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template <class ElemType>
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void GPUMatrix<ElemType>::SetGaussianRandomValue(RNGHandle& rngHandle, const ElemType mean, const ElemType stdev)
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{
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}
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template <class ElemType>
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void GPUMatrix<ElemType>::SetGumbelRandomValue(RNGHandle& rngHandle, const ElemType loc, const ElemType scale)
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{
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}
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template <class ElemType>
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void GPUMatrix<ElemType>::SetGaussianRandomValue(const ElemType mean, const ElemType sigma, unsigned long seed)
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{
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}
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template <class ElemType>
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void GPUMatrix<ElemType>::SetTruncatedNormalRandomValue(const ElemType mean, const ElemType sigma, unsigned long seed)
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{
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}
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//maskRate: percentage of values masked out (similar to dropout rate)
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//scaleValue: which scale value to set to the left ones (unmasked items).
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template <class ElemType>
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void GPUMatrix<ElemType>::SetUniformRandomMask(const ElemType maskRate, const ElemType scaleValue, RNGHandle& seed)
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{
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}
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template <class ElemType>
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ElemType GPUMatrix<ElemType>::Adagrad(GPUMatrix<ElemType>& gradients, const bool needAveMultiplier)
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{
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return 0;
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}
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template <class ElemType>
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void GPUMatrix<ElemType>::FSAdagrad(GPUMatrix<ElemType>& gradients, GPUMatrix<ElemType>& functionValues, ElemType learnRatePerSample, ElemType momentum, ElemType adaWeight, ElemType adaMul, ElemType unitGainFactor)
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{
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}
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template <class ElemType>
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void GPUMatrix<ElemType>::Adam(GPUMatrix<ElemType>& gradients, GPUMatrix<ElemType>& functionValues, ElemType learnRatePerSample,
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ElemType momentum, ElemType adaWeight, ElemType adaMul, ElemType epsilon, ElemType unitGainFactor, bool adamax)
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{
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}
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template <class ElemType>
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ElemType GPUMatrix<ElemType>::RmsProp(GPUMatrix<ElemType>& gradients, ElemType RMS_GAMMA, ElemType RMS_WGT_INC, ElemType RMS_WGT_MAX, ElemType RMS_WGT_DEC, ElemType RMS_WGT_MIN, const bool needAveMultiplier, const bool initialized)
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{
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return 0;
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}
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template <class ElemType>
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template <class GradType>
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void GPUMatrix<ElemType>::AdaDelta(GPUMatrix<GradType>& gradients, GPUMatrix<ElemType>& functionValues, ElemType learningRate, ElemType rho, ElemType epsilon)
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{
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}
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template <class ElemType>
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void GPUMatrix<ElemType>::AdaDeltaFlushTimestamps(size_t cols, ElemType rho, int* timestamps, int currentTimestamp)
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{
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}
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template <class ElemType>
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void GPUMatrix<ElemType>::Reshape(const size_t numRows, const size_t numCols)
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{
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}
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template <class ElemType>
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void GPUMatrix<ElemType>::RequireSize(const size_t numRows, const size_t numCols, bool growOnly)
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{
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}
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template <class ElemType>
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void GPUMatrix<ElemType>::Resize(const size_t numRows, const size_t numCols, bool growOnly)
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{
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}
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template <class ElemType>
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size_t GPUMatrix<ElemType>::LocateElement(const size_t row, const size_t col) const
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{
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return 0;
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}
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template <class ElemType>
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std::unique_ptr<GPUMatrix<ElemType>> GPUMatrix<ElemType>::GetOrCreateWorkspace() const
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{
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return NULL;
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}
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template <class ElemType>
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void GPUMatrix<ElemType>::ReleaseWorkspace(std::unique_ptr<GPUMatrix<ElemType>> src) const
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{
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}
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template <class ElemType>
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size_t GPUMatrix<ElemType>::LocateColumn(const size_t col) const
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{
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return 0;
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}
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