| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2017 Google Inc. All rights reserved. |
| // http://ceres-solver.org/ |
| // |
| // Redistribution and use in source and binary forms, with or without |
| // modification, are permitted provided that the following conditions are met: |
| // |
| // * Redistributions of source code must retain the above copyright notice, |
| // this list of conditions and the following disclaimer. |
| // * Redistributions in binary form must reproduce the above copyright notice, |
| // this list of conditions and the following disclaimer in the documentation |
| // and/or other materials provided with the distribution. |
| // * Neither the name of Google Inc. nor the names of its contributors may be |
| // used to endorse or promote products derived from this software without |
| // specific prior written permission. |
| // |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" |
| // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE |
| // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE |
| // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE |
| // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR |
| // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF |
| // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS |
| // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN |
| // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) |
| // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE |
| // POSSIBILITY OF SUCH DAMAGE. |
| // |
| // Author: sameeragarwal@google.com (Sameer Agarwal) |
| // |
| // Template specialization of PartitionedMatrixView. |
| // |
| // ======================================== |
| // THIS FILE IS AUTOGENERATED. DO NOT EDIT. |
| // THIS FILE IS AUTOGENERATED. DO NOT EDIT. |
| // THIS FILE IS AUTOGENERATED. DO NOT EDIT. |
| // THIS FILE IS AUTOGENERATED. DO NOT EDIT. |
| //========================================= |
| // |
| // This file is generated using generate_template_specializations.py. |
| |
| #include <memory> |
| |
| #include "ceres/linear_solver.h" |
| #include "ceres/partitioned_matrix_view.h" |
| |
| namespace ceres::internal { |
| |
| PartitionedMatrixViewBase::~PartitionedMatrixViewBase() = default; |
| |
| std::unique_ptr<PartitionedMatrixViewBase> PartitionedMatrixViewBase::Create( |
| const LinearSolver::Options& options, const BlockSparseMatrix& matrix) { |
| #ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 2) && |
| (options.f_block_size == 2)) { |
| return std::make_unique<PartitionedMatrixView<2,2, 2>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 2) && |
| (options.f_block_size == 3)) { |
| return std::make_unique<PartitionedMatrixView<2,2, 3>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 2) && |
| (options.f_block_size == 4)) { |
| return std::make_unique<PartitionedMatrixView<2,2, 4>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 2)) { |
| return std::make_unique<PartitionedMatrixView<2,2, Eigen::Dynamic>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 3) && |
| (options.f_block_size == 3)) { |
| return std::make_unique<PartitionedMatrixView<2,3, 3>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 3) && |
| (options.f_block_size == 4)) { |
| return std::make_unique<PartitionedMatrixView<2,3, 4>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 3) && |
| (options.f_block_size == 6)) { |
| return std::make_unique<PartitionedMatrixView<2,3, 6>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 3) && |
| (options.f_block_size == 9)) { |
| return std::make_unique<PartitionedMatrixView<2,3, 9>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 3)) { |
| return std::make_unique<PartitionedMatrixView<2,3, Eigen::Dynamic>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 4) && |
| (options.f_block_size == 3)) { |
| return std::make_unique<PartitionedMatrixView<2,4, 3>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 4) && |
| (options.f_block_size == 4)) { |
| return std::make_unique<PartitionedMatrixView<2,4, 4>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 4) && |
| (options.f_block_size == 6)) { |
| return std::make_unique<PartitionedMatrixView<2,4, 6>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 4) && |
| (options.f_block_size == 8)) { |
| return std::make_unique<PartitionedMatrixView<2,4, 8>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 4) && |
| (options.f_block_size == 9)) { |
| return std::make_unique<PartitionedMatrixView<2,4, 9>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 2) && |
| (options.e_block_size == 4)) { |
| return std::make_unique<PartitionedMatrixView<2,4, Eigen::Dynamic>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if (options.row_block_size == 2) { |
| return std::make_unique<PartitionedMatrixView<2,Eigen::Dynamic, Eigen::Dynamic>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 3) && |
| (options.e_block_size == 3) && |
| (options.f_block_size == 3)) { |
| return std::make_unique<PartitionedMatrixView<3,3, 3>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 4) && |
| (options.e_block_size == 4) && |
| (options.f_block_size == 2)) { |
| return std::make_unique<PartitionedMatrixView<4,4, 2>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 4) && |
| (options.e_block_size == 4) && |
| (options.f_block_size == 3)) { |
| return std::make_unique<PartitionedMatrixView<4,4, 3>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 4) && |
| (options.e_block_size == 4) && |
| (options.f_block_size == 4)) { |
| return std::make_unique<PartitionedMatrixView<4,4, 4>>( |
| matrix, options.elimination_groups[0]); |
| } |
| if ((options.row_block_size == 4) && |
| (options.e_block_size == 4)) { |
| return std::make_unique<PartitionedMatrixView<4,4, Eigen::Dynamic>>( |
| matrix, options.elimination_groups[0]); |
| } |
| |
| #endif |
| VLOG(1) << "Template specializations not found for <" |
| << options.row_block_size << "," << options.e_block_size << "," |
| << options.f_block_size << ">"; |
| return std::make_unique<PartitionedMatrixView<Eigen::Dynamic, |
| Eigen::Dynamic, |
| Eigen::Dynamic>>( |
| matrix, options.elimination_groups[0]); |
| }; |
| |
| } // namespace ceres::internal |
