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2.2M
template <class ElemType>
void GPUSparseMatrix<ElemType>::SetMatrixFromCSCFormat(const CPUSPARSE_INDEX_TYPE* h_CSCCol, const CPUSPARSE_INDEX_TYPE* h_Row, const ElemType* h_Val,
const size_t nz, const size_t numRows, const size_t numCols, const bool IsOnDevice /*= false*/, const DEVICEID_TYPE devId /*= -1*/, DataTransferer* transferer)
{
}
template <class ElemType>
void GPUSparseMatrix<ElemType>::SetMatrixFromSBCFormat(const size_t*, const ElemType*, const size_t, const size_t, const size_t)
{
}
// forward pass from feature to hidden layer
template <class ElemType>
void GPUSparseMatrix<ElemType>::MultiplyAndWeightedAdd(ElemType alpha, const GPUMatrix<ElemType>& lhs, const bool transposeA,
const GPUSparseMatrix<ElemType>& rhs, const bool transposeB, ElemType beta, GPUMatrix<ElemType>& c)
{
}
// backward pass from hidden layer to feature weight
template <class ElemType>
void GPUSparseMatrix<ElemType>::MultiplyAndAdd(ElemType alpha, const GPUMatrix<ElemType>& lhs, const bool transposeA,
const GPUSparseMatrix<ElemType>& rhs, const bool transposeB, GPUSparseMatrix<ElemType>& c)
{
}
template <class ElemType>
void GPUSparseMatrix<ElemType>::ColumnwiseScaleAndWeightedAdd(ElemType alpha, const GPUSparseMatrix<ElemType>& a, const GPUMatrix<ElemType>& v, ElemType beta, GPUMatrix<ElemType>& c)
{
}
// used for gradients udpate
template <class ElemType>
void GPUSparseMatrix<ElemType>::ScaleAndAdd(const ElemType alpha, const GPUSparseMatrix<ElemType>& lhs, GPUMatrix<ElemType>& rhs)
{
}
template <class ElemType>
GPUSparseMatrix<ElemType>& GPUSparseMatrix<ElemType>::InplaceTruncate(const ElemType threshold)
{
return *this;
}
// normal update for smoothed gradients c and current gradients (this)
template <class ElemType>
void GPUSparseMatrix<ElemType>::NormalGrad(GPUMatrix<ElemType>& c, const ElemType momentum, ElemType unitGainFactor)
{
}
template <class ElemType>
ElemType GPUSparseMatrix<ElemType>::Adagrad(GPUMatrix<ElemType>& c, const bool needAveMultiplier)
{
return 1;
}
template<class ElemType>
void GPUSparseMatrix<ElemType>::FSAdagrad(GPUMatrix<ElemType>&, GPUMatrix<ElemType>&, ElemType, ElemType, ElemType, ElemType, ElemType)
{
}
template<class ElemType>
void GPUSparseMatrix<ElemType>::Adam(GPUMatrix<ElemType>& c, GPUMatrix<ElemType>& functionValues, ElemType learnRatePerSample, ElemType momentum, ElemType adaWeight, ElemType adaMul, ElemType epsilon, ElemType unitGainFactor, bool adamax)
{
}
template<class ElemType>
ElemType GPUSparseMatrix<ElemType>::RmsProp(GPUMatrix<ElemType>&, ElemType, ElemType, ElemType, ElemType, ElemType, const bool, const bool)
{
return 1;
}
template<class ElemType>
template<class AccumType>
void GPUSparseMatrix<ElemType>::AdaDelta(GPUMatrix<AccumType>&c, GPUMatrix<AccumType>&functionValues, AccumType learningRate, AccumType rho, AccumType epsilon, int* timestamps, int currentTimestamp)
{
}
template <class ElemType>
void GPUSparseMatrix<ElemType>::MultiplyAndWeightedAdd(ElemType alpha, const GPUSparseMatrix<ElemType>& a, const bool transposeA,
const GPUMatrix<ElemType>& b, const bool transposeD, ElemType beta, GPUMatrix<ElemType>& c)
{
}
template <class ElemType>
void GPUSparseMatrix<ElemType>::Multiply(const GPUSparseMatrix<ElemType>& S, const GPUMatrix<ElemType>& D, GPUMatrix<ElemType>& C)
{
}
template <class ElemType>
void GPUSparseMatrix<ElemType>::Multiply(const GPUMatrix<ElemType>& D, const GPUSparseMatrix<ElemType>& S, GPUMatrix<ElemType>& C)
{
}
template <class ElemType>
size_t GPUSparseMatrix<ElemType>::ElemCountFromBufferSize(const size_t numRows, const size_t numCols, const MatrixFormat format, const size_t totalBufferSize) const
{
return 0;
}
template <class ElemType>
size_t GPUSparseMatrix<ElemType>::ElemCountFromBufferSize() const
{
return 0;
}