// Ceres Solver - A fast non-linear least squares minimizer
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// 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_partitioned_matrix_view_specializations.py.
// Editing it manually is not recommended.

#include "ceres/linear_solver.h"
#include "ceres/partitioned_matrix_view.h"
#include "ceres/internal/eigen.h"

namespace ceres {
namespace internal {

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 new 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 new 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 new PartitionedMatrixView<2, 2, 4>(
                 matrix, options.elimination_groups[0]);
  }
  if ((options.row_block_size == 2) &&
      (options.e_block_size == 2) &&
      (options.f_block_size == Eigen::Dynamic)) {
    return new 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 new 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 new 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 new 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 new PartitionedMatrixView<2, 3, 9>(
                 matrix, options.elimination_groups[0]);
  }
  if ((options.row_block_size == 2) &&
      (options.e_block_size == 3) &&
      (options.f_block_size == Eigen::Dynamic)) {
    return new 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 new 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 new PartitionedMatrixView<2, 4, 4>(
                 matrix, options.elimination_groups[0]);
  }
  if ((options.row_block_size == 2) &&
      (options.e_block_size == 4) &&
      (options.f_block_size == 8)) {
    return new 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 new PartitionedMatrixView<2, 4, 9>(
                 matrix, options.elimination_groups[0]);
  }
  if ((options.row_block_size == 2) &&
      (options.e_block_size == 4) &&
      (options.f_block_size == Eigen::Dynamic)) {
    return new PartitionedMatrixView<2, 4, Eigen::Dynamic>(
                 matrix, options.elimination_groups[0]);
  }
  if ((options.row_block_size == 2) &&
      (options.e_block_size == Eigen::Dynamic) &&
      (options.f_block_size == Eigen::Dynamic)) {
    return new PartitionedMatrixView<2, Eigen::Dynamic, Eigen::Dynamic>(
                 matrix, options.elimination_groups[0]);
  }
  if ((options.row_block_size == 4) &&
      (options.e_block_size == 4) &&
      (options.f_block_size == 2)) {
    return new 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 new 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 new PartitionedMatrixView<4, 4, 4>(
                 matrix, options.elimination_groups[0]);
  }
  if ((options.row_block_size == 4) &&
      (options.e_block_size == 4) &&
      (options.f_block_size == Eigen::Dynamic)) {
    return new PartitionedMatrixView<4, 4, Eigen::Dynamic>(
                 matrix, options.elimination_groups[0]);
  }
  if ((options.row_block_size == Eigen::Dynamic) &&
      (options.e_block_size == Eigen::Dynamic) &&
      (options.f_block_size == Eigen::Dynamic)) {
    return new PartitionedMatrixView<Eigen::Dynamic, Eigen::Dynamic, 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 new PartitionedMatrixView<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic>(
               matrix, options.elimination_groups[0]);
};

}  // namespace internal
}  // namespace ceres
