diff options
author | Manjunath Kudlur <keveman@gmail.com> | 2015-11-06 16:27:58 -0800 |
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committer | Manjunath Kudlur <keveman@gmail.com> | 2015-11-06 16:27:58 -0800 |
commit | f41959ccb2d9d4c722fe8fc3351401d53bcf4900 (patch) | |
tree | ef0ca22cb2a5ac4bdec9d080d8e0788a53ed496d /third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h |
TensorFlow: Initial commit of TensorFlow library.
TensorFlow is an open source software library for numerical computation
using data flow graphs.
Base CL: 107276108
Diffstat (limited to 'third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h')
-rw-r--r-- | third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h | 185 |
1 files changed, 185 insertions, 0 deletions
diff --git a/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h b/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h new file mode 100644 index 0000000000..91a73669a4 --- /dev/null +++ b/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h @@ -0,0 +1,185 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com> +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_CXX11_TENSOR_TENSOR_GENERATOR_H +#define EIGEN_CXX11_TENSOR_TENSOR_GENERATOR_H + +namespace Eigen { + +/** \class TensorGenerator + * \ingroup CXX11_Tensor_Module + * + * \brief Tensor generator class. + * + * + */ +namespace internal { +template<typename Generator, typename XprType> +struct traits<TensorGeneratorOp<Generator, XprType> > : public traits<XprType> +{ + typedef typename XprType::Scalar Scalar; + typedef traits<XprType> XprTraits; + typedef typename packet_traits<Scalar>::type Packet; + typedef typename XprTraits::StorageKind StorageKind; + typedef typename XprTraits::Index Index; + typedef typename XprType::Nested Nested; + typedef typename remove_reference<Nested>::type _Nested; + static const int NumDimensions = XprTraits::NumDimensions; + static const int Layout = XprTraits::Layout; +}; + +template<typename Generator, typename XprType> +struct eval<TensorGeneratorOp<Generator, XprType>, Eigen::Dense> +{ + typedef const TensorGeneratorOp<Generator, XprType>& type; +}; + +template<typename Generator, typename XprType> +struct nested<TensorGeneratorOp<Generator, XprType>, 1, typename eval<TensorGeneratorOp<Generator, XprType> >::type> +{ + typedef TensorGeneratorOp<Generator, XprType> type; +}; + +} // end namespace internal + + + +template<typename Generator, typename XprType> +class TensorGeneratorOp : public TensorBase<TensorGeneratorOp<Generator, XprType>, ReadOnlyAccessors> +{ + public: + typedef typename Eigen::internal::traits<TensorGeneratorOp>::Scalar Scalar; + typedef typename Eigen::internal::traits<TensorGeneratorOp>::Packet Packet; + typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; + typedef typename XprType::CoeffReturnType CoeffReturnType; + typedef typename XprType::PacketReturnType PacketReturnType; + typedef typename Eigen::internal::nested<TensorGeneratorOp>::type Nested; + typedef typename Eigen::internal::traits<TensorGeneratorOp>::StorageKind StorageKind; + typedef typename Eigen::internal::traits<TensorGeneratorOp>::Index Index; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorGeneratorOp(const XprType& expr, const Generator& generator) + : m_xpr(expr), m_generator(generator) {} + + EIGEN_DEVICE_FUNC + const Generator& generator() const { return m_generator; } + + EIGEN_DEVICE_FUNC + const typename internal::remove_all<typename XprType::Nested>::type& + expression() const { return m_xpr; } + + protected: + typename XprType::Nested m_xpr; + const Generator m_generator; +}; + + +// Eval as rvalue +template<typename Generator, typename ArgType, typename Device> +struct TensorEvaluator<const TensorGeneratorOp<Generator, ArgType>, Device> +{ + typedef TensorGeneratorOp<Generator, ArgType> XprType; + typedef typename XprType::Index Index; + typedef typename TensorEvaluator<ArgType, Device>::Dimensions Dimensions; + static const int NumDims = internal::array_size<Dimensions>::value; + typedef typename XprType::Scalar Scalar; + + enum { + IsAligned = false, + PacketAccess = (internal::packet_traits<Scalar>::size > 1), + BlockAccess = false, + Layout = TensorEvaluator<ArgType, Device>::Layout, + CoordAccess = false, // to be implemented + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device) + : m_generator(op.generator()) + { + TensorEvaluator<ArgType, Device> impl(op.expression(), device); + m_dimensions = impl.dimensions(); + + if (NumDims > 0) { + if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { + m_strides[0] = 1; + for (int i = 1; i < NumDims; ++i) { + m_strides[i] = m_strides[i - 1] * m_dimensions[i - 1]; + } + } else { + m_strides[NumDims - 1] = 1; + for (int i = NumDims - 2; i >= 0; --i) { + m_strides[i] = m_strides[i + 1] * m_dimensions[i + 1]; + } + } + } + } + + typedef typename XprType::CoeffReturnType CoeffReturnType; + typedef typename XprType::PacketReturnType PacketReturnType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) { + return true; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() { + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const + { + array<Index, NumDims> coords; + extract_coordinates(index, coords); + return m_generator(coords); + } + + template<int LoadMode> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const + { + const int packetSize = internal::unpacket_traits<PacketReturnType>::size; + EIGEN_STATIC_ASSERT(packetSize > 1, YOU_MADE_A_PROGRAMMING_MISTAKE) + eigen_assert(index+packetSize-1 < dimensions().TotalSize()); + + EIGEN_ALIGN_DEFAULT typename internal::remove_const<CoeffReturnType>::type values[packetSize]; + for (int i = 0; i < packetSize; ++i) { + values[i] = coeff(index+i); + } + PacketReturnType rslt = internal::pload<PacketReturnType>(values); + return rslt; + } + + EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; } + + protected: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE + void extract_coordinates(Index index, array<Index, NumDims>& coords) const { + if (NumDims > 0) { + if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { + for (int i = NumDims - 1; i > 0; --i) { + const Index idx = index / m_strides[i]; + index -= idx * m_strides[i]; + coords[i] = idx; + } + coords[0] = index; + } else { + for (int i = 0; i < NumDims - 1; ++i) { + const Index idx = index / m_strides[i]; + index -= idx * m_strides[i]; + coords[i] = idx; + } + coords[NumDims-1] = index; + } + } + } + + Dimensions m_dimensions; + array<Index, NumDims> m_strides; + Generator m_generator; +}; + +} // end namespace Eigen + +#endif // EIGEN_CXX11_TENSOR_TENSOR_GENERATOR_H |