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Marked the tensor constructors as EIGEN_DEVICE_FUNC: This makes it possible to call them from a CUDA kernel.

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Benoit Steiner 2015-12-14 15:12:55 -08:00
parent 140f3a02a8
commit 75e19fc7ca
1 changed files with 7 additions and 7 deletions
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14
unsupported/Eigen/CXX11/src/Tensor/Tensor.h
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@ -340,34 +340,34 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
#ifdef EIGEN_HAS_VARIADIC_TEMPLATES #ifdef EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes> template<typename... IndexTypes>
inline Tensor(Index firstDimension, IndexTypes... otherDimensions) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor(Index firstDimension, IndexTypes... otherDimensions)
: m_storage(internal::array_prod(array<Index, NumIndices>{{firstDimension, otherDimensions...}}), array<Index, NumIndices>{{firstDimension, otherDimensions...}}) : m_storage(internal::array_prod(array<Index, NumIndices>{{firstDimension, otherDimensions...}}), array<Index, NumIndices>{{firstDimension, otherDimensions...}})
{ {
// The number of dimensions used to construct a tensor must be equal to the rank of the tensor. // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
EIGEN_STATIC_ASSERT(sizeof...(otherDimensions) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE) EIGEN_STATIC_ASSERT(sizeof...(otherDimensions) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
} }
#else #else
inline explicit Tensor(Index dim1) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Tensor(Index dim1)
: m_storage(dim1, array<Index, 1>(dim1)) : m_storage(dim1, array<Index, 1>(dim1))
{ {
EIGEN_STATIC_ASSERT(1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE) EIGEN_STATIC_ASSERT(1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
} }
inline explicit Tensor(Index dim1, Index dim2) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Tensor(Index dim1, Index dim2)
: m_storage(dim1*dim2, array<Index, 2>(dim1, dim2)) : m_storage(dim1*dim2, array<Index, 2>(dim1, dim2))
{ {
EIGEN_STATIC_ASSERT(2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE) EIGEN_STATIC_ASSERT(2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
} }
inline explicit Tensor(Index dim1, Index dim2, Index dim3) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Tensor(Index dim1, Index dim2, Index dim3)
: m_storage(dim1*dim2*dim3, array<Index, 3>(dim1, dim2, dim3)) : m_storage(dim1*dim2*dim3, array<Index, 3>(dim1, dim2, dim3))
{ {
EIGEN_STATIC_ASSERT(3 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE) EIGEN_STATIC_ASSERT(3 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
} }
inline explicit Tensor(Index dim1, Index dim2, Index dim3, Index dim4) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Tensor(Index dim1, Index dim2, Index dim3, Index dim4)
: m_storage(dim1*dim2*dim3*dim4, array<Index, 4>(dim1, dim2, dim3, dim4)) : m_storage(dim1*dim2*dim3*dim4, array<Index, 4>(dim1, dim2, dim3, dim4))
{ {
EIGEN_STATIC_ASSERT(4 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE) EIGEN_STATIC_ASSERT(4 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
} }
inline explicit Tensor(Index dim1, Index dim2, Index dim3, Index dim4, Index dim5) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Tensor(Index dim1, Index dim2, Index dim3, Index dim4, Index dim5)
: m_storage(dim1*dim2*dim3*dim4*dim5, array<Index, 5>(dim1, dim2, dim3, dim4, dim5)) : m_storage(dim1*dim2*dim3*dim4*dim5, array<Index, 5>(dim1, dim2, dim3, dim4, dim5))
{ {
EIGEN_STATIC_ASSERT(5 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE) EIGEN_STATIC_ASSERT(5 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
@ -375,7 +375,7 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
#endif #endif
/** Normal Dimension */ /** Normal Dimension */
inline explicit Tensor(const array<Index, NumIndices>& dimensions) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Tensor(const array<Index, NumIndices>& dimensions)
: m_storage(internal::array_prod(dimensions), dimensions) : m_storage(internal::array_prod(dimensions), dimensions)
{ {
EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED