// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2014 Benoit Steiner <[email protected]> // Copyright (C) 2013 Christian Seiler <[email protected]> // // 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_H #define EIGEN_CXX11_TENSOR_TENSOR_H // IWYU pragma: private #include "./InternalHeaderCheck.h" namespace Eigen { /** \class Tensor * \ingroup CXX11_Tensor_Module * * \brief The tensor class. * * The %Tensor class is the work-horse for all \em dense tensors within Eigen. * * The %Tensor class encompasses only dynamic-size objects so far. * * The first two template parameters are required: * \tparam Scalar_ Numeric type, e.g. float, double, int or `std::complex<float>`. * User defined scalar types are supported as well (see \ref user_defined_scalars "here"). * \tparam NumIndices_ Number of indices (i.e. rank of the tensor) * * The remaining template parameters are optional -- in most cases you don't have to worry about them. * \tparam Options_ A combination of either \b #RowMajor or \b #ColMajor, and of either * \b #AutoAlign or \b #DontAlign. * The former controls \ref TopicStorageOrders "storage order", and defaults to column-major. The latter * controls alignment, which is required for vectorization. It defaults to aligning tensors. Note that tensors currently * do not support any operations that profit from vectorization. Support for such operations (i.e. adding two tensors * etc.) is planned. * * You can access elements of tensors using normal subscripting: * * \code * Eigen::Tensor<double, 4> t(10, 10, 10, 10); * t(0, 1, 2, 3) = 42.0; * \endcode * * This class can be extended with the help of the plugin mechanism described on the page * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_TENSOR_PLUGIN, * \c EIGEN_TENSORBASE_PLUGIN, and \c EIGEN_READONLY_TENSORBASE_PLUGIN. * * <i><b>Some notes:</b></i> * * <dl> * <dt><b>Relation to other parts of Eigen:</b></dt> * <dd>The midterm development goal for this class is to have a similar hierarchy as Eigen uses for matrices, so that * taking blocks or using tensors in expressions is easily possible, including an interface with the vector/matrix code * by providing .asMatrix() and .asVector() (or similar) methods for rank 2 and 1 tensors. However, currently, the * %Tensor class does not provide any of these features and is only available as a stand-alone class that just allows * for coefficient access. Also, when fixed-size tensors are implemented, the number of template arguments is likely to * change dramatically.</dd> * </dl> * * \ref TopicStorageOrders */ template <typename Scalar_, int NumIndices_, int Options_, typename IndexType_> class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexType_> > { … }; } // end namespace Eigen #endif // EIGEN_CXX11_TENSOR_TENSOR_H
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