TMVA::DNN::VGeneralLayer< Architecture_t > Member List

This is the complete list of members for TMVA::DNN::VGeneralLayer< Architecture_t >, including all inherited members.

AddWeightsXMLTo(void *parent)=0	TMVA::DNN::VGeneralLayer< Architecture_t >	pure virtual
Backward(std::vector< Matrix_t > &gradients_backward, const std::vector< Matrix_t > &activations_backward, std::vector< Matrix_t > &inp1, std::vector< Matrix_t > &inp2)=0	TMVA::DNN::VGeneralLayer< Architecture_t >	pure virtual
CopyBiases(const std::vector< Matrix_t > &otherBiases)	TMVA::DNN::VGeneralLayer< Architecture_t >
CopyWeights(const std::vector< Matrix_t > &otherWeights)	TMVA::DNN::VGeneralLayer< Architecture_t >
fActivationGradients	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
fBatchSize	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
fBiases	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
fBiasGradients	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
fDepth	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
fHeight	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
fInit	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
fInputDepth	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
fInputHeight	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
fInputWidth	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
fIsTraining	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
Forward(std::vector< Matrix_t > &input, bool applyDropout=false)=0	TMVA::DNN::VGeneralLayer< Architecture_t >	pure virtual
fOutput	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
fWeightGradients	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
fWeights	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
fWidth	TMVA::DNN::VGeneralLayer< Architecture_t >	protected
GetActivationGradients() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetActivationGradients()	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetActivationGradientsAt(size_t i)	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetActivationGradientsAt(size_t i) const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetBatchSize() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetBiases() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetBiases()	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetBiasesAt(size_t i) const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetBiasesAt(size_t i)	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetBiasGradients() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetBiasGradients()	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetBiasGradientsAt(size_t i) const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetBiasGradientsAt(size_t i)	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetDepth() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetHeight() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetInitialization() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetInputDepth() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetInputHeight() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetInputWidth() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetOutput() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetOutput()	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetOutputAt(size_t i)	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetOutputAt(size_t i) const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetWeightGradients() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetWeightGradients()	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetWeightGradientsAt(size_t i) const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetWeightGradientsAt(size_t i)	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetWeights() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetWeights()	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetWeightsAt(size_t i) const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetWeightsAt(size_t i)	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
GetWidth() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
Initialize()	TMVA::DNN::VGeneralLayer< Architecture_t >
IsTraining() const	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
Matrix_t typedef	TMVA::DNN::VGeneralLayer< Architecture_t >	private
Print() const =0	TMVA::DNN::VGeneralLayer< Architecture_t >	pure virtual
ReadMatrixXML(void *node, const char *name, Matrix_t &matrix)	TMVA::DNN::VGeneralLayer< Architecture_t >
ReadWeightsFromXML(void *parent)=0	TMVA::DNN::VGeneralLayer< Architecture_t >	pure virtual
Scalar_t typedef	TMVA::DNN::VGeneralLayer< Architecture_t >	private
SetBatchSize(size_t batchSize)	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
SetDepth(size_t depth)	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
SetDropoutProbability(Scalar_t)	TMVA::DNN::VGeneralLayer< Architecture_t >	inlinevirtual
SetHeight(size_t height)	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
SetInputDepth(size_t inputDepth)	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
SetInputHeight(size_t inputHeight)	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
SetInputWidth(size_t inputWidth)	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
SetIsTraining(bool isTraining)	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
SetWidth(size_t width)	TMVA::DNN::VGeneralLayer< Architecture_t >	inline
Update(const Scalar_t learningRate)	TMVA::DNN::VGeneralLayer< Architecture_t >
UpdateBiases(const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate)	TMVA::DNN::VGeneralLayer< Architecture_t >
UpdateBiasGradients(const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate)	TMVA::DNN::VGeneralLayer< Architecture_t >
UpdateWeightGradients(const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate)	TMVA::DNN::VGeneralLayer< Architecture_t >
UpdateWeights(const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate)	TMVA::DNN::VGeneralLayer< Architecture_t >
VGeneralLayer(size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t Depth, size_t Height, size_t Width, size_t WeightsNSlices, size_t WeightsNRows, size_t WeightsNCols, size_t BiasesNSlices, size_t BiasesNRows, size_t BiasesNCols, size_t OutputNSlices, size_t OutputNRows, size_t OutputNCols, EInitialization Init)	TMVA::DNN::VGeneralLayer< Architecture_t >
VGeneralLayer(size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t Depth, size_t Height, size_t Width, size_t WeightsNSlices, std::vector< size_t > WeightsNRows, std::vector< size_t > WeightsNCols, size_t BiasesNSlices, std::vector< size_t > BiasesNRows, std::vector< size_t > BiasesNCols, size_t OutputNSlices, size_t OutputNRows, size_t OutputNCols, EInitialization Init)	TMVA::DNN::VGeneralLayer< Architecture_t >
VGeneralLayer(VGeneralLayer< Architecture_t > *layer)	TMVA::DNN::VGeneralLayer< Architecture_t >
VGeneralLayer(const VGeneralLayer &)	TMVA::DNN::VGeneralLayer< Architecture_t >
WriteMatrixToXML(void *node, const char *name, const Matrix_t &matrix)	TMVA::DNN::VGeneralLayer< Architecture_t >
WriteTensorToXML(void *node, const char *name, const std::vector< Matrix_t > &tensor)	TMVA::DNN::VGeneralLayer< Architecture_t >
~VGeneralLayer()	TMVA::DNN::VGeneralLayer< Architecture_t >	virtual