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) override
	Writes the information and the weights about the layer in an XML node.
void	Backward (Tensor_t &gradients_backward, const Tensor_t &activations_backward) override
	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).
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.
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) override
	Computes the next hidden state and next cell state with given input matrix.
DNN::EActivationFunction	GetActivationFunctionF1 () const
DNN::EActivationFunction	GetActivationFunctionF2 () const
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
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
size_t	GetDepth () 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 ()
virtual std::vector< Matrix_t >	GetExtraLayerParameters () const
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
size_t	GetHeight () const
EInitialization	GetInitialization () const
Matrix_t &	GetInputBiasGradients ()
const Matrix_t &	GetInputBiasGradients () const
size_t	GetInputDepth () 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	GetInputHeight () const
size_t	GetInputSize () const
	Getters.
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
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
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
Tensor_t &	GetWeightGradientsTensor ()
const Tensor_t &	GetWeightGradientsTensor () 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
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
size_t	GetWidth () const
Tensor_t &	GetX ()
Tensor_t &	GetY ()
void	Initialize () override
	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).
bool	IsTraining () const
void	OutputGate (const Matrix_t &input, Matrix_t &dout)
	Computes output values (NN with Sigmoid).
void	Print () const override
	Prints the info about the layer.
void	ReadMatrixXML (void node, const char name, Matrix_t &matrix)
void	ReadWeightsFromXML (void *parent) override
	Read the information and the weights about the layer from XML node.
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)
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

Protected Attributes
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.

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
	Activation 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

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

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

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 )

inlineoverridevirtual

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

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

Definition at line 923 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 )

inlineoverridevirtual

Backpropagates the error.

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

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

Definition at line 681 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 863 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 655 of file LSTMLayer.h.

◆ CopyBiases()

template<typename Architecture_t>

auto TMVA::DNN::VGeneralLayer< Architecture_t >::CopyBiases ( const std::vector< Matrix_t > & otherBiases )

inherited

Copies the biases provided as an input.

Definition at line 468 of file GeneralLayer.h.

◆ CopyParameters()

template<typename Architecture_t>

template<typename Arch>

void TMVA::DNN::VGeneralLayer< Architecture_t >::CopyParameters ( const VGeneralLayer< Arch > & layer )

inherited

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.

Definition at line 478 of file GeneralLayer.h.

◆ CopyWeights()

template<typename Architecture_t>

auto TMVA::DNN::VGeneralLayer< Architecture_t >::CopyWeights ( const std::vector< Matrix_t > & otherWeights )

inherited

Copies the weights provided as an input.

Definition at line 458 of file GeneralLayer.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 )

inlineoverridevirtual

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.

◆ GetActivationGradients() [1/2]

template<typename Architecture_t>

Tensor_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetActivationGradients ( )

inlineinherited

Definition at line 200 of file GeneralLayer.h.

◆ GetActivationGradients() [2/2]

template<typename Architecture_t>

const Tensor_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetActivationGradients ( ) const

inlineinherited

Definition at line 199 of file GeneralLayer.h.

◆ GetActivationGradientsAt() [1/2]

template<typename Architecture_t>

Matrix_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetActivationGradientsAt ( size_t i )

inlineinherited

Definition at line 205 of file GeneralLayer.h.

◆ GetActivationGradientsAt() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetActivationGradientsAt ( size_t i ) const

inlineinherited

Definition at line 206 of file GeneralLayer.h.

◆ GetBatchSize()

template<typename Architecture_t>

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetBatchSize ( ) const

inlineinherited

Getters.

Definition at line 163 of file GeneralLayer.h.

◆ GetBiases() [1/2]

template<typename Architecture_t>

std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiases ( )

inlineinherited

Definition at line 179 of file GeneralLayer.h.

◆ GetBiases() [2/2]

template<typename Architecture_t>

const std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiases ( ) const

inlineinherited

Definition at line 178 of file GeneralLayer.h.

◆ GetBiasesAt() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiasesAt ( size_t i )

inlineinherited

Definition at line 182 of file GeneralLayer.h.

◆ GetBiasesAt() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiasesAt ( size_t i ) const

inlineinherited

Definition at line 181 of file GeneralLayer.h.

◆ GetBiasGradients() [1/2]

template<typename Architecture_t>

std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiasGradients ( )

inlineinherited

Definition at line 191 of file GeneralLayer.h.

◆ GetBiasGradients() [2/2]

template<typename Architecture_t>

const std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiasGradients ( ) const

inlineinherited

Definition at line 190 of file GeneralLayer.h.

◆ GetBiasGradientsAt() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiasGradientsAt ( size_t i )

inlineinherited

Definition at line 194 of file GeneralLayer.h.

◆ GetBiasGradientsAt() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiasGradientsAt ( size_t i ) const

inlineinherited

Definition at line 193 of file GeneralLayer.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.

◆ GetDepth()

template<typename Architecture_t>

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetDepth ( ) const

inlineinherited

Definition at line 167 of file GeneralLayer.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.

◆ GetExtraLayerParameters()

template<typename Architecture_t>

virtual std::vector< Matrix_t > TMVA::DNN::VGeneralLayer< Architecture_t >::GetExtraLayerParameters ( ) const

inlinevirtualinherited

Reimplemented in TMVA::DNN::TBatchNormLayer< Architecture_t >, TMVA::DNN::TBatchNormLayer< TCpu< AReal > >, and TMVA::DNN::TBatchNormLayer< TCuda< AReal > >.

Definition at line 210 of file GeneralLayer.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.

◆ GetHeight()

template<typename Architecture_t>

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetHeight ( ) const

inlineinherited

Definition at line 168 of file GeneralLayer.h.

◆ GetInitialization()

template<typename Architecture_t>

EInitialization TMVA::DNN::VGeneralLayer< Architecture_t >::GetInitialization ( ) const

inlineinherited

Definition at line 214 of file GeneralLayer.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.

◆ GetInputDepth()

template<typename Architecture_t>

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetInputDepth ( ) const

inlineinherited

Definition at line 164 of file GeneralLayer.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.

◆ GetInputHeight()

template<typename Architecture_t>

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetInputHeight ( ) const

inlineinherited

Definition at line 165 of file GeneralLayer.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.

◆ GetInputWidth()

template<typename Architecture_t>

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetInputWidth ( ) const

inlineinherited

Definition at line 166 of file GeneralLayer.h.

◆ GetOutput() [1/2]

template<typename Architecture_t>

Tensor_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetOutput ( )

inlineinherited

Definition at line 197 of file GeneralLayer.h.

◆ GetOutput() [2/2]

template<typename Architecture_t>

const Tensor_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetOutput ( ) const

inlineinherited

Definition at line 196 of file GeneralLayer.h.

◆ GetOutputAt() [1/2]

template<typename Architecture_t>

Matrix_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetOutputAt ( size_t i )

inlineinherited

Definition at line 202 of file GeneralLayer.h.

◆ GetOutputAt() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetOutputAt ( size_t i ) const

inlineinherited

Definition at line 203 of file GeneralLayer.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.

◆ GetWeightGradients() [1/2]

template<typename Architecture_t>

std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeightGradients ( )

inlineinherited

Definition at line 185 of file GeneralLayer.h.

◆ GetWeightGradients() [2/2]

template<typename Architecture_t>

const std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeightGradients ( ) const

inlineinherited

Definition at line 184 of file GeneralLayer.h.

◆ GetWeightGradientsAt() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeightGradientsAt ( size_t i )

inlineinherited

Definition at line 188 of file GeneralLayer.h.

◆ GetWeightGradientsAt() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeightGradientsAt ( size_t i ) const

inlineinherited

Definition at line 187 of file GeneralLayer.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.

◆ GetWeights() [1/2]

template<typename Architecture_t>

std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeights ( )

inlineinherited

Definition at line 173 of file GeneralLayer.h.

◆ GetWeights() [2/2]

template<typename Architecture_t>

const std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeights ( ) const

inlineinherited

Definition at line 172 of file GeneralLayer.h.

◆ GetWeightsAt() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeightsAt ( size_t i )

inlineinherited

Definition at line 176 of file GeneralLayer.h.

◆ GetWeightsAt() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeightsAt ( size_t i ) const

inlineinherited

Definition at line 175 of file GeneralLayer.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.

◆ GetWidth()

template<typename Architecture_t>

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetWidth ( ) const

inlineinherited

Definition at line 169 of file GeneralLayer.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 ( )

overridevirtual

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 902 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.

◆ IsTraining()

template<typename Architecture_t>

bool TMVA::DNN::VGeneralLayer< Architecture_t >::IsTraining ( ) const

inlineinherited

Definition at line 170 of file GeneralLayer.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 ( ) const

overridevirtual

Prints the info about the layer.

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

Definition at line 911 of file LSTMLayer.h.

◆ ReadMatrixXML()

template<typename Architecture_t>

auto TMVA::DNN::VGeneralLayer< Architecture_t >::ReadMatrixXML	(	void *	node,
		const char *	name,
		Matrix_t &	matrix )

inherited

Definition at line 544 of file GeneralLayer.h.

◆ ReadWeightsFromXML()

template<typename Architecture_t>

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

inlineoverridevirtual

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

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

Definition at line 953 of file LSTMLayer.h.

◆ ResetTraining()

template<typename Architecture_t>

virtual void TMVA::DNN::VGeneralLayer< Architecture_t >::ResetTraining ( )

inlinevirtualinherited

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

batchnormalization) might need to implement the function in case some operations are needed after looping an all batches

Reimplemented in TMVA::DNN::TBatchNormLayer< Architecture_t >, TMVA::DNN::TBatchNormLayer< TCpu< AReal > >, and TMVA::DNN::TBatchNormLayer< TCuda< AReal > >.

Definition at line 121 of file GeneralLayer.h.

◆ SetBatchSize()

template<typename Architecture_t>

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetBatchSize ( size_t batchSize )

inlineinherited

Setters.

Definition at line 217 of file GeneralLayer.h.

◆ SetDepth()

template<typename Architecture_t>

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetDepth ( size_t depth )

inlineinherited

Definition at line 221 of file GeneralLayer.h.

◆ SetDropoutProbability()

template<typename Architecture_t>

virtual void TMVA::DNN::VGeneralLayer< Architecture_t >::SetDropoutProbability ( Scalar_t )

inlinevirtualinherited

Set Dropout probability.

Reimplemented for layers supporting droput

Reimplemented in TMVA::DNN::TDenseLayer< Architecture_t >.

Definition at line 160 of file GeneralLayer.h.

◆ SetExtraLayerParameters()

template<typename Architecture_t>

virtual void TMVA::DNN::VGeneralLayer< Architecture_t >::SetExtraLayerParameters ( const std::vector< Matrix_t > & )

inlinevirtualinherited

Reimplemented in TMVA::DNN::TBatchNormLayer< Architecture_t >, TMVA::DNN::TBatchNormLayer< TCpu< AReal > >, and TMVA::DNN::TBatchNormLayer< TCuda< AReal > >.

Definition at line 212 of file GeneralLayer.h.

◆ SetHeight()

template<typename Architecture_t>

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetHeight ( size_t height )

inlineinherited

Definition at line 222 of file GeneralLayer.h.

◆ SetInputDepth()

template<typename Architecture_t>

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetInputDepth ( size_t inputDepth )

inlineinherited

Definition at line 218 of file GeneralLayer.h.

◆ SetInputHeight()

template<typename Architecture_t>

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetInputHeight ( size_t inputHeight )

inlineinherited

Definition at line 219 of file GeneralLayer.h.

◆ SetInputWidth()

template<typename Architecture_t>

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetInputWidth ( size_t inputWidth )

inlineinherited

Definition at line 220 of file GeneralLayer.h.

◆ SetIsTraining()

template<typename Architecture_t>

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetIsTraining ( bool isTraining )

inlineinherited

Definition at line 224 of file GeneralLayer.h.

◆ SetWidth()

template<typename Architecture_t>

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetWidth ( size_t width )

inlineinherited

Definition at line 223 of file GeneralLayer.h.

◆ Update()

template<typename Architecture_t>

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

◆ UpdateBiases()

template<typename Architecture_t>

auto TMVA::DNN::VGeneralLayer< Architecture_t >::UpdateBiases	(	const std::vector< Matrix_t > &	biasGradients,
		const Scalar_t	learningRate )

inherited

Updates the biases, given the gradients and the learning rate.

Definition at line 428 of file GeneralLayer.h.

◆ UpdateBiasGradients()

template<typename Architecture_t>

auto TMVA::DNN::VGeneralLayer< Architecture_t >::UpdateBiasGradients	(	const std::vector< Matrix_t > &	biasGradients,
		const Scalar_t	learningRate )

inherited

Updates the bias gradients, given some other weight gradients and learning rate.

Definition at line 448 of file GeneralLayer.h.

◆ UpdateWeightGradients()

template<typename Architecture_t>

auto TMVA::DNN::VGeneralLayer< Architecture_t >::UpdateWeightGradients	(	const std::vector< Matrix_t > &	weightGradients,
		const Scalar_t	learningRate )

inherited

Updates the weight gradients, given some other weight gradients and learning rate.

Definition at line 438 of file GeneralLayer.h.

◆ UpdateWeights()

template<typename Architecture_t>

auto TMVA::DNN::VGeneralLayer< Architecture_t >::UpdateWeights	(	const std::vector< Matrix_t > &	weightGradients,
		const Scalar_t	learningRate )

inherited

Updates the weights, given the gradients and the learning rate,.

Definition at line 418 of file GeneralLayer.h.

◆ WriteMatrixToXML()

template<typename Architecture_t>

auto TMVA::DNN::VGeneralLayer< Architecture_t >::WriteMatrixToXML	(	void *	node,
		const char *	name,
		const Matrix_t &	matrix )

inherited

Definition at line 521 of file GeneralLayer.h.

◆ WriteTensorToXML()

template<typename Architecture_t>

auto TMVA::DNN::VGeneralLayer< Architecture_t >::WriteTensorToXML	(	void *	node,
		const char *	name,
		const std::vector< Matrix_t > &	tensor )

inherited

helper functions for XML

Definition at line 496 of file GeneralLayer.h.

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.

◆ fActivationGradients

template<typename Architecture_t>

Tensor_t TMVA::DNN::VGeneralLayer< Architecture_t >::fActivationGradients

protectedinherited

Gradients w.r.t. the activations of this layer.

Definition at line 78 of file GeneralLayer.h.

◆ fBatchSize

template<typename Architecture_t>

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::fBatchSize

protectedinherited

Batch size used for training and evaluation.

Definition at line 59 of file GeneralLayer.h.

◆ fBiases

template<typename Architecture_t>

std::vector<Matrix_t> TMVA::DNN::VGeneralLayer< Architecture_t >::fBiases

protectedinherited

The biases associated to the layer.

Definition at line 72 of file GeneralLayer.h.

◆ fBiasGradients

template<typename Architecture_t>

std::vector<Matrix_t> TMVA::DNN::VGeneralLayer< Architecture_t >::fBiasGradients

protectedinherited

Gradients w.r.t. the bias values of the layer.

Definition at line 75 of file GeneralLayer.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.

◆ fDepth

template<typename Architecture_t>

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::fDepth

protectedinherited

The depth of the layer.

Definition at line 65 of file GeneralLayer.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

Activation 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.

◆ fHeight

template<typename Architecture_t>

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::fHeight

protectedinherited

The height of the layer.

Definition at line 66 of file GeneralLayer.h.

◆ fInit

template<typename Architecture_t>

EInitialization TMVA::DNN::VGeneralLayer< Architecture_t >::fInit

protectedinherited

The initialization method.

Definition at line 80 of file GeneralLayer.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.

◆ fInputDepth

template<typename Architecture_t>

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::fInputDepth

protectedinherited

The depth of the previous layer or input.

Definition at line 61 of file GeneralLayer.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.

◆ fInputHeight

template<typename Architecture_t>

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::fInputHeight

protectedinherited

The height of the previous layer or input.

Definition at line 62 of file GeneralLayer.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.

◆ fInputWidth

template<typename Architecture_t>

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::fInputWidth

protectedinherited

The width of the previous layer or input.

Definition at line 63 of file GeneralLayer.h.

◆ fIsTraining

template<typename Architecture_t>

bool TMVA::DNN::VGeneralLayer< Architecture_t >::fIsTraining

protectedinherited

Flag indicating the mode.

Definition at line 69 of file GeneralLayer.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.

◆ fOutput

template<typename Architecture_t>

Tensor_t TMVA::DNN::VGeneralLayer< Architecture_t >::fOutput

protectedinherited

Activations of this layer.

Definition at line 77 of file GeneralLayer.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.

◆ fWeightGradients

template<typename Architecture_t>

std::vector<Matrix_t> TMVA::DNN::VGeneralLayer< Architecture_t >::fWeightGradients

protectedinherited

Gradients w.r.t. the weights of the layer.

Definition at line 74 of file GeneralLayer.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.

◆ fWeights

template<typename Architecture_t>

std::vector<Matrix_t> TMVA::DNN::VGeneralLayer< Architecture_t >::fWeights

protectedinherited

The weights associated to the layer.

Definition at line 71 of file GeneralLayer.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.

◆ fWidth

template<typename Architecture_t>

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::fWidth

protectedinherited

The width of this layer.

Definition at line 67 of file GeneralLayer.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.

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

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

Public Types

Public Member Functions

Protected Attributes

Private Attributes

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()

◆ CopyBiases()

◆ CopyParameters()

◆ CopyWeights()

◆ DoesRememberState()

◆ DoesReturnSequence()

◆ ForgetGate()

◆ Forward()

◆ GetActivationFunctionF1()

◆ GetActivationFunctionF2()

◆ GetActivationGradients() [1/2]

◆ GetActivationGradients() [2/2]

◆ GetActivationGradientsAt() [1/2]

◆ GetActivationGradientsAt() [2/2]

◆ GetBatchSize()

◆ GetBiases() [1/2]

◆ GetBiases() [2/2]

◆ GetBiasesAt() [1/2]

◆ GetBiasesAt() [2/2]

◆ GetBiasGradients() [1/2]

◆ GetBiasGradients() [2/2]

◆ GetBiasGradientsAt() [1/2]

◆ GetBiasGradientsAt() [2/2]

◆ 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]

◆ GetDepth()

◆ 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()

◆ GetExtraLayerParameters()

◆ GetForgetBiasGradients() [1/2]

◆ GetForgetBiasGradients() [2/2]

◆ GetForgetDerivativesAt() [1/2]

◆ GetForgetDerivativesAt() [2/2]