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Added support for fixed sized tensors.

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Improved support for tensor expressions.
This commit is contained in:
Benoit Steiner
2014-05-06 11:18:37 -07:00
parent c0f2cb016e
commit 0320f7e3a7
18 changed files with 1319 additions and 82 deletions
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31
unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
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@@ -43,24 +43,38 @@ template<typename PlainObjectType> class TensorMap : public TensorBase<TensorMap
typedef Scalar* PointerType;
typedef PointerType PointerArgType;
// Fixed size plain object type only
/* EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr) : m_data(dataPtr) {
// The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
//EIGEN_STATIC_ASSERT(1 == PlainObjectType::NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
// todo: add assert to ensure we don't screw up here.
}*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension) : m_data(dataPtr), m_dimensions({{firstDimension}}) {
EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension) : m_data(dataPtr), m_dimensions(array<DenseIndex, PlainObjectType::NumIndices>({{firstDimension}})) {
// The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
EIGEN_STATIC_ASSERT(1 == PlainObjectType::NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
}
#ifdef EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes> EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension, IndexTypes... otherDimensions) : m_data(dataPtr), m_dimensions({{firstDimension, otherDimensions...}}) {
EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension, IndexTypes... otherDimensions) : m_data(dataPtr), m_dimensions(array<DenseIndex, PlainObjectType::NumIndices>({{firstDimension, otherDimensions...}})) {
// The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
EIGEN_STATIC_ASSERT(sizeof...(otherDimensions) + 1 == PlainObjectType::NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
}
#endif
inline TensorMap(PointerArgType dataPtr, const array<Index, PlainObjectType::NumIndices>& dimensions)
: m_data(dataPtr), m_dimensions(dimensions)
{ }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index dimension(Index n) const { return m_dimensions[n]; }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index size() const { return internal::array_prod(m_dimensions); }
EIGEN_STRONG_INLINE const typename PlainObjectType::Dimensions& dimensions() const { return m_dimensions; }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index size() const { return m_dimensions.TotalSize(); }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar* data() { return m_data; }
EIGEN_DEVICE_FUNC
@@ -78,8 +92,13 @@ template<typename PlainObjectType> class TensorMap : public TensorBase<TensorMap
EIGEN_STRONG_INLINE Scalar& operator()(Index firstIndex, IndexTypes... otherIndices)
{
static_assert(sizeof...(otherIndices) + 1 == PlainObjectType::NumIndices, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor.");
const Index index = internal::tensor_index_linearization_helper<Index, PlainObjectType::NumIndices, PlainObjectType::NumIndices - 1, PlainObjectType::Options&RowMajor>::run(array<Index, PlainObjectType::NumIndices>{{firstIndex, otherIndices...}}, m_dimensions);
return m_data[index];
if (PlainObjectType::Options&RowMajor) {
const Index index = m_dimensions.IndexOfRowMajor(array<Index, PlainObjectType::NumIndices>{{firstIndex, otherIndices...}});
return m_data[index];
} else {
const Index index = m_dimensions.IndexOfColMajor(array<Index, PlainObjectType::NumIndices>{{firstIndex, otherIndices...}});
return m_data[index];
}
}
#endif
@@ -93,7 +112,7 @@ template<typename PlainObjectType> class TensorMap : public TensorBase<TensorMap
private:
typename PlainObjectType::Scalar* m_data;
array<DenseIndex, PlainObjectType::NumIndices> m_dimensions;
typename PlainObjectType::Dimensions m_dimensions;
};
} // end namespace Eigen