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68 lines
2.5 KiB
C++
68 lines
2.5 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#ifndef EIGEN_CXX11_TENSOR_TENSOR_DEVICE_H
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#define EIGEN_CXX11_TENSOR_TENSOR_DEVICE_H
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namespace Eigen {
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/** \class TensorDevice
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* \ingroup CXX11_Tensor_Module
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*
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* \brief Pseudo expression providing an operator = that will evaluate its argument
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* on the specified computing 'device' (GPU, thread pool, ...)
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*
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* Example:
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* C.device(EIGEN_GPU) = A + B;
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*
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* Todo: operator *= and /=.
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*/
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template <typename ExpressionType, typename DeviceType> class TensorDevice {
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public:
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TensorDevice(const DeviceType& device, ExpressionType& expression) : m_device(device), m_expression(expression) {}
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE TensorDevice& operator=(const OtherDerived& other) {
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typedef TensorAssignOp<ExpressionType, const OtherDerived> Assign;
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Assign assign(m_expression, other);
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internal::TensorExecutor<const Assign, DeviceType>::run(assign, m_device);
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return *this;
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}
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE TensorDevice& operator+=(const OtherDerived& other) {
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typedef typename OtherDerived::Scalar Scalar;
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typedef TensorCwiseBinaryOp<internal::scalar_sum_op<Scalar>, const ExpressionType, const OtherDerived> Sum;
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Sum sum(m_expression, other);
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typedef TensorAssignOp<ExpressionType, const Sum> Assign;
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Assign assign(m_expression, sum);
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internal::TensorExecutor<const Assign, DeviceType>::run(assign, m_device);
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return *this;
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}
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE TensorDevice& operator-=(const OtherDerived& other) {
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typedef typename OtherDerived::Scalar Scalar;
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typedef TensorCwiseBinaryOp<internal::scalar_difference_op<Scalar>, const ExpressionType, const OtherDerived> Difference;
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Difference difference(m_expression, other);
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typedef TensorAssignOp<ExpressionType, const Difference> Assign;
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Assign assign(m_expression, difference);
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internal::TensorExecutor<const Assign, DeviceType>::run(assign, m_device);
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return *this;
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}
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protected:
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const DeviceType& m_device;
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ExpressionType& m_expression;
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};
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} // end namespace Eigen
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#endif // EIGEN_CXX11_TENSOR_TENSOR_DEVICE_H
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