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void GPUMatrix<ElemType>::Clear()
{
}
#pragma endregion Constructors and Destructor
#pragma region Basic Operators
template <class ElemType>
GPUMatrix<ElemType> GPUMatrix<ElemType>::ColumnSlice(size_t startColumn, size_t numCols) const
{
GPUMatrix<ElemType> slice(0);
return slice;
}
template <class ElemType>
GPUMatrix<ElemType>& GPUMatrix<ElemType>::AssignColumnSlice(const GPUMatrix<ElemType>& fromMatrix, size_t startColumn, size_t numCols)
{
return *this;
}
template <class ElemType>
GPUMatrix<ElemType>& GPUMatrix<ElemType>::SetColumnSlice(const GPUMatrix<ElemType>& fromMatrix, size_t startColumn, size_t numCols)
{
return *this;
}
template <class ElemType>
GPUMatrix<ElemType> GPUMatrix<ElemType>::Diagonal() const
{
GPUMatrix<ElemType> diag(0);
return diag;
}
//for each column of a, we assign numRows starting from startIndex to this
template <class ElemType>
GPUMatrix<ElemType>& GPUMatrix<ElemType>::AssignRowSliceValuesOf(const GPUMatrix<ElemType>& /*a*/, const size_t startIndex, const size_t numRows)
{
return *this;
}
//for each column of a, we assign all rows of a to this starting from startIndex
template <class ElemType>
GPUMatrix<ElemType>& GPUMatrix<ElemType>::AssignToRowSliceValuesOf(const GPUMatrix<ElemType>& a, const size_t startIndex, const size_t numRows)
{
return *this;
}
//for each column of a, we add all rows of a to this starting from startIndex
template <class ElemType>
GPUMatrix<ElemType>& GPUMatrix<ElemType>::AddToRowSliceValuesOf(const GPUMatrix<ElemType>& /*a*/, const size_t startIndex, const size_t numRows)
{
return *this;
}
template <class ElemType>
GPUMatrix<ElemType>& GPUMatrix<ElemType>::AddWithRowSliceValuesOf(const GPUMatrix<ElemType>& /*a*/, const size_t startIndex, const size_t numRows)
{
return *this;
}
//template<class ElemType> GPUMatrix<ElemType>& GPUMatrix<ElemType>::AssignRowStackValuesOf(const std::vector<const GPUMatrix<ElemType>*>& inputMatrices, const size_t sliceStartCol, const size_t sliceNumCols) { return *this; }
template <class ElemType>
GPUMatrix<ElemType>& GPUMatrix<ElemType>::AssignRepeatOf(const GPUMatrix<ElemType>& /*a*/, const size_t numRowRepeats, const size_t numColRepeats)
{
return *this;
}
template <class ElemType>
GPUMatrix<ElemType>& GPUMatrix<ElemType>::AddToRowRepeatValuesOf(const GPUMatrix<ElemType>& /*a*/, const size_t numRowRepeats)
{
return *this;
}
template <class ElemType>
GPUMatrix<ElemType>& GPUMatrix<ElemType>::AssignPositiveAndShiftedNegSample(const GPUMatrix<ElemType>& a, const size_t posNumber, const size_t negNumber, const size_t shiftNumber)
{
return *this;
}
template <class ElemType>
GPUMatrix<ElemType>& GPUMatrix<ElemType>::AddFoldedPositiveAndShiftedNegSample(const GPUMatrix<ElemType>& a, const size_t posNumber, const size_t negNumber, const size_t shiftNumber)
{
return *this;
}
template <class ElemType>
GPUMatrix<ElemType> GPUMatrix<ElemType>::Transpose() const
{
return *this;
}
// GetCublasHandle - get a cublas handle for the given GPU, should only need one per GPU
// computeDevice - The compute device for which the cublas handle is desired
// returns: cublas handle
// NOTE: we currently don't bother to ever free the CUBLAS handle, it will be freed automatically by CUDA when the process ends
template <class ElemType>
cublasHandle_t GPUMatrix<ElemType>::GetCublasHandle(int computeDevice /*=-1*/)
{
cublasHandle_t cuHandle = 0;
return cuHandle;
}
template <class ElemType>
GPUMatrix<ElemType>& GPUMatrix<ElemType>::AssignTransposeOf(const GPUMatrix<ElemType>& /*a*/)
{
return *this;