diff options
-rw-r--r-- | unsupported/Eigen/CXX11/Tensor | 1 | ||||
-rw-r--r-- | unsupported/Eigen/CXX11/src/Tensor/TensorBase.h | 7 | ||||
-rw-r--r-- | unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h | 1 | ||||
-rw-r--r-- | unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h | 29 | ||||
-rw-r--r-- | unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h | 181 | ||||
-rw-r--r-- | unsupported/test/CMakeLists.txt | 1 | ||||
-rw-r--r-- | unsupported/test/cxx11_tensor_generator.cpp | 87 |
7 files changed, 307 insertions, 0 deletions
diff --git a/unsupported/Eigen/CXX11/Tensor b/unsupported/Eigen/CXX11/Tensor index ed64712e5..520da66bb 100644 --- a/unsupported/Eigen/CXX11/Tensor +++ b/unsupported/Eigen/CXX11/Tensor @@ -79,6 +79,7 @@ #include "unsupported/Eigen/CXX11/src/Tensor/TensorStriding.h" #include "unsupported/Eigen/CXX11/src/Tensor/TensorEvalTo.h" #include "unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h" +#include "unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h" #include "unsupported/Eigen/CXX11/src/Tensor/TensorAssign.h" #include "unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h" diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h b/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h index d44060258..c7cfbfce0 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h @@ -57,6 +57,13 @@ class TensorBase<Derived, ReadOnlyAccessors> return nullaryExpr(gen); } + // Tensor generation + template <typename Generator> EIGEN_DEVICE_FUNC + EIGEN_STRONG_INLINE const TensorGeneratorOp<Generator, const Derived> + generate(const Generator& generator) const { + return TensorGeneratorOp<Generator, const Derived>(derived(), generator); + } + // Generic unary operation support. template <typename CustomUnaryOp> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<CustomUnaryOp, const Derived> diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h b/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h index 1441943c3..a4224c372 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h @@ -38,6 +38,7 @@ template<typename ReverseDimensions, typename XprType> class TensorReverseOp; template<typename PaddingDimensions, typename XprType> class TensorPaddingOp; template<typename Shuffle, typename XprType> class TensorShufflingOp; template<typename Strides, typename XprType> class TensorStridingOp; +template<typename Generator, typename XprType> class TensorGeneratorOp; template<typename LeftXprType, typename RightXprType> class TensorAssignOp; template<typename XprType> class TensorEvalToOp; diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h b/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h index b5adb4041..450b1df40 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h @@ -496,6 +496,35 @@ template <typename T> class NormalRandomGenerator { #endif +template <typename T, typename Index, size_t NumDims> +class GaussianGenerator { + public: + static const bool PacketAccess = false; + + EIGEN_DEVICE_FUNC GaussianGenerator(const array<T, NumDims>& means, + const array<T, NumDims>& std_devs) + : m_means(means) + { + for (int i = 0; i < NumDims; ++i) { + m_two_sigmas[i] = std_devs[i] * std_devs[i] * 2; + } + } + + T operator()(const array<Index, NumDims>& coordinates) const { + T tmp = T(0); + for (int i = 0; i < NumDims; ++i) { + T offset = coordinates[i] - m_means[i]; + tmp += offset * offset / m_two_sigmas[i]; + } + return std::exp(-tmp); + } + + private: + array<T, NumDims> m_means; + array<T, NumDims> m_two_sigmas; +}; + + } // end namespace internal } // end namespace Eigen diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h b/unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h new file mode 100644 index 000000000..3a181d6c3 --- /dev/null +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h @@ -0,0 +1,181 @@ +// 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 (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 (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 diff --git a/unsupported/test/CMakeLists.txt b/unsupported/test/CMakeLists.txt index f952af752..f438d4107 100644 --- a/unsupported/test/CMakeLists.txt +++ b/unsupported/test/CMakeLists.txt @@ -135,6 +135,7 @@ if(EIGEN_TEST_CXX11) ei_add_test(cxx11_tensor_reverse "-std=c++0x") ei_add_test(cxx11_tensor_layout_swap "-std=c++0x") ei_add_test(cxx11_tensor_io "-std=c++0x") + ei_add_test(cxx11_tensor_generator "-std=c++0x") # These tests needs nvcc # ei_add_test(cxx11_tensor_device "-std=c++0x") diff --git a/unsupported/test/cxx11_tensor_generator.cpp b/unsupported/test/cxx11_tensor_generator.cpp new file mode 100644 index 000000000..8ca52c7a5 --- /dev/null +++ b/unsupported/test/cxx11_tensor_generator.cpp @@ -0,0 +1,87 @@ +// 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/. + +#include "main.h" + +#include <Eigen/CXX11/Tensor> + +struct Generator1D { + Generator1D() { } + + float operator()(const array<Eigen::DenseIndex, 1>& coordinates) const { + return coordinates[0]; + } +}; + +template <int DataLayout> +static void test_1D() +{ + Tensor<float, 1> vec(6); + Tensor<float, 1> result = vec.generate(Generator1D()); + + for (int i = 0; i < 6; ++i) { + VERIFY_IS_EQUAL(result(i), i); + } +} + + +struct Generator2D { + Generator2D() { } + + float operator()(const array<Eigen::DenseIndex, 2>& coordinates) const { + return 3 * coordinates[0] + 11 * coordinates[1]; + } +}; + +template <int DataLayout> +static void test_2D() +{ + Tensor<float, 2> matrix(5, 7); + Tensor<float, 2> result = matrix.generate(Generator2D()); + + for (int i = 0; i < 5; ++i) { + for (int j = 0; j < 5; ++j) { + VERIFY_IS_EQUAL(result(i, j), 3*i + 11*j); + } + } +} + + +template <int DataLayout> +static void test_gaussian() +{ + int rows = 32; + int cols = 48; + array<float, 2> means = { rows / 2.0f, cols / 2.0f }; + array<float, 2> std_devs = { 3.14f, 2.7f }; + internal::GaussianGenerator<float, Eigen::DenseIndex, 2> gaussian_gen(means, std_devs); + + Tensor<float, 2> matrix(rows, cols); + Tensor<float, 2> result = matrix.generate(gaussian_gen); + + for (int i = 0; i < rows; ++i) { + for (int j = 0; j < cols; ++j) { + float g_rows = powf(rows/2.0f - i, 2) / (3.14f * 3.14f) * 0.5f; + float g_cols = powf(cols/2.0f - j, 2) / (2.7f * 2.7f) * 0.5f; + float gaussian = expf(-g_rows - g_cols); + VERIFY_IS_EQUAL(result(i, j), gaussian); + } + } +} + + +void test_cxx11_tensor_generator() +{ + CALL_SUBTEST(test_1D<ColMajor>()); + CALL_SUBTEST(test_1D<RowMajor>()); + CALL_SUBTEST(test_2D<ColMajor>()); + CALL_SUBTEST(test_2D<RowMajor>()); + CALL_SUBTEST(test_gaussian<ColMajor>()); + CALL_SUBTEST(test_gaussian<RowMajor>()); +} |