# Ceres Solver - A fast non-linear least squares minimizer
# Copyright 2013 Google Inc. All rights reserved.
# http://code.google.com/p/ceres-solver/
#
# 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)
#
# Script for explicitly generating template specialization of the
# PartitionedMatrixView class. Explicitly generating these
# instantiations in separate .cc files breaks the compilation into
# separate compilation unit rather than one large cc file.
#
# This script creates two sets of files.
#
# 1. partitioned_matrix_view_x_x_x.cc
# where the x indicates the template parameters and
#
# 2. partitioned_matrix_view.cc
#
# that contains a factory function for instantiating these classes
# based on runtime parameters.
#
# The list of tuples, specializations indicates the set of
# specializations that is generated.
# Set of template specializations to generate
SPECIALIZATIONS = [(2, 2, 2),
(2, 2, 3),
(2, 2, 4),
(2, 2, "Eigen::Dynamic"),
(2, 3, 3),
(2, 3, 4),
(2, 3, 9),
(2, 3, "Eigen::Dynamic"),
(2, 4, 3),
(2, 4, 4),
(2, 4, 8),
(2, 4, 9),
(2, 4, "Eigen::Dynamic"),
(2, "Eigen::Dynamic", "Eigen::Dynamic"),
(4, 4, 2),
(4, 4, 3),
(4, 4, 4),
(4, 4, "Eigen::Dynamic"),
("Eigen::Dynamic", "Eigen::Dynamic", "Eigen::Dynamic")]
HEADER = """// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2013 Google Inc. All rights reserved.
// http://code.google.com/p/ceres-solver/
//
// 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_partitioned_matrix_view_specializations.py.
// Editing it manually is not recommended.
"""
DYNAMIC_FILE = """
#include "ceres/partitioned_matrix_view_impl.h"
#include "ceres/internal/eigen.h"
namespace ceres {
namespace internal {
template class PartitionedMatrixView<%s, %s, %s>;
} // namespace internal
} // namespace ceres
"""
SPECIALIZATION_FILE = """
// This include must come before any #ifndef check on Ceres compile options.
#include "ceres/internal/port.h"
#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
#include "ceres/partitioned_matrix_view_impl.h"
#include "ceres/internal/eigen.h"
namespace ceres {
namespace internal {
template class PartitionedMatrixView<%s, %s, %s>;
} // namespace internal
} // namespace ceres
#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
"""
FACTORY_FILE_HEADER = """
#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
"""
FACTORY_CONDITIONAL = """ if ((options.row_block_size == %s) &&
(options.e_block_size == %s) &&
(options.f_block_size == %s)) {
return new PartitionedMatrixView<%s, %s, %s>(
matrix, options.elimination_groups[0]);
}
"""
FACTORY_FOOTER = """
#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
"""
def SuffixForSize(size):
if size == "Eigen::Dynamic":
return "d"
return str(size)
def SpecializationFilename(prefix, row_block_size, e_block_size, f_block_size):
return "_".join([prefix] + map(SuffixForSize, (row_block_size,
e_block_size,
f_block_size)))
def Specialize():
"""
Generate specialization code and the conditionals to instantiate it.
"""
f = open("partitioned_matrix_view.cc", "w")
f.write(HEADER)
f.write(FACTORY_FILE_HEADER)
for row_block_size, e_block_size, f_block_size in SPECIALIZATIONS:
output = SpecializationFilename("generated/partitioned_matrix_view",
row_block_size,
e_block_size,
f_block_size) + ".cc"
fptr = open(output, "w")
fptr.write(HEADER)
template = SPECIALIZATION_FILE
if (row_block_size == "Eigen::Dynamic" and
e_block_size == "Eigen::Dynamic" and
f_block_size == "Eigen::Dynamic"):
template = DYNAMIC_FILE
fptr.write(template % (row_block_size, e_block_size, f_block_size))
fptr.close()
f.write(FACTORY_CONDITIONAL % (row_block_size,
e_block_size,
f_block_size,
row_block_size,
e_block_size,
f_block_size))
f.write(FACTORY_FOOTER)
f.close()
if __name__ == "__main__":
Specialize()