From eeb43f9e2b7ac56af685d8fc494685df8227a53f Mon Sep 17 00:00:00 2001 From: Benoit Steiner Date: Thu, 14 Aug 2014 00:22:47 -0700 Subject: Added support for padding, stridding, and shuffling --- unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h | 163 +++++++++++++++++++++ 1 file changed, 163 insertions(+) create mode 100644 unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h (limited to 'unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h') diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h b/unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h new file mode 100644 index 000000000..45558d7dd --- /dev/null +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h @@ -0,0 +1,163 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2014 Benoit Steiner +// +// 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_PADDING_H +#define EIGEN_CXX11_TENSOR_TENSOR_PADDING_H + +namespace Eigen { + +/** \class TensorPadding + * \ingroup CXX11_Tensor_Module + * + * \brief Tensor padding class. + * At the moment only 0-padding is supported. + * + */ +namespace internal { +template +struct traits > : public traits +{ + typedef typename XprType::Scalar Scalar; + typedef typename internal::packet_traits::type Packet; + typedef typename traits::StorageKind StorageKind; + typedef typename traits::Index Index; + typedef typename XprType::Nested Nested; + typedef typename remove_reference::type _Nested; +}; + +template +struct eval, Eigen::Dense> +{ + typedef const TensorPaddingOp& type; +}; + +template +struct nested, 1, typename eval >::type> +{ + typedef TensorPaddingOp type; +}; + +} // end namespace internal + + + +template +class TensorPaddingOp : public TensorBase > +{ + public: + typedef typename Eigen::internal::traits::Scalar Scalar; + typedef typename Eigen::internal::traits::Packet Packet; + typedef typename Eigen::NumTraits::Real RealScalar; + typedef typename XprType::CoeffReturnType CoeffReturnType; + typedef typename XprType::PacketReturnType PacketReturnType; + typedef typename Eigen::internal::nested::type Nested; + typedef typename Eigen::internal::traits::StorageKind StorageKind; + typedef typename Eigen::internal::traits::Index Index; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorPaddingOp(const XprType& expr, const PaddingDimensions& padding_dims) + : m_xpr(expr), m_padding_dims(padding_dims) {} + + EIGEN_DEVICE_FUNC + const PaddingDimensions& padding() const { return m_padding_dims; } + + EIGEN_DEVICE_FUNC + const typename internal::remove_all::type& + expression() const { return m_xpr; } + + protected: + typename XprType::Nested m_xpr; + const PaddingDimensions m_padding_dims; +}; + + +// Eval as rvalue +template +struct TensorEvaluator, Device> +{ + typedef TensorPaddingOp XprType; + typedef typename XprType::Index Index; + static const int NumDims = internal::array_size::value; + typedef DSizes Dimensions; + + enum { + IsAligned = false, + PacketAccess = /*TensorEvaluator::PacketAccess*/false, + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device) + : m_impl(op.expression(), device), m_padding(op.padding()) + { + // Compute dimensions + m_dimensions = m_impl.dimensions(); + for (int i = 0; i < NumDims; ++i) { + m_dimensions[i] += m_padding[i].first + m_padding[i].second; + } + + const typename TensorEvaluator::Dimensions& input_dims = m_impl.dimensions(); + for (int i = 0; i < NumDims; ++i) { + if (i > 0) { + m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1]; + m_outputStrides[i] = m_outputStrides[i-1] * m_dimensions[i-1]; + } else { + m_inputStrides[0] = 1; + m_outputStrides[0] = 1; + } + } + } + + typedef typename XprType::Scalar Scalar; + 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*) { + m_impl.evalSubExprsIfNeeded(NULL); + return true; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() { + m_impl.cleanup(); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const + { + Index inputIndex = 0; + for (int i = NumDims - 1; i >= 0; --i) { + const Index idx = index / m_outputStrides[i]; + if (idx < m_padding[i].first || idx >= m_dimensions[i] - m_padding[i].second) { + return Scalar(0); + } + inputIndex += (idx - m_padding[i].first) * m_inputStrides[i]; + index -= idx * m_outputStrides[i]; + } + return m_impl.coeff(inputIndex); + } + + /* template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const + { + return m_impl.template packet(index); + }*/ + + Scalar* data() const { return NULL; } + + protected: + PaddingDimensions m_padding; + Dimensions m_dimensions; + array m_outputStrides; + array m_inputStrides; + TensorEvaluator m_impl; +}; + + + + +} // end namespace Eigen + +#endif // EIGEN_CXX11_TENSOR_TENSOR_PADDING_H -- cgit v1.2.3