mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-30 00:50:37 +08:00
Sameer Agarwal
1cfec3c666
1. Refactor the python code that generates the template specializations to remove code duplication. 2. Improved the logic for template specialization selection where Eigen::Dynamic now serves as a wildcard. 3. Added schur_templates.h/cc which allows querying the set of available template specializations without instantiating a linear solver. 4. Added Solver::Summary::schur_structre_given and Solver::Summary::schur_structure_used and expose them in Solver::Summary::FullReport for better performance debugging. 5. Updated the templates with newer dates and some minor comments cleanup which lead to the the template specializations to be re-generated. Change-Id: Iaf3c6f714353597899916c300465da01f151c3de
232 lines
8.7 KiB
Python
232 lines
8.7 KiB
Python
# Ceres Solver - A fast non-linear least squares minimizer
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# Copyright 2015 Google Inc. All rights reserved.
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# http://ceres-solver.org/
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# * Redistributions of source code must retain the above copyright notice,
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# this list of conditions and the following disclaimer.
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# * Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions and the following disclaimer in the documentation
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# and/or other materials provided with the distribution.
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# * Neither the name of Google Inc. nor the names of its contributors may be
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# used to endorse or promote products derived from this software without
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# specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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# POSSIBILITY OF SUCH DAMAGE.
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#
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# Author: sameeragarwal@google.com (Sameer Agarwal)
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#
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# Script for explicitly generating template specialization of the
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# SchurEliminator class. It is a rather large class
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# and the number of explicit instantiations is also large. Explicitly
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# generating these instantiations in separate .cc files breaks the
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# compilation into separate compilation unit rather than one large cc
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# file which takes 2+GB of RAM to compile.
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#
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# This script creates two sets of files.
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#
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# 1. schur_eliminator_x_x_x.cc
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# where, the x indicates the template parameters and
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#
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# 2. schur_eliminator.cc
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#
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# that contains a factory function for instantiating these classes
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# based on runtime parameters.
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#
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# The list of tuples, specializations indicates the set of
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# specializations that is generated.
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# Set of template specializations to generate
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SPECIALIZATIONS = [(2, 2, 2),
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(2, 2, 3),
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(2, 2, 4),
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(2, 2, "Eigen::Dynamic"),
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(2, 3, 3),
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(2, 3, 4),
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(2, 3, 6),
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(2, 3, 9),
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(2, 3, "Eigen::Dynamic"),
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(2, 4, 3),
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(2, 4, 4),
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(2, 4, 8),
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(2, 4, 9),
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(2, 4, "Eigen::Dynamic"),
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(2, "Eigen::Dynamic", "Eigen::Dynamic"),
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(4, 4, 2),
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(4, 4, 3),
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(4, 4, 4),
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(4, 4, "Eigen::Dynamic")]
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import schur_eliminator_template
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import partitioned_matrix_view_template
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def SuffixForSize(size):
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if size == "Eigen::Dynamic":
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return "d"
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return str(size)
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def SpecializationFilename(prefix, row_block_size, e_block_size, f_block_size):
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return "_".join([prefix] + map(SuffixForSize, (row_block_size,
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e_block_size,
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f_block_size)))
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def GenerateFactoryConditional(row_block_size, e_block_size, f_block_size):
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conditionals = []
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if (row_block_size != "Eigen::Dynamic"):
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conditionals.append("(options.row_block_size == %s)" % row_block_size)
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if (e_block_size != "Eigen::Dynamic"):
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conditionals.append("(options.e_block_size == %s)" % e_block_size)
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if (f_block_size != "Eigen::Dynamic"):
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conditionals.append("(options.f_block_size == %s)" % f_block_size)
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if (len(conditionals) == 0):
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return "%s"
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if (len(conditionals) == 1):
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return " if " + conditionals[0] + "{\n %s\n }\n"
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return " if (" + " &&\n ".join(conditionals) + ") {\n %s\n }\n"
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def Specialize(name, data):
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"""
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Generate specialization code and the conditionals to instantiate it.
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"""
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f = open(name + ".cc", "w")
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f.write(data["HEADER"])
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f.write(data["FACTORY_FILE_HEADER"])
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for row_block_size, e_block_size, f_block_size in SPECIALIZATIONS:
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output = SpecializationFilename("generated/" + name,
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row_block_size,
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e_block_size,
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f_block_size) + ".cc"
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fptr = open(output, "w")
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fptr.write(data["HEADER"])
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template = data["SPECIALIZATION_FILE"]
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if (row_block_size == "Eigen::Dynamic" and
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e_block_size == "Eigen::Dynamic" and
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f_block_size == "Eigen::Dynamic"):
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template = data["DYNAMIC_FILE"]
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fptr.write(template % (row_block_size, e_block_size, f_block_size))
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fptr.close()
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FACTORY_CONDITIONAL =
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GenerateFactoryConditional(row_block_size, e_block_size, f_block_size)
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f.write(FACTORY_CONDITIONAL % data["FACTORY"] %
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(row_block_size, e_block_size, f_block_size));
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f.write(data["FACTORY_FOOTER"])
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f.close()
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QUERY_HEADER = """// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2017 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
|
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
|
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: sameeragarwal@google.com (Sameer Agarwal)
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//
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// What template specializations are available.
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//
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// ========================================
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// THIS FILE IS AUTOGENERATED. DO NOT EDIT.
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// THIS FILE IS AUTOGENERATED. DO NOT EDIT.
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// THIS FILE IS AUTOGENERATED. DO NOT EDIT.
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// THIS FILE IS AUTOGENERATED. DO NOT EDIT.
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//=========================================
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//
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// This file is generated using generate_template_specializations.py.
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"""
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QUERY_FILE_HEADER = """
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#include "ceres/internal/eigen.h"
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#include "ceres/schur_templates.h"
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namespace ceres {
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namespace internal {
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void GetBestSchurTemplateSpecialization(int* row_block_size,
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int* e_block_size,
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int* f_block_size) {
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LinearSolver::Options options;
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options.row_block_size = *row_block_size;
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options.e_block_size = *e_block_size;
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options.f_block_size = *f_block_size;
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*row_block_size = Eigen::Dynamic;
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*e_block_size = Eigen::Dynamic;
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*f_block_size = Eigen::Dynamic;
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#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
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"""
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QUERY_FOOTER = """
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#endif
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return;
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}
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} // namespace internal
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} // namespace ceres
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"""
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QUERY_ACTION = """*row_block_size = %s;
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*e_block_size = %s;
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*f_block_size = %s;
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return;"""
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def GenerateQueryFile():
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"""
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Generate specialization code and the conditionals to instantiate it.
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"""
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f = open("schur_templates.cc", "w")
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f.write(QUERY_HEADER)
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f.write(QUERY_FILE_HEADER)
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for row_block_size, e_block_size, f_block_size in SPECIALIZATIONS:
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FACTORY_CONDITIONAL = GenerateFactoryConditional(row_block_size, e_block_size, f_block_size)
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f.write(FACTORY_CONDITIONAL % QUERY_ACTION % (row_block_size, e_block_size, f_block_size));
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f.write(QUERY_FOOTER)
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f.close()
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if __name__ == "__main__":
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Specialize("schur_eliminator", schur_eliminator_template.__dict__)
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Specialize("partitioned_matrix_view", partitioned_matrix_view_template.__dict__)
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GenerateQueryFile()
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