TMVA::DNN::TReference< Real_t > Member List

This is the complete list of members for TMVA::DNN::TReference< Real_t >, including all inherited members.

AddL1RegularizationGradients(TMatrixT< Real_t > &A, const TMatrixT< Real_t > &W, Real_t weightDecay)	TMVA::DNN::TReference< Real_t >	static
AddL2RegularizationGradients(TMatrixT< Real_t > &A, const TMatrixT< Real_t > &W, Real_t weightDecay)	TMVA::DNN::TReference< Real_t >	static
AddRowWise(TMatrixT< Scalar_t > &output, const TMatrixT< Scalar_t > &biases)	TMVA::DNN::TReference< Real_t >	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< Real_t >	static
Copy(TMatrixT< Scalar_t > &A, const TMatrixT< Scalar_t > &B)	TMVA::DNN::TReference< Real_t >	static
CrossEntropy(const TMatrixT< Real_t > &Y, const TMatrixT< Real_t > &output)	TMVA::DNN::TReference< Real_t >	static
CrossEntropyGradients(TMatrixT< Real_t > &dY, const TMatrixT< Real_t > &Y, const TMatrixT< Real_t > &output)	TMVA::DNN::TReference< Real_t >	static
Dropout(TMatrixT< Real_t > &A, Real_t dropoutProbability)	TMVA::DNN::TReference< Real_t >	static
Gauss(TMatrixT< Real_t > &B)	TMVA::DNN::TReference< Real_t >	inlinestatic
GaussDerivative(TMatrixT< Real_t > &B, const TMatrixT< Real_t > &A)	TMVA::DNN::TReference< Real_t >	inlinestatic
Identity(TMatrixT< Real_t > &B)	TMVA::DNN::TReference< Real_t >	static
IdentityDerivative(TMatrixT< Real_t > &B, const TMatrixT< Real_t > &A)	TMVA::DNN::TReference< Real_t >	static
InitializeGauss(TMatrixT< Real_t > &A)	TMVA::DNN::TReference< Real_t >	static
InitializeIdentity(TMatrixT< Real_t > &A)	TMVA::DNN::TReference< Real_t >	static
InitializeUniform(TMatrixT< Real_t > &A)	TMVA::DNN::TReference< Real_t >	static
InitializeZero(TMatrixT< Real_t > &A)	TMVA::DNN::TReference< Real_t >	static
L1Regularization(const TMatrixT< Real_t > &W)	TMVA::DNN::TReference< Real_t >	static
L2Regularization(const TMatrixT< Real_t > &W)	TMVA::DNN::TReference< Real_t >	static
Matrix_t typedef	TMVA::DNN::TReference< Real_t >
MeanSquaredError(const TMatrixT< Real_t > &Y, const TMatrixT< Real_t > &output)	TMVA::DNN::TReference< Real_t >	static
MeanSquaredErrorGradients(TMatrixT< Real_t > &dY, const TMatrixT< Real_t > &Y, const TMatrixT< Real_t > &output)	TMVA::DNN::TReference< Real_t >	static
MultiplyTranspose(TMatrixT< Scalar_t > &output, const TMatrixT< Scalar_t > &input, const TMatrixT< Scalar_t > &weights)	TMVA::DNN::TReference< Real_t >	static
Relu(TMatrixT< Real_t > &B)	TMVA::DNN::TReference< Real_t >	static
ReluDerivative(TMatrixT< Real_t > &B, const TMatrixT< Real_t > &A)	TMVA::DNN::TReference< Real_t >	inlinestatic
Scalar_t typedef	TMVA::DNN::TReference< Real_t >
ScaleAdd(TMatrixT< Scalar_t > &A, const TMatrixT< Scalar_t > &B, Scalar_t beta=1.0)	TMVA::DNN::TReference< Real_t >	static
Sigmoid(TMatrixT< Real_t > &B)	TMVA::DNN::TReference< Real_t >	static
Sigmoid(TMatrixT< Real_t > &YHat, const TMatrixT< Real_t > &)	TMVA::DNN::TReference< Real_t >	static
SigmoidDerivative(TMatrixT< Real_t > &B, const TMatrixT< Real_t > &A)	TMVA::DNN::TReference< Real_t >	inlinestatic
SoftSign(TMatrixT< Real_t > &B)	TMVA::DNN::TReference< Real_t >	inlinestatic
SoftSignDerivative(TMatrixT< Real_t > &B, const TMatrixT< Real_t > &A)	TMVA::DNN::TReference< Real_t >	inlinestatic
SymmetricRelu(TMatrixT< Real_t > &B)	TMVA::DNN::TReference< Real_t >	inlinestatic
SymmetricReluDerivative(TMatrixT< Real_t > &B, const TMatrixT< Real_t > &A)	TMVA::DNN::TReference< Real_t >	inlinestatic
Tanh(TMatrixT< Real_t > &B)	TMVA::DNN::TReference< Real_t >	inlinestatic
TanhDerivative(TMatrixT< Real_t > &B, const TMatrixT< Real_t > &A)	TMVA::DNN::TReference< Real_t >	inlinestatic