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TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > Member List

This is the complete list of members for TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >, including all inherited members.

AddWeightsXMLTo(void *parent)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inlinevirtual
Backward(Tensor_t &gradients_backward, const Tensor_t &activations_backward)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inlinevirtual
candidate_gate_valueTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
CandidateValue(const Matrix_t &input, Matrix_t &dc)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
cell_valueTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
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)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
CellForward(Matrix_t &inputGateValues, const Matrix_t &forgetGateValues, const Matrix_t &candidateValues, const Matrix_t &outputGateValues)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
CopyBiases(const std::vector< Matrix_t > &otherBiases)TMVA::DNN::VGeneralLayer< Architecture_t >
CopyParameters(const VGeneralLayer< Arch > &layer)TMVA::DNN::VGeneralLayer< Architecture_t >
CopyWeights(const std::vector< Matrix_t > &otherWeights)TMVA::DNN::VGeneralLayer< Architecture_t >
DoesRememberState() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
DoesReturnSequence() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
fActivationGradientsTMVA::DNN::VGeneralLayer< Architecture_t >protected
fBatchSizeTMVA::DNN::VGeneralLayer< Architecture_t >protected
fBiasesTMVA::DNN::VGeneralLayer< Architecture_t >protected
fBiasGradientsTMVA::DNN::VGeneralLayer< Architecture_t >protected
fCandidateBiasTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fCandidateBiasGradientsTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fCandidateValueTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fCellTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fCellSizeTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fDepthTMVA::DNN::VGeneralLayer< Architecture_t >protected
fDerivativesCandidateTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fDerivativesForgetTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fDerivativesInputTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fDerivativesOutputTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fDescriptorsTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fDxTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fDyTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fF1TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fF2TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fForgetBiasGradientsTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fForgetGateBiasTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fForgetValueTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fHeightTMVA::DNN::VGeneralLayer< Architecture_t >protected
fInitTMVA::DNN::VGeneralLayer< Architecture_t >protected
fInputBiasGradientsTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fInputDepthTMVA::DNN::VGeneralLayer< Architecture_t >protected
fInputGateBiasTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fInputHeightTMVA::DNN::VGeneralLayer< Architecture_t >protected
fInputValueTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fInputWidthTMVA::DNN::VGeneralLayer< Architecture_t >protected
fIsTrainingTMVA::DNN::VGeneralLayer< Architecture_t >protected
forget_gate_valueTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
ForgetGate(const Matrix_t &input, Matrix_t &df)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
Forward(Tensor_t &input, bool isTraining=true)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inlinevirtual
fOutputTMVA::DNN::VGeneralLayer< Architecture_t >protected
fOutputBiasGradientsTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fOutputGateBiasTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fOutputValueTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fRememberStateTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fReturnSequenceTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fStateTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fStateSizeTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fTimeStepsTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightGradientsTMVA::DNN::VGeneralLayer< Architecture_t >protected
fWeightGradientsTensorTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsTMVA::DNN::VGeneralLayer< Architecture_t >protected
fWeightsCandidateTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsCandidateGradientsTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsCandidateStateTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsCandidateStateGradientsTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsForgetGateTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsForgetGateStateTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsForgetGradientsTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsForgetStateGradientsTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsInputGateTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsInputGateStateTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsInputGradientsTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsInputStateGradientsTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsOutputGateTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsOutputGateStateTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsOutputGradientsTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsOutputStateGradientsTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWeightsTensorTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fWidthTMVA::DNN::VGeneralLayer< Architecture_t >protected
fWorkspaceTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fXTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
fYTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
GetActivationFunctionF1() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetActivationFunctionF2() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetActivationGradients() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetActivationGradients()TMVA::DNN::VGeneralLayer< Architecture_t >inline
GetActivationGradientsAt(size_t i)TMVA::DNN::VGeneralLayer< Architecture_t >inline
GetActivationGradientsAt(size_t i) constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetBatchSize() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetBiases() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetBiases()TMVA::DNN::VGeneralLayer< Architecture_t >inline
GetBiasesAt(size_t i) constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetBiasesAt(size_t i)TMVA::DNN::VGeneralLayer< Architecture_t >inline
GetBiasGradients() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetBiasGradients()TMVA::DNN::VGeneralLayer< Architecture_t >inline
GetBiasGradientsAt(size_t i) constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetBiasGradientsAt(size_t i)TMVA::DNN::VGeneralLayer< Architecture_t >inline
GetCandidateBias() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCandidateBias()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCandidateBiasGradients() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCandidateBiasGradients()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCandidateDerivativesAt(size_t i) constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCandidateDerivativesAt(size_t i)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCandidateGateTensor() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCandidateGateTensor()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCandidateGateTensorAt(size_t i) constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCandidateGateTensorAt(size_t i)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCandidateValue() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCandidateValue()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCell() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCell()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCellSize() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCellTensor() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCellTensor()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCellTensorAt(size_t i) constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetCellTensorAt(size_t i)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetDepth() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetDerivativesCandidate() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetDerivativesCandidate()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetDerivativesForget() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetDerivativesForget()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetDerivativesInput() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetDerivativesInput()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetDerivativesOutput() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetDerivativesOutput()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetDX()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetDY()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetExtraLayerParameters() constTMVA::DNN::VGeneralLayer< Architecture_t >inlinevirtual
GetForgetBiasGradients() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetForgetBiasGradients()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetForgetDerivativesAt(size_t i) constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetForgetDerivativesAt(size_t i)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetForgetGateBias() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetForgetGateBias()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetForgetGateTensor() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetForgetGateTensor()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetForgetGateTensorAt(size_t i) constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetForgetGateTensorAt(size_t i)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetForgetGateValue() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetForgetGateValue()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetHeight() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetInitialization() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetInputBiasGradients() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetInputBiasGradients()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetInputDepth() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetInputDerivativesAt(size_t i) constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetInputDerivativesAt(size_t i)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetInputGateBias() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetInputGateBias()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetInputGateTensor() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetInputGateTensor()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetInputGateTensorAt(size_t i) constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetInputGateTensorAt(size_t i)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetInputGateValue() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetInputGateValue()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetInputHeight() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetInputSize() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetInputWidth() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetOutput() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetOutput()TMVA::DNN::VGeneralLayer< Architecture_t >inline
GetOutputAt(size_t i)TMVA::DNN::VGeneralLayer< Architecture_t >inline
GetOutputAt(size_t i) constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetOutputBiasGradients() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetOutputBiasGradients()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetOutputDerivativesAt(size_t i) constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetOutputDerivativesAt(size_t i)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetOutputGateBias() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetOutputGateBias()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetOutputGateTensor() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetOutputGateTensor()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetOutputGateTensorAt(size_t i) constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetOutputGateTensorAt(size_t i)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetOutputGateValue() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetOutputGateValue()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetState() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetState()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetStateSize() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetTimeSteps() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightGradients() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetWeightGradients()TMVA::DNN::VGeneralLayer< Architecture_t >inline
GetWeightGradientsAt(size_t i) constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetWeightGradientsAt(size_t i)TMVA::DNN::VGeneralLayer< Architecture_t >inline
GetWeightGradientsTensor()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightGradientsTensor() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeights() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetWeights()TMVA::DNN::VGeneralLayer< Architecture_t >inline
GetWeightsAt(size_t i) constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetWeightsAt(size_t i)TMVA::DNN::VGeneralLayer< Architecture_t >inline
GetWeightsCandidate() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsCandidate()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsCandidateGradients() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsCandidateGradients()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsCandidateState() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsCandidateState()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsCandidateStateGradients() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsCandidateStateGradients()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsForgetGate() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsForgetGate()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsForgetGateState() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsForgetGateState()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsForgetGradients() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsForgetGradients()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsForgetStateGradients()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsInputGate() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsInputGate()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsInputGateState() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsInputGateState()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsInputGradients() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsInputGradients()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsInputStateGradients() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsInputStateGradients()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsOutputGate() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsOutputGate()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsOutputGateState() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsOutputGateState()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsOutputGradients() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsOutputGradients()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsOutputStateGradients() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsOutputStateGradients()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsTensor()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeightsTensor() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWeigthsForgetStateGradients() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetWidth() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
GetX()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
GetY()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
HelperDescriptor_t typedefTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >
Initialize()TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >virtual
InitState(DNN::EInitialization m=DNN::EInitialization::kZero)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >
input_gate_valueTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
InputGate(const Matrix_t &input, Matrix_t &di)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
IsTraining() constTMVA::DNN::VGeneralLayer< Architecture_t >inline
LayerDescriptor_t typedefTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >
Matrix_t typedefTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >
output_gate_valueTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >private
OutputGate(const Matrix_t &input, Matrix_t &dout)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inline
Print() constTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >virtual
ReadMatrixXML(void *node, const char *name, Matrix_t &matrix)TMVA::DNN::VGeneralLayer< Architecture_t >
ReadWeightsFromXML(void *parent)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >inlinevirtual
ResetTraining()TMVA::DNN::VGeneralLayer< Architecture_t >inlinevirtual
RNNDescriptors_t typedefTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >
RNNWorkspace_t typedefTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >
Scalar_t typedefTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >
SetBatchSize(size_t batchSize)TMVA::DNN::VGeneralLayer< Architecture_t >inline
SetDepth(size_t depth)TMVA::DNN::VGeneralLayer< Architecture_t >inline
SetDropoutProbability(Scalar_t)TMVA::DNN::VGeneralLayer< Architecture_t >inlinevirtual
SetExtraLayerParameters(const std::vector< Matrix_t > &)TMVA::DNN::VGeneralLayer< Architecture_t >inlinevirtual
SetHeight(size_t height)TMVA::DNN::VGeneralLayer< Architecture_t >inline
SetInputDepth(size_t inputDepth)TMVA::DNN::VGeneralLayer< Architecture_t >inline
SetInputHeight(size_t inputHeight)TMVA::DNN::VGeneralLayer< Architecture_t >inline
SetInputWidth(size_t inputWidth)TMVA::DNN::VGeneralLayer< Architecture_t >inline
SetIsTraining(bool isTraining)TMVA::DNN::VGeneralLayer< Architecture_t >inline
SetWidth(size_t width)TMVA::DNN::VGeneralLayer< Architecture_t >inline
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)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >
TBasicLSTMLayer(const TBasicLSTMLayer &)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >
Tensor_t typedefTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >
TensorDescriptor_t typedefTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >
Update(const Scalar_t learningRate)TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >
UpdateBiases(const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate)TMVA::DNN::VGeneralLayer< Architecture_t >
UpdateBiasGradients(const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate)TMVA::DNN::VGeneralLayer< Architecture_t >
UpdateWeightGradients(const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate)TMVA::DNN::VGeneralLayer< Architecture_t >
UpdateWeights(const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate)TMVA::DNN::VGeneralLayer< Architecture_t >
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)TMVA::DNN::VGeneralLayer< Architecture_t >
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)TMVA::DNN::VGeneralLayer< Architecture_t >
VGeneralLayer(VGeneralLayer< Architecture_t > *layer)TMVA::DNN::VGeneralLayer< Architecture_t >
VGeneralLayer(const VGeneralLayer &)TMVA::DNN::VGeneralLayer< Architecture_t >
WeightsDescriptor_t typedefTMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >
WriteMatrixToXML(void *node, const char *name, const Matrix_t &matrix)TMVA::DNN::VGeneralLayer< Architecture_t >
WriteTensorToXML(void *node, const char *name, const std::vector< Matrix_t > &tensor)TMVA::DNN::VGeneralLayer< Architecture_t >
~VGeneralLayer()TMVA::DNN::VGeneralLayer< Architecture_t >virtual