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Diffstat (limited to 'internal/ceres/generate_partitioned_matrix_view_specializations.py')
| -rw-r--r-- | internal/ceres/generate_partitioned_matrix_view_specializations.py | 231 |
1 files changed, 231 insertions, 0 deletions
diff --git a/internal/ceres/generate_partitioned_matrix_view_specializations.py b/internal/ceres/generate_partitioned_matrix_view_specializations.py new file mode 100644 index 0000000..c9bdf23 --- /dev/null +++ b/internal/ceres/generate_partitioned_matrix_view_specializations.py @@ -0,0 +1,231 @@ +# 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() |