| AddLayer(size_t width, EActivationFunction f, Scalar_t dropoutProbability=1.0) | TMVA::DNN::TNet< Architecture_t, Layer_t > | |
| AddLayer(SharedLayer &layer) | TMVA::DNN::TNet< Architecture_t, Layer_t > | |
| AddLayer(SharedLayer_t &layer) | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| Backward(const Matrix_t &X, const Matrix_t &Y, const Matrix_t &weights) | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| Clear() | TMVA::DNN::TNet< Architecture_t, Layer_t > | |
| CreateClone(size_t batchSize) | TMVA::DNN::TNet< Architecture_t, Layer_t > | |
| fBatchSize | TMVA::DNN::TNet< Architecture_t, Layer_t > | private |
| fDummy | TMVA::DNN::TNet< Architecture_t, Layer_t > | private |
| fInputWidth | TMVA::DNN::TNet< Architecture_t, Layer_t > | private |
| fJ | TMVA::DNN::TNet< Architecture_t, Layer_t > | private |
| fLayers | TMVA::DNN::TNet< Architecture_t, Layer_t > | private |
| Forward(Matrix_t &X, bool applyDropout=false) | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| fR | TMVA::DNN::TNet< Architecture_t, Layer_t > | private |
| fWeightDecay | TMVA::DNN::TNet< Architecture_t, Layer_t > | private |
| GetBatchSize() const | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| GetDepth() const | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| GetInputWidth() const | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| GetLayer(size_t i) | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| GetLayer(size_t i) const | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| GetLossFunction() const | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| GetNFlops() | TMVA::DNN::TNet< Architecture_t, Layer_t > | |
| GetOutput() | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| GetOutputWidth() const | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| GetRegularization() const | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| GetWeightDecay() const | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| Initialize(EInitialization m) | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| InitializeGradients() | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| LayerIterator_t typedef | TMVA::DNN::TNet< Architecture_t, Layer_t > | |
| LayersBegin() | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| LayersEnd() | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| Loss(const Matrix_t &Y, const Matrix_t &weights, bool includeRegularization=true) const | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| Loss(Matrix_t &X, const Matrix_t &Y, const Matrix_t &weights, bool applyDropout=false, bool includeRegularization=true) | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| Matrix_t typedef | TMVA::DNN::TNet< Architecture_t, Layer_t > | |
| Prediction(Matrix_t &Y_hat, Matrix_t &X, EOutputFunction f) | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| Prediction(Matrix_t &Y_hat, EOutputFunction f) const | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| Print() | TMVA::DNN::TNet< Architecture_t, Layer_t > | |
| Scalar_t typedef | TMVA::DNN::TNet< Architecture_t, Layer_t > | |
| SetBatchSize(size_t batchSize) | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| SetDropoutProbabilities(const std::vector< Double_t > &probabilities) | TMVA::DNN::TNet< Architecture_t, Layer_t > | |
| SetInputWidth(size_t inputWidth) | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| SetLossFunction(ELossFunction J) | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| SetRegularization(ERegularization R) | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| SetWeightDecay(Scalar_t weightDecay) | TMVA::DNN::TNet< Architecture_t, Layer_t > | inline |
| TNet() | TMVA::DNN::TNet< Architecture_t, Layer_t > | |
| TNet(const TNet &other) | TMVA::DNN::TNet< Architecture_t, Layer_t > | |
| TNet(size_t batchSize, const TNet< OtherArchitecture_t > &) | TMVA::DNN::TNet< Architecture_t, Layer_t > | |
| TNet(size_t batchSize, size_t inputWidth, ELossFunction fJ, ERegularization fR=ERegularization::kNone, Scalar_t fWeightDecay=0.0) | TMVA::DNN::TNet< Architecture_t, Layer_t > | |
