
OutputDataType const &	Delta () const
	Get the detla. More...
OutputDataType &	Delta ()
	Modify the delta. More...
bool	Deterministic () const
	The value of the deterministic parameter. More...
bool &	Deterministic ()
	Modify the value of the deterministic parameter. More...
template
void	Forward (const arma::Mat< eT > &input, arma::Mat< eT > &output)
	Ordinary feed forward pass of the dropout layer. More...
OutputDataType const &	OutputParameter () const
	Get the output parameter. More...
OutputDataType &	OutputParameter ()
	Modify the output parameter. More...
double	Ratio () const
	The probability of setting a value to zero. More...
void	Ratio (const double r)
	Modify the probability of setting a value to zero. More...
template
void	serialize (Archive &ar, const unsigned int)
	Serialize the layer. More...

Detailed Description

template
class mlpack::ann::Dropout< InputDataType, OutputDataType >

The dropout layer is a regularizer that randomly with probability 'ratio' sets input values to zero and scales the remaining elements by factor 1 / (1 - ratio) rather than during test time so as to keep the expected sum same.

In the deterministic mode (during testing), there is no change in the input.

Note: During training you should set deterministic to false and during testing you should set deterministic to true.

For more information, see the following.

@article{Hinton2012,
  author  = {Geoffrey E. Hinton, Nitish Srivastava, Alex Krizhevsky,
             Ilya Sutskever, Ruslan Salakhutdinov},
  title   = {Improving neural networks by preventing co-adaptation of feature
             detectors},
  journal = {CoRR},
  volume  = {abs/1207.0580},
  year    = {2012},
  url     = {https://arxiv.org/abs/1207.0580}
}

Template Parameters

InputDataType	Type of the input data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).
OutputDataType	Type of the output data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).

Definition at line 53 of file dropout.hpp.

Constructor & Destructor Documentation

Dropout()

Dropout

(

const double

ratio = 0.5

)

Create the Dropout object using the specified ratio parameter.

Parameters

ratio

The probability of setting a value to zero.

Member Function Documentation

Backward()

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

Ordinary feed backward pass of the dropout layer.

Parameters

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

Delta() [1/2]

OutputDataType const& Delta ( ) const

inline

Get the detla.

Definition at line 90 of file dropout.hpp.

Delta() [2/2]

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 92 of file dropout.hpp.

Deterministic() [1/2]

bool Deterministic ( ) const

inline

The value of the deterministic parameter.

Definition at line 95 of file dropout.hpp.

Deterministic() [2/2]

bool& Deterministic ( )

inline

Modify the value of the deterministic parameter.

Definition at line 97 of file dropout.hpp.

Forward()

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

Ordinary feed forward pass of the dropout layer.

Parameters

input	Input data used for evaluating the specified function.
output	Resulting output activation.

OutputParameter() [1/2]

OutputDataType const& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 85 of file dropout.hpp.

OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 87 of file dropout.hpp.

Ratio() [1/2]

double Ratio ( ) const

inline

The probability of setting a value to zero.

Definition at line 100 of file dropout.hpp.

Ratio() [2/2]

void Ratio ( const double  r )

inline

Modify the probability of setting a value to zero.

Definition at line 103 of file dropout.hpp.

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

serialize()

void serialize	(	Archive &	ar,
		const unsigned	int
	)

Serialize the layer.

Referenced by Dropout< InputDataType, OutputDataType >::Ratio().

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

• /home/jenkins-mlpack/mlpack.org/_src/mlpack-3.4.2/src/mlpack/methods/ann/layer/dropout.hpp