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

Definition at line 56 of file LSTMLayer.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
	TBasicLSTMLayer (const TBasicLSTMLayer &)
	Copy Constructor.

	TBasicLSTMLayer (size_t batchSize, size_t stateSize, size_t inputSize, size_t timeSteps, bool rememberState=false, bool returnSequence=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, Matrix_t &cell_gradients_backward, const Matrix_t &precStateActivations, const Matrix_t &precCellActivations, const Matrix_t &input_gate, const Matrix_t &forget_gate, const Matrix_t &candidate_gate, const Matrix_t &output_gate, const Matrix_t &input, Matrix_t &input_gradient, Matrix_t &di, Matrix_t &df, Matrix_t &dc, Matrix_t &dout, size_t t)
	Backward for a single time unit a the corresponding call to Forward(...).

void	CellForward (Matrix_t &inputGateValues, const Matrix_t &forgetGateValues, const Matrix_t &candidateValues, const Matrix_t &outputGateValues)
	Forward for a single cell (time unit)

bool	DoesRememberState () const

bool	DoesReturnSequence () const

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

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

size_t	GetCellSize () const

std::vector< Matrix_t > &	GetCellTensor ()

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

Matrix_t &	GetCellTensorAt (size_t i)

const Matrix_t &	GetCellTensorAt (size_t i) const

std::vector< Matrix_t > &	GetDerivativesCandidate ()

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

std::vector< Matrix_t > &	GetDerivativesForget ()

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

std::vector< Matrix_t > &	GetDerivativesInput ()

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

std::vector< Matrix_t > &	GetDerivativesOutput ()

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

Tensor_t &	GetDX ()

Tensor_t &	GetDY ()

Matrix_t &	GetForgetBiasGradients ()

const Matrix_t &	GetForgetBiasGradients () const

Matrix_t &	GetForgetDerivativesAt (size_t i)

const Matrix_t &	GetForgetDerivativesAt (size_t i) const

Matrix_t &	GetForgetGateBias ()

const Matrix_t &	GetForgetGateBias () const

std::vector< Matrix_t > &	GetForgetGateTensor ()

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

Matrix_t &	GetForgetGateTensorAt (size_t i)

const Matrix_t &	GetForgetGateTensorAt (size_t i) const

Matrix_t &	GetForgetGateValue ()

const Matrix_t &	GetForgetGateValue () const

Matrix_t &	GetInputBiasGradients ()

const Matrix_t &	GetInputBiasGradients () const

Matrix_t &	GetInputDerivativesAt (size_t i)

const Matrix_t &	GetInputDerivativesAt (size_t i) const

Matrix_t &	GetInputGateBias ()

const Matrix_t &	GetInputGateBias () const

std::vector< Matrix_t > &	GetInputGateTensor ()

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

Matrix_t &	GetInputGateTensorAt (size_t i)

const Matrix_t &	GetInputGateTensorAt (size_t i) const

Matrix_t &	GetInputGateValue ()

const Matrix_t &	GetInputGateValue () const

size_t	GetInputSize () const
	Getters.

Matrix_t &	GetOutputBiasGradients ()

const Matrix_t &	GetOutputBiasGradients () const

Matrix_t &	GetOutputDerivativesAt (size_t i)

const Matrix_t &	GetOutputDerivativesAt (size_t i) const

Matrix_t &	GetOutputGateBias ()

const Matrix_t &	GetOutputGateBias () const

std::vector< Matrix_t > &	GetOutputGateTensor ()

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

Matrix_t &	GetOutputGateTensorAt (size_t i)

const Matrix_t &	GetOutputGateTensorAt (size_t i) const

Matrix_t &	GetOutputGateValue ()

const Matrix_t &	GetOutputGateValue () const

Matrix_t &	GetState ()

const Matrix_t &	GetState () const

size_t	GetStateSize () const

size_t	GetTimeSteps () 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 &	GetWeightsForgetGate ()

const Matrix_t &	GetWeightsForgetGate () const

Matrix_t &	GetWeightsForgetGateState ()

const Matrix_t &	GetWeightsForgetGateState () const

Matrix_t &	GetWeightsForgetGradients ()

const Matrix_t &	GetWeightsForgetGradients () const

Matrix_t &	GetWeightsForgetStateGradients ()

Matrix_t &	GetWeightsInputGate ()

const Matrix_t &	GetWeightsInputGate () const

Matrix_t &	GetWeightsInputGateState ()

const Matrix_t &	GetWeightsInputGateState () const

Matrix_t &	GetWeightsInputGradients ()

const Matrix_t &	GetWeightsInputGradients () const

Matrix_t &	GetWeightsInputStateGradients ()

const Matrix_t &	GetWeightsInputStateGradients () const

Matrix_t &	GetWeightsOutputGate ()

const Matrix_t &	GetWeightsOutputGate () const

Matrix_t &	GetWeightsOutputGateState ()

const Matrix_t &	GetWeightsOutputGateState () const

Matrix_t &	GetWeightsOutputGradients ()

const Matrix_t &	GetWeightsOutputGradients () const

Matrix_t &	GetWeightsOutputStateGradients ()

const Matrix_t &	GetWeightsOutputStateGradients () const

Tensor_t &	GetWeightsTensor ()

const Tensor_t &	GetWeightsTensor () const

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

void	OutputGate (const Matrix_t &input, Matrix_t &dout)
	Computes output values (NN with Sigmoid)

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	Update (const Scalar_t learningRate)

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

std::vector< Matrix_t >	cell_value
	cell 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
	Cell state of LSTM.

size_t	fCellSize
	Cell state size of LSTM.

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

std::vector< Matrix_t >	fDerivativesForget
	First fDerivatives of the activations forget gate.

std::vector< Matrix_t >	fDerivativesInput
	First fDerivatives of the activations input gate.

std::vector< Matrix_t >	fDerivativesOutput
	First fDerivatives of the activations output 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.

Matrix_t &	fForgetBiasGradients
	Gradients w.r.t the forget gate - bias weights.

Matrix_t &	fForgetGateBias
	Forget Gate bias.

Matrix_t	fForgetValue
	Computed forget gate values.

Matrix_t &	fInputBiasGradients
	Gradients w.r.t the input gate - bias weights.

Matrix_t &	fInputGateBias
	Input Gate bias.

Matrix_t	fInputValue
	Computed input gate values.

std::vector< Matrix_t >	forget_gate_value
	forget gate value for every time step

Matrix_t &	fOutputBiasGradients
	Gradients w.r.t the output gate - bias weights.

Matrix_t &	fOutputGateBias
	Output Gate bias.

Matrix_t	fOutputValue
	Computed output gate values.

bool	fRememberState
	Remember state in next pass.

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

Matrix_t	fState
	Hidden state of LSTM.

size_t	fStateSize
	Hidden state size for LSTM.

size_t	fTimeSteps
	Timesteps for LSTM.

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 &	fWeightsForgetGate
	Forget Gate weights for input, fWeights[2].

Matrix_t &	fWeightsForgetGateState
	Forget Gate weights for prev state, fWeights[3].

Matrix_t &	fWeightsForgetGradients
	Gradients w.r.t the forget gate - input weights.

Matrix_t &	fWeightsForgetStateGradients
	Gradients w.r.t the forget gate - hidden state weights.

Matrix_t &	fWeightsInputGate
	Input Gate weights for input, fWeights[0].

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

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

Matrix_t &	fWeightsInputStateGradients
	Gradients w.r.t the input gate - hidden state weights.

Matrix_t &	fWeightsOutputGate
	Output Gate weights for input, fWeights[6].

Matrix_t &	fWeightsOutputGateState
	Output Gate weights for prev state, fWeights[7].

Matrix_t &	fWeightsOutputGradients
	Gradients w.r.t the output gate - input weights.

Matrix_t &	fWeightsOutputStateGradients
	Gradients w.r.t the output gate - hidden state weights.

Tensor_t	fWeightsTensor
	Tensor for all 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 >	input_gate_value
	input gate value for every time step

std::vector< Matrix_t >	output_gate_value
	output 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/LSTMLayer.h>

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

[legend]

Member Typedef Documentation

◆ HelperDescriptor_t

template<typename Architecture_t >

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

Definition at line 68 of file LSTMLayer.h.

◆ LayerDescriptor_t

template<typename Architecture_t >

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

Definition at line 65 of file LSTMLayer.h.

◆ Matrix_t

template<typename Architecture_t >

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

Definition at line 61 of file LSTMLayer.h.

◆ RNNDescriptors_t

template<typename Architecture_t >

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

Definition at line 71 of file LSTMLayer.h.

◆ RNNWorkspace_t

template<typename Architecture_t >

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

Definition at line 70 of file LSTMLayer.h.

◆ Scalar_t

template<typename Architecture_t >

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

Definition at line 62 of file LSTMLayer.h.

◆ Tensor_t

template<typename Architecture_t >

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

Definition at line 63 of file LSTMLayer.h.

◆ TensorDescriptor_t

template<typename Architecture_t >

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

Definition at line 67 of file LSTMLayer.h.

◆ WeightsDescriptor_t

template<typename Architecture_t >

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

Definition at line 66 of file LSTMLayer.h.

Constructor & Destructor Documentation

◆ TBasicLSTMLayer() [1/2]

template<typename Architecture_t >

TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::TBasicLSTMLayer	(	size_t	batchSize,
		size_t	stateSize,
		size_t	inputSize,
		size_t	timeSteps,
		bool	rememberState = `false`,
		bool	returnSequence = `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 341 of file LSTMLayer.h.

◆ TBasicLSTMLayer() [2/2]

template<typename Architecture_t >

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

Copy Constructor.

Definition at line 385 of file LSTMLayer.h.

Member Function Documentation

◆ AddWeightsXMLTo()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicLSTMLayer< 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 922 of file LSTMLayer.h.

◆ Backward()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicLSTMLayer< 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 680 of file LSTMLayer.h.

◆ CandidateValue()

template<typename Architecture_t >

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

inline

Decides the new candidate values (NN with Tanh)

Definition at line 515 of file LSTMLayer.h.

◆ CellBackward()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::CellBackward	(	Matrix_t &	state_gradients_backward,
		Matrix_t &	cell_gradients_backward,
		const Matrix_t &	precStateActivations,
		const Matrix_t &	precCellActivations,
		const Matrix_t &	input_gate,
		const Matrix_t &	forget_gate,
		const Matrix_t &	candidate_gate,
		const Matrix_t &	output_gate,
		const Matrix_t &	input,
		Matrix_t &	input_gradient,
		Matrix_t &	di,
		Matrix_t &	df,
		Matrix_t &	dc,
		Matrix_t &	dout,
		size_t	t
	)

inline

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

Definition at line 862 of file LSTMLayer.h.

◆ CellForward()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::CellForward	(	Matrix_t &	inputGateValues,
		const Matrix_t &	forgetGateValues,
		const Matrix_t &	candidateValues,
		const Matrix_t &	outputGateValues
	)

inline

Forward for a single cell (time unit)

Definition at line 654 of file LSTMLayer.h.

◆ DoesRememberState()

template<typename Architecture_t >

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

inline

Definition at line 216 of file LSTMLayer.h.

◆ DoesReturnSequence()

template<typename Architecture_t >

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

inline

Definition at line 217 of file LSTMLayer.h.

◆ ForgetGate()

template<typename Architecture_t >

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

inline

Forgets the past values (NN with Sigmoid)

Definition at line 497 of file LSTMLayer.h.

◆ Forward()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicLSTMLayer< 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 553 of file LSTMLayer.h.

◆ GetActivationFunctionF1()

template<typename Architecture_t >

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

inline

Definition at line 219 of file LSTMLayer.h.

◆ GetActivationFunctionF2()

template<typename Architecture_t >

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

inline

Definition at line 220 of file LSTMLayer.h.

◆ GetCandidateBias() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 296 of file LSTMLayer.h.

◆ GetCandidateBias() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 295 of file LSTMLayer.h.

◆ GetCandidateBiasGradients() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 316 of file LSTMLayer.h.

◆ GetCandidateBiasGradients() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 315 of file LSTMLayer.h.

◆ GetCandidateDerivativesAt() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 264 of file LSTMLayer.h.

◆ GetCandidateDerivativesAt() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 263 of file LSTMLayer.h.

◆ GetCandidateGateTensor() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 279 of file LSTMLayer.h.

◆ GetCandidateGateTensor() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 278 of file LSTMLayer.h.

◆ GetCandidateGateTensorAt() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 281 of file LSTMLayer.h.

◆ GetCandidateGateTensorAt() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 280 of file LSTMLayer.h.

◆ GetCandidateValue() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 225 of file LSTMLayer.h.

◆ GetCandidateValue() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 224 of file LSTMLayer.h.

◆ GetCell() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 234 of file LSTMLayer.h.

◆ GetCell() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 233 of file LSTMLayer.h.

◆ GetCellSize()

template<typename Architecture_t >

size_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetCellSize ( ) const

inline

Definition at line 214 of file LSTMLayer.h.

◆ GetCellTensor() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetCellTensor ( )

inline

Definition at line 287 of file LSTMLayer.h.

◆ GetCellTensor() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetCellTensor ( ) const

inline

Definition at line 286 of file LSTMLayer.h.

◆ GetCellTensorAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetCellTensorAt ( size_t i )

inline

Definition at line 289 of file LSTMLayer.h.

◆ GetCellTensorAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetCellTensorAt ( size_t i ) const

inline

Definition at line 288 of file LSTMLayer.h.

◆ GetDerivativesCandidate() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 262 of file LSTMLayer.h.

◆ GetDerivativesCandidate() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 261 of file LSTMLayer.h.

◆ GetDerivativesForget() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetDerivativesForget ( )

inline

Definition at line 258 of file LSTMLayer.h.

◆ GetDerivativesForget() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetDerivativesForget ( ) const

inline

Definition at line 257 of file LSTMLayer.h.

◆ GetDerivativesInput() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetDerivativesInput ( )

inline

Definition at line 254 of file LSTMLayer.h.

◆ GetDerivativesInput() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetDerivativesInput ( ) const

inline

Definition at line 253 of file LSTMLayer.h.

◆ GetDerivativesOutput() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetDerivativesOutput ( )

inline

Definition at line 266 of file LSTMLayer.h.

◆ GetDerivativesOutput() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetDerivativesOutput ( ) const

inline

Definition at line 265 of file LSTMLayer.h.

◆ GetDX()

template<typename Architecture_t >

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

inline

Definition at line 331 of file LSTMLayer.h.

◆ GetDY()

template<typename Architecture_t >

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

inline

Definition at line 332 of file LSTMLayer.h.

◆ GetForgetBiasGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetForgetBiasGradients ( )

inline

Definition at line 310 of file LSTMLayer.h.

◆ GetForgetBiasGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetForgetBiasGradients ( ) const

inline

Definition at line 309 of file LSTMLayer.h.

◆ GetForgetDerivativesAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetForgetDerivativesAt ( size_t i )

inline

Definition at line 260 of file LSTMLayer.h.

◆ GetForgetDerivativesAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetForgetDerivativesAt ( size_t i ) const

inline

Definition at line 259 of file LSTMLayer.h.

◆ GetForgetGateBias() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetForgetGateBias ( )

inline

Definition at line 294 of file LSTMLayer.h.

◆ GetForgetGateBias() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetForgetGateBias ( ) const

inline

Definition at line 293 of file LSTMLayer.h.

◆ GetForgetGateTensor() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetForgetGateTensor ( )

inline

Definition at line 275 of file LSTMLayer.h.

◆ GetForgetGateTensor() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetForgetGateTensor ( ) const

inline

Definition at line 274 of file LSTMLayer.h.

◆ GetForgetGateTensorAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetForgetGateTensorAt ( size_t i )

inline

Definition at line 277 of file LSTMLayer.h.

◆ GetForgetGateTensorAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetForgetGateTensorAt ( size_t i ) const

inline

Definition at line 276 of file LSTMLayer.h.

◆ GetForgetGateValue() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetForgetGateValue ( )

inline

Definition at line 227 of file LSTMLayer.h.

◆ GetForgetGateValue() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetForgetGateValue ( ) const

inline

Definition at line 226 of file LSTMLayer.h.

◆ GetInputBiasGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetInputBiasGradients ( )

inline

Definition at line 304 of file LSTMLayer.h.

◆ GetInputBiasGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetInputBiasGradients ( ) const

inline

Definition at line 303 of file LSTMLayer.h.

◆ GetInputDerivativesAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetInputDerivativesAt ( size_t i )

inline

Definition at line 256 of file LSTMLayer.h.

◆ GetInputDerivativesAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetInputDerivativesAt ( size_t i ) const

inline

Definition at line 255 of file LSTMLayer.h.

◆ GetInputGateBias() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetInputGateBias ( )

inline

Definition at line 292 of file LSTMLayer.h.

◆ GetInputGateBias() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetInputGateBias ( ) const

inline

Definition at line 291 of file LSTMLayer.h.

◆ GetInputGateTensor() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetInputGateTensor ( )

inline

Definition at line 271 of file LSTMLayer.h.

◆ GetInputGateTensor() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetInputGateTensor ( ) const

inline

Definition at line 270 of file LSTMLayer.h.

◆ GetInputGateTensorAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetInputGateTensorAt ( size_t i )

inline

Definition at line 273 of file LSTMLayer.h.

◆ GetInputGateTensorAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetInputGateTensorAt ( size_t i ) const

inline

Definition at line 272 of file LSTMLayer.h.

◆ GetInputGateValue() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetInputGateValue ( )

inline

Definition at line 223 of file LSTMLayer.h.

◆ GetInputGateValue() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetInputGateValue ( ) const

inline

Definition at line 222 of file LSTMLayer.h.

◆ GetInputSize()

template<typename Architecture_t >

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

inline

Getters.

Definition at line 211 of file LSTMLayer.h.

◆ GetOutputBiasGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetOutputBiasGradients ( )

inline

Definition at line 322 of file LSTMLayer.h.

◆ GetOutputBiasGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetOutputBiasGradients ( ) const

inline

Definition at line 321 of file LSTMLayer.h.

◆ GetOutputDerivativesAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetOutputDerivativesAt ( size_t i )

inline

Definition at line 268 of file LSTMLayer.h.

◆ GetOutputDerivativesAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetOutputDerivativesAt ( size_t i ) const

inline

Definition at line 267 of file LSTMLayer.h.

◆ GetOutputGateBias() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetOutputGateBias ( )

inline

Definition at line 298 of file LSTMLayer.h.

◆ GetOutputGateBias() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetOutputGateBias ( ) const

inline

Definition at line 297 of file LSTMLayer.h.

◆ GetOutputGateTensor() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetOutputGateTensor ( )

inline

Definition at line 283 of file LSTMLayer.h.

◆ GetOutputGateTensor() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetOutputGateTensor ( ) const

inline

Definition at line 282 of file LSTMLayer.h.

◆ GetOutputGateTensorAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetOutputGateTensorAt ( size_t i )

inline

Definition at line 285 of file LSTMLayer.h.

◆ GetOutputGateTensorAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetOutputGateTensorAt ( size_t i ) const

inline

Definition at line 284 of file LSTMLayer.h.

◆ GetOutputGateValue() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetOutputGateValue ( )

inline

Definition at line 229 of file LSTMLayer.h.

◆ GetOutputGateValue() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetOutputGateValue ( ) const

inline

Definition at line 228 of file LSTMLayer.h.

◆ GetState() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 232 of file LSTMLayer.h.

◆ GetState() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 231 of file LSTMLayer.h.

◆ GetStateSize()

template<typename Architecture_t >

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

inline

Definition at line 213 of file LSTMLayer.h.

◆ GetTimeSteps()

template<typename Architecture_t >

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

inline

Definition at line 212 of file LSTMLayer.h.

◆ GetWeightGradientsTensor() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 326 of file LSTMLayer.h.

◆ GetWeightGradientsTensor() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 327 of file LSTMLayer.h.

◆ GetWeightsCandidate() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 239 of file LSTMLayer.h.

◆ GetWeightsCandidate() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 238 of file LSTMLayer.h.

◆ GetWeightsCandidateGradients() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 312 of file LSTMLayer.h.

◆ GetWeightsCandidateGradients() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 311 of file LSTMLayer.h.

◆ GetWeightsCandidateState() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 249 of file LSTMLayer.h.

◆ GetWeightsCandidateState() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 248 of file LSTMLayer.h.

◆ GetWeightsCandidateStateGradients() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 314 of file LSTMLayer.h.

◆ GetWeightsCandidateStateGradients() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 313 of file LSTMLayer.h.

◆ GetWeightsForgetGate() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsForgetGate ( )

inline

Definition at line 241 of file LSTMLayer.h.

◆ GetWeightsForgetGate() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsForgetGate ( ) const

inline

Definition at line 240 of file LSTMLayer.h.

◆ GetWeightsForgetGateState() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsForgetGateState ( )

inline

Definition at line 247 of file LSTMLayer.h.

◆ GetWeightsForgetGateState() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsForgetGateState ( ) const

inline

Definition at line 246 of file LSTMLayer.h.

◆ GetWeightsForgetGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsForgetGradients ( )

inline

Definition at line 306 of file LSTMLayer.h.

◆ GetWeightsForgetGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsForgetGradients ( ) const

inline

Definition at line 305 of file LSTMLayer.h.

◆ GetWeightsForgetStateGradients()

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsForgetStateGradients ( )

inline

Definition at line 308 of file LSTMLayer.h.

◆ GetWeightsInputGate() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsInputGate ( )

inline

Definition at line 237 of file LSTMLayer.h.

◆ GetWeightsInputGate() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsInputGate ( ) const

inline

Definition at line 236 of file LSTMLayer.h.

◆ GetWeightsInputGateState() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsInputGateState ( )

inline

Definition at line 245 of file LSTMLayer.h.

◆ GetWeightsInputGateState() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsInputGateState ( ) const

inline

Definition at line 244 of file LSTMLayer.h.

◆ GetWeightsInputGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsInputGradients ( )

inline

Definition at line 300 of file LSTMLayer.h.

◆ GetWeightsInputGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsInputGradients ( ) const

inline

Definition at line 299 of file LSTMLayer.h.

◆ GetWeightsInputStateGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsInputStateGradients ( )

inline

Definition at line 302 of file LSTMLayer.h.

◆ GetWeightsInputStateGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsInputStateGradients ( ) const

inline

Definition at line 301 of file LSTMLayer.h.

◆ GetWeightsOutputGate() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsOutputGate ( )

inline

Definition at line 243 of file LSTMLayer.h.

◆ GetWeightsOutputGate() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsOutputGate ( ) const

inline

Definition at line 242 of file LSTMLayer.h.

◆ GetWeightsOutputGateState() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsOutputGateState ( )

inline

Definition at line 251 of file LSTMLayer.h.

◆ GetWeightsOutputGateState() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsOutputGateState ( ) const

inline

Definition at line 250 of file LSTMLayer.h.

◆ GetWeightsOutputGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsOutputGradients ( )

inline

Definition at line 318 of file LSTMLayer.h.

◆ GetWeightsOutputGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsOutputGradients ( ) const

inline

Definition at line 317 of file LSTMLayer.h.

◆ GetWeightsOutputStateGradients() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsOutputStateGradients ( )

inline

Definition at line 320 of file LSTMLayer.h.

◆ GetWeightsOutputStateGradients() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeightsOutputStateGradients ( ) const

inline

Definition at line 319 of file LSTMLayer.h.

◆ GetWeightsTensor() [1/2]

template<typename Architecture_t >

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

inline

Definition at line 324 of file LSTMLayer.h.

◆ GetWeightsTensor() [2/2]

template<typename Architecture_t >

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

inline

Definition at line 325 of file LSTMLayer.h.

◆ GetWeigthsForgetStateGradients()

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetWeigthsForgetStateGradients ( ) const

inline

Definition at line 307 of file LSTMLayer.h.

◆ GetX()

template<typename Architecture_t >

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

inline

Definition at line 329 of file LSTMLayer.h.

◆ GetY()

template<typename Architecture_t >

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

inline

Definition at line 330 of file LSTMLayer.h.

◆ Initialize()

template<typename Architecture_t >

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

virtual

Initialize the weights according to the given initialization method.

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

Definition at line 469 of file LSTMLayer.h.

◆ InitState()

template<typename Architecture_t >

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

Initialize the hidden state and cell state method.

Definition at line 901 of file LSTMLayer.h.

◆ InputGate()

template<typename Architecture_t >

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

inline

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

Definition at line 479 of file LSTMLayer.h.

◆ OutputGate()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::OutputGate	(	const Matrix_t &	input,
		Matrix_t &	dout
	)

inline

Computes output values (NN with Sigmoid)

Definition at line 533 of file LSTMLayer.h.

◆ Print()

template<typename Architecture_t >

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

virtual

Prints the info about the layer.

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

Definition at line 910 of file LSTMLayer.h.

◆ ReadWeightsFromXML()

template<typename Architecture_t >

auto TMVA::DNN::RNN::TBasicLSTMLayer< 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 952 of file LSTMLayer.h.

◆ Update()

template<typename Architecture_t >

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

Member Data Documentation

◆ candidate_gate_value

template<typename Architecture_t >

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

private

candidate gate value for every time step

Definition at line 110 of file LSTMLayer.h.

◆ cell_value

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::cell_value

private

cell value for every time step

Definition at line 112 of file LSTMLayer.h.

◆ fCandidateBias

template<typename Architecture_t >

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

private

Candidate Gate bias.

Definition at line 102 of file LSTMLayer.h.

◆ fCandidateBiasGradients

template<typename Architecture_t >

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

private

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

Definition at line 126 of file LSTMLayer.h.

◆ fCandidateValue

template<typename Architecture_t >

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

private

Computed candidate values.

Definition at line 86 of file LSTMLayer.h.

◆ fCell

template<typename Architecture_t >

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

private

Cell state of LSTM.

Definition at line 90 of file LSTMLayer.h.

◆ fCellSize

template<typename Architecture_t >

size_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fCellSize

private

Cell state size of LSTM.

Definition at line 76 of file LSTMLayer.h.

◆ fDerivativesCandidate

template<typename Architecture_t >

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

private

First fDerivatives of the activations candidate gate.

Definition at line 115 of file LSTMLayer.h.

◆ fDerivativesForget

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fDerivativesForget

private

First fDerivatives of the activations forget gate.

Definition at line 114 of file LSTMLayer.h.

◆ fDerivativesInput

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fDerivativesInput

private

First fDerivatives of the activations input gate.

Definition at line 113 of file LSTMLayer.h.

◆ fDerivativesOutput

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fDerivativesOutput

private

First fDerivatives of the activations output gate.

Definition at line 116 of file LSTMLayer.h.

◆ fDescriptors

template<typename Architecture_t >

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

private

Keeps all the RNN descriptors.

Definition at line 141 of file LSTMLayer.h.

◆ fDx

template<typename Architecture_t >

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

private

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

Definition at line 138 of file LSTMLayer.h.

◆ fDy

template<typename Architecture_t >

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

private

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

Definition at line 139 of file LSTMLayer.h.

◆ fF1

template<typename Architecture_t >

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

private

Activation function: sigmoid.

Definition at line 82 of file LSTMLayer.h.

◆ fF2

template<typename Architecture_t >

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

private

Activaton function: tanh.

Definition at line 83 of file LSTMLayer.h.

◆ fForgetBiasGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fForgetBiasGradients

private

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

Definition at line 123 of file LSTMLayer.h.

◆ fForgetGateBias

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fForgetGateBias

private

Forget Gate bias.

Definition at line 98 of file LSTMLayer.h.

◆ fForgetValue

template<typename Architecture_t >

Matrix_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fForgetValue

private

Computed forget gate values.

Definition at line 87 of file LSTMLayer.h.

◆ fInputBiasGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fInputBiasGradients

private

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

Definition at line 120 of file LSTMLayer.h.

◆ fInputGateBias

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fInputGateBias

private

Input Gate bias.

Definition at line 94 of file LSTMLayer.h.

◆ fInputValue

template<typename Architecture_t >

Matrix_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fInputValue

private

Computed input gate values.

Definition at line 85 of file LSTMLayer.h.

◆ forget_gate_value

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::forget_gate_value

private

forget gate value for every time step

Definition at line 109 of file LSTMLayer.h.

◆ fOutputBiasGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fOutputBiasGradients

private

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

Definition at line 129 of file LSTMLayer.h.

◆ fOutputGateBias

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fOutputGateBias

private

Output Gate bias.

Definition at line 106 of file LSTMLayer.h.

◆ fOutputValue

template<typename Architecture_t >

Matrix_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fOutputValue

private

Computed output gate values.

Definition at line 88 of file LSTMLayer.h.

◆ fRememberState

template<typename Architecture_t >

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

private

Remember state in next pass.

Definition at line 79 of file LSTMLayer.h.

◆ fReturnSequence

template<typename Architecture_t >

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

private

Return in output full sequence or just last element.

Definition at line 80 of file LSTMLayer.h.

◆ fState

template<typename Architecture_t >

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

private

Hidden state of LSTM.

Definition at line 89 of file LSTMLayer.h.

◆ fStateSize

template<typename Architecture_t >

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

private

Hidden state size for LSTM.

Definition at line 75 of file LSTMLayer.h.

◆ fTimeSteps

template<typename Architecture_t >

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

private

Timesteps for LSTM.

Definition at line 77 of file LSTMLayer.h.

◆ fWeightGradientsTensor

template<typename Architecture_t >

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

private

Tensor for all weight gradients.

Definition at line 133 of file LSTMLayer.h.

◆ fWeightsCandidate

template<typename Architecture_t >

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

private

Candidate Gate weights for input, fWeights[4].

Definition at line 100 of file LSTMLayer.h.

◆ fWeightsCandidateGradients

template<typename Architecture_t >

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

private

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

Definition at line 124 of file LSTMLayer.h.

◆ fWeightsCandidateState

template<typename Architecture_t >

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

private

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

Definition at line 101 of file LSTMLayer.h.

◆ fWeightsCandidateStateGradients

template<typename Architecture_t >

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

private

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

Definition at line 125 of file LSTMLayer.h.

◆ fWeightsForgetGate

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsForgetGate

private

Forget Gate weights for input, fWeights[2].

Definition at line 96 of file LSTMLayer.h.

◆ fWeightsForgetGateState

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsForgetGateState

private

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

Definition at line 97 of file LSTMLayer.h.

◆ fWeightsForgetGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsForgetGradients

private

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

Definition at line 121 of file LSTMLayer.h.

◆ fWeightsForgetStateGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsForgetStateGradients

private

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

Definition at line 122 of file LSTMLayer.h.

◆ fWeightsInputGate

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsInputGate

private

Input Gate weights for input, fWeights[0].

Definition at line 92 of file LSTMLayer.h.

◆ fWeightsInputGateState

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsInputGateState

private

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

Definition at line 93 of file LSTMLayer.h.

◆ fWeightsInputGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsInputGradients

private

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

Definition at line 118 of file LSTMLayer.h.

◆ fWeightsInputStateGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsInputStateGradients

private

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

Definition at line 119 of file LSTMLayer.h.

◆ fWeightsOutputGate

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsOutputGate

private

Output Gate weights for input, fWeights[6].

Definition at line 104 of file LSTMLayer.h.

◆ fWeightsOutputGateState

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsOutputGateState

private

Output Gate weights for prev state, fWeights[7].

Definition at line 105 of file LSTMLayer.h.

◆ fWeightsOutputGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsOutputGradients

private

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

Definition at line 127 of file LSTMLayer.h.

◆ fWeightsOutputStateGradients

template<typename Architecture_t >

Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsOutputStateGradients

private

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

Definition at line 128 of file LSTMLayer.h.

◆ fWeightsTensor

template<typename Architecture_t >

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

private

Tensor for all weights.

Definition at line 132 of file LSTMLayer.h.

◆ fWorkspace

template<typename Architecture_t >

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

private

Definition at line 142 of file LSTMLayer.h.

◆ fX

template<typename Architecture_t >

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

private

cached input tensor as T x B x I

Definition at line 136 of file LSTMLayer.h.

◆ fY

template<typename Architecture_t >

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

private

cached output tensor as T x B x S

Definition at line 137 of file LSTMLayer.h.

◆ input_gate_value

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::input_gate_value

private

input gate value for every time step

Definition at line 108 of file LSTMLayer.h.

◆ output_gate_value

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::output_gate_value

private

output gate value for every time step

Definition at line 111 of file LSTMLayer.h.

tmva/tmva/inc/TMVA/DNN/RNN/LSTMLayer.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

◆ TBasicLSTMLayer() [1/2]

◆ TBasicLSTMLayer() [2/2]

Member Function Documentation

◆ AddWeightsXMLTo()

◆ Backward()

◆ CandidateValue()

◆ CellBackward()

◆ CellForward()

◆ DoesRememberState()

◆ DoesReturnSequence()

◆ ForgetGate()

◆ 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]

◆ GetCellSize()

◆ GetCellTensor() [1/2]

◆ GetCellTensor() [2/2]

◆ GetCellTensorAt() [1/2]

◆ GetCellTensorAt() [2/2]

◆ GetDerivativesCandidate() [1/2]

◆ GetDerivativesCandidate() [2/2]

◆ GetDerivativesForget() [1/2]

◆ GetDerivativesForget() [2/2]

◆ GetDerivativesInput() [1/2]

◆ GetDerivativesInput() [2/2]

◆ GetDerivativesOutput() [1/2]

◆ GetDerivativesOutput() [2/2]

◆ GetDX()

◆ GetDY()

◆ GetForgetBiasGradients() [1/2]

◆ GetForgetBiasGradients() [2/2]

◆ GetForgetDerivativesAt() [1/2]

◆ GetForgetDerivativesAt() [2/2]

◆ GetForgetGateBias() [1/2]

◆ GetForgetGateBias() [2/2]

◆ GetForgetGateTensor() [1/2]

◆ GetForgetGateTensor() [2/2]

◆ GetForgetGateTensorAt() [1/2]

◆ GetForgetGateTensorAt() [2/2]

◆ GetForgetGateValue() [1/2]

◆ GetForgetGateValue() [2/2]

◆ GetInputBiasGradients() [1/2]

◆ GetInputBiasGradients() [2/2]

◆ GetInputDerivativesAt() [1/2]

◆ GetInputDerivativesAt() [2/2]

◆ GetInputGateBias() [1/2]

◆ GetInputGateBias() [2/2]

◆ GetInputGateTensor() [1/2]

◆ GetInputGateTensor() [2/2]

◆ GetInputGateTensorAt() [1/2]

◆ GetInputGateTensorAt() [2/2]