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Marked a few functions as EIGEN_DEVICE_FUNC to enable the use of tensors in cuda kernels.
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@@ -350,7 +350,7 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_> >
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}
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#endif
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void resize(const array<Index, NumIndices>& dimensions)
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EIGEN_DEVICE_FUNC void resize(const array<Index, NumIndices>& dimensions)
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{
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std::size_t i;
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Index size = Index(1);
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@@ -367,7 +367,7 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_> >
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#endif
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}
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void resize(const DSizes<Index, NumIndices>& dimensions) {
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EIGEN_DEVICE_FUNC void resize(const DSizes<Index, NumIndices>& dimensions) {
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array<Index, NumIndices> dims;
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for (std::size_t i = 0; i < NumIndices; ++i) {
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dims[i] = dimensions[i];
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@@ -275,7 +275,7 @@ struct DSizes : array<DenseIndex, NumDims> {
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}
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#endif
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DSizes& operator = (const array<DenseIndex, NumDims>& other) {
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EIGEN_DEVICE_FUNC DSizes& operator = (const array<DenseIndex, NumDims>& other) {
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*static_cast<Base*>(this) = other;
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return *this;
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}
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@@ -112,9 +112,9 @@ class TensorStorage<T, NumIndices_, Dynamic, Options_, typename internal::gen_nu
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void swap(Self_& other)
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{ std::swap(m_data,other.m_data); std::swap(m_dimensions,other.m_dimensions); }
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const DSizes<DenseIndex, NumIndices_>& dimensions() const {return m_dimensions;}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const DSizes<DenseIndex, NumIndices_>& dimensions() const {return m_dimensions;}
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void resize(DenseIndex size, const array<DenseIndex, NumIndices_>& nbDimensions)
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EIGEN_DEVICE_FUNC void resize(DenseIndex size, const array<DenseIndex, NumIndices_>& nbDimensions)
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{
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const DenseIndex currentSz = internal::array_prod(m_dimensions);
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if(size != currentSz)
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