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TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > Class Template Reference

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. More...
 
 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. More...
 
void AddWeightsXMLTo (void *parent)
 Writes the information and the weights about the layer in an XML node. More...
 
void Backward (Tensor_t &gradients_backward, const Tensor_t &activations_backward)
 Backpropagates the error. More...
 
void CandidateValue (const Matrix_t &input, Matrix_t &dc)
 Decides the new candidate values (NN with Tanh) More...
 
Matrix_tCellBackward (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(...). More...
 
void CellForward (Matrix_t &inputGateValues, const Matrix_t &forgetGateValues, const Matrix_t &candidateValues, const Matrix_t &outputGateValues)
 Forward for a single cell (time unit) More...
 
bool DoesRememberState () const
 
bool DoesReturnSequence () const
 
void ForgetGate (const Matrix_t &input, Matrix_t &df)
 Forgets the past values (NN with Sigmoid) More...
 
void Forward (Tensor_t &input, bool isTraining=true)
 Computes the next hidden state and next cell state with given input matrix. More...
 
DNN::EActivationFunction GetActivationFunctionF1 () const
 
DNN::EActivationFunction GetActivationFunctionF2 () const
 
Matrix_tGetCandidateBias ()
 
const Matrix_tGetCandidateBias () const
 
Matrix_tGetCandidateBiasGradients ()
 
const Matrix_tGetCandidateBiasGradients () const
 
Matrix_tGetCandidateDerivativesAt (size_t i)
 
const Matrix_tGetCandidateDerivativesAt (size_t i) const
 
std::vector< Matrix_t > & GetCandidateGateTensor ()
 
const std::vector< Matrix_t > & GetCandidateGateTensor () const
 
Matrix_tGetCandidateGateTensorAt (size_t i)
 
const Matrix_tGetCandidateGateTensorAt (size_t i) const
 
Matrix_tGetCandidateValue ()
 
const Matrix_tGetCandidateValue () const
 
Matrix_tGetCell ()
 
const Matrix_tGetCell () const
 
size_t GetCellSize () const
 
std::vector< Matrix_t > & GetCellTensor ()
 
const std::vector< Matrix_t > & GetCellTensor () const
 
Matrix_tGetCellTensorAt (size_t i)
 
const Matrix_tGetCellTensorAt (size_t i) const
 
std::vector< Matrix_t > & GetDerivativesCandidate ()
 
const std::vector< Matrix_t > & GetDerivativesCandidate () const
 
std::vector< Matrix_t > & GetDerivativesForget ()
 
const std::vector< Matrix_t > & GetDerivativesForget () const
 
std::vector< Matrix_t > & GetDerivativesInput ()
 
const std::vector< Matrix_t > & GetDerivativesInput () const
 
std::vector< Matrix_t > & GetDerivativesOutput ()
 
const std::vector< Matrix_t > & GetDerivativesOutput () const
 
Tensor_tGetDX ()
 
Tensor_tGetDY ()
 
Matrix_tGetForgetBiasGradients ()
 
const Matrix_tGetForgetBiasGradients () const
 
Matrix_tGetForgetDerivativesAt (size_t i)
 
const Matrix_tGetForgetDerivativesAt (size_t i) const
 
Matrix_tGetForgetGateBias ()
 
const Matrix_tGetForgetGateBias () const
 
std::vector< Matrix_t > & GetForgetGateTensor ()
 
const std::vector< Matrix_t > & GetForgetGateTensor () const
 
Matrix_tGetForgetGateTensorAt (size_t i)
 
const Matrix_tGetForgetGateTensorAt (size_t i) const
 
Matrix_tGetForgetGateValue ()
 
const Matrix_tGetForgetGateValue () const
 
Matrix_tGetInputBiasGradients ()
 
const Matrix_tGetInputBiasGradients () const
 
Matrix_tGetInputDerivativesAt (size_t i)
 
const Matrix_tGetInputDerivativesAt (size_t i) const
 
Matrix_tGetInputGateBias ()
 
const Matrix_tGetInputGateBias () const
 
std::vector< Matrix_t > & GetInputGateTensor ()
 
const std::vector< Matrix_t > & GetInputGateTensor () const
 
Matrix_tGetInputGateTensorAt (size_t i)
 
const Matrix_tGetInputGateTensorAt (size_t i) const
 
Matrix_tGetInputGateValue ()
 
const Matrix_tGetInputGateValue () const
 
size_t GetInputSize () const
 Getters. More...
 
Matrix_tGetOutputBiasGradients ()
 
const Matrix_tGetOutputBiasGradients () const
 
Matrix_tGetOutputDerivativesAt (size_t i)
 
const Matrix_tGetOutputDerivativesAt (size_t i) const
 
Matrix_tGetOutputGateBias ()
 
const Matrix_tGetOutputGateBias () const
 
std::vector< Matrix_t > & GetOutputGateTensor ()
 
const std::vector< Matrix_t > & GetOutputGateTensor () const
 
Matrix_tGetOutputGateTensorAt (size_t i)
 
const Matrix_tGetOutputGateTensorAt (size_t i) const
 
Matrix_tGetOutputGateValue ()
 
const Matrix_tGetOutputGateValue () const
 
Matrix_tGetState ()
 
const Matrix_tGetState () const
 
size_t GetStateSize () const
 
size_t GetTimeSteps () const
 
Tensor_tGetWeightGradientsTensor ()
 
const Tensor_tGetWeightGradientsTensor () const
 
Matrix_tGetWeightsCandidate ()
 
const Matrix_tGetWeightsCandidate () const
 
Matrix_tGetWeightsCandidateGradients ()
 
const Matrix_tGetWeightsCandidateGradients () const
 
Matrix_tGetWeightsCandidateState ()
 
const Matrix_tGetWeightsCandidateState () const
 
Matrix_tGetWeightsCandidateStateGradients ()
 
const Matrix_tGetWeightsCandidateStateGradients () const
 
Matrix_tGetWeightsForgetGate ()
 
const Matrix_tGetWeightsForgetGate () const
 
Matrix_tGetWeightsForgetGateState ()
 
const Matrix_tGetWeightsForgetGateState () const
 
Matrix_tGetWeightsForgetGradients ()
 
const Matrix_tGetWeightsForgetGradients () const
 
Matrix_tGetWeightsForgetStateGradients ()
 
Matrix_tGetWeightsInputGate ()
 
const Matrix_tGetWeightsInputGate () const
 
Matrix_tGetWeightsInputGateState ()
 
const Matrix_tGetWeightsInputGateState () const
 
Matrix_tGetWeightsInputGradients ()
 
const Matrix_tGetWeightsInputGradients () const
 
Matrix_tGetWeightsInputStateGradients ()
 
const Matrix_tGetWeightsInputStateGradients () const
 
Matrix_tGetWeightsOutputGate ()
 
const Matrix_tGetWeightsOutputGate () const
 
Matrix_tGetWeightsOutputGateState ()
 
const Matrix_tGetWeightsOutputGateState () const
 
Matrix_tGetWeightsOutputGradients ()
 
const Matrix_tGetWeightsOutputGradients () const
 
Matrix_tGetWeightsOutputStateGradients ()
 
const Matrix_tGetWeightsOutputStateGradients () const
 
Tensor_tGetWeightsTensor ()
 
const Tensor_tGetWeightsTensor () const
 
const Matrix_tGetWeigthsForgetStateGradients () const
 
Tensor_tGetX ()
 
Tensor_tGetY ()
 
virtual void Initialize ()
 Initialize the weights according to the given initialization method. More...
 
void InitState (DNN::EInitialization m=DNN::EInitialization::kZero)
 Initialize the hidden state and cell state method. More...
 
void InputGate (const Matrix_t &input, Matrix_t &di)
 Decides the values we'll update (NN with Sigmoid) More...
 
void OutputGate (const Matrix_t &input, Matrix_t &dout)
 Computes output values (NN with Sigmoid) More...
 
void Print () const
 Prints the info about the layer. More...
 
void ReadWeightsFromXML (void *parent)
 Read the information and the weights about the layer from XML node. More...
 
void Update (const Scalar_t learningRate)
 
- Public Member Functions inherited from TMVA::DNN::VGeneralLayer< Architecture_t >
 VGeneralLayer (const VGeneralLayer &)
 Copy Constructor. More...
 
 VGeneralLayer (size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t Depth, size_t Height, size_t Width, size_t WeightsNSlices, size_t WeightsNRows, size_t WeightsNCols, size_t BiasesNSlices, size_t BiasesNRows, size_t BiasesNCols, size_t OutputNSlices, size_t OutputNRows, size_t OutputNCols, EInitialization Init)
 Constructor. More...
 
 VGeneralLayer (size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t Depth, size_t Height, size_t Width, size_t WeightsNSlices, std::vector< size_t > WeightsNRows, std::vector< size_t > WeightsNCols, size_t BiasesNSlices, std::vector< size_t > BiasesNRows, std::vector< size_t > BiasesNCols, size_t OutputNSlices, size_t OutputNRows, size_t OutputNCols, EInitialization Init)
 General Constructor with different weights dimension. More...
 
 VGeneralLayer (VGeneralLayer< Architecture_t > *layer)
 Copy the layer provided as a pointer. More...
 
virtual ~VGeneralLayer ()
 Virtual Destructor. More...
 
void CopyBiases (const std::vector< Matrix_t > &otherBiases)
 Copies the biases provided as an input. More...
 
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. More...
 
void CopyWeights (const std::vector< Matrix_t > &otherWeights)
 Copies the weights provided as an input. More...
 
Tensor_tGetActivationGradients ()
 
const Tensor_tGetActivationGradients () const
 
Matrix_t GetActivationGradientsAt (size_t i)
 
const Matrix_tGetActivationGradientsAt (size_t i) const
 
size_t GetBatchSize () const
 Getters. More...
 
std::vector< Matrix_t > & GetBiases ()
 
const std::vector< Matrix_t > & GetBiases () const
 
Matrix_tGetBiasesAt (size_t i)
 
const Matrix_tGetBiasesAt (size_t i) const
 
std::vector< Matrix_t > & GetBiasGradients ()
 
const std::vector< Matrix_t > & GetBiasGradients () const
 
Matrix_tGetBiasGradientsAt (size_t i)
 
const Matrix_tGetBiasGradientsAt (size_t i) const
 
size_t GetDepth () const
 
virtual std::vector< Matrix_tGetExtraLayerParameters () const
 
size_t GetHeight () const
 
EInitialization GetInitialization () const
 
size_t GetInputDepth () const
 
size_t GetInputHeight () const
 
size_t GetInputWidth () const
 
Tensor_tGetOutput ()
 
const Tensor_tGetOutput () const
 
Matrix_t GetOutputAt (size_t i)
 
const Matrix_tGetOutputAt (size_t i) const
 
std::vector< Matrix_t > & GetWeightGradients ()
 
const std::vector< Matrix_t > & GetWeightGradients () const
 
Matrix_tGetWeightGradientsAt (size_t i)
 
const Matrix_tGetWeightGradientsAt (size_t i) const
 
std::vector< Matrix_t > & GetWeights ()
 
const std::vector< Matrix_t > & GetWeights () const
 
Matrix_tGetWeightsAt (size_t i)
 
const Matrix_tGetWeightsAt (size_t i) const
 
size_t GetWidth () const
 
bool IsTraining () const
 
void ReadMatrixXML (void *node, const char *name, Matrix_t &matrix)
 
virtual void ResetTraining ()
 Reset some training flags after a loop on all batches Some layer (e.g. More...
 
void SetBatchSize (size_t batchSize)
 Setters. More...
 
void SetDepth (size_t depth)
 
virtual void SetDropoutProbability (Scalar_t)
 Set Dropout probability. More...
 
virtual void SetExtraLayerParameters (const std::vector< Matrix_t > &)
 
void SetHeight (size_t height)
 
void SetInputDepth (size_t inputDepth)
 
void SetInputHeight (size_t inputHeight)
 
void SetInputWidth (size_t inputWidth)
 
void SetIsTraining (bool isTraining)
 
void SetWidth (size_t width)
 
void Update (const Scalar_t learningRate)
 Updates the weights and biases, given the learning rate. More...
 
void UpdateBiases (const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate)
 Updates the biases, given the gradients and the learning rate. More...
 
void UpdateBiasGradients (const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate)
 Updates the bias gradients, given some other weight gradients and learning rate. More...
 
void UpdateWeightGradients (const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate)
 Updates the weight gradients, given some other weight gradients and learning rate. More...
 
void UpdateWeights (const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate)
 Updates the weights, given the gradients and the learning rate,. More...
 
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 More...
 

Private Attributes

std::vector< Matrix_tcandidate_gate_value
 candidate gate value for every time step More...
 
std::vector< Matrix_tcell_value
 cell value for every time step More...
 
Matrix_tfCandidateBias
 Candidate Gate bias. More...
 
Matrix_tfCandidateBiasGradients
 Gradients w.r.t the candidate gate - bias weights. More...
 
Matrix_t fCandidateValue
 Computed candidate values. More...
 
Matrix_t fCell
 Cell state of LSTM. More...
 
size_t fCellSize
 Cell state size of LSTM. More...
 
std::vector< Matrix_tfDerivativesCandidate
 First fDerivatives of the activations candidate gate. More...
 
std::vector< Matrix_tfDerivativesForget
 First fDerivatives of the activations forget gate. More...
 
std::vector< Matrix_tfDerivativesInput
 First fDerivatives of the activations input gate. More...
 
std::vector< Matrix_tfDerivativesOutput
 First fDerivatives of the activations output gate. More...
 
TDescriptorsfDescriptors = nullptr
 Keeps all the RNN descriptors. More...
 
Tensor_t fDx
 cached gradient on the input (output of backward) as T x B x I More...
 
Tensor_t fDy
 cached activation gradient (input of backward) as T x B x S More...
 
DNN::EActivationFunction fF1
 Activation function: sigmoid. More...
 
DNN::EActivationFunction fF2
 Activaton function: tanh. More...
 
Matrix_tfForgetBiasGradients
 Gradients w.r.t the forget gate - bias weights. More...
 
Matrix_tfForgetGateBias
 Forget Gate bias. More...
 
Matrix_t fForgetValue
 Computed forget gate values. More...
 
Matrix_tfInputBiasGradients
 Gradients w.r.t the input gate - bias weights. More...
 
Matrix_tfInputGateBias
 Input Gate bias. More...
 
Matrix_t fInputValue
 Computed input gate values. More...
 
std::vector< Matrix_tforget_gate_value
 forget gate value for every time step More...
 
Matrix_tfOutputBiasGradients
 Gradients w.r.t the output gate - bias weights. More...
 
Matrix_tfOutputGateBias
 Output Gate bias. More...
 
Matrix_t fOutputValue
 Computed output gate values. More...
 
bool fRememberState
 Remember state in next pass. More...
 
bool fReturnSequence = false
 Return in output full sequence or just last element. More...
 
Matrix_t fState
 Hidden state of LSTM. More...
 
size_t fStateSize
 Hidden state size for LSTM. More...
 
size_t fTimeSteps
 Timesteps for LSTM. More...
 
Tensor_t fWeightGradientsTensor
 Tensor for all weight gradients. More...
 
Matrix_tfWeightsCandidate
 Candidate Gate weights for input, fWeights[4]. More...
 
Matrix_tfWeightsCandidateGradients
 Gradients w.r.t the candidate gate - input weights. More...
 
Matrix_tfWeightsCandidateState
 Candidate Gate weights for prev state, fWeights[5]. More...
 
Matrix_tfWeightsCandidateStateGradients
 Gradients w.r.t the candidate gate - hidden state weights. More...
 
Matrix_tfWeightsForgetGate
 Forget Gate weights for input, fWeights[2]. More...
 
Matrix_tfWeightsForgetGateState
 Forget Gate weights for prev state, fWeights[3]. More...
 
Matrix_tfWeightsForgetGradients
 Gradients w.r.t the forget gate - input weights. More...
 
Matrix_tfWeightsForgetStateGradients
 Gradients w.r.t the forget gate - hidden state weights. More...
 
Matrix_tfWeightsInputGate
 Input Gate weights for input, fWeights[0]. More...
 
Matrix_tfWeightsInputGateState
 Input Gate weights for prev state, fWeights[1]. More...
 
Matrix_tfWeightsInputGradients
 Gradients w.r.t the input gate - input weights. More...
 
Matrix_tfWeightsInputStateGradients
 Gradients w.r.t the input gate - hidden state weights. More...
 
Matrix_tfWeightsOutputGate
 Output Gate weights for input, fWeights[6]. More...
 
Matrix_tfWeightsOutputGateState
 Output Gate weights for prev state, fWeights[7]. More...
 
Matrix_tfWeightsOutputGradients
 Gradients w.r.t the output gate - input weights. More...
 
Matrix_tfWeightsOutputStateGradients
 Gradients w.r.t the output gate - hidden state weights. More...
 
Tensor_t fWeightsTensor
 Tensor for all weights. More...
 
TWorkspacefWorkspace = nullptr
 
Tensor_t fX
 cached input tensor as T x B x I More...
 
Tensor_t fY
 cached output tensor as T x B x S More...
 
std::vector< Matrix_tinput_gate_value
 input gate value for every time step More...
 
std::vector< Matrix_toutput_gate_value
 output gate value for every time step More...
 

Additional Inherited Members

- Protected Attributes inherited from TMVA::DNN::VGeneralLayer< Architecture_t >
Tensor_t fActivationGradients
 Gradients w.r.t. the activations of this layer. More...
 
size_t fBatchSize
 Batch size used for training and evaluation. More...
 
std::vector< Matrix_tfBiases
 The biases associated to the layer. More...
 
std::vector< Matrix_tfBiasGradients
 Gradients w.r.t. the bias values of the layer. More...
 
size_t fDepth
 The depth of the layer. More...
 
size_t fHeight
 The height of the layer. More...
 
EInitialization fInit
 The initialization method. More...
 
size_t fInputDepth
 The depth of the previous layer or input. More...
 
size_t fInputHeight
 The height of the previous layer or input. More...
 
size_t fInputWidth
 The width of the previous layer or input. More...
 
bool fIsTraining
 Flag indicating the mode. More...
 
Tensor_t fOutput
 Activations of this layer. More...
 
std::vector< Matrix_tfWeightGradients
 Gradients w.r.t. the weights of the layer. More...
 
std::vector< Matrix_tfWeights
 The weights associated to the layer. More...
 
size_t fWidth
 The width of this layer. More...
 

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

Inheritance diagram for TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >:
[legend]

Member Typedef Documentation

◆ HelperDescriptor_t

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

Definition at line 68 of file LSTMLayer.h.

◆ LayerDescriptor_t

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

Definition at line 65 of file LSTMLayer.h.

◆ Matrix_t

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

Definition at line 61 of file LSTMLayer.h.

◆ RNNDescriptors_t

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

Definition at line 71 of file LSTMLayer.h.

◆ RNNWorkspace_t

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

Definition at line 70 of file LSTMLayer.h.

◆ Scalar_t

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

Definition at line 62 of file LSTMLayer.h.

◆ Tensor_t

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

Definition at line 63 of file LSTMLayer.h.

◆ TensorDescriptor_t

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

Definition at line 67 of file LSTMLayer.h.

◆ WeightsDescriptor_t

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

Definition at line 66 of file LSTMLayer.h.

Constructor & Destructor Documentation

◆ TBasicLSTMLayer() [1/2]

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

Constructor.

Definition at line 341 of file LSTMLayer.h.

◆ TBasicLSTMLayer() [2/2]

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

Copy Constructor.

Definition at line 385 of file LSTMLayer.h.

Member Function Documentation

◆ AddWeightsXMLTo()

template<typename Architecture_t >
auto TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::AddWeightsXMLTo ( void parent)
inlinevirtual

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

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

Definition at line 922 of file LSTMLayer.h.

◆ Backward()

template<typename Architecture_t >
auto TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::Backward ( Tensor_t gradients_backward,
const Tensor_t activations_backward 
)
inlinevirtual

Backpropagates the error.

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

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

Definition at line 680 of file LSTMLayer.h.

◆ CandidateValue()

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

Decides the new candidate values (NN with Tanh)

Definition at line 515 of file LSTMLayer.h.

◆ CellBackward()

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

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

Definition at line 862 of file LSTMLayer.h.

◆ CellForward()

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

Forward for a single cell (time unit)

Definition at line 654 of file LSTMLayer.h.

◆ DoesRememberState()

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

Definition at line 216 of file LSTMLayer.h.

◆ DoesReturnSequence()

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

Definition at line 217 of file LSTMLayer.h.

◆ ForgetGate()

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

Forgets the past values (NN with Sigmoid)

Definition at line 497 of file LSTMLayer.h.

◆ Forward()

template<typename Architecture_t >
auto TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::Forward ( Tensor_t input,
bool  isTraining = true 
)
inlinevirtual

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

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

Definition at line 553 of file LSTMLayer.h.

◆ GetActivationFunctionF1()

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

Definition at line 219 of file LSTMLayer.h.

◆ GetActivationFunctionF2()

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

Definition at line 220 of file LSTMLayer.h.

◆ GetCandidateBias() [1/2]

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

Definition at line 296 of file LSTMLayer.h.

◆ GetCandidateBias() [2/2]

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

Definition at line 295 of file LSTMLayer.h.

◆ GetCandidateBiasGradients() [1/2]

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

Definition at line 316 of file LSTMLayer.h.

◆ GetCandidateBiasGradients() [2/2]

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

Definition at line 315 of file LSTMLayer.h.

◆ GetCandidateDerivativesAt() [1/2]

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

Definition at line 264 of file LSTMLayer.h.

◆ GetCandidateDerivativesAt() [2/2]

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

Definition at line 263 of file LSTMLayer.h.

◆ GetCandidateGateTensor() [1/2]

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

Definition at line 279 of file LSTMLayer.h.

◆ GetCandidateGateTensor() [2/2]

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

Definition at line 278 of file LSTMLayer.h.

◆ GetCandidateGateTensorAt() [1/2]

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

Definition at line 281 of file LSTMLayer.h.

◆ GetCandidateGateTensorAt() [2/2]

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

Definition at line 280 of file LSTMLayer.h.

◆ GetCandidateValue() [1/2]

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

Definition at line 225 of file LSTMLayer.h.

◆ GetCandidateValue() [2/2]

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

Definition at line 224 of file LSTMLayer.h.

◆ GetCell() [1/2]

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

Definition at line 234 of file LSTMLayer.h.

◆ GetCell() [2/2]

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

Definition at line 233 of file LSTMLayer.h.

◆ GetCellSize()

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

Definition at line 214 of file LSTMLayer.h.

◆ GetCellTensor() [1/2]

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

Definition at line 287 of file LSTMLayer.h.

◆ GetCellTensor() [2/2]

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

Definition at line 286 of file LSTMLayer.h.

◆ GetCellTensorAt() [1/2]

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

Definition at line 289 of file LSTMLayer.h.

◆ GetCellTensorAt() [2/2]

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

Definition at line 288 of file LSTMLayer.h.

◆ GetDerivativesCandidate() [1/2]

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

Definition at line 262 of file LSTMLayer.h.

◆ GetDerivativesCandidate() [2/2]

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

Definition at line 261 of file LSTMLayer.h.

◆ GetDerivativesForget() [1/2]

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

Definition at line 258 of file LSTMLayer.h.

◆ GetDerivativesForget() [2/2]

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

Definition at line 257 of file LSTMLayer.h.

◆ GetDerivativesInput() [1/2]

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

Definition at line 254 of file LSTMLayer.h.

◆ GetDerivativesInput() [2/2]

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

Definition at line 253 of file LSTMLayer.h.

◆ GetDerivativesOutput() [1/2]

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

Definition at line 266 of file LSTMLayer.h.

◆ GetDerivativesOutput() [2/2]

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

Definition at line 265 of file LSTMLayer.h.

◆ GetDX()

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

Definition at line 331 of file LSTMLayer.h.

◆ GetDY()

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

Definition at line 332 of file LSTMLayer.h.

◆ GetForgetBiasGradients() [1/2]

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

Definition at line 310 of file LSTMLayer.h.

◆ GetForgetBiasGradients() [2/2]

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

Definition at line 309 of file LSTMLayer.h.

◆ GetForgetDerivativesAt() [1/2]

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

Definition at line 260 of file LSTMLayer.h.

◆ GetForgetDerivativesAt() [2/2]

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

Definition at line 259 of file LSTMLayer.h.

◆ GetForgetGateBias() [1/2]

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

Definition at line 294 of file LSTMLayer.h.

◆ GetForgetGateBias() [2/2]

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

Definition at line 293 of file LSTMLayer.h.

◆ GetForgetGateTensor() [1/2]

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

Definition at line 275 of file LSTMLayer.h.

◆ GetForgetGateTensor() [2/2]

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

Definition at line 274 of file LSTMLayer.h.

◆ GetForgetGateTensorAt() [1/2]

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

Definition at line 277 of file LSTMLayer.h.

◆ GetForgetGateTensorAt() [2/2]

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

Definition at line 276 of file LSTMLayer.h.

◆ GetForgetGateValue() [1/2]

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

Definition at line 227 of file LSTMLayer.h.

◆ GetForgetGateValue() [2/2]

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

Definition at line 226 of file LSTMLayer.h.

◆ GetInputBiasGradients() [1/2]

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

Definition at line 304 of file LSTMLayer.h.

◆ GetInputBiasGradients() [2/2]

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

Definition at line 303 of file LSTMLayer.h.

◆ GetInputDerivativesAt() [1/2]

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

Definition at line 256 of file LSTMLayer.h.

◆ GetInputDerivativesAt() [2/2]

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

Definition at line 255 of file LSTMLayer.h.

◆ GetInputGateBias() [1/2]

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

Definition at line 292 of file LSTMLayer.h.

◆ GetInputGateBias() [2/2]

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

Definition at line 291 of file LSTMLayer.h.

◆ GetInputGateTensor() [1/2]

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

Definition at line 271 of file LSTMLayer.h.

◆ GetInputGateTensor() [2/2]

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

Definition at line 270 of file LSTMLayer.h.

◆ GetInputGateTensorAt() [1/2]

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

Definition at line 273 of file LSTMLayer.h.

◆ GetInputGateTensorAt() [2/2]

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

Definition at line 272 of file LSTMLayer.h.

◆ GetInputGateValue() [1/2]

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

Definition at line 223 of file LSTMLayer.h.

◆ GetInputGateValue() [2/2]

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

Definition at line 222 of file LSTMLayer.h.

◆ GetInputSize()

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

Getters.

Definition at line 211 of file LSTMLayer.h.

◆ GetOutputBiasGradients() [1/2]

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

Definition at line 322 of file LSTMLayer.h.

◆ GetOutputBiasGradients() [2/2]

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

Definition at line 321 of file LSTMLayer.h.

◆ GetOutputDerivativesAt() [1/2]

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

Definition at line 268 of file LSTMLayer.h.

◆ GetOutputDerivativesAt() [2/2]

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

Definition at line 267 of file LSTMLayer.h.

◆ GetOutputGateBias() [1/2]

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

Definition at line 298 of file LSTMLayer.h.

◆ GetOutputGateBias() [2/2]

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

Definition at line 297 of file LSTMLayer.h.

◆ GetOutputGateTensor() [1/2]

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

Definition at line 283 of file LSTMLayer.h.

◆ GetOutputGateTensor() [2/2]

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

Definition at line 282 of file LSTMLayer.h.

◆ GetOutputGateTensorAt() [1/2]

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

Definition at line 285 of file LSTMLayer.h.

◆ GetOutputGateTensorAt() [2/2]

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

Definition at line 284 of file LSTMLayer.h.

◆ GetOutputGateValue() [1/2]

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

Definition at line 229 of file LSTMLayer.h.

◆ GetOutputGateValue() [2/2]

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

Definition at line 228 of file LSTMLayer.h.

◆ GetState() [1/2]

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

Definition at line 232 of file LSTMLayer.h.

◆ GetState() [2/2]

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

Definition at line 231 of file LSTMLayer.h.

◆ GetStateSize()

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

Definition at line 213 of file LSTMLayer.h.

◆ GetTimeSteps()

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

Definition at line 212 of file LSTMLayer.h.

◆ GetWeightGradientsTensor() [1/2]

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

Definition at line 326 of file LSTMLayer.h.

◆ GetWeightGradientsTensor() [2/2]

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

Definition at line 327 of file LSTMLayer.h.

◆ GetWeightsCandidate() [1/2]

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

Definition at line 239 of file LSTMLayer.h.

◆ GetWeightsCandidate() [2/2]

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

Definition at line 238 of file LSTMLayer.h.

◆ GetWeightsCandidateGradients() [1/2]

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

Definition at line 312 of file LSTMLayer.h.

◆ GetWeightsCandidateGradients() [2/2]

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

Definition at line 311 of file LSTMLayer.h.

◆ GetWeightsCandidateState() [1/2]

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

Definition at line 249 of file LSTMLayer.h.

◆ GetWeightsCandidateState() [2/2]

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

Definition at line 248 of file LSTMLayer.h.

◆ GetWeightsCandidateStateGradients() [1/2]

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

Definition at line 314 of file LSTMLayer.h.

◆ GetWeightsCandidateStateGradients() [2/2]

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

Definition at line 313 of file LSTMLayer.h.

◆ GetWeightsForgetGate() [1/2]

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

Definition at line 241 of file LSTMLayer.h.

◆ GetWeightsForgetGate() [2/2]

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

Definition at line 240 of file LSTMLayer.h.

◆ GetWeightsForgetGateState() [1/2]

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

Definition at line 247 of file LSTMLayer.h.

◆ GetWeightsForgetGateState() [2/2]

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

Definition at line 246 of file LSTMLayer.h.

◆ GetWeightsForgetGradients() [1/2]

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

Definition at line 306 of file LSTMLayer.h.

◆ GetWeightsForgetGradients() [2/2]

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

Definition at line 305 of file LSTMLayer.h.

◆ GetWeightsForgetStateGradients()

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

Definition at line 308 of file LSTMLayer.h.

◆ GetWeightsInputGate() [1/2]

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

Definition at line 237 of file LSTMLayer.h.

◆ GetWeightsInputGate() [2/2]

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

Definition at line 236 of file LSTMLayer.h.

◆ GetWeightsInputGateState() [1/2]

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

Definition at line 245 of file LSTMLayer.h.

◆ GetWeightsInputGateState() [2/2]

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

Definition at line 244 of file LSTMLayer.h.

◆ GetWeightsInputGradients() [1/2]

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

Definition at line 300 of file LSTMLayer.h.

◆ GetWeightsInputGradients() [2/2]

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

Definition at line 299 of file LSTMLayer.h.

◆ GetWeightsInputStateGradients() [1/2]

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

Definition at line 302 of file LSTMLayer.h.

◆ GetWeightsInputStateGradients() [2/2]

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

Definition at line 301 of file LSTMLayer.h.

◆ GetWeightsOutputGate() [1/2]

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

Definition at line 243 of file LSTMLayer.h.

◆ GetWeightsOutputGate() [2/2]

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

Definition at line 242 of file LSTMLayer.h.

◆ GetWeightsOutputGateState() [1/2]

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

Definition at line 251 of file LSTMLayer.h.

◆ GetWeightsOutputGateState() [2/2]

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

Definition at line 250 of file LSTMLayer.h.

◆ GetWeightsOutputGradients() [1/2]

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

Definition at line 318 of file LSTMLayer.h.

◆ GetWeightsOutputGradients() [2/2]

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

Definition at line 317 of file LSTMLayer.h.

◆ GetWeightsOutputStateGradients() [1/2]

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

Definition at line 320 of file LSTMLayer.h.

◆ GetWeightsOutputStateGradients() [2/2]

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

Definition at line 319 of file LSTMLayer.h.

◆ GetWeightsTensor() [1/2]

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

Definition at line 324 of file LSTMLayer.h.

◆ GetWeightsTensor() [2/2]

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

Definition at line 325 of file LSTMLayer.h.

◆ GetWeigthsForgetStateGradients()

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

Definition at line 307 of file LSTMLayer.h.

◆ GetX()

template<typename Architecture_t >
Tensor_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::GetX ( void  )
inline

Definition at line 329 of file LSTMLayer.h.

◆ GetY()

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

Definition at line 330 of file LSTMLayer.h.

◆ Initialize()

template<typename Architecture_t >
void TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::Initialize
virtual

Initialize the weights according to the given initialization method.

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

Definition at line 469 of file LSTMLayer.h.

◆ InitState()

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

Initialize the hidden state and cell state method.

Definition at line 901 of file LSTMLayer.h.

◆ InputGate()

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

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

Definition at line 479 of file LSTMLayer.h.

◆ OutputGate()

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

Computes output values (NN with Sigmoid)

Definition at line 533 of file LSTMLayer.h.

◆ Print()

template<typename Architecture_t >
auto TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::Print
virtual

Prints the info about the layer.

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

Definition at line 910 of file LSTMLayer.h.

◆ ReadWeightsFromXML()

template<typename Architecture_t >
auto TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::ReadWeightsFromXML ( void parent)
inlinevirtual

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

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

Definition at line 952 of file LSTMLayer.h.

◆ Update()

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

Member Data Documentation

◆ candidate_gate_value

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

candidate gate value for every time step

Definition at line 110 of file LSTMLayer.h.

◆ cell_value

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

cell value for every time step

Definition at line 112 of file LSTMLayer.h.

◆ fCandidateBias

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fCandidateBias
private

Candidate Gate bias.

Definition at line 102 of file LSTMLayer.h.

◆ fCandidateBiasGradients

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fCandidateBiasGradients
private

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

Definition at line 126 of file LSTMLayer.h.

◆ fCandidateValue

template<typename Architecture_t >
Matrix_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fCandidateValue
private

Computed candidate values.

Definition at line 86 of file LSTMLayer.h.

◆ fCell

template<typename Architecture_t >
Matrix_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fCell
private

Cell state of LSTM.

Definition at line 90 of file LSTMLayer.h.

◆ fCellSize

template<typename Architecture_t >
size_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fCellSize
private

Cell state size of LSTM.

Definition at line 76 of file LSTMLayer.h.

◆ fDerivativesCandidate

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

First fDerivatives of the activations candidate gate.

Definition at line 115 of file LSTMLayer.h.

◆ fDerivativesForget

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

First fDerivatives of the activations forget gate.

Definition at line 114 of file LSTMLayer.h.

◆ fDerivativesInput

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

First fDerivatives of the activations input gate.

Definition at line 113 of file LSTMLayer.h.

◆ fDerivativesOutput

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

First fDerivatives of the activations output gate.

Definition at line 116 of file LSTMLayer.h.

◆ fDescriptors

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

Keeps all the RNN descriptors.

Definition at line 141 of file LSTMLayer.h.

◆ fDx

template<typename Architecture_t >
Tensor_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fDx
private

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

Definition at line 138 of file LSTMLayer.h.

◆ fDy

template<typename Architecture_t >
Tensor_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fDy
private

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

Definition at line 139 of file LSTMLayer.h.

◆ fF1

template<typename Architecture_t >
DNN::EActivationFunction TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fF1
private

Activation function: sigmoid.

Definition at line 82 of file LSTMLayer.h.

◆ fF2

template<typename Architecture_t >
DNN::EActivationFunction TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fF2
private

Activaton function: tanh.

Definition at line 83 of file LSTMLayer.h.

◆ fForgetBiasGradients

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fForgetBiasGradients
private

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

Definition at line 123 of file LSTMLayer.h.

◆ fForgetGateBias

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fForgetGateBias
private

Forget Gate bias.

Definition at line 98 of file LSTMLayer.h.

◆ fForgetValue

template<typename Architecture_t >
Matrix_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fForgetValue
private

Computed forget gate values.

Definition at line 87 of file LSTMLayer.h.

◆ fInputBiasGradients

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fInputBiasGradients
private

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

Definition at line 120 of file LSTMLayer.h.

◆ fInputGateBias

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fInputGateBias
private

Input Gate bias.

Definition at line 94 of file LSTMLayer.h.

◆ fInputValue

template<typename Architecture_t >
Matrix_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fInputValue
private

Computed input gate values.

Definition at line 85 of file LSTMLayer.h.

◆ forget_gate_value

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

forget gate value for every time step

Definition at line 109 of file LSTMLayer.h.

◆ fOutputBiasGradients

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fOutputBiasGradients
private

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

Definition at line 129 of file LSTMLayer.h.

◆ fOutputGateBias

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fOutputGateBias
private

Output Gate bias.

Definition at line 106 of file LSTMLayer.h.

◆ fOutputValue

template<typename Architecture_t >
Matrix_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fOutputValue
private

Computed output gate values.

Definition at line 88 of file LSTMLayer.h.

◆ fRememberState

template<typename Architecture_t >
bool TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fRememberState
private

Remember state in next pass.

Definition at line 79 of file LSTMLayer.h.

◆ fReturnSequence

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

Return in output full sequence or just last element.

Definition at line 80 of file LSTMLayer.h.

◆ fState

template<typename Architecture_t >
Matrix_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fState
private

Hidden state of LSTM.

Definition at line 89 of file LSTMLayer.h.

◆ fStateSize

template<typename Architecture_t >
size_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fStateSize
private

Hidden state size for LSTM.

Definition at line 75 of file LSTMLayer.h.

◆ fTimeSteps

template<typename Architecture_t >
size_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fTimeSteps
private

Timesteps for LSTM.

Definition at line 77 of file LSTMLayer.h.

◆ fWeightGradientsTensor

template<typename Architecture_t >
Tensor_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightGradientsTensor
private

Tensor for all weight gradients.

Definition at line 133 of file LSTMLayer.h.

◆ fWeightsCandidate

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsCandidate
private

Candidate Gate weights for input, fWeights[4].

Definition at line 100 of file LSTMLayer.h.

◆ fWeightsCandidateGradients

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsCandidateGradients
private

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

Definition at line 124 of file LSTMLayer.h.

◆ fWeightsCandidateState

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsCandidateState
private

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

Definition at line 101 of file LSTMLayer.h.

◆ fWeightsCandidateStateGradients

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsCandidateStateGradients
private

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

Definition at line 125 of file LSTMLayer.h.

◆ fWeightsForgetGate

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsForgetGate
private

Forget Gate weights for input, fWeights[2].

Definition at line 96 of file LSTMLayer.h.

◆ fWeightsForgetGateState

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsForgetGateState
private

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

Definition at line 97 of file LSTMLayer.h.

◆ fWeightsForgetGradients

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsForgetGradients
private

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

Definition at line 121 of file LSTMLayer.h.

◆ fWeightsForgetStateGradients

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsForgetStateGradients
private

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

Definition at line 122 of file LSTMLayer.h.

◆ fWeightsInputGate

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsInputGate
private

Input Gate weights for input, fWeights[0].

Definition at line 92 of file LSTMLayer.h.

◆ fWeightsInputGateState

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsInputGateState
private

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

Definition at line 93 of file LSTMLayer.h.

◆ fWeightsInputGradients

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsInputGradients
private

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

Definition at line 118 of file LSTMLayer.h.

◆ fWeightsInputStateGradients

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsInputStateGradients
private

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

Definition at line 119 of file LSTMLayer.h.

◆ fWeightsOutputGate

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsOutputGate
private

Output Gate weights for input, fWeights[6].

Definition at line 104 of file LSTMLayer.h.

◆ fWeightsOutputGateState

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsOutputGateState
private

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

Definition at line 105 of file LSTMLayer.h.

◆ fWeightsOutputGradients

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsOutputGradients
private

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

Definition at line 127 of file LSTMLayer.h.

◆ fWeightsOutputStateGradients

template<typename Architecture_t >
Matrix_t& TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsOutputStateGradients
private

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

Definition at line 128 of file LSTMLayer.h.

◆ fWeightsTensor

template<typename Architecture_t >
Tensor_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fWeightsTensor
private

Tensor for all weights.

Definition at line 132 of file LSTMLayer.h.

◆ fWorkspace

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

Definition at line 142 of file LSTMLayer.h.

◆ fX

template<typename Architecture_t >
Tensor_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fX
private

cached input tensor as T x B x I

Definition at line 136 of file LSTMLayer.h.

◆ fY

template<typename Architecture_t >
Tensor_t TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >::fY
private

cached output tensor as T x B x S

Definition at line 137 of file LSTMLayer.h.

◆ input_gate_value

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

input gate value for every time step

Definition at line 108 of file LSTMLayer.h.

◆ output_gate_value

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

output gate value for every time step

Definition at line 111 of file LSTMLayer.h.


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