233 lines
8.4 KiB
Python
233 lines
8.4 KiB
Python
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# 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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# PartitionedMatrixView class. Explicitly generating these
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# instantiations in separate .cc files breaks the compilation into
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# separate compilation unit rather than one large cc file.
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#
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# This script creates two sets of files.
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#
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# 1. partitioned_matrix_view_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. partitioned_matrix_view.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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("Eigen::Dynamic", "Eigen::Dynamic", "Eigen::Dynamic")]
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HEADER = """// 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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// Template specialization of PartitionedMatrixView.
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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_partitioned_matrix_view_specializations.py.
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// Editing it manually is not recommended.
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"""
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DYNAMIC_FILE = """
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#include "ceres/partitioned_matrix_view_impl.h"
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#include "ceres/internal/eigen.h"
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namespace ceres {
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namespace internal {
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template class PartitionedMatrixView<%s, %s, %s>;
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} // namespace internal
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} // namespace ceres
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"""
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SPECIALIZATION_FILE = """
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// This include must come before any #ifndef check on Ceres compile options.
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#include "ceres/internal/port.h"
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#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
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#include "ceres/partitioned_matrix_view_impl.h"
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#include "ceres/internal/eigen.h"
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namespace ceres {
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namespace internal {
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template class PartitionedMatrixView<%s, %s, %s>;
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} // namespace internal
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} // namespace ceres
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#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
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"""
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FACTORY_FILE_HEADER = """
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#include "ceres/linear_solver.h"
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#include "ceres/partitioned_matrix_view.h"
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#include "ceres/internal/eigen.h"
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namespace ceres {
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namespace internal {
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PartitionedMatrixViewBase*
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PartitionedMatrixViewBase::Create(const LinearSolver::Options& options,
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const BlockSparseMatrix& matrix) {
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#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
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"""
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FACTORY_CONDITIONAL = """ if ((options.row_block_size == %s) &&
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(options.e_block_size == %s) &&
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(options.f_block_size == %s)) {
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return new PartitionedMatrixView<%s, %s, %s>(
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matrix, options.elimination_groups[0]);
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}
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"""
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FACTORY_FOOTER = """
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#endif
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VLOG(1) << "Template specializations not found for <"
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<< options.row_block_size << ","
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<< options.e_block_size << ","
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<< options.f_block_size << ">";
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return new PartitionedMatrixView<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic>(
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matrix, options.elimination_groups[0]);
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};
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} // namespace internal
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} // namespace ceres
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"""
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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 Specialize():
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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("partitioned_matrix_view.cc", "w")
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f.write(HEADER)
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f.write(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/partitioned_matrix_view",
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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(HEADER)
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template = 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 = 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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f.write(FACTORY_CONDITIONAL % (row_block_size,
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e_block_size,
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f_block_size,
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row_block_size,
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e_block_size,
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f_block_size))
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f.write(FACTORY_FOOTER)
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f.close()
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if __name__ == "__main__":
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Specialize()
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