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Added support for tensor maps of rank 0.
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@ -52,6 +52,12 @@ template<typename PlainObjectType, int Options_> class TensorMap : public Tensor
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CoordAccess = true,
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};
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr) : m_data(dataPtr), m_dimensions() {
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// The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
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EIGEN_STATIC_ASSERT((0 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
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}
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#ifdef EIGEN_HAS_VARIADIC_TEMPLATES
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template<typename... IndexTypes> EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension, IndexTypes... otherDimensions) : m_data(dataPtr), m_dimensions(firstDimension, otherDimensions...) {
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@ -121,11 +127,18 @@ template<typename PlainObjectType, int Options_> class TensorMap : public Tensor
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}
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const Scalar& operator()() const
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{
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EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE)
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return m_data[0];
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}
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#ifdef EIGEN_HAS_VARIADIC_TEMPLATES
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template<typename... IndexTypes> EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const Scalar& operator()(Index firstIndex, IndexTypes... otherIndices) const
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{
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static_assert(sizeof...(otherIndices) + 1 == NumIndices, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor.");
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EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
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if (PlainObjectType::Options&RowMajor) {
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const Index index = m_dimensions.IndexOfRowMajor(array<Index, NumIndices>{{firstIndex, otherIndices...}});
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return m_data[index];
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@ -200,6 +213,13 @@ template<typename PlainObjectType, int Options_> class TensorMap : public Tensor
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}
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE Scalar& operator()()
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{
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EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE)
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return m_data[0];
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}
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#ifdef EIGEN_HAS_VARIADIC_TEMPLATES
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template<typename... IndexTypes> EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE Scalar& operator()(Index firstIndex, IndexTypes... otherIndices)
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