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). More...

Public Member Functions
	Dropout (const double ratio=0.5, const bool rescale=true)
	Create the Dropout object using the specified ratio and rescale parameter. More...

template<typename eT >
void	Backward (const arma::Mat< eT > &&, 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<typename eT >
void	Forward (const arma::Mat< eT > &&input, arma::Mat< eT > &&output)
	Ordinary feed forward pass of the dropout layer. More...

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

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

bool	Rescale () const
	The value of the rescale parameter. More...

bool &	Rescale ()
	Modify the value of the rescale parameter. More...

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

Private Attributes
OutputDataType	delta
	Locally-stored delta object. More...

bool	deterministic
	If true dropout and scaling is disabled, see notes above. More...

InputDataType	inputParameter
	Locally-stored input parameter object. More...

OutputDataType	mask
	Locally-stored mast object. More...

OutputDataType	outputParameter
	Locally-stored output parameter object. More...

double	ratio
	The probability of setting a value to zero. More...

bool	rescale
	If true the input is rescaled when deterministic is False. More...

double	scale
	The scale fraction. More...

Detailed Description

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

If rescale is true the input is scaled with 1 / (1-p) when deterministic is false. In the deterministic mode (during testing), the layer just scales the output.

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},
}

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 54 of file dropout.hpp.