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ROOT 6.18/05 Reference Guide |
This is the complete list of members for TMVA::DNN::TReference< AReal >, including all inherited members.
AdamUpdate(TMatrixT< AReal > &A, const TMatrixT< AReal > &M, const TMatrixT< AReal > &V, AReal alpha, AReal eps) | TMVA::DNN::TReference< AReal > | static |
AdamUpdateFirstMom(TMatrixT< AReal > &A, const TMatrixT< AReal > &B, AReal beta) | TMVA::DNN::TReference< AReal > | static |
AdamUpdateSecondMom(TMatrixT< AReal > &A, const TMatrixT< AReal > &B, AReal beta) | TMVA::DNN::TReference< AReal > | static |
AddBiases(TMatrixT< AReal > &A, const TMatrixT< AReal > &biases) | TMVA::DNN::TReference< AReal > | static |
AddConvBiases(TMatrixT< AReal > &output, const TMatrixT< AReal > &biases) | TMVA::DNN::TReference< AReal > | static |
AddL1RegularizationGradients(TMatrixT< AReal > &A, const TMatrixT< AReal > &W, AReal weightDecay) | TMVA::DNN::TReference< AReal > | static |
AddL2RegularizationGradients(TMatrixT< AReal > &A, const TMatrixT< AReal > &W, AReal weightDecay) | TMVA::DNN::TReference< AReal > | static |
AddRowWise(TMatrixT< Scalar_t > &output, const TMatrixT< Scalar_t > &biases) | TMVA::DNN::TReference< AReal > | static |
Backward(TMatrixT< Scalar_t > &activationGradientsBackward, TMatrixT< Scalar_t > &weightGradients, TMatrixT< Scalar_t > &biasGradients, TMatrixT< Scalar_t > &df, const TMatrixT< Scalar_t > &activationGradients, const TMatrixT< Scalar_t > &weights, const TMatrixT< Scalar_t > &activationBackward) | TMVA::DNN::TReference< AReal > | static |
ConstAdd(TMatrixT< AReal > &A, AReal beta) | TMVA::DNN::TReference< AReal > | static |
ConstMult(TMatrixT< AReal > &A, AReal beta) | TMVA::DNN::TReference< AReal > | static |
ConvLayerBackward(std::vector< TMatrixT< AReal > > &, TMatrixT< AReal > &, TMatrixT< AReal > &, std::vector< TMatrixT< AReal > > &, const std::vector< TMatrixT< AReal > > &, const TMatrixT< AReal > &, const std::vector< TMatrixT< AReal > > &, size_t, size_t, size_t, size_t, size_t, size_t, size_t, size_t, size_t, size_t) | TMVA::DNN::TReference< AReal > | inlinestatic |
ConvLayerForward(std::vector< TMatrixT< AReal > > &, std::vector< TMatrixT< AReal > > &, const std::vector< TMatrixT< AReal > > &, const TMatrixT< AReal > &, const TMatrixT< AReal > &, const DNN::CNN::TConvParams &, EActivationFunction, std::vector< TMatrixT< AReal > > &) | TMVA::DNN::TReference< AReal > | inlinestatic |
Copy(TMatrixT< Scalar_t > &A, const TMatrixT< Scalar_t > &B) | TMVA::DNN::TReference< AReal > | static |
Copy(std::vector< TMatrixT< Scalar_t > > &A, const std::vector< TMatrixT< Scalar_t > > &B) | TMVA::DNN::TReference< AReal > | static |
CopyDiffArch(TMatrixT< Scalar_t > &A, const AMatrix_t &B) | TMVA::DNN::TReference< AReal > | static |
CopyDiffArch(std::vector< TMatrixT< Scalar_t > > &A, const std::vector< AMatrix_t > &B) | TMVA::DNN::TReference< AReal > | static |
CorruptInput(TMatrixT< AReal > &input, TMatrixT< AReal > &corruptedInput, AReal corruptionLevel) | TMVA::DNN::TReference< AReal > | static |
CrossEntropy(const TMatrixT< AReal > &Y, const TMatrixT< AReal > &output, const TMatrixT< AReal > &weights) | TMVA::DNN::TReference< AReal > | static |
CrossEntropyGradients(TMatrixT< AReal > &dY, const TMatrixT< AReal > &Y, const TMatrixT< AReal > &output, const TMatrixT< AReal > &weights) | TMVA::DNN::TReference< AReal > | static |
Deflatten(std::vector< TMatrixT< AReal > > &A, const TMatrixT< Scalar_t > &B, size_t index, size_t nRows, size_t nCols) | TMVA::DNN::TReference< AReal > | static |
Downsample(TMatrixT< AReal > &A, TMatrixT< AReal > &B, const TMatrixT< AReal > &C, size_t imgHeight, size_t imgWidth, size_t fltHeight, size_t fltWidth, size_t strideRows, size_t strideCols) | TMVA::DNN::TReference< AReal > | static |
Dropout(TMatrixT< AReal > &A, AReal dropoutProbability) | TMVA::DNN::TReference< AReal > | static |
EncodeInput(TMatrixT< AReal > &input, TMatrixT< AReal > &compressedInput, TMatrixT< AReal > &Weights) | TMVA::DNN::TReference< AReal > | static |
fgRandomGen | TMVA::DNN::TReference< AReal > | privatestatic |
Flatten(TMatrixT< AReal > &A, const std::vector< TMatrixT< AReal > > &B, size_t size, size_t nRows, size_t nCols) | TMVA::DNN::TReference< AReal > | static |
ForwardLogReg(TMatrixT< AReal > &input, TMatrixT< AReal > &p, TMatrixT< AReal > &fWeights) | TMVA::DNN::TReference< AReal > | static |
Gauss(TMatrixT< AReal > &B) | TMVA::DNN::TReference< AReal > | inlinestatic |
GaussDerivative(TMatrixT< AReal > &B, const TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | inlinestatic |
GetRandomGenerator() | TMVA::DNN::TReference< AReal > | static |
Hadamard(TMatrixT< AReal > &A, const TMatrixT< AReal > &B) | TMVA::DNN::TReference< AReal > | static |
Identity(TMatrixT< AReal > &B) | TMVA::DNN::TReference< AReal > | static |
IdentityDerivative(TMatrixT< AReal > &B, const TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | static |
Im2col(TMatrixT< AReal > &A, const TMatrixT< AReal > &B, size_t imgHeight, size_t imgWidth, size_t fltHeight, size_t fltWidth, size_t strideRows, size_t strideCols, size_t zeroPaddingHeight, size_t zeroPaddingWidth) | TMVA::DNN::TReference< AReal > | static |
Im2colFast(TMatrixT< AReal > &, const TMatrixT< AReal > &, const std::vector< int > &) | TMVA::DNN::TReference< AReal > | inlinestatic |
Im2colIndices(std::vector< int > &, const TMatrixT< AReal > &, size_t, size_t, size_t, size_t, size_t, size_t, size_t, size_t, size_t) | TMVA::DNN::TReference< AReal > | inlinestatic |
InitializeGauss(TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | static |
InitializeGlorotNormal(TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | static |
InitializeGlorotUniform(TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | static |
InitializeIdentity(TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | static |
InitializeUniform(TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | static |
InitializeZero(TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | static |
L1Regularization(const TMatrixT< AReal > &W) | TMVA::DNN::TReference< AReal > | static |
L2Regularization(const TMatrixT< AReal > &W) | TMVA::DNN::TReference< AReal > | static |
Matrix_t typedef | TMVA::DNN::TReference< AReal > | |
MaxPoolLayerBackward(TMatrixT< AReal > &activationGradientsBackward, const TMatrixT< AReal > &activationGradients, const TMatrixT< AReal > &indexMatrix, size_t imgHeight, size_t imgWidth, size_t fltHeight, size_t fltWidth, size_t strideRows, size_t strideCol, size_t nLocalViews) | TMVA::DNN::TReference< AReal > | static |
MeanSquaredError(const TMatrixT< AReal > &Y, const TMatrixT< AReal > &output, const TMatrixT< AReal > &weights) | TMVA::DNN::TReference< AReal > | static |
MeanSquaredErrorGradients(TMatrixT< AReal > &dY, const TMatrixT< AReal > &Y, const TMatrixT< AReal > &output, const TMatrixT< AReal > &weights) | TMVA::DNN::TReference< AReal > | static |
MultiplyTranspose(TMatrixT< Scalar_t > &output, const TMatrixT< Scalar_t > &input, const TMatrixT< Scalar_t > &weights) | TMVA::DNN::TReference< AReal > | static |
PrepareInternals(std::vector< TMatrixT< AReal > > &) | TMVA::DNN::TReference< AReal > | inlinestatic |
Rearrange(std::vector< TMatrixT< AReal > > &out, const std::vector< TMatrixT< AReal > > &in) | TMVA::DNN::TReference< AReal > | static |
ReciprocalElementWise(TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | static |
ReconstructInput(TMatrixT< AReal > &compressedInput, TMatrixT< AReal > &reconstructedInput, TMatrixT< AReal > &fWeights) | TMVA::DNN::TReference< AReal > | static |
RecurrentLayerBackward(TMatrixT< Scalar_t > &state_gradients_backward, TMatrixT< Scalar_t > &input_weight_gradients, TMatrixT< Scalar_t > &state_weight_gradients, TMatrixT< Scalar_t > &bias_gradients, TMatrixT< Scalar_t > &df, const TMatrixT< Scalar_t > &state, const TMatrixT< Scalar_t > &weights_input, const TMatrixT< Scalar_t > &weights_state, const TMatrixT< Scalar_t > &input, TMatrixT< Scalar_t > &input_gradient) | TMVA::DNN::TReference< AReal > | static |
Relu(TMatrixT< AReal > &B) | TMVA::DNN::TReference< AReal > | static |
ReluDerivative(TMatrixT< AReal > &B, const TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | inlinestatic |
Reshape(TMatrixT< AReal > &A, const TMatrixT< AReal > &B) | TMVA::DNN::TReference< AReal > | static |
RotateWeights(TMatrixT< AReal > &A, const TMatrixT< AReal > &B, size_t filterDepth, size_t filterHeight, size_t filterWidth, size_t numFilters) | TMVA::DNN::TReference< AReal > | static |
Scalar_t typedef | TMVA::DNN::TReference< AReal > | |
ScaleAdd(TMatrixT< Scalar_t > &A, const TMatrixT< Scalar_t > &B, Scalar_t beta=1.0) | TMVA::DNN::TReference< AReal > | static |
ScaleAdd(std::vector< TMatrixT< Scalar_t > > &A, const std::vector< TMatrixT< Scalar_t > > &B, Scalar_t beta=1.0) | TMVA::DNN::TReference< AReal > | static |
SetRandomSeed(size_t seed) | TMVA::DNN::TReference< AReal > | static |
Sigmoid(TMatrixT< AReal > &B) | TMVA::DNN::TReference< AReal > | static |
Sigmoid(TMatrixT< AReal > &YHat, const TMatrixT< AReal > &) | TMVA::DNN::TReference< AReal > | static |
SigmoidDerivative(TMatrixT< AReal > &B, const TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | inlinestatic |
Softmax(TMatrixT< AReal > &YHat, const TMatrixT< AReal > &) | TMVA::DNN::TReference< AReal > | static |
SoftmaxAE(TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | static |
SoftmaxCrossEntropy(const TMatrixT< AReal > &Y, const TMatrixT< AReal > &output, const TMatrixT< AReal > &weights) | TMVA::DNN::TReference< AReal > | static |
SoftmaxCrossEntropyGradients(TMatrixT< AReal > &dY, const TMatrixT< AReal > &Y, const TMatrixT< AReal > &output, const TMatrixT< AReal > &weights) | TMVA::DNN::TReference< AReal > | static |
SoftSign(TMatrixT< AReal > &B) | TMVA::DNN::TReference< AReal > | inlinestatic |
SoftSignDerivative(TMatrixT< AReal > &B, const TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | inlinestatic |
SqrtElementWise(TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | static |
SquareElementWise(TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | static |
SumColumns(TMatrixT< AReal > &B, const TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | static |
SymmetricRelu(TMatrixT< AReal > &B) | TMVA::DNN::TReference< AReal > | inlinestatic |
SymmetricReluDerivative(TMatrixT< AReal > &B, const TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | inlinestatic |
Tanh(TMatrixT< AReal > &B) | TMVA::DNN::TReference< AReal > | inlinestatic |
TanhDerivative(TMatrixT< AReal > &B, const TMatrixT< AReal > &A) | TMVA::DNN::TReference< AReal > | inlinestatic |
UpdateParams(TMatrixT< AReal > &x, TMatrixT< AReal > &tildeX, TMatrixT< AReal > &y, TMatrixT< AReal > &z, TMatrixT< AReal > &fVBiases, TMatrixT< AReal > &fHBiases, TMatrixT< AReal > &fWeights, TMatrixT< AReal > &VBiasError, TMatrixT< AReal > &HBiasError, AReal learningRate, size_t fBatchSize) | TMVA::DNN::TReference< AReal > | static |
UpdateParamsLogReg(TMatrixT< AReal > &input, TMatrixT< AReal > &output, TMatrixT< AReal > &difference, TMatrixT< AReal > &p, TMatrixT< AReal > &fWeights, TMatrixT< AReal > &fBiases, AReal learningRate, size_t fBatchSize) | TMVA::DNN::TReference< AReal > | static |