template<typename Architecture_t>
class TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >

Definition at line 56 of file GRULayer.h.

Public Types
using	HelperDescriptor_t = typename Architecture_t::DropoutDescriptor_t

using	LayerDescriptor_t = typename Architecture_t::RecurrentDescriptor_t

using	Matrix_t = typename Architecture_t::Matrix_t

using	RNNDescriptors_t = typename Architecture_t::RNNDescriptors_t

using	RNNWorkspace_t = typename Architecture_t::RNNWorkspace_t

using	Scalar_t = typename Architecture_t::Scalar_t

using	Tensor_t = typename Architecture_t::Tensor_t

using	TensorDescriptor_t = typename Architecture_t::TensorDescriptor_t

using	WeightsDescriptor_t = typename Architecture_t::FilterDescriptor_t

Public Member Functions
	TBasicGRULayer (const TBasicGRULayer &)
	Copy Constructor.

	TBasicGRULayer (size_t batchSize, size_t stateSize, size_t inputSize, size_t timeSteps, bool rememberState=false, bool returnSequence=false, bool resetGateAfter=false, DNN::EActivationFunction f1=DNN::EActivationFunction::kSigmoid, DNN::EActivationFunction f2=DNN::EActivationFunction::kTanh, bool training=true, DNN::EInitialization fA=DNN::EInitialization::kZero)
	Constructor.

void	AddWeightsXMLTo (void *parent)
	Writes the information and the weights about the layer in an XML node.

void	Backward (Tensor_t &gradients_backward, const Tensor_t &activations_backward)
	Backpropagates the error.

void	CandidateValue (const Matrix_t &input, Matrix_t &dc)
	Decides the new candidate values (NN with Tanh)

Matrix_t &	CellBackward (Matrix_t &state_gradients_backward, const Matrix_t &precStateActivations, const Matrix_t &reset_gate, const Matrix_t &update_gate, const Matrix_t &candidate_gate, const Matrix_t &input, Matrix_t &input_gradient, Matrix_t &dr, Matrix_t &du, Matrix_t &dc)
	Backward for a single time unit a the corresponding call to Forward(...).

void	CellForward (Matrix_t &updateGateValues, Matrix_t &candidateValues)
	Forward for a single cell (time unit)

bool	DoesRememberState () const

bool	DoesReturnSequence () const

void	Forward (Tensor_t &input, bool isTraining=true)
	Computes the next hidden state and next cell state with given input matrix.

DNN::EActivationFunction	GetActivationFunctionF1 () const

DNN::EActivationFunction	GetActivationFunctionF2 () const

Matrix_t &	GetCandidateBias ()

const Matrix_t &	GetCandidateBias () const

Matrix_t &	GetCandidateBiasGradients ()

const Matrix_t &	GetCandidateBiasGradients () const

Matrix_t &	GetCandidateDerivativesAt (size_t i)

const Matrix_t &	GetCandidateDerivativesAt (size_t i) const

std::vector< Matrix_t > &	GetCandidateGateTensor ()

const std::vector< Matrix_t > &	GetCandidateGateTensor () const

Matrix_t &	GetCandidateGateTensorAt (size_t i)

const Matrix_t &	GetCandidateGateTensorAt (size_t i) const

Matrix_t &	GetCandidateValue ()

const Matrix_t &	GetCandidateValue () const

Matrix_t &	GetCell ()

const Matrix_t &	GetCell () const

std::vector< Matrix_t > &	GetDerivativesCandidate ()

const std::vector< Matrix_t > &	GetDerivativesCandidate () const

std::vector< Matrix_t > &	GetDerivativesReset ()

const std::vector< Matrix_t > &	GetDerivativesReset () const

std::vector< Matrix_t > &	GetDerivativesUpdate ()

const std::vector< Matrix_t > &	GetDerivativesUpdate () const

Tensor_t &	GetDX ()

Tensor_t &	GetDY ()

size_t	GetInputSize () const
	Getters.

Matrix_t &	GetResetBiasGradients ()

const Matrix_t &	GetResetBiasGradients () const

Matrix_t &	GetResetDerivativesAt (size_t i)

const Matrix_t &	GetResetDerivativesAt (size_t i) const

Matrix_t &	GetResetGateBias ()

const Matrix_t &	GetResetGateBias () const

std::vector< Matrix_t > &	GetResetGateTensor ()

const std::vector< Matrix_t > &	GetResetGateTensor () const

Matrix_t &	GetResetGateTensorAt (size_t i)

const Matrix_t &	GetResetGateTensorAt (size_t i) const

Matrix_t &	GetResetGateValue ()

const Matrix_t &	GetResetGateValue () const

Matrix_t &	GetState ()

const Matrix_t &	GetState () const

size_t	GetStateSize () const

size_t	GetTimeSteps () const

Matrix_t &	GetUpdateBiasGradients ()

const Matrix_t &	GetUpdateBiasGradients () const

Matrix_t &	GetUpdateDerivativesAt (size_t i)

const Matrix_t &	GetUpdateDerivativesAt (size_t i) const

Matrix_t &	GetUpdateGateBias ()

const Matrix_t &	GetUpdateGateBias () const

std::vector< Matrix_t > &	GetUpdateGateTensor ()

const std::vector< Matrix_t > &	GetUpdateGateTensor () const

Matrix_t &	GetUpdateGateTensorAt (size_t i)

const Matrix_t &	GetUpdateGateTensorAt (size_t i) const

Matrix_t &	GetUpdateGateValue ()

const Matrix_t &	GetUpdateGateValue () const

Tensor_t &	GetWeightGradientsTensor ()

const Tensor_t &	GetWeightGradientsTensor () const

Matrix_t &	GetWeightsCandidate ()

const Matrix_t &	GetWeightsCandidate () const

Matrix_t &	GetWeightsCandidateGradients ()

const Matrix_t &	GetWeightsCandidateGradients () const

Matrix_t &	GetWeightsCandidateState ()

const Matrix_t &	GetWeightsCandidateState () const

Matrix_t &	GetWeightsCandidateStateGradients ()

const Matrix_t &	GetWeightsCandidateStateGradients () const

Matrix_t &	GetWeightsResetGate ()

const Matrix_t &	GetWeightsResetGate () const

Matrix_t &	GetWeightsResetGateState ()

const Matrix_t &	GetWeightsResetGateState () const

Matrix_t &	GetWeightsResetGradients ()

const Matrix_t &	GetWeightsResetGradients () const

Matrix_t &	GetWeightsResetStateGradients ()

const Matrix_t &	GetWeightsResetStateGradients () const

Tensor_t &	GetWeightsTensor ()

const Tensor_t &	GetWeightsTensor () const

Matrix_t &	GetWeightsUpdateGate ()

const Matrix_t &	GetWeightsUpdateGate () const

Matrix_t &	GetWeightsUpdateGateState ()

const Matrix_t &	GetWeightsUpdateGateState () const

Matrix_t &	GetWeightsUpdateGradients ()

const Matrix_t &	GetWeightsUpdateGradients () const

Matrix_t &	GetWeightsUpdateStateGradients ()

const Matrix_t &	GetWeigthsUpdateStateGradients () const

Tensor_t &	GetX ()

Tensor_t &	GetY ()

virtual void	Initialize ()
	Initialize the weights according to the given initialization method.

void	InitState (DNN::EInitialization m=DNN::EInitialization::kZero)
	Initialize the hidden state and cell state method.

void	Print () const
	Prints the info about the layer.

void	ReadWeightsFromXML (void *parent)
	Read the information and the weights about the layer from XML node.

void	ResetGate (const Matrix_t &input, Matrix_t &di)
	Decides the values we'll update (NN with Sigmoid)

void	Update (const Scalar_t learningRate)

void	UpdateGate (const Matrix_t &input, Matrix_t &df)
	Forgets the past values (NN with Sigmoid)

Public Member Functions inherited from TMVA::DNN::VGeneralLayer< Architecture_t >
	VGeneralLayer (const VGeneralLayer &)
	Copy Constructor.

	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)
	Constructor.

	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)
	General Constructor with different weights dimension.

	VGeneralLayer (VGeneralLayer< Architecture_t > *layer)
	Copy the layer provided as a pointer.

virtual	~VGeneralLayer ()
	Virtual Destructor.

void	CopyBiases (const std::vector< Matrix_t > &otherBiases)
	Copies the biases provided as an input.

template<typename Arch >
void	CopyParameters (const VGeneralLayer< Arch > &layer)
	Copy all trainable weight and biases from another equivalent layer but with different architecture The function can copy also extra parameters in addition to weights and biases if they are return by the function GetExtraLayerParameters.

void	CopyWeights (const std::vector< Matrix_t > &otherWeights)
	Copies the weights provided as an input.

Tensor_t &	GetActivationGradients ()

const Tensor_t &	GetActivationGradients () const

Matrix_t	GetActivationGradientsAt (size_t i)

const Matrix_t &	GetActivationGradientsAt (size_t i) const

size_t	GetBatchSize () const
	Getters.

std::vector< Matrix_t > &	GetBiases ()

const std::vector< Matrix_t > &	GetBiases () const

Matrix_t &	GetBiasesAt (size_t i)

const Matrix_t &	GetBiasesAt (size_t i) const

std::vector< Matrix_t > &	GetBiasGradients ()

const std::vector< Matrix_t > &	GetBiasGradients () const

Matrix_t &	GetBiasGradientsAt (size_t i)

const Matrix_t &	GetBiasGradientsAt (size_t i) const

size_t	GetDepth () const

virtual std::vector< Matrix_t >	GetExtraLayerParameters () const

size_t	GetHeight () const

EInitialization	GetInitialization () const

size_t	GetInputDepth () const

size_t	GetInputHeight () const

size_t	GetInputWidth () const

Tensor_t &	GetOutput ()

const Tensor_t &	GetOutput () const

Matrix_t	GetOutputAt (size_t i)

const Matrix_t &	GetOutputAt (size_t i) const

std::vector< Matrix_t > &	GetWeightGradients ()

const std::vector< Matrix_t > &	GetWeightGradients () const

Matrix_t &	GetWeightGradientsAt (size_t i)

const Matrix_t &	GetWeightGradientsAt (size_t i) const

std::vector< Matrix_t > &	GetWeights ()

const std::vector< Matrix_t > &	GetWeights () const

Matrix_t &	GetWeightsAt (size_t i)

const Matrix_t &	GetWeightsAt (size_t i) const

size_t	GetWidth () const

bool	IsTraining () const

void	ReadMatrixXML (void node, const char name, Matrix_t &matrix)

virtual void	ResetTraining ()
	Reset some training flags after a loop on all batches Some layer (e.g.

void	SetBatchSize (size_t batchSize)
	Setters.

void	SetDepth (size_t depth)

virtual void	SetDropoutProbability (Scalar_t)
	Set Dropout probability.

virtual void	SetExtraLayerParameters (const std::vector< Matrix_t > &)

void	SetHeight (size_t height)

void	SetInputDepth (size_t inputDepth)

void	SetInputHeight (size_t inputHeight)

void	SetInputWidth (size_t inputWidth)

void	SetIsTraining (bool isTraining)

void	SetWidth (size_t width)

void	Update (const Scalar_t learningRate)
	Updates the weights and biases, given the learning rate.

void	UpdateBiases (const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate)
	Updates the biases, given the gradients and the learning rate.

void	UpdateBiasGradients (const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate)
	Updates the bias gradients, given some other weight gradients and learning rate.

void	UpdateWeightGradients (const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate)
	Updates the weight gradients, given some other weight gradients and learning rate.

void	UpdateWeights (const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate)
	Updates the weights, given the gradients and the learning rate,.

void	WriteMatrixToXML (void node, const char name, const Matrix_t &matrix)

void	WriteTensorToXML (void node, const char name, const std::vector< Matrix_t > &tensor)
	helper functions for XML

Private Attributes
std::vector< Matrix_t >	candidate_gate_value
	Candidate gate value for every time step.

Matrix_t &	fCandidateBias
	Candidate Gate bias.

Matrix_t &	fCandidateBiasGradients
	Gradients w.r.t the candidate gate - bias weights.

Matrix_t	fCandidateValue
	Computed candidate values.

Matrix_t	fCell
	EMpty matrix for GRU.

std::vector< Matrix_t >	fDerivativesCandidate
	First fDerivatives of the activations candidate gate.

std::vector< Matrix_t >	fDerivativesReset
	First fDerivatives of the activations reset gate.

std::vector< Matrix_t >	fDerivativesUpdate
	First fDerivatives of the activations update gate.

TDescriptors *	fDescriptors = nullptr
	Keeps all the RNN descriptors.

Tensor_t	fDx
	cached gradient on the input (output of backward) as T x B x I

Tensor_t	fDy
	cached activation gradient (input of backward) as T x B x S

DNN::EActivationFunction	fF1
	Activation function: sigmoid.

DNN::EActivationFunction	fF2
	Activaton function: tanh.

bool	fRememberState
	Remember state in next pass.

Matrix_t &	fResetBiasGradients
	Gradients w.r.t the reset gate - bias weights.

bool	fResetGateAfter = false
	GRU variant to Apply the reset gate multiplication afterwards (used by cuDNN)

Matrix_t &	fResetGateBias
	Input Gate bias.

Matrix_t	fResetValue
	Computed reset gate values.

bool	fReturnSequence = false
	Return in output full sequence or just last element.

Matrix_t	fState
	Hidden state of GRU.

size_t	fStateSize
	Hidden state size for GRU.

size_t	fTimeSteps
	Timesteps for GRU.

Matrix_t &	fUpdateBiasGradients
	Gradients w.r.t the update gate - bias weights.

Matrix_t &	fUpdateGateBias
	Update Gate bias.

Matrix_t	fUpdateValue
	Computed forget gate values.

Tensor_t	fWeightGradientsTensor
	Tensor for all weight gradients.

Matrix_t &	fWeightsCandidate
	Candidate Gate weights for input, fWeights[4].

Matrix_t &	fWeightsCandidateGradients
	Gradients w.r.t the candidate gate - input weights.

Matrix_t &	fWeightsCandidateState
	Candidate Gate weights for prev state, fWeights[5].

Matrix_t &	fWeightsCandidateStateGradients
	Gradients w.r.t the candidate gate - hidden state weights.

Matrix_t &	fWeightsResetGate
	Reset Gate weights for input, fWeights[0].

Matrix_t &	fWeightsResetGateState
	Input Gate weights for prev state, fWeights[1].

Matrix_t &	fWeightsResetGradients
	Gradients w.r.t the reset gate - input weights.

Matrix_t &	fWeightsResetStateGradients
	Gradients w.r.t the reset gate - hidden state weights.

Tensor_t	fWeightsTensor
	Tensor for all weights.

Matrix_t &	fWeightsUpdateGate
	Update Gate weights for input, fWeights[2].

Matrix_t &	fWeightsUpdateGateState
	Update Gate weights for prev state, fWeights[3].

Matrix_t &	fWeightsUpdateGradients
	Gradients w.r.t the update gate - input weights.

Matrix_t &	fWeightsUpdateStateGradients
	Gradients w.r.t the update gate - hidden state weights.

TWorkspace *	fWorkspace = nullptr

Tensor_t	fX
	cached input tensor as T x B x I

Tensor_t	fY
	cached output tensor as T x B x S

std::vector< Matrix_t >	reset_gate_value
	Reset gate value for every time step.

std::vector< Matrix_t >	update_gate_value
	Update gate value for every time step.

Additional Inherited Members
Protected Attributes inherited from TMVA::DNN::VGeneralLayer< Architecture_t >
Tensor_t	fActivationGradients
	Gradients w.r.t. the activations of this layer.

size_t	fBatchSize
	Batch size used for training and evaluation.

std::vector< Matrix_t >	fBiases
	The biases associated to the layer.

std::vector< Matrix_t >	fBiasGradients
	Gradients w.r.t. the bias values of the layer.

size_t	fDepth
	The depth of the layer.

size_t	fHeight
	The height of the layer.

EInitialization	fInit
	The initialization method.

size_t	fInputDepth
	The depth of the previous layer or input.

size_t	fInputHeight
	The height of the previous layer or input.

size_t	fInputWidth
	The width of the previous layer or input.

bool	fIsTraining
	Flag indicating the mode.

Tensor_t	fOutput
	Activations of this layer.

std::vector< Matrix_t >	fWeightGradients
	Gradients w.r.t. the weights of the layer.

std::vector< Matrix_t >	fWeights
	The weights associated to the layer.

size_t	fWidth
	The width of this layer.

#include <TMVA/DNN/RNN/GRULayer.h>

Inheritance diagram for TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >:

[legend]

Member Typedef Documentation

◆ HelperDescriptor_t

template<typename Architecture_t >

using TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::HelperDescriptor_t = typename Architecture_t::DropoutDescriptor_t

Definition at line 68 of file GRULayer.h.

◆ LayerDescriptor_t

template<typename Architecture_t >

using TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::LayerDescriptor_t = typename Architecture_t::RecurrentDescriptor_t

Definition at line 65 of file GRULayer.h.

◆ Matrix_t

template<typename Architecture_t >

using TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::Matrix_t = typename Architecture_t::Matrix_t

Definition at line 61 of file GRULayer.h.

◆ RNNDescriptors_t

template<typename Architecture_t >

using TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::RNNDescriptors_t = typename Architecture_t::RNNDescriptors_t

Definition at line 71 of file GRULayer.h.

◆ RNNWorkspace_t

template<typename Architecture_t >

using TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::RNNWorkspace_t = typename Architecture_t::RNNWorkspace_t

Definition at line 70 of file GRULayer.h.

◆ Scalar_t

template<typename Architecture_t >

using TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::Scalar_t = typename Architecture_t::Scalar_t

Definition at line 62 of file GRULayer.h.

◆ Tensor_t

template<typename Architecture_t >

using TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::Tensor_t = typename Architecture_t::Tensor_t

Definition at line 63 of file GRULayer.h.

◆ TensorDescriptor_t

template<typename Architecture_t >

using TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::TensorDescriptor_t = typename Architecture_t::TensorDescriptor_t

Definition at line 67 of file GRULayer.h.

◆ WeightsDescriptor_t

template<typename Architecture_t >

using TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::WeightsDescriptor_t = typename Architecture_t::FilterDescriptor_t

Definition at line 66 of file GRULayer.h.

Constructor & Destructor Documentation

◆ TBasicGRULayer() [1/2]

template<typename Architecture_t >

TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::TBasicGRULayer	(	size_t	batchSize,
		size_t	stateSize,
		size_t	inputSize,
		size_t	timeSteps,
		bool	rememberState = `false`,
		bool	returnSequence = `false`,
		bool	resetGateAfter = `false`,
		DNN::EActivationFunction	f1 = `DNN::EActivationFunction::kSigmoid`,
		DNN::EActivationFunction	f2 = `DNN::EActivationFunction::kTanh`,
		bool	training = `true`,
		DNN::EInitialization	fA = `DNN::EInitialization::kZero`
	)

Constructor.

Definition at line 308 of file GRULayer.h.

◆ TBasicGRULayer() [2/2]

template<typename Architecture_t >

TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::TBasicGRULayer ( const TBasicGRULayer< Architecture_t > & layer )

Copy Constructor.

Definition at line 344 of file GRULayer.h.

Member Function Documentation

◆ AddWeightsXMLTo()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::AddWeightsXMLTo ( void * parent )

inlinevirtual

Writes the information and the weights about the layer in an XML node.

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 820 of file GRULayer.h.

◆ Backward()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::Backward	(	Tensor_t &	gradients_backward,
		const Tensor_t &	activations_backward
	)

inlinevirtual

Backpropagates the error.

Must only be called directly at the corresponding call to Forward(...).

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 610 of file GRULayer.h.

◆ CandidateValue()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::CandidateValue	(	const Matrix_t &	input,
		Matrix_t &	dc
	)

inline

Decides the new candidate values (NN with Tanh)

Definition at line 459 of file GRULayer.h.

◆ CellBackward()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::CellBackward	(	Matrix_t &	state_gradients_backward,
		const Matrix_t &	precStateActivations,
		const Matrix_t &	reset_gate,
		const Matrix_t &	update_gate,
		const Matrix_t &	candidate_gate,
		const Matrix_t &	input,
		Matrix_t &	input_gradient,
		Matrix_t &	dr,
		Matrix_t &	du,
		Matrix_t &	dc
	)

inline

Backward for a single time unit a the corresponding call to Forward(...).

Definition at line 775 of file GRULayer.h.

◆ CellForward()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::CellForward	(	Matrix_t &	updateGateValues,
		Matrix_t &	candidateValues
	)

inline

Forward for a single cell (time unit)

Definition at line 590 of file GRULayer.h.

◆ DoesRememberState()

template<typename Architecture_t >

bool TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::DoesRememberState ( ) const

inline

Definition at line 204 of file GRULayer.h.

◆ DoesReturnSequence()

template<typename Architecture_t >

bool TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::DoesReturnSequence ( ) const

inline

Definition at line 205 of file GRULayer.h.

◆ Forward()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::Forward	(	Tensor_t &	input,
		bool	isTraining = `true`
	)

inlinevirtual

Computes the next hidden state and next cell state with given input matrix.

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 494 of file GRULayer.h.

◆ GetActivationFunctionF1()

template<typename Architecture_t >

DNN::EActivationFunction TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetActivationFunctionF1 ( ) const

inline

Definition at line 207 of file GRULayer.h.

◆ GetActivationFunctionF2()

template<typename Architecture_t >

DNN::EActivationFunction TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetActivationFunctionF2 ( ) const

inline

Definition at line 208 of file GRULayer.h.

◆ GetCandidateBias() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetCandidateBias ( )

inline

Definition at line 269 of file GRULayer.h.

◆ GetCandidateBias() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetCandidateBias ( ) const

inline

Definition at line 268 of file GRULayer.h.

◆ GetCandidateBiasGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetCandidateBiasGradients ( )

inline

Definition at line 288 of file GRULayer.h.

◆ GetCandidateBiasGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetCandidateBiasGradients ( ) const

inline

Definition at line 287 of file GRULayer.h.

◆ GetCandidateDerivativesAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetCandidateDerivativesAt ( size_t i )

inline

Definition at line 247 of file GRULayer.h.

◆ GetCandidateDerivativesAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetCandidateDerivativesAt ( size_t i ) const

inline

Definition at line 246 of file GRULayer.h.

◆ GetCandidateGateTensor() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetCandidateGateTensor ( )

inline

Definition at line 258 of file GRULayer.h.

◆ GetCandidateGateTensor() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetCandidateGateTensor ( ) const

inline

Definition at line 257 of file GRULayer.h.

◆ GetCandidateGateTensorAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetCandidateGateTensorAt ( size_t i )

inline

Definition at line 260 of file GRULayer.h.

◆ GetCandidateGateTensorAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetCandidateGateTensorAt ( size_t i ) const

inline

Definition at line 259 of file GRULayer.h.

◆ GetCandidateValue() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetCandidateValue ( )

inline

Definition at line 213 of file GRULayer.h.

◆ GetCandidateValue() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetCandidateValue ( ) const

inline

Definition at line 212 of file GRULayer.h.

◆ GetCell() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetCell ( )

inline

Definition at line 220 of file GRULayer.h.

◆ GetCell() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetCell ( ) const

inline

Definition at line 219 of file GRULayer.h.

◆ GetDerivativesCandidate() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetDerivativesCandidate ( )

inline

Definition at line 245 of file GRULayer.h.

◆ GetDerivativesCandidate() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetDerivativesCandidate ( ) const

inline

Definition at line 244 of file GRULayer.h.

◆ GetDerivativesReset() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetDerivativesReset ( )

inline

Definition at line 237 of file GRULayer.h.

◆ GetDerivativesReset() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetDerivativesReset ( ) const

inline

Definition at line 236 of file GRULayer.h.

◆ GetDerivativesUpdate() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetDerivativesUpdate ( )

inline

Definition at line 241 of file GRULayer.h.

◆ GetDerivativesUpdate() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetDerivativesUpdate ( ) const

inline

Definition at line 240 of file GRULayer.h.

◆ GetDX()

template<typename Architecture_t >

Tensor_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetDX ( )

inline

Definition at line 297 of file GRULayer.h.

◆ GetDY()

template<typename Architecture_t >

Tensor_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetDY ( )

inline

Definition at line 298 of file GRULayer.h.

◆ GetInputSize()

template<typename Architecture_t >

size_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetInputSize ( ) const

inline

Getters.

Definition at line 200 of file GRULayer.h.

◆ GetResetBiasGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetResetBiasGradients ( )

inline

Definition at line 276 of file GRULayer.h.

◆ GetResetBiasGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetResetBiasGradients ( ) const

inline

Definition at line 275 of file GRULayer.h.

◆ GetResetDerivativesAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetResetDerivativesAt ( size_t i )

inline

Definition at line 239 of file GRULayer.h.

◆ GetResetDerivativesAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetResetDerivativesAt ( size_t i ) const

inline

Definition at line 238 of file GRULayer.h.

◆ GetResetGateBias() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetResetGateBias ( )

inline

Definition at line 265 of file GRULayer.h.

◆ GetResetGateBias() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetResetGateBias ( ) const

inline

Definition at line 264 of file GRULayer.h.

◆ GetResetGateTensor() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetResetGateTensor ( )

inline

Definition at line 250 of file GRULayer.h.

◆ GetResetGateTensor() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetResetGateTensor ( ) const

inline

Definition at line 249 of file GRULayer.h.

◆ GetResetGateTensorAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetResetGateTensorAt ( size_t i )

inline

Definition at line 252 of file GRULayer.h.

◆ GetResetGateTensorAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetResetGateTensorAt ( size_t i ) const

inline

Definition at line 251 of file GRULayer.h.

◆ GetResetGateValue() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetResetGateValue ( )

inline

Definition at line 211 of file GRULayer.h.

◆ GetResetGateValue() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetResetGateValue ( ) const

inline

Definition at line 210 of file GRULayer.h.

◆ GetState() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetState ( )

inline

Definition at line 218 of file GRULayer.h.

◆ GetState() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetState ( ) const

inline

Definition at line 217 of file GRULayer.h.

◆ GetStateSize()

template<typename Architecture_t >

size_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetStateSize ( ) const

inline

Definition at line 202 of file GRULayer.h.

◆ GetTimeSteps()

template<typename Architecture_t >

size_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetTimeSteps ( ) const

inline

Definition at line 201 of file GRULayer.h.

◆ GetUpdateBiasGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetUpdateBiasGradients ( )

inline

Definition at line 282 of file GRULayer.h.

◆ GetUpdateBiasGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetUpdateBiasGradients ( ) const

inline

Definition at line 281 of file GRULayer.h.

◆ GetUpdateDerivativesAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetUpdateDerivativesAt ( size_t i )

inline

Definition at line 243 of file GRULayer.h.

◆ GetUpdateDerivativesAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetUpdateDerivativesAt ( size_t i ) const

inline

Definition at line 242 of file GRULayer.h.

◆ GetUpdateGateBias() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetUpdateGateBias ( )

inline

Definition at line 267 of file GRULayer.h.

◆ GetUpdateGateBias() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetUpdateGateBias ( ) const

inline

Definition at line 266 of file GRULayer.h.

◆ GetUpdateGateTensor() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetUpdateGateTensor ( )

inline

Definition at line 254 of file GRULayer.h.

◆ GetUpdateGateTensor() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetUpdateGateTensor ( ) const

inline

Definition at line 253 of file GRULayer.h.

◆ GetUpdateGateTensorAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetUpdateGateTensorAt ( size_t i )

inline

Definition at line 256 of file GRULayer.h.

◆ GetUpdateGateTensorAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetUpdateGateTensorAt ( size_t i ) const

inline

Definition at line 255 of file GRULayer.h.

◆ GetUpdateGateValue() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetUpdateGateValue ( )

inline

Definition at line 215 of file GRULayer.h.

◆ GetUpdateGateValue() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetUpdateGateValue ( ) const

inline

Definition at line 214 of file GRULayer.h.

◆ GetWeightGradientsTensor() [1/2]

template<typename Architecture_t >

Tensor_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightGradientsTensor ( )

inline

Definition at line 292 of file GRULayer.h.

◆ GetWeightGradientsTensor() [2/2]

template<typename Architecture_t >

const Tensor_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightGradientsTensor ( ) const

inline

Definition at line 293 of file GRULayer.h.

◆ GetWeightsCandidate() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsCandidate ( )

inline

Definition at line 225 of file GRULayer.h.

◆ GetWeightsCandidate() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsCandidate ( ) const

inline

Definition at line 224 of file GRULayer.h.

◆ GetWeightsCandidateGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsCandidateGradients ( )

inline

Definition at line 284 of file GRULayer.h.

◆ GetWeightsCandidateGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsCandidateGradients ( ) const

inline

Definition at line 283 of file GRULayer.h.

◆ GetWeightsCandidateState() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsCandidateState ( )

inline

Definition at line 234 of file GRULayer.h.

◆ GetWeightsCandidateState() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsCandidateState ( ) const

inline

Definition at line 233 of file GRULayer.h.

◆ GetWeightsCandidateStateGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsCandidateStateGradients ( )

inline

Definition at line 286 of file GRULayer.h.

◆ GetWeightsCandidateStateGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsCandidateStateGradients ( ) const

inline

Definition at line 285 of file GRULayer.h.

◆ GetWeightsResetGate() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsResetGate ( )

inline

Definition at line 223 of file GRULayer.h.

◆ GetWeightsResetGate() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsResetGate ( ) const

inline

Definition at line 222 of file GRULayer.h.

◆ GetWeightsResetGateState() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsResetGateState ( )

inline

Definition at line 230 of file GRULayer.h.

◆ GetWeightsResetGateState() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsResetGateState ( ) const

inline

Definition at line 229 of file GRULayer.h.

◆ GetWeightsResetGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsResetGradients ( )

inline

Definition at line 272 of file GRULayer.h.

◆ GetWeightsResetGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsResetGradients ( ) const

inline

Definition at line 271 of file GRULayer.h.

◆ GetWeightsResetStateGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsResetStateGradients ( )

inline

Definition at line 274 of file GRULayer.h.

◆ GetWeightsResetStateGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsResetStateGradients ( ) const

inline

Definition at line 273 of file GRULayer.h.

◆ GetWeightsTensor() [1/2]

template<typename Architecture_t >

Tensor_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsTensor ( )

inline

Definition at line 290 of file GRULayer.h.

◆ GetWeightsTensor() [2/2]

template<typename Architecture_t >

const Tensor_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsTensor ( ) const

inline

Definition at line 291 of file GRULayer.h.

◆ GetWeightsUpdateGate() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsUpdateGate ( )

inline

Definition at line 227 of file GRULayer.h.

◆ GetWeightsUpdateGate() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsUpdateGate ( ) const

inline

Definition at line 226 of file GRULayer.h.

◆ GetWeightsUpdateGateState() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsUpdateGateState ( )

inline

Definition at line 232 of file GRULayer.h.

◆ GetWeightsUpdateGateState() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsUpdateGateState ( ) const

inline

Definition at line 231 of file GRULayer.h.

◆ GetWeightsUpdateGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsUpdateGradients ( )

inline

Definition at line 278 of file GRULayer.h.

◆ GetWeightsUpdateGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsUpdateGradients ( ) const

inline

Definition at line 277 of file GRULayer.h.

◆ GetWeightsUpdateStateGradients()

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeightsUpdateStateGradients ( )

inline

Definition at line 280 of file GRULayer.h.

◆ GetWeigthsUpdateStateGradients()

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetWeigthsUpdateStateGradients ( ) const

inline

Definition at line 279 of file GRULayer.h.

◆ GetX()

template<typename Architecture_t >

Tensor_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetX ( )

inline

Definition at line 295 of file GRULayer.h.

◆ GetY()

template<typename Architecture_t >

Tensor_t & TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::GetY ( )

inline

Definition at line 296 of file GRULayer.h.

◆ Initialize()

template<typename Architecture_t >

void TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::Initialize

virtual

Initialize the weights according to the given initialization method.

Reimplemented from TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 409 of file GRULayer.h.

◆ InitState()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::InitState ( DNN::EInitialization m = DNN::EInitialization::kZero )

Initialize the hidden state and cell state method.

Definition at line 800 of file GRULayer.h.

◆ Print()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::Print

virtual

Prints the info about the layer.

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 808 of file GRULayer.h.

◆ ReadWeightsFromXML()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::ReadWeightsFromXML ( void * parent )

inlinevirtual

Read the information and the weights about the layer from XML node.

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 847 of file GRULayer.h.

◆ ResetGate()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::ResetGate	(	const Matrix_t &	input,
		Matrix_t &	di
	)

inline

Decides the values we'll update (NN with Sigmoid)

Definition at line 423 of file GRULayer.h.

◆ Update()

template<typename Architecture_t >

void TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::Update ( const Scalar_t learningRate )

◆ UpdateGate()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::UpdateGate	(	const Matrix_t &	input,
		Matrix_t &	df
	)

inline

Forgets the past values (NN with Sigmoid)

Definition at line 441 of file GRULayer.h.

Member Data Documentation

◆ candidate_gate_value

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::candidate_gate_value

private

Candidate gate value for every time step.

Definition at line 106 of file GRULayer.h.

◆ fCandidateBias

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fCandidateBias

private

Candidate Gate bias.

Definition at line 101 of file GRULayer.h.

◆ fCandidateBiasGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fCandidateBiasGradients

private

Gradients w.r.t the candidate gate - bias weights.

Definition at line 120 of file GRULayer.h.

◆ fCandidateValue

template<typename Architecture_t >

Matrix_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fCandidateValue

private

Computed candidate values.

Definition at line 87 of file GRULayer.h.

◆ fCell

template<typename Architecture_t >

Matrix_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fCell

private

EMpty matrix for GRU.

Definition at line 122 of file GRULayer.h.

◆ fDerivativesCandidate

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fDerivativesCandidate

private

First fDerivatives of the activations candidate gate.

Definition at line 110 of file GRULayer.h.

◆ fDerivativesReset

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fDerivativesReset

private

First fDerivatives of the activations reset gate.

Definition at line 108 of file GRULayer.h.

◆ fDerivativesUpdate

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fDerivativesUpdate

private

First fDerivatives of the activations update gate.

Definition at line 109 of file GRULayer.h.

◆ fDescriptors

template<typename Architecture_t >

TDescriptors* TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fDescriptors = nullptr

private

Keeps all the RNN descriptors.

Definition at line 134 of file GRULayer.h.

◆ fDx

template<typename Architecture_t >

Tensor_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fDx

private

cached gradient on the input (output of backward) as T x B x I

Definition at line 131 of file GRULayer.h.

◆ fDy

template<typename Architecture_t >

Tensor_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fDy

private

cached activation gradient (input of backward) as T x B x S

Definition at line 132 of file GRULayer.h.

◆ fF1

template<typename Architecture_t >

DNN::EActivationFunction TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fF1

private

Activation function: sigmoid.

Definition at line 82 of file GRULayer.h.

◆ fF2

template<typename Architecture_t >

DNN::EActivationFunction TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fF2

private

Activaton function: tanh.

Definition at line 83 of file GRULayer.h.

◆ fRememberState

template<typename Architecture_t >

bool TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fRememberState

private

Remember state in next pass.

Definition at line 78 of file GRULayer.h.

◆ fResetBiasGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fResetBiasGradients

private

Gradients w.r.t the reset gate - bias weights.

Definition at line 114 of file GRULayer.h.

◆ fResetGateAfter

template<typename Architecture_t >

bool TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fResetGateAfter = false

private

GRU variant to Apply the reset gate multiplication afterwards (used by cuDNN)

Definition at line 80 of file GRULayer.h.

◆ fResetGateBias

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fResetGateBias

private

Input Gate bias.

Definition at line 93 of file GRULayer.h.

◆ fResetValue

template<typename Architecture_t >

Matrix_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fResetValue

private

Computed reset gate values.

Definition at line 85 of file GRULayer.h.

◆ fReturnSequence

template<typename Architecture_t >

bool TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fReturnSequence = false

private

Return in output full sequence or just last element.

Definition at line 79 of file GRULayer.h.

◆ fState

template<typename Architecture_t >

Matrix_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fState

private

Hidden state of GRU.

Definition at line 88 of file GRULayer.h.

◆ fStateSize

template<typename Architecture_t >

size_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fStateSize

private

Hidden state size for GRU.

Definition at line 75 of file GRULayer.h.

◆ fTimeSteps

template<typename Architecture_t >

size_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fTimeSteps

private

Timesteps for GRU.

Definition at line 76 of file GRULayer.h.

◆ fUpdateBiasGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fUpdateBiasGradients

private

Gradients w.r.t the update gate - bias weights.

Definition at line 117 of file GRULayer.h.

◆ fUpdateGateBias

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fUpdateGateBias

private

Update Gate bias.

Definition at line 97 of file GRULayer.h.

◆ fUpdateValue

template<typename Architecture_t >

Matrix_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fUpdateValue

private

Computed forget gate values.

Definition at line 86 of file GRULayer.h.

◆ fWeightGradientsTensor

template<typename Architecture_t >

Tensor_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWeightGradientsTensor

private

Tensor for all weight gradients.

Definition at line 126 of file GRULayer.h.

◆ fWeightsCandidate

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWeightsCandidate

private

Candidate Gate weights for input, fWeights[4].

Definition at line 99 of file GRULayer.h.

◆ fWeightsCandidateGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWeightsCandidateGradients

private

Gradients w.r.t the candidate gate - input weights.

Definition at line 118 of file GRULayer.h.

◆ fWeightsCandidateState

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWeightsCandidateState

private

Candidate Gate weights for prev state, fWeights[5].

Definition at line 100 of file GRULayer.h.

◆ fWeightsCandidateStateGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWeightsCandidateStateGradients

private

Gradients w.r.t the candidate gate - hidden state weights.

Definition at line 119 of file GRULayer.h.

◆ fWeightsResetGate

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWeightsResetGate

private

Reset Gate weights for input, fWeights[0].

Definition at line 91 of file GRULayer.h.

◆ fWeightsResetGateState

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWeightsResetGateState

private

Input Gate weights for prev state, fWeights[1].

Definition at line 92 of file GRULayer.h.

◆ fWeightsResetGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWeightsResetGradients

private

Gradients w.r.t the reset gate - input weights.

Definition at line 112 of file GRULayer.h.

◆ fWeightsResetStateGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWeightsResetStateGradients

private

Gradients w.r.t the reset gate - hidden state weights.

Definition at line 113 of file GRULayer.h.

◆ fWeightsTensor

template<typename Architecture_t >

Tensor_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWeightsTensor

private

Tensor for all weights.

Definition at line 125 of file GRULayer.h.

◆ fWeightsUpdateGate

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWeightsUpdateGate

private

Update Gate weights for input, fWeights[2].

Definition at line 95 of file GRULayer.h.

◆ fWeightsUpdateGateState

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWeightsUpdateGateState

private

Update Gate weights for prev state, fWeights[3].

Definition at line 96 of file GRULayer.h.

◆ fWeightsUpdateGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWeightsUpdateGradients

private

Gradients w.r.t the update gate - input weights.

Definition at line 115 of file GRULayer.h.

◆ fWeightsUpdateStateGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWeightsUpdateStateGradients

private

Gradients w.r.t the update gate - hidden state weights.

Definition at line 116 of file GRULayer.h.

◆ fWorkspace

template<typename Architecture_t >

TWorkspace* TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fWorkspace = nullptr

private

Definition at line 135 of file GRULayer.h.

◆ fX

template<typename Architecture_t >

Tensor_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fX

private

cached input tensor as T x B x I

Definition at line 129 of file GRULayer.h.

◆ fY

template<typename Architecture_t >

Tensor_t TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::fY

private

cached output tensor as T x B x S

Definition at line 130 of file GRULayer.h.

◆ reset_gate_value

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::reset_gate_value

private

Reset gate value for every time step.

Definition at line 104 of file GRULayer.h.

◆ update_gate_value

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >::update_gate_value

private

Update gate value for every time step.

Definition at line 105 of file GRULayer.h.

tmva/tmva/inc/TMVA/DNN/RNN/GRULayer.h

Public Types

Public Member Functions

Private Attributes

Additional Inherited Members

Member Typedef Documentation

◆ HelperDescriptor_t

◆ LayerDescriptor_t

◆ Matrix_t

◆ RNNDescriptors_t

◆ RNNWorkspace_t

◆ Scalar_t

◆ Tensor_t

◆ TensorDescriptor_t

◆ WeightsDescriptor_t

Constructor & Destructor Documentation

◆ TBasicGRULayer() [1/2]

◆ TBasicGRULayer() [2/2]

Member Function Documentation

◆ AddWeightsXMLTo()

◆ Backward()

◆ CandidateValue()

◆ CellBackward()

◆ CellForward()

◆ DoesRememberState()

◆ DoesReturnSequence()

◆ Forward()

◆ GetActivationFunctionF1()

◆ GetActivationFunctionF2()

◆ GetCandidateBias() [1/2]

◆ GetCandidateBias() [2/2]

◆ GetCandidateBiasGradients() [1/2]

◆ GetCandidateBiasGradients() [2/2]

◆ GetCandidateDerivativesAt() [1/2]

◆ GetCandidateDerivativesAt() [2/2]

◆ GetCandidateGateTensor() [1/2]

◆ GetCandidateGateTensor() [2/2]

◆ GetCandidateGateTensorAt() [1/2]

◆ GetCandidateGateTensorAt() [2/2]

◆ GetCandidateValue() [1/2]

◆ GetCandidateValue() [2/2]

◆ GetCell() [1/2]

◆ GetCell() [2/2]

◆ GetDerivativesCandidate() [1/2]

◆ GetDerivativesCandidate() [2/2]

◆ GetDerivativesReset() [1/2]

◆ GetDerivativesReset() [2/2]

◆ GetDerivativesUpdate() [1/2]

◆ GetDerivativesUpdate() [2/2]

◆ GetDX()

◆ GetDY()

◆ GetInputSize()

◆ GetResetBiasGradients() [1/2]

◆ GetResetBiasGradients() [2/2]

◆ GetResetDerivativesAt() [1/2]

◆ GetResetDerivativesAt() [2/2]

◆ GetResetGateBias() [1/2]

◆ GetResetGateBias() [2/2]

◆ GetResetGateTensor() [1/2]

◆ GetResetGateTensor() [2/2]

◆ GetResetGateTensorAt() [1/2]

◆ GetResetGateTensorAt() [2/2]

◆ GetResetGateValue() [1/2]

◆ GetResetGateValue() [2/2]

◆ GetState() [1/2]

◆ GetState() [2/2]

◆ GetStateSize()

◆ GetTimeSteps()

◆ GetUpdateBiasGradients() [1/2]

◆ GetUpdateBiasGradients() [2/2]

◆ GetUpdateDerivativesAt() [1/2]

◆ GetUpdateDerivativesAt() [2/2]

◆ GetUpdateGateBias() [1/2]

◆ GetUpdateGateBias() [2/2]

◆ GetUpdateGateTensor() [1/2]

◆ GetUpdateGateTensor() [2/2]

◆ GetUpdateGateTensorAt() [1/2]

◆ GetUpdateGateTensorAt() [2/2]

◆ GetUpdateGateValue() [1/2]

◆ GetUpdateGateValue() [2/2]

◆ GetWeightGradientsTensor() [1/2]