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

Definition at line 56 of file RNNLayer.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
	TBasicRNNLayer (const TBasicRNNLayer &)
	Copy Constructor.
	TBasicRNNLayer (size_t batchSize, size_t stateSize, size_t inputSize, size_t timeSteps, bool rememberState=false, bool returnSequence=false, DNN::EActivationFunction f=DNN::EActivationFunction::kTanh, bool training=true, DNN::EInitialization fA=DNN::EInitialization::kZero)
	Constructor.
virtual	~TBasicRNNLayer ()
	Destructor.
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.
Matrix_t &	CellBackward (Matrix_t &state_gradients_backward, const Matrix_t &precStateActivations, const Matrix_t &input, Matrix_t &input_gradient, Matrix_t &dF)
	Backward for a single time unit a the corresponding call to Forward(...).
void	CellForward (const Matrix_t &input, Matrix_t &dF)
	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	Forward (Tensor_t &input, bool isTraining=true) override
	Compute and return the next state with given input matrix.
DNN::EActivationFunction	GetActivationFunction () 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
Matrix_t &	GetBiasesState ()
const Matrix_t &	GetBiasesState () 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 &	GetBiasStateGradients ()
const Matrix_t &	GetBiasStateGradients () const
Matrix_t &	GetCell ()
const Matrix_t &	GetCell () const
size_t	GetDepth () const
Tensor_t &	GetDerivatives ()
const Tensor_t &	GetDerivatives () const
Tensor_t &	GetDX ()
Tensor_t &	GetDY ()
virtual std::vector< Matrix_t >	GetExtraLayerParameters () const
size_t	GetHeight () const
EInitialization	GetInitialization () const
size_t	GetInputDepth () const
size_t	GetInputHeight () const
size_t	GetInputSize () 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
Matrix_t &	GetState ()
const Matrix_t &	GetState () const
size_t	GetStateSize () const
size_t	GetTimeSteps () const
	Getters.
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
Matrix_t &	GetWeightInputGradients ()
const Matrix_t &	GetWeightInputGradients () 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 &	GetWeightsInput ()
const Matrix_t &	GetWeightsInput () const
Matrix_t &	GetWeightsState ()
const Matrix_t &	GetWeightsState () const
Matrix_t &	GetWeightStateGradients ()
const Matrix_t &	GetWeightStateGradients () const
Tensor_t &	GetWeightsTensor ()
const Tensor_t &	GetWeightsTensor () 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 state method.
void	InitTensors ()
bool	IsTraining () const
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.
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
Architecture_t::ActivationDescriptor_t	fActivationDesc
Matrix_t &	fBiases
	Biases.
Matrix_t &	fBiasGradients
	Gradients w.r.t. the bias values.
Matrix_t	fCell
	Empty matrix for RNN.
Tensor_t	fDerivatives
	First fDerivatives of the activations.
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	fF
	Activation function of the hidden state.
bool	fRememberState
	Remember state in next pass.
bool	fReturnSequence = false
	Return in output full sequence or just last element in time.
Matrix_t	fState
	Hidden State.
size_t	fStateSize
	Hidden state size of RNN.
size_t	fTimeSteps
	Timesteps for RNN.
Tensor_t	fWeightGradientsTensor
Matrix_t &	fWeightInputGradients
	Gradients w.r.t. the input weights.
Matrix_t &	fWeightsInput
	Input weights, fWeights[0].
Matrix_t &	fWeightsState
	Prev state weights, fWeights[1].
Matrix_t &	fWeightStateGradients
	Gradients w.r.t. the recurring weights.
Tensor_t	fWeightsTensor
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

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

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

Member Typedef Documentation

◆ HelperDescriptor_t

template<typename Architecture_t>

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

Definition at line 68 of file RNNLayer.h.

◆ LayerDescriptor_t

template<typename Architecture_t>

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

Definition at line 65 of file RNNLayer.h.

◆ Matrix_t

template<typename Architecture_t>

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

Definition at line 62 of file RNNLayer.h.

◆ RNNDescriptors_t

template<typename Architecture_t>

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

Definition at line 71 of file RNNLayer.h.

◆ RNNWorkspace_t

template<typename Architecture_t>

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

Definition at line 70 of file RNNLayer.h.

◆ Scalar_t

template<typename Architecture_t>

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

Definition at line 63 of file RNNLayer.h.

◆ Tensor_t

template<typename Architecture_t>

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

Definition at line 61 of file RNNLayer.h.

◆ TensorDescriptor_t

template<typename Architecture_t>

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

Definition at line 67 of file RNNLayer.h.

◆ WeightsDescriptor_t

template<typename Architecture_t>

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

Definition at line 66 of file RNNLayer.h.

Constructor & Destructor Documentation

◆ TBasicRNNLayer() [1/2]

template<typename Architecture_t>

TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::TBasicRNNLayer	(	size_t	batchSize,
		size_t	stateSize,
		size_t	inputSize,
		size_t	timeSteps,
		bool	rememberState = false,
		bool	returnSequence = false,
		DNN::EActivationFunction	f = DNN::EActivationFunction::kTanh,
		bool	training = true,
		DNN::EInitialization	fA = DNN::EInitialization::kZero )

Constructor.

Definition at line 213 of file RNNLayer.h.

◆ TBasicRNNLayer() [2/2]

template<typename Architecture_t>

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

Copy Constructor.

Definition at line 231 of file RNNLayer.h.

◆ ~TBasicRNNLayer()

template<typename Architecture_t>

TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::~TBasicRNNLayer ( )

virtual

Destructor.

Definition at line 249 of file RNNLayer.h.

Member Function Documentation

◆ AddWeightsXMLTo()

template<typename Architecture_t>

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

overridevirtual

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

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

Definition at line 599 of file RNNLayer.h.

◆ Backward()

template<typename Architecture_t>

auto TMVA::DNN::RNN::TBasicRNNLayer< 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 431 of file RNNLayer.h.

◆ CellBackward()

template<typename Architecture_t>

auto TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::CellBackward	(	Matrix_t &	state_gradients_backward,
		const Matrix_t &	precStateActivations,
		const Matrix_t &	input,
		Matrix_t &	input_gradient,
		Matrix_t &	dF )

inline

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

Definition at line 587 of file RNNLayer.h.

◆ CellForward()

template<typename Architecture_t>

auto TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::CellForward	(	const Matrix_t &	input,
		Matrix_t &	dF )

inline

Forward for a single cell (time unit).

Definition at line 408 of file RNNLayer.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::TBasicRNNLayer< Architecture_t >::DoesRememberState ( ) const

inline

Definition at line 171 of file RNNLayer.h.

◆ DoesReturnSequence()

template<typename Architecture_t>

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

inline

Definition at line 172 of file RNNLayer.h.

◆ Forward()

template<typename Architecture_t>

void TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::Forward	(	Tensor_t &	input,
		bool	isTraining = true )

overridevirtual

Compute and return the next state with given input matrix.

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

Definition at line 322 of file RNNLayer.h.

◆ GetActivationFunction()

template<typename Architecture_t>

DNN::EActivationFunction TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetActivationFunction ( ) const

inline

Definition at line 173 of file RNNLayer.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.

◆ GetBiasesState() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetBiasesState ( )

inline

Definition at line 188 of file RNNLayer.h.

◆ GetBiasesState() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetBiasesState ( ) const

inline

Definition at line 189 of file RNNLayer.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.

◆ GetBiasStateGradients() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetBiasStateGradients ( )

inline

Definition at line 190 of file RNNLayer.h.

◆ GetBiasStateGradients() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetBiasStateGradients ( ) const

inline

Definition at line 191 of file RNNLayer.h.

◆ GetCell() [1/2]

template<typename Architecture_t>

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

inline

Definition at line 176 of file RNNLayer.h.

◆ GetCell() [2/2]

template<typename Architecture_t>

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

inline

Definition at line 177 of file RNNLayer.h.

◆ GetDepth()

template<typename Architecture_t>

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

inlineinherited

Definition at line 167 of file GeneralLayer.h.

◆ GetDerivatives() [1/2]

template<typename Architecture_t>

Tensor_t & TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetDerivatives ( )

inline

Definition at line 183 of file RNNLayer.h.

◆ GetDerivatives() [2/2]

template<typename Architecture_t>

const Tensor_t & TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetDerivatives ( ) const

inline

Definition at line 184 of file RNNLayer.h.

◆ GetDX()

template<typename Architecture_t>

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

inline

Definition at line 204 of file RNNLayer.h.

◆ GetDY()

template<typename Architecture_t>

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

inline

Definition at line 205 of file RNNLayer.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.

◆ 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.

◆ GetInputDepth()

template<typename Architecture_t>

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

inlineinherited

Definition at line 164 of file GeneralLayer.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::TBasicRNNLayer< Architecture_t >::GetInputSize ( ) const

inline

Definition at line 170 of file RNNLayer.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.

◆ GetState() [1/2]

template<typename Architecture_t>

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

inline

Definition at line 174 of file RNNLayer.h.

◆ GetState() [2/2]

template<typename Architecture_t>

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

inline

Definition at line 175 of file RNNLayer.h.

◆ GetStateSize()

template<typename Architecture_t>

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

inline

Definition at line 169 of file RNNLayer.h.

◆ GetTimeSteps()

template<typename Architecture_t>

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

inline

Getters.

Definition at line 168 of file RNNLayer.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::TBasicRNNLayer< Architecture_t >::GetWeightGradientsTensor ( )

inline

Definition at line 199 of file RNNLayer.h.

◆ GetWeightGradientsTensor() [2/2]

template<typename Architecture_t>

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

inline

Definition at line 200 of file RNNLayer.h.

◆ GetWeightInputGradients() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetWeightInputGradients ( )

inline

Definition at line 192 of file RNNLayer.h.

◆ GetWeightInputGradients() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetWeightInputGradients ( ) const

inline

Definition at line 193 of file RNNLayer.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.

◆ GetWeightsInput() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetWeightsInput ( )

inline

Definition at line 179 of file RNNLayer.h.

◆ GetWeightsInput() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetWeightsInput ( ) const

inline

Definition at line 180 of file RNNLayer.h.

◆ GetWeightsState() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetWeightsState ( )

inline

Definition at line 181 of file RNNLayer.h.

◆ GetWeightsState() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetWeightsState ( ) const

inline

Definition at line 182 of file RNNLayer.h.

◆ GetWeightStateGradients() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetWeightStateGradients ( )

inline

Definition at line 194 of file RNNLayer.h.

◆ GetWeightStateGradients() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::GetWeightStateGradients ( ) const

inline

Definition at line 195 of file RNNLayer.h.

◆ GetWeightsTensor() [1/2]

template<typename Architecture_t>

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

inline

Definition at line 197 of file RNNLayer.h.

◆ GetWeightsTensor() [2/2]

template<typename Architecture_t>

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

inline

Definition at line 198 of file RNNLayer.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::TBasicRNNLayer< Architecture_t >::GetX ( )

inline

Definition at line 202 of file RNNLayer.h.

◆ GetY()

template<typename Architecture_t>

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

inline

Definition at line 203 of file RNNLayer.h.

◆ Initialize()

template<typename Architecture_t>

void TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::Initialize ( )

overridevirtual

Initialize the weights according to the given initialization method.

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

Definition at line 264 of file RNNLayer.h.

◆ InitState()

template<typename Architecture_t>

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

Initialize the state method.

Definition at line 286 of file RNNLayer.h.

◆ InitTensors()

template<typename Architecture_t>

void TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::InitTensors ( )

Definition at line 279 of file RNNLayer.h.

◆ IsTraining()

template<typename Architecture_t>

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

inlineinherited

Definition at line 170 of file GeneralLayer.h.

◆ Print()

template<typename Architecture_t>

auto TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::Print ( ) const

overridevirtual

Prints the info about the layer.

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

Definition at line 295 of file RNNLayer.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>

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

overridevirtual

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

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

Definition at line 620 of file RNNLayer.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::TBasicRNNLayer< 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

◆ fActivationDesc

template<typename Architecture_t>

Architecture_t::ActivationDescriptor_t TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::fActivationDesc

private

Definition at line 95 of file RNNLayer.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>

Matrix_t& TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::fBiases

private

Biases.

Definition at line 85 of file RNNLayer.h.

◆ fBiasGradients

template<typename Architecture_t>

Matrix_t& TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::fBiasGradients

private

Gradients w.r.t. the bias values.

Definition at line 90 of file RNNLayer.h.

◆ fCell

template<typename Architecture_t>

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

private

Empty matrix for RNN.

Definition at line 100 of file RNNLayer.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.

◆ fDerivatives

template<typename Architecture_t>

Tensor_t TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::fDerivatives

private

First fDerivatives of the activations.

Definition at line 87 of file RNNLayer.h.

◆ fDescriptors

template<typename Architecture_t>

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

private

Keeps all the RNN descriptors.

Definition at line 97 of file RNNLayer.h.

◆ fDx

template<typename Architecture_t>

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

private

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

Definition at line 105 of file RNNLayer.h.

◆ fDy

template<typename Architecture_t>

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

private

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

Definition at line 106 of file RNNLayer.h.

◆ fF

template<typename Architecture_t>

DNN::EActivationFunction TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::fF

private

Activation function of the hidden state.

Definition at line 80 of file RNNLayer.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.

◆ 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.

◆ 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.

◆ 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.

◆ 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.

◆ fRememberState

template<typename Architecture_t>

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

private

Remember state in next pass.

Definition at line 77 of file RNNLayer.h.

◆ fReturnSequence

template<typename Architecture_t>

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

private

Return in output full sequence or just last element in time.

Definition at line 78 of file RNNLayer.h.

◆ fState

template<typename Architecture_t>

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

private

Hidden State.

Definition at line 82 of file RNNLayer.h.

◆ fStateSize

template<typename Architecture_t>

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

private

Hidden state size of RNN.

Definition at line 76 of file RNNLayer.h.

◆ fTimeSteps

template<typename Architecture_t>

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

private

Timesteps for RNN.

Definition at line 75 of file RNNLayer.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::TBasicRNNLayer< Architecture_t >::fWeightGradientsTensor

private

Definition at line 93 of file RNNLayer.h.

◆ fWeightInputGradients

template<typename Architecture_t>

Matrix_t& TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::fWeightInputGradients

private

Gradients w.r.t. the input weights.

Definition at line 88 of file RNNLayer.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.

◆ fWeightsInput

template<typename Architecture_t>

Matrix_t& TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::fWeightsInput

private

Input weights, fWeights[0].

Definition at line 83 of file RNNLayer.h.

◆ fWeightsState

template<typename Architecture_t>

Matrix_t& TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::fWeightsState

private

Prev state weights, fWeights[1].

Definition at line 84 of file RNNLayer.h.

◆ fWeightStateGradients

template<typename Architecture_t>

Matrix_t& TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >::fWeightStateGradients

private

Gradients w.r.t. the recurring weights.

Definition at line 89 of file RNNLayer.h.

◆ fWeightsTensor

template<typename Architecture_t>

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

private

Definition at line 92 of file RNNLayer.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::TBasicRNNLayer< Architecture_t >::fWorkspace = nullptr

private

Definition at line 98 of file RNNLayer.h.

◆ fX

template<typename Architecture_t>

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

private

cached input tensor as T x B x I

Definition at line 103 of file RNNLayer.h.

◆ fY

template<typename Architecture_t>

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

private

cached output tensor as T x B x S

Definition at line 104 of file RNNLayer.h.

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

tmva/tmva/inc/TMVA/DNN/RNN/RNNLayer.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

◆ TBasicRNNLayer() [1/2]

◆ TBasicRNNLayer() [2/2]

◆ ~TBasicRNNLayer()

Member Function Documentation

◆ AddWeightsXMLTo()

◆ Backward()

◆ CellBackward()

◆ CellForward()

◆ CopyBiases()

◆ CopyParameters()

◆ CopyWeights()

◆ DoesRememberState()

◆ DoesReturnSequence()

◆ Forward()

◆ GetActivationFunction()

◆ 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]

◆ GetBiasesState() [1/2]

◆ GetBiasesState() [2/2]

◆ GetBiasGradients() [1/2]

◆ GetBiasGradients() [2/2]

◆ GetBiasGradientsAt() [1/2]

◆ GetBiasGradientsAt() [2/2]

◆ GetBiasStateGradients() [1/2]

◆ GetBiasStateGradients() [2/2]

◆ GetCell() [1/2]

◆ GetCell() [2/2]

◆ GetDepth()

◆ GetDerivatives() [1/2]

◆ GetDerivatives() [2/2]

◆ GetDX()

◆ GetDY()

◆ GetExtraLayerParameters()

◆ GetHeight()

◆ GetInitialization()

◆ GetInputDepth()

◆ GetInputHeight()

◆ GetInputSize()

◆ GetInputWidth()

◆ GetOutput() [1/2]

◆ GetOutput() [2/2]

◆ GetOutputAt() [1/2]

◆ GetOutputAt() [2/2]

◆ GetState() [1/2]

◆ GetState() [2/2]

◆ GetStateSize()

◆ GetTimeSteps()

◆ GetWeightGradients() [1/2]

◆ GetWeightGradients() [2/2]

◆ GetWeightGradientsAt() [1/2]

◆ GetWeightGradientsAt() [2/2]

◆ GetWeightGradientsTensor() [1/2]

◆ GetWeightGradientsTensor() [2/2]

◆ GetWeightInputGradients() [1/2]

◆ GetWeightInputGradients() [2/2]

◆ GetWeights() [1/2]

◆ GetWeights() [2/2]

◆ GetWeightsAt() [1/2]