Template specializations for PartitionedMatrixView.
This speeds up the matrix vector products in the
IterativeSchurSolver by upto 40%.
Change-Id: Ib5e8d77c7269cf5ffdd2d161893734bb6d38215d
diff --git a/internal/ceres/CMakeLists.txt b/internal/ceres/CMakeLists.txt
index 02a1731..d963fd6 100644
--- a/internal/ceres/CMakeLists.txt
+++ b/internal/ceres/CMakeLists.txt
@@ -128,7 +128,7 @@
FILE(GLOB CERES_INTERNAL_SCHUR_FILES generated/*.cc)
ELSE (SCHUR_SPECIALIZATIONS)
# Only the fully dynamic solver. The build is much faster this way.
- FILE(GLOB CERES_INTERNAL_SCHUR_FILES generated/schur_eliminator_d_d_d.cc)
+ FILE(GLOB CERES_INTERNAL_SCHUR_FILES generated/*_d_d_d.cc)
ENDIF (SCHUR_SPECIALIZATIONS)
# Primarily for Android, but optionally for others, use the minimal internal
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..1ee8b8e
--- /dev/null
+++ b/internal/ceres/generate_partitioned_matrix_view_specializations.py
@@ -0,0 +1,226 @@
+# 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, "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_eliminator_specialization.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 = """
+#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()
diff --git a/internal/ceres/generated/partitioned_matrix_view_2_2_2.cc b/internal/ceres/generated/partitioned_matrix_view_2_2_2.cc
new file mode 100644
index 0000000..3079cff
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_2_2_2.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<2, 2, 2>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_2_2_3.cc b/internal/ceres/generated/partitioned_matrix_view_2_2_3.cc
new file mode 100644
index 0000000..d2ea113
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_2_2_3.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<2, 2, 3>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_2_2_4.cc b/internal/ceres/generated/partitioned_matrix_view_2_2_4.cc
new file mode 100644
index 0000000..4e59910
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_2_2_4.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<2, 2, 4>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_2_2_d.cc b/internal/ceres/generated/partitioned_matrix_view_2_2_d.cc
new file mode 100644
index 0000000..8239295
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_2_2_d.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<2, 2, Eigen::Dynamic>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_2_3_3.cc b/internal/ceres/generated/partitioned_matrix_view_2_3_3.cc
new file mode 100644
index 0000000..b408ca5
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_2_3_3.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<2, 3, 3>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_2_3_4.cc b/internal/ceres/generated/partitioned_matrix_view_2_3_4.cc
new file mode 100644
index 0000000..fc468bf
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_2_3_4.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<2, 3, 4>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_2_3_9.cc b/internal/ceres/generated/partitioned_matrix_view_2_3_9.cc
new file mode 100644
index 0000000..3633a1c
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_2_3_9.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<2, 3, 9>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_2_3_d.cc b/internal/ceres/generated/partitioned_matrix_view_2_3_d.cc
new file mode 100644
index 0000000..8314727
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_2_3_d.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<2, 3, Eigen::Dynamic>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_2_4_3.cc b/internal/ceres/generated/partitioned_matrix_view_2_4_3.cc
new file mode 100644
index 0000000..04ebe93
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_2_4_3.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<2, 4, 3>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_2_4_4.cc b/internal/ceres/generated/partitioned_matrix_view_2_4_4.cc
new file mode 100644
index 0000000..5374554
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_2_4_4.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<2, 4, 4>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_2_4_d.cc b/internal/ceres/generated/partitioned_matrix_view_2_4_d.cc
new file mode 100644
index 0000000..69eccf9
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_2_4_d.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<2, 4, Eigen::Dynamic>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_2_d_d.cc b/internal/ceres/generated/partitioned_matrix_view_2_d_d.cc
new file mode 100644
index 0000000..3238812
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_2_d_d.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<2, Eigen::Dynamic, Eigen::Dynamic>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_4_4_2.cc b/internal/ceres/generated/partitioned_matrix_view_4_4_2.cc
new file mode 100644
index 0000000..1a223ff
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_4_4_2.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<4, 4, 2>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_4_4_3.cc b/internal/ceres/generated/partitioned_matrix_view_4_4_3.cc
new file mode 100644
index 0000000..d50c18d
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_4_4_3.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<4, 4, 3>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_4_4_4.cc b/internal/ceres/generated/partitioned_matrix_view_4_4_4.cc
new file mode 100644
index 0000000..adf7783
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_4_4_4.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<4, 4, 4>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_4_4_d.cc b/internal/ceres/generated/partitioned_matrix_view_4_4_d.cc
new file mode 100644
index 0000000..06f75ea
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_4_4_d.cc
@@ -0,0 +1,56 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<4, 4, Eigen::Dynamic>;
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION
diff --git a/internal/ceres/generated/partitioned_matrix_view_d_d_d.cc b/internal/ceres/generated/partitioned_matrix_view_d_d_d.cc
new file mode 100644
index 0000000..b392fd5
--- /dev/null
+++ b/internal/ceres/generated/partitioned_matrix_view_d_d_d.cc
@@ -0,0 +1,53 @@
+// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
+
+
+#include "ceres/partitioned_matrix_view_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class PartitionedMatrixView<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic>;
+
+} // namespace internal
+} // namespace ceres
diff --git a/internal/ceres/implicit_schur_complement.cc b/internal/ceres/implicit_schur_complement.cc
index 32722bb..8ab6b6d 100644
--- a/internal/ceres/implicit_schur_complement.cc
+++ b/internal/ceres/implicit_schur_complement.cc
@@ -35,21 +35,17 @@
#include "ceres/block_structure.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/scoped_ptr.h"
+#include "ceres/linear_solver.h"
#include "ceres/types.h"
#include "glog/logging.h"
namespace ceres {
namespace internal {
-ImplicitSchurComplement::ImplicitSchurComplement(int num_eliminate_blocks,
- bool preconditioner)
- : num_eliminate_blocks_(num_eliminate_blocks),
- preconditioner_(preconditioner),
- A_(NULL),
+ImplicitSchurComplement::ImplicitSchurComplement(const LinearSolver::Options& options)
+ : options_(options),
D_(NULL),
- b_(NULL),
- block_diagonal_EtE_inverse_(NULL),
- block_diagonal_FtF_inverse_(NULL) {
+ b_(NULL) {
}
ImplicitSchurComplement::~ImplicitSchurComplement() {
@@ -61,7 +57,7 @@
// Since initialization is reasonably heavy, perhaps we can save on
// constructing a new object everytime.
if (A_ == NULL) {
- A_.reset(new PartitionedMatrixView(A, num_eliminate_blocks_));
+ A_.reset(PartitionedMatrixViewBase::Create(options_, A));
}
D_ = D;
@@ -71,7 +67,7 @@
// E'E and F'E.
if (block_diagonal_EtE_inverse_ == NULL) {
block_diagonal_EtE_inverse_.reset(A_->CreateBlockDiagonalEtE());
- if (preconditioner_) {
+ if (options_.preconditioner_type == JACOBI) {
block_diagonal_FtF_inverse_.reset(A_->CreateBlockDiagonalFtF());
}
rhs_.resize(A_->num_cols_f());
@@ -82,7 +78,7 @@
tmp_f_cols_.resize(A_->num_cols_f());
} else {
A_->UpdateBlockDiagonalEtE(block_diagonal_EtE_inverse_.get());
- if (preconditioner_) {
+ if (options_.preconditioner_type == JACOBI) {
A_->UpdateBlockDiagonalFtF(block_diagonal_FtF_inverse_.get());
}
}
@@ -91,7 +87,7 @@
// contributions from the diagonal D if it is non-null. Add that to
// the block diagonals and invert them.
AddDiagonalAndInvert(D_, block_diagonal_EtE_inverse_.get());
- if (preconditioner_) {
+ if (options_.preconditioner_type == JACOBI) {
AddDiagonalAndInvert((D_ == NULL) ? NULL : D_ + A_->num_cols_e(),
block_diagonal_FtF_inverse_.get());
}
diff --git a/internal/ceres/implicit_schur_complement.h b/internal/ceres/implicit_schur_complement.h
index c1bb6e1..c992bdc 100644
--- a/internal/ceres/implicit_schur_complement.h
+++ b/internal/ceres/implicit_schur_complement.h
@@ -35,6 +35,7 @@
#define CERES_INTERNAL_IMPLICIT_SCHUR_COMPLEMENT_H_
#include "ceres/linear_operator.h"
+#include "ceres/linear_solver.h"
#include "ceres/partitioned_matrix_view.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/scoped_ptr.h"
@@ -96,7 +97,7 @@
//
// TODO(sameeragarwal): Get rid of the two bools below and replace
// them with enums.
- ImplicitSchurComplement(int num_eliminate_blocks, bool preconditioner);
+ ImplicitSchurComplement(const LinearSolver::Options& options);
virtual ~ImplicitSchurComplement();
// Initialize the Schur complement for a linear least squares
@@ -142,10 +143,9 @@
void AddDiagonalAndInvert(const double* D, BlockSparseMatrix* matrix);
void UpdateRhs();
- int num_eliminate_blocks_;
- bool preconditioner_;
+ const LinearSolver::Options& options_;
- scoped_ptr<PartitionedMatrixView> A_;
+ scoped_ptr<PartitionedMatrixViewBase> A_;
const double* D_;
const double* b_;
diff --git a/internal/ceres/implicit_schur_complement_test.cc b/internal/ceres/implicit_schur_complement_test.cc
index 1694273..3369ecb 100644
--- a/internal/ceres/implicit_schur_complement_test.cc
+++ b/internal/ceres/implicit_schur_complement_test.cc
@@ -120,7 +120,10 @@
Vector reference_solution;
ReducedLinearSystemAndSolution(D, &lhs, &rhs, &reference_solution);
- ImplicitSchurComplement isc(num_eliminate_blocks_, true);
+ LinearSolver::Options options;
+ options.elimination_groups.push_back(num_eliminate_blocks_);
+ options.preconditioner_type = JACOBI;
+ ImplicitSchurComplement isc(options);
isc.Init(*A_, D, b_.get());
int num_sc_cols = lhs.cols();
diff --git a/internal/ceres/iterative_schur_complement_solver.cc b/internal/ceres/iterative_schur_complement_solver.cc
index 1aac565..90013ff 100644
--- a/internal/ceres/iterative_schur_complement_solver.cc
+++ b/internal/ceres/iterative_schur_complement_solver.cc
@@ -38,6 +38,7 @@
#include "ceres/block_sparse_matrix.h"
#include "ceres/block_structure.h"
#include "ceres/conjugate_gradients_solver.h"
+#include "ceres/detect_structure.h"
#include "ceres/implicit_schur_complement.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/scoped_ptr.h"
@@ -69,17 +70,20 @@
EventLogger event_logger("IterativeSchurComplementSolver::Solve");
CHECK_NOTNULL(A->block_structure());
-
+ const int num_eliminate_blocks = options_.elimination_groups[0];
// Initialize a ImplicitSchurComplement object.
if (schur_complement_ == NULL) {
- schur_complement_.reset(
- new ImplicitSchurComplement(options_.elimination_groups[0],
- options_.preconditioner_type == JACOBI));
+ DetectStructure(*(A->block_structure()),
+ num_eliminate_blocks,
+ &options_.row_block_size,
+ &options_.e_block_size,
+ &options_.f_block_size);
+ schur_complement_.reset(new ImplicitSchurComplement(options_));
}
schur_complement_->Init(*A, per_solve_options.D, b);
const int num_schur_complement_blocks =
- A->block_structure()->cols.size() - options_.elimination_groups[0];
+ A->block_structure()->cols.size() - num_eliminate_blocks;
if (num_schur_complement_blocks == 0) {
VLOG(2) << "No parameter blocks left in the schur complement.";
LinearSolver::Summary cg_summary;
@@ -90,14 +94,12 @@
}
// Initialize the solution to the Schur complement system to zero.
- //
- // TODO(sameeragarwal): There maybe a better initialization than an
- // all zeros solution. Explore other cheap starting points.
reduced_linear_system_solution_.resize(schur_complement_->num_rows());
reduced_linear_system_solution_.setZero();
- // Instantiate a conjugate gradient solver that runs on the Schur complement
- // matrix with the block diagonal of the matrix F'F as the preconditioner.
+ // Instantiate a conjugate gradient solver that runs on the Schur
+ // complement matrix with the block diagonal of the matrix F'F as
+ // the preconditioner.
LinearSolver::Options cg_options;
cg_options.max_num_iterations = options_.max_num_iterations;
ConjugateGradientsSolver cg_solver(cg_options);
diff --git a/internal/ceres/partitioned_matrix_view.cc b/internal/ceres/partitioned_matrix_view.cc
index 59eaff8..7936a40 100644
--- a/internal/ceres/partitioned_matrix_view.cc
+++ b/internal/ceres/partitioned_matrix_view.cc
@@ -1,5 +1,5 @@
// Ceres Solver - A fast non-linear least squares minimizer
-// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
+// 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
@@ -27,277 +27,141 @@
// 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_eliminator_specialization.py.
+// Editing it manually is not recommended.
-#define EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD 10
-
+#include "ceres/linear_solver.h"
#include "ceres/partitioned_matrix_view.h"
-
-#include <algorithm>
-#include <cstring>
-#include <vector>
-#include "ceres/block_sparse_matrix.h"
-#include "ceres/block_structure.h"
#include "ceres/internal/eigen.h"
-#include "ceres/small_blas.h"
-#include "glog/logging.h"
namespace ceres {
namespace internal {
-PartitionedMatrixView::PartitionedMatrixView(
- const BlockSparseMatrix& matrix,
- int num_col_blocks_a)
- : matrix_(matrix),
- num_col_blocks_e_(num_col_blocks_a) {
- const CompressedRowBlockStructure* bs = matrix_.block_structure();
- CHECK_NOTNULL(bs);
-
- num_col_blocks_f_ = bs->cols.size() - num_col_blocks_a;
-
- // Compute the number of row blocks in E. The number of row blocks
- // in E maybe less than the number of row blocks in the input matrix
- // as some of the row blocks at the bottom may not have any
- // e_blocks. For a definition of what an e_block is, please see
- // explicit_schur_complement_solver.h
- num_row_blocks_e_ = 0;
- for (int r = 0; r < bs->rows.size(); ++r) {
- const vector<Cell>& cells = bs->rows[r].cells;
- if (cells[0].block_id < num_col_blocks_a) {
- ++num_row_blocks_e_;
- }
+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 == 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 == 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]);
}
- // Compute the number of columns in E and F.
- num_cols_e_ = 0;
- num_cols_f_ = 0;
-
- for (int c = 0; c < bs->cols.size(); ++c) {
- const Block& block = bs->cols[c];
- if (c < num_col_blocks_a) {
- num_cols_e_ += block.size;
- } else {
- num_cols_f_ += block.size;
- }
- }
-
- CHECK_EQ(num_cols_e_ + num_cols_f_, matrix_.num_cols());
-}
-
-PartitionedMatrixView::~PartitionedMatrixView() {
-}
-
-// The next four methods don't seem to be particularly cache
-// friendly. This is an artifact of how the BlockStructure of the
-// input matrix is constructed. These methods will benefit from
-// multithreading as well as improved data layout.
-
-void PartitionedMatrixView::RightMultiplyE(const double* x, double* y) const {
- const CompressedRowBlockStructure* bs = matrix_.block_structure();
-
- // Iterate over the first num_row_blocks_e_ row blocks, and multiply
- // by the first cell in each row block.
- const double* values = matrix_.values();
- for (int r = 0; r < num_row_blocks_e_; ++r) {
- const Cell& cell = bs->rows[r].cells[0];
- const int row_block_pos = bs->rows[r].block.position;
- const int row_block_size = bs->rows[r].block.size;
- const int col_block_id = cell.block_id;
- const int col_block_pos = bs->cols[col_block_id].position;
- const int col_block_size = bs->cols[col_block_id].size;
- MatrixVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
- values + cell.position, row_block_size, col_block_size,
- x + col_block_pos,
- y + row_block_pos);
- }
-}
-
-void PartitionedMatrixView::RightMultiplyF(const double* x, double* y) const {
- const CompressedRowBlockStructure* bs = matrix_.block_structure();
-
- // Iterate over row blocks, and if the row block is in E, then
- // multiply by all the cells except the first one which is of type
- // E. If the row block is not in E (i.e its in the bottom
- // num_row_blocks - num_row_blocks_e row blocks), then all the cells
- // are of type F and multiply by them all.
- const double* values = matrix_.values();
- for (int r = 0; r < bs->rows.size(); ++r) {
- const int row_block_pos = bs->rows[r].block.position;
- const int row_block_size = bs->rows[r].block.size;
- const vector<Cell>& cells = bs->rows[r].cells;
- for (int c = (r < num_row_blocks_e_) ? 1 : 0; c < cells.size(); ++c) {
- const int col_block_id = cells[c].block_id;
- const int col_block_pos = bs->cols[col_block_id].position;
- const int col_block_size = bs->cols[col_block_id].size;
- MatrixVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
- values + cells[c].position, row_block_size, col_block_size,
- x + col_block_pos - num_cols_e(),
- y + row_block_pos);
- }
- }
-}
-
-void PartitionedMatrixView::LeftMultiplyE(const double* x, double* y) const {
- const CompressedRowBlockStructure* bs = matrix_.block_structure();
-
- // Iterate over the first num_row_blocks_e_ row blocks, and multiply
- // by the first cell in each row block.
- const double* values = matrix_.values();
- for (int r = 0; r < num_row_blocks_e_; ++r) {
- const Cell& cell = bs->rows[r].cells[0];
- const int row_block_pos = bs->rows[r].block.position;
- const int row_block_size = bs->rows[r].block.size;
- const int col_block_id = cell.block_id;
- const int col_block_pos = bs->cols[col_block_id].position;
- const int col_block_size = bs->cols[col_block_id].size;
- MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
- values + cell.position, row_block_size, col_block_size,
- x + row_block_pos,
- y + col_block_pos);
- }
-}
-
-void PartitionedMatrixView::LeftMultiplyF(const double* x, double* y) const {
- const CompressedRowBlockStructure* bs = matrix_.block_structure();
-
- // Iterate over row blocks, and if the row block is in E, then
- // multiply by all the cells except the first one which is of type
- // E. If the row block is not in E (i.e its in the bottom
- // num_row_blocks - num_row_blocks_e row blocks), then all the cells
- // are of type F and multiply by them all.
- const double* values = matrix_.values();
- for (int r = 0; r < bs->rows.size(); ++r) {
- const int row_block_pos = bs->rows[r].block.position;
- const int row_block_size = bs->rows[r].block.size;
- const vector<Cell>& cells = bs->rows[r].cells;
- for (int c = (r < num_row_blocks_e_) ? 1 : 0; c < cells.size(); ++c) {
- const int col_block_id = cells[c].block_id;
- const int col_block_pos = bs->cols[col_block_id].position;
- const int col_block_size = bs->cols[col_block_id].size;
- MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
- values + cells[c].position, row_block_size, col_block_size,
- x + row_block_pos,
- y + col_block_pos - num_cols_e());
- }
- }
-}
-
-// Given a range of columns blocks of a matrix m, compute the block
-// structure of the block diagonal of the matrix m(:,
-// start_col_block:end_col_block)'m(:, start_col_block:end_col_block)
-// and return a BlockSparseMatrix with the this block structure. The
-// caller owns the result.
-BlockSparseMatrix* PartitionedMatrixView::CreateBlockDiagonalMatrixLayout(
- int start_col_block, int end_col_block) const {
- const CompressedRowBlockStructure* bs = matrix_.block_structure();
- CompressedRowBlockStructure* block_diagonal_structure =
- new CompressedRowBlockStructure;
-
- int block_position = 0;
- int diagonal_cell_position = 0;
-
- // Iterate over the column blocks, creating a new diagonal block for
- // each column block.
- for (int c = start_col_block; c < end_col_block; ++c) {
- const Block& block = bs->cols[c];
- block_diagonal_structure->cols.push_back(Block());
- Block& diagonal_block = block_diagonal_structure->cols.back();
- diagonal_block.size = block.size;
- diagonal_block.position = block_position;
-
- block_diagonal_structure->rows.push_back(CompressedRow());
- CompressedRow& row = block_diagonal_structure->rows.back();
- row.block = diagonal_block;
-
- row.cells.push_back(Cell());
- Cell& cell = row.cells.back();
- cell.block_id = c - start_col_block;
- cell.position = diagonal_cell_position;
-
- block_position += block.size;
- diagonal_cell_position += block.size * block.size;
- }
-
- // Build a BlockSparseMatrix with the just computed block
- // structure.
- return new BlockSparseMatrix(block_diagonal_structure);
-}
-
-BlockSparseMatrix* PartitionedMatrixView::CreateBlockDiagonalEtE() const {
- BlockSparseMatrix* block_diagonal =
- CreateBlockDiagonalMatrixLayout(0, num_col_blocks_e_);
- UpdateBlockDiagonalEtE(block_diagonal);
- return block_diagonal;
-}
-
-BlockSparseMatrix* PartitionedMatrixView::CreateBlockDiagonalFtF() const {
- BlockSparseMatrix* block_diagonal =
- CreateBlockDiagonalMatrixLayout(
- num_col_blocks_e_, num_col_blocks_e_ + num_col_blocks_f_);
- UpdateBlockDiagonalFtF(block_diagonal);
- return block_diagonal;
-}
-
-// Similar to the code in RightMultiplyE, except instead of the matrix
-// vector multiply its an outer product.
-//
-// block_diagonal = block_diagonal(E'E)
-void PartitionedMatrixView::UpdateBlockDiagonalEtE(
- BlockSparseMatrix* block_diagonal) const {
- const CompressedRowBlockStructure* bs = matrix_.block_structure();
- const CompressedRowBlockStructure* block_diagonal_structure =
- block_diagonal->block_structure();
-
- block_diagonal->SetZero();
- const double* values = matrix_.values();
- for (int r = 0; r < num_row_blocks_e_ ; ++r) {
- const Cell& cell = bs->rows[r].cells[0];
- const int row_block_size = bs->rows[r].block.size;
- const int block_id = cell.block_id;
- const int col_block_size = bs->cols[block_id].size;
- const int cell_position =
- block_diagonal_structure->rows[block_id].cells[0].position;
-
- MatrixTransposeMatrixMultiply
- <Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, 1>(
- values + cell.position, row_block_size, col_block_size,
- values + cell.position, row_block_size, col_block_size,
- block_diagonal->mutable_values() + cell_position,
- 0, 0, col_block_size, col_block_size);
- }
-}
-
-// Similar to the code in RightMultiplyF, except instead of the matrix
-// vector multiply its an outer product.
-//
-// block_diagonal = block_diagonal(F'F)
-//
-void PartitionedMatrixView::UpdateBlockDiagonalFtF(
- BlockSparseMatrix* block_diagonal) const {
- const CompressedRowBlockStructure* bs = matrix_.block_structure();
- const CompressedRowBlockStructure* block_diagonal_structure =
- block_diagonal->block_structure();
-
- block_diagonal->SetZero();
- const double* values = matrix_.values();
- for (int r = 0; r < bs->rows.size(); ++r) {
- const int row_block_size = bs->rows[r].block.size;
- const vector<Cell>& cells = bs->rows[r].cells;
- for (int c = (r < num_row_blocks_e_) ? 1 : 0; c < cells.size(); ++c) {
- const int col_block_id = cells[c].block_id;
- const int col_block_size = bs->cols[col_block_id].size;
- const int diagonal_block_id = col_block_id - num_col_blocks_e_;
- const int cell_position =
- block_diagonal_structure->rows[diagonal_block_id].cells[0].position;
-
- MatrixTransposeMatrixMultiply
- <Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, 1>(
- values + cells[c].position, row_block_size, col_block_size,
- values + cells[c].position, row_block_size, col_block_size,
- block_diagonal->mutable_values() + cell_position,
- 0, 0, col_block_size, col_block_size);
- }
- }
-}
+#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
diff --git a/internal/ceres/partitioned_matrix_view.h b/internal/ceres/partitioned_matrix_view.h
index ebfbe40..98423a0 100644
--- a/internal/ceres/partitioned_matrix_view.h
+++ b/internal/ceres/partitioned_matrix_view.h
@@ -36,7 +36,15 @@
#ifndef CERES_INTERNAL_PARTITIONED_MATRIX_VIEW_H_
#define CERES_INTERNAL_PARTITIONED_MATRIX_VIEW_H_
-#include "ceres/block_sparse_matrix.h"
+#include <algorithm>
+#include <cstring>
+#include <vector>
+
+#include "ceres/block_structure.h"
+#include "ceres/internal/eigen.h"
+#include "ceres/linear_solver.h"
+#include "ceres/small_blas.h"
+#include "glog/logging.h"
namespace ceres {
namespace internal {
@@ -51,57 +59,78 @@
// block structure of the matrix does not satisfy the requirements of
// the Schur complement solver it will result in unpredictable and
// wrong output.
-//
-// This class lives in the internal name space as its a utility class
-// to be used by the IterativeSchurComplementSolver class, found in
-// iterative_schur_complement_solver.h, and is not meant for general
-// consumption.
-class PartitionedMatrixView {
+class PartitionedMatrixViewBase {
public:
- // matrix = [E F], where the matrix E contains the first
- // num_col_blocks_a column blocks.
- PartitionedMatrixView(const BlockSparseMatrix& matrix,
- int num_col_blocks_a);
- ~PartitionedMatrixView();
+ virtual ~PartitionedMatrixViewBase() {}
// y += E'x
- void LeftMultiplyE(const double* x, double* y) const;
+ virtual void LeftMultiplyE(const double* x, double* y) const = 0;
// y += F'x
- void LeftMultiplyF(const double* x, double* y) const;
+ virtual void LeftMultiplyF(const double* x, double* y) const = 0;
// y += Ex
- void RightMultiplyE(const double* x, double* y) const;
+ virtual void RightMultiplyE(const double* x, double* y) const = 0;
// y += Fx
- void RightMultiplyF(const double* x, double* y) const;
+ virtual void RightMultiplyF(const double* x, double* y) const = 0;
// Create and return the block diagonal of the matrix E'E.
- BlockSparseMatrix* CreateBlockDiagonalEtE() const;
+ virtual BlockSparseMatrix* CreateBlockDiagonalEtE() const = 0;
- // Create and return the block diagonal of the matrix F'F.
- BlockSparseMatrix* CreateBlockDiagonalFtF() const;
+ // Create and return the block diagonal of the matrix F'F. Caller
+ // owns the result.
+ virtual BlockSparseMatrix* CreateBlockDiagonalFtF() const = 0;
// Compute the block diagonal of the matrix E'E and store it in
// block_diagonal. The matrix block_diagonal is expected to have a
// BlockStructure (preferably created using
// CreateBlockDiagonalMatrixEtE) which is has the same structure as
// the block diagonal of E'E.
- void UpdateBlockDiagonalEtE(BlockSparseMatrix* block_diagonal) const;
+ virtual void UpdateBlockDiagonalEtE(BlockSparseMatrix* block_diagonal) const = 0;
// Compute the block diagonal of the matrix F'F and store it in
// block_diagonal. The matrix block_diagonal is expected to have a
// BlockStructure (preferably created using
// CreateBlockDiagonalMatrixFtF) which is has the same structure as
// the block diagonal of F'F.
- void UpdateBlockDiagonalFtF(BlockSparseMatrix* block_diagonal) const;
+ virtual void UpdateBlockDiagonalFtF(BlockSparseMatrix* block_diagonal) const = 0;
- int num_col_blocks_e() const { return num_col_blocks_e_; }
- int num_col_blocks_f() const { return num_col_blocks_f_; }
- int num_cols_e() const { return num_cols_e_; }
- int num_cols_f() const { return num_cols_f_; }
- int num_rows() const { return matrix_.num_rows(); }
- int num_cols() const { return matrix_.num_cols(); }
+ virtual int num_col_blocks_e() const = 0;
+ virtual int num_col_blocks_f() const = 0;
+ virtual int num_cols_e() const = 0;
+ virtual int num_cols_f() const = 0;
+ virtual int num_rows() const = 0;
+ virtual int num_cols() const = 0;
+
+ static PartitionedMatrixViewBase* Create(const LinearSolver::Options& options,
+ const BlockSparseMatrix& matrix);
+};
+
+template <int kRowBlockSize = Eigen::Dynamic,
+ int kEBlockSize = Eigen::Dynamic,
+ int kFBlockSize = Eigen::Dynamic >
+class PartitionedMatrixView : public PartitionedMatrixViewBase {
+ public:
+ // matrix = [E F], where the matrix E contains the first
+ // num_col_blocks_a column blocks.
+ PartitionedMatrixView(const BlockSparseMatrix& matrix, int num_col_blocks_e);
+
+ virtual ~PartitionedMatrixView();
+ virtual void LeftMultiplyE(const double* x, double* y) const;
+ virtual void LeftMultiplyF(const double* x, double* y) const;
+ virtual void RightMultiplyE(const double* x, double* y) const;
+ virtual void RightMultiplyF(const double* x, double* y) const;
+ virtual BlockSparseMatrix* CreateBlockDiagonalEtE() const;
+ virtual BlockSparseMatrix* CreateBlockDiagonalFtF() const;
+ virtual void UpdateBlockDiagonalEtE(BlockSparseMatrix* block_diagonal) const;
+ virtual void UpdateBlockDiagonalFtF(BlockSparseMatrix* block_diagonal) const;
+ virtual int num_col_blocks_e() const { return num_col_blocks_e_; }
+ virtual int num_col_blocks_f() const { return num_col_blocks_f_; }
+ virtual int num_cols_e() const { return num_cols_e_; }
+ virtual int num_cols_f() const { return num_cols_f_; }
+ virtual int num_rows() const { return matrix_.num_rows(); }
+ virtual int num_cols() const { return matrix_.num_cols(); }
private:
BlockSparseMatrix* CreateBlockDiagonalMatrixLayout(int start_col_block,
diff --git a/internal/ceres/partitioned_matrix_view_impl.h b/internal/ceres/partitioned_matrix_view_impl.h
new file mode 100644
index 0000000..5fd5fe1
--- /dev/null
+++ b/internal/ceres/partitioned_matrix_view_impl.h
@@ -0,0 +1,379 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2010, 2011, 2012 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)
+
+#include "ceres/partitioned_matrix_view.h"
+
+#include <algorithm>
+#include <cstring>
+#include <vector>
+#include "ceres/block_sparse_matrix.h"
+#include "ceres/block_structure.h"
+#include "ceres/internal/eigen.h"
+#include "ceres/small_blas.h"
+#include "glog/logging.h"
+
+namespace ceres {
+namespace internal {
+
+template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
+PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>::
+PartitionedMatrixView(
+ const BlockSparseMatrix& matrix,
+ int num_col_blocks_e)
+ : matrix_(matrix),
+ num_col_blocks_e_(num_col_blocks_e) {
+ const CompressedRowBlockStructure* bs = matrix_.block_structure();
+ CHECK_NOTNULL(bs);
+
+ num_col_blocks_f_ = bs->cols.size() - num_col_blocks_e_;
+
+ // Compute the number of row blocks in E. The number of row blocks
+ // in E maybe less than the number of row blocks in the input matrix
+ // as some of the row blocks at the bottom may not have any
+ // e_blocks. For a definition of what an e_block is, please see
+ // explicit_schur_complement_solver.h
+ num_row_blocks_e_ = 0;
+ for (int r = 0; r < bs->rows.size(); ++r) {
+ const vector<Cell>& cells = bs->rows[r].cells;
+ if (cells[0].block_id < num_col_blocks_e_) {
+ ++num_row_blocks_e_;
+ }
+ }
+
+ // Compute the number of columns in E and F.
+ num_cols_e_ = 0;
+ num_cols_f_ = 0;
+
+ for (int c = 0; c < bs->cols.size(); ++c) {
+ const Block& block = bs->cols[c];
+ if (c < num_col_blocks_e_) {
+ num_cols_e_ += block.size;
+ } else {
+ num_cols_f_ += block.size;
+ }
+ }
+
+ CHECK_EQ(num_cols_e_ + num_cols_f_, matrix_.num_cols());
+}
+
+template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
+PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>::
+~PartitionedMatrixView() {
+}
+
+// The next four methods don't seem to be particularly cache
+// friendly. This is an artifact of how the BlockStructure of the
+// input matrix is constructed. These methods will benefit from
+// multithreading as well as improved data layout.
+
+template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
+void
+PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>::
+RightMultiplyE(const double* x, double* y) const {
+ const CompressedRowBlockStructure* bs = matrix_.block_structure();
+
+ // Iterate over the first num_row_blocks_e_ row blocks, and multiply
+ // by the first cell in each row block.
+ const double* values = matrix_.values();
+ for (int r = 0; r < num_row_blocks_e_; ++r) {
+ const Cell& cell = bs->rows[r].cells[0];
+ const int row_block_pos = bs->rows[r].block.position;
+ const int row_block_size = bs->rows[r].block.size;
+ const int col_block_id = cell.block_id;
+ const int col_block_pos = bs->cols[col_block_id].position;
+ const int col_block_size = bs->cols[col_block_id].size;
+ MatrixVectorMultiply<kRowBlockSize, kEBlockSize, 1>(
+ values + cell.position, row_block_size, col_block_size,
+ x + col_block_pos,
+ y + row_block_pos);
+ }
+}
+
+template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
+void
+PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>::
+RightMultiplyF(const double* x, double* y) const {
+ const CompressedRowBlockStructure* bs = matrix_.block_structure();
+
+ // Iterate over row blocks, and if the row block is in E, then
+ // multiply by all the cells except the first one which is of type
+ // E. If the row block is not in E (i.e its in the bottom
+ // num_row_blocks - num_row_blocks_e row blocks), then all the cells
+ // are of type F and multiply by them all.
+ const double* values = matrix_.values();
+ for (int r = 0; r < num_row_blocks_e_; ++r) {
+ const int row_block_pos = bs->rows[r].block.position;
+ const int row_block_size = bs->rows[r].block.size;
+ const vector<Cell>& cells = bs->rows[r].cells;
+ for (int c = 1; c < cells.size(); ++c) {
+ const int col_block_id = cells[c].block_id;
+ const int col_block_pos = bs->cols[col_block_id].position;
+ const int col_block_size = bs->cols[col_block_id].size;
+ MatrixVectorMultiply<kRowBlockSize, kFBlockSize, 1>(
+ values + cells[c].position, row_block_size, col_block_size,
+ x + col_block_pos - num_cols_e_,
+ y + row_block_pos);
+ }
+ }
+
+ for (int r = num_row_blocks_e_; r < bs->rows.size(); ++r) {
+ const int row_block_pos = bs->rows[r].block.position;
+ const int row_block_size = bs->rows[r].block.size;
+ const vector<Cell>& cells = bs->rows[r].cells;
+ for (int c = 0; c < cells.size(); ++c) {
+ const int col_block_id = cells[c].block_id;
+ const int col_block_pos = bs->cols[col_block_id].position;
+ const int col_block_size = bs->cols[col_block_id].size;
+ MatrixVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
+ values + cells[c].position, row_block_size, col_block_size,
+ x + col_block_pos - num_cols_e_,
+ y + row_block_pos);
+ }
+ }
+}
+
+template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
+void
+PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>::
+LeftMultiplyE(const double* x, double* y) const {
+ const CompressedRowBlockStructure* bs = matrix_.block_structure();
+
+ // Iterate over the first num_row_blocks_e_ row blocks, and multiply
+ // by the first cell in each row block.
+ const double* values = matrix_.values();
+ for (int r = 0; r < num_row_blocks_e_; ++r) {
+ const Cell& cell = bs->rows[r].cells[0];
+ const int row_block_pos = bs->rows[r].block.position;
+ const int row_block_size = bs->rows[r].block.size;
+ const int col_block_id = cell.block_id;
+ const int col_block_pos = bs->cols[col_block_id].position;
+ const int col_block_size = bs->cols[col_block_id].size;
+ MatrixTransposeVectorMultiply<kRowBlockSize, kEBlockSize, 1>(
+ values + cell.position, row_block_size, col_block_size,
+ x + row_block_pos,
+ y + col_block_pos);
+ }
+}
+
+template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
+void
+PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>::
+LeftMultiplyF(const double* x, double* y) const {
+ const CompressedRowBlockStructure* bs = matrix_.block_structure();
+
+ // Iterate over row blocks, and if the row block is in E, then
+ // multiply by all the cells except the first one which is of type
+ // E. If the row block is not in E (i.e its in the bottom
+ // num_row_blocks - num_row_blocks_e row blocks), then all the cells
+ // are of type F and multiply by them all.
+ const double* values = matrix_.values();
+ for (int r = 0; r < num_row_blocks_e_; ++r) {
+ const int row_block_pos = bs->rows[r].block.position;
+ const int row_block_size = bs->rows[r].block.size;
+ const vector<Cell>& cells = bs->rows[r].cells;
+ for (int c = 1; c < cells.size(); ++c) {
+ const int col_block_id = cells[c].block_id;
+ const int col_block_pos = bs->cols[col_block_id].position;
+ const int col_block_size = bs->cols[col_block_id].size;
+ MatrixTransposeVectorMultiply<kRowBlockSize, kFBlockSize, 1>(
+ values + cells[c].position, row_block_size, col_block_size,
+ x + row_block_pos,
+ y + col_block_pos - num_cols_e_);
+ }
+ }
+
+ for (int r = num_row_blocks_e_; r < bs->rows.size(); ++r) {
+ const int row_block_pos = bs->rows[r].block.position;
+ const int row_block_size = bs->rows[r].block.size;
+ const vector<Cell>& cells = bs->rows[r].cells;
+ for (int c = 0; c < cells.size(); ++c) {
+ const int col_block_id = cells[c].block_id;
+ const int col_block_pos = bs->cols[col_block_id].position;
+ const int col_block_size = bs->cols[col_block_id].size;
+ MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
+ values + cells[c].position, row_block_size, col_block_size,
+ x + row_block_pos,
+ y + col_block_pos - num_cols_e_);
+ }
+ }
+}
+
+// Given a range of columns blocks of a matrix m, compute the block
+// structure of the block diagonal of the matrix m(:,
+// start_col_block:end_col_block)'m(:, start_col_block:end_col_block)
+// and return a BlockSparseMatrix with the this block structure. The
+// caller owns the result.
+template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
+BlockSparseMatrix*
+PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>::
+CreateBlockDiagonalMatrixLayout(int start_col_block, int end_col_block) const {
+ const CompressedRowBlockStructure* bs = matrix_.block_structure();
+ CompressedRowBlockStructure* block_diagonal_structure =
+ new CompressedRowBlockStructure;
+
+ int block_position = 0;
+ int diagonal_cell_position = 0;
+
+ // Iterate over the column blocks, creating a new diagonal block for
+ // each column block.
+ for (int c = start_col_block; c < end_col_block; ++c) {
+ const Block& block = bs->cols[c];
+ block_diagonal_structure->cols.push_back(Block());
+ Block& diagonal_block = block_diagonal_structure->cols.back();
+ diagonal_block.size = block.size;
+ diagonal_block.position = block_position;
+
+ block_diagonal_structure->rows.push_back(CompressedRow());
+ CompressedRow& row = block_diagonal_structure->rows.back();
+ row.block = diagonal_block;
+
+ row.cells.push_back(Cell());
+ Cell& cell = row.cells.back();
+ cell.block_id = c - start_col_block;
+ cell.position = diagonal_cell_position;
+
+ block_position += block.size;
+ diagonal_cell_position += block.size * block.size;
+ }
+
+ // Build a BlockSparseMatrix with the just computed block
+ // structure.
+ return new BlockSparseMatrix(block_diagonal_structure);
+}
+
+template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
+BlockSparseMatrix*
+PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>::
+CreateBlockDiagonalEtE() const {
+ BlockSparseMatrix* block_diagonal =
+ CreateBlockDiagonalMatrixLayout(0, num_col_blocks_e_);
+ UpdateBlockDiagonalEtE(block_diagonal);
+ return block_diagonal;
+}
+
+template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
+BlockSparseMatrix* PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>::
+CreateBlockDiagonalFtF() const {
+ BlockSparseMatrix* block_diagonal =
+ CreateBlockDiagonalMatrixLayout(
+ num_col_blocks_e_, num_col_blocks_e_ + num_col_blocks_f_);
+ UpdateBlockDiagonalFtF(block_diagonal);
+ return block_diagonal;
+}
+
+// Similar to the code in RightMultiplyE, except instead of the matrix
+// vector multiply its an outer product.
+//
+// block_diagonal = block_diagonal(E'E)
+//
+template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
+void
+PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>::
+UpdateBlockDiagonalEtE(
+ BlockSparseMatrix* block_diagonal) const {
+ const CompressedRowBlockStructure* bs = matrix_.block_structure();
+ const CompressedRowBlockStructure* block_diagonal_structure =
+ block_diagonal->block_structure();
+
+ block_diagonal->SetZero();
+ const double* values = matrix_.values();
+ for (int r = 0; r < num_row_blocks_e_ ; ++r) {
+ const Cell& cell = bs->rows[r].cells[0];
+ const int row_block_size = bs->rows[r].block.size;
+ const int block_id = cell.block_id;
+ const int col_block_size = bs->cols[block_id].size;
+ const int cell_position =
+ block_diagonal_structure->rows[block_id].cells[0].position;
+
+ MatrixTransposeMatrixMultiply
+ <kRowBlockSize, kEBlockSize, kRowBlockSize, kEBlockSize, 1>(
+ values + cell.position, row_block_size, col_block_size,
+ values + cell.position, row_block_size, col_block_size,
+ block_diagonal->mutable_values() + cell_position,
+ 0, 0, col_block_size, col_block_size);
+ }
+}
+
+// Similar to the code in RightMultiplyF, except instead of the matrix
+// vector multiply its an outer product.
+//
+// block_diagonal = block_diagonal(F'F)
+//
+template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
+void
+PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>::
+UpdateBlockDiagonalFtF(BlockSparseMatrix* block_diagonal) const {
+ const CompressedRowBlockStructure* bs = matrix_.block_structure();
+ const CompressedRowBlockStructure* block_diagonal_structure =
+ block_diagonal->block_structure();
+
+ block_diagonal->SetZero();
+ const double* values = matrix_.values();
+ for (int r = 0; r < num_row_blocks_e_; ++r) {
+ const int row_block_size = bs->rows[r].block.size;
+ const vector<Cell>& cells = bs->rows[r].cells;
+ for (int c = 1; c < cells.size(); ++c) {
+ const int col_block_id = cells[c].block_id;
+ const int col_block_size = bs->cols[col_block_id].size;
+ const int diagonal_block_id = col_block_id - num_col_blocks_e_;
+ const int cell_position =
+ block_diagonal_structure->rows[diagonal_block_id].cells[0].position;
+
+ MatrixTransposeMatrixMultiply
+ <kRowBlockSize, kFBlockSize, kRowBlockSize, kFBlockSize, 1>(
+ values + cells[c].position, row_block_size, col_block_size,
+ values + cells[c].position, row_block_size, col_block_size,
+ block_diagonal->mutable_values() + cell_position,
+ 0, 0, col_block_size, col_block_size);
+ }
+ }
+
+ for (int r = num_row_blocks_e_; r < bs->rows.size(); ++r) {
+ const int row_block_size = bs->rows[r].block.size;
+ const vector<Cell>& cells = bs->rows[r].cells;
+ for (int c = 0; c < cells.size(); ++c) {
+ const int col_block_id = cells[c].block_id;
+ const int col_block_size = bs->cols[col_block_id].size;
+ const int diagonal_block_id = col_block_id - num_col_blocks_e_;
+ const int cell_position =
+ block_diagonal_structure->rows[diagonal_block_id].cells[0].position;
+
+ MatrixTransposeMatrixMultiply
+ <Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, 1>(
+ values + cells[c].position, row_block_size, col_block_size,
+ values + cells[c].position, row_block_size, col_block_size,
+ block_diagonal->mutable_values() + cell_position,
+ 0, 0, col_block_size, col_block_size);
+ }
+ }
+}
+
+} // namespace internal
+} // namespace ceres
diff --git a/internal/ceres/partitioned_matrix_view_test.cc b/internal/ceres/partitioned_matrix_view_test.cc
index 48f7d24..ef5dae9 100644
--- a/internal/ceres/partitioned_matrix_view_test.cc
+++ b/internal/ceres/partitioned_matrix_view_test.cc
@@ -49,6 +49,7 @@
class PartitionedMatrixViewTest : public ::testing::Test {
protected :
virtual void SetUp() {
+ srand(5);
scoped_ptr<LinearLeastSquaresProblem> problem(
CreateLinearLeastSquaresProblemFromId(2));
CHECK_NOTNULL(problem.get());
@@ -57,108 +58,93 @@
num_cols_ = A_->num_cols();
num_rows_ = A_->num_rows();
num_eliminate_blocks_ = problem->num_eliminate_blocks;
+ LinearSolver::Options options;
+ options.elimination_groups.push_back(num_eliminate_blocks_);
+ pmv_.reset(PartitionedMatrixViewBase::Create(
+ options,
+ *down_cast<BlockSparseMatrix*>(A_.get())));
}
int num_rows_;
int num_cols_;
int num_eliminate_blocks_;
-
scoped_ptr<SparseMatrix> A_;
+ scoped_ptr<PartitionedMatrixViewBase> pmv_;
};
TEST_F(PartitionedMatrixViewTest, DimensionsTest) {
- PartitionedMatrixView m(*down_cast<BlockSparseMatrix*>(A_.get()),
- num_eliminate_blocks_);
- EXPECT_EQ(m.num_col_blocks_e(), num_eliminate_blocks_);
- EXPECT_EQ(m.num_col_blocks_f(), num_cols_ - num_eliminate_blocks_);
- EXPECT_EQ(m.num_cols_e(), num_eliminate_blocks_);
- EXPECT_EQ(m.num_cols_f(), num_cols_ - num_eliminate_blocks_);
- EXPECT_EQ(m.num_cols(), A_->num_cols());
- EXPECT_EQ(m.num_rows(), A_->num_rows());
+ EXPECT_EQ(pmv_->num_col_blocks_e(), num_eliminate_blocks_);
+ EXPECT_EQ(pmv_->num_col_blocks_f(), num_cols_ - num_eliminate_blocks_);
+ EXPECT_EQ(pmv_->num_cols_e(), num_eliminate_blocks_);
+ EXPECT_EQ(pmv_->num_cols_f(), num_cols_ - num_eliminate_blocks_);
+ EXPECT_EQ(pmv_->num_cols(), A_->num_cols());
+ EXPECT_EQ(pmv_->num_rows(), A_->num_rows());
}
TEST_F(PartitionedMatrixViewTest, RightMultiplyE) {
- PartitionedMatrixView m(*down_cast<BlockSparseMatrix*>(A_.get()),
- num_eliminate_blocks_);
-
- srand(5);
-
- Vector x1(m.num_cols_e());
- Vector x2(m.num_cols());
+ Vector x1(pmv_->num_cols_e());
+ Vector x2(pmv_->num_cols());
x2.setZero();
- for (int i = 0; i < m.num_cols_e(); ++i) {
+ for (int i = 0; i < pmv_->num_cols_e(); ++i) {
x1(i) = x2(i) = RandDouble();
}
- Vector y1 = Vector::Zero(m.num_rows());
- m.RightMultiplyE(x1.data(), y1.data());
+ Vector y1 = Vector::Zero(pmv_->num_rows());
+ pmv_->RightMultiplyE(x1.data(), y1.data());
- Vector y2 = Vector::Zero(m.num_rows());
+ Vector y2 = Vector::Zero(pmv_->num_rows());
A_->RightMultiply(x2.data(), y2.data());
- for (int i = 0; i < m.num_rows(); ++i) {
+ for (int i = 0; i < pmv_->num_rows(); ++i) {
EXPECT_NEAR(y1(i), y2(i), kEpsilon);
}
}
TEST_F(PartitionedMatrixViewTest, RightMultiplyF) {
- PartitionedMatrixView m(*down_cast<BlockSparseMatrix*>(A_.get()),
- num_eliminate_blocks_);
+ Vector x1(pmv_->num_cols_f());
+ Vector x2 = Vector::Zero(pmv_->num_cols());
- srand(5);
-
- Vector x1(m.num_cols_f());
- Vector x2 = Vector::Zero(m.num_cols());
-
- for (int i = 0; i < m.num_cols_f(); ++i) {
+ for (int i = 0; i < pmv_->num_cols_f(); ++i) {
x1(i) = RandDouble();
- x2(i + m.num_cols_e()) = x1(i);
+ x2(i + pmv_->num_cols_e()) = x1(i);
}
- Vector y1 = Vector::Zero(m.num_rows());
- m.RightMultiplyF(x1.data(), y1.data());
+ Vector y1 = Vector::Zero(pmv_->num_rows());
+ pmv_->RightMultiplyF(x1.data(), y1.data());
- Vector y2 = Vector::Zero(m.num_rows());
+ Vector y2 = Vector::Zero(pmv_->num_rows());
A_->RightMultiply(x2.data(), y2.data());
- for (int i = 0; i < m.num_rows(); ++i) {
+ for (int i = 0; i < pmv_->num_rows(); ++i) {
EXPECT_NEAR(y1(i), y2(i), kEpsilon);
}
}
TEST_F(PartitionedMatrixViewTest, LeftMultiply) {
- PartitionedMatrixView m(*down_cast<BlockSparseMatrix*>(A_.get()),
- num_eliminate_blocks_);
-
- srand(5);
-
- Vector x = Vector::Zero(m.num_rows());
- for (int i = 0; i < m.num_rows(); ++i) {
+ Vector x = Vector::Zero(pmv_->num_rows());
+ for (int i = 0; i < pmv_->num_rows(); ++i) {
x(i) = RandDouble();
}
- Vector y = Vector::Zero(m.num_cols());
- Vector y1 = Vector::Zero(m.num_cols_e());
- Vector y2 = Vector::Zero(m.num_cols_f());
+ Vector y = Vector::Zero(pmv_->num_cols());
+ Vector y1 = Vector::Zero(pmv_->num_cols_e());
+ Vector y2 = Vector::Zero(pmv_->num_cols_f());
A_->LeftMultiply(x.data(), y.data());
- m.LeftMultiplyE(x.data(), y1.data());
- m.LeftMultiplyF(x.data(), y2.data());
+ pmv_->LeftMultiplyE(x.data(), y1.data());
+ pmv_->LeftMultiplyF(x.data(), y2.data());
- for (int i = 0; i < m.num_cols(); ++i) {
+ for (int i = 0; i < pmv_->num_cols(); ++i) {
EXPECT_NEAR(y(i),
- (i < m.num_cols_e()) ? y1(i) : y2(i - m.num_cols_e()),
+ (i < pmv_->num_cols_e()) ? y1(i) : y2(i - pmv_->num_cols_e()),
kEpsilon);
}
}
TEST_F(PartitionedMatrixViewTest, BlockDiagonalEtE) {
- PartitionedMatrixView m(*down_cast<BlockSparseMatrix*>(A_.get()),
- num_eliminate_blocks_);
-
scoped_ptr<BlockSparseMatrix>
- block_diagonal_ee(m.CreateBlockDiagonalEtE());
+ block_diagonal_ee(pmv_->CreateBlockDiagonalEtE());
const CompressedRowBlockStructure* bs = block_diagonal_ee->block_structure();
EXPECT_EQ(block_diagonal_ee->num_rows(), 2);
@@ -171,11 +157,8 @@
}
TEST_F(PartitionedMatrixViewTest, BlockDiagonalFtF) {
- PartitionedMatrixView m(*down_cast<BlockSparseMatrix*>(A_.get()),
- num_eliminate_blocks_);
-
scoped_ptr<BlockSparseMatrix>
- block_diagonal_ff(m.CreateBlockDiagonalFtF());
+ block_diagonal_ff(pmv_->CreateBlockDiagonalFtF());
const CompressedRowBlockStructure* bs = block_diagonal_ff->block_structure();
EXPECT_EQ(block_diagonal_ff->num_rows(), 3);
diff --git a/internal/ceres/schur_jacobi_preconditioner.cc b/internal/ceres/schur_jacobi_preconditioner.cc
index 5b87e9f..46e6d02 100644
--- a/internal/ceres/schur_jacobi_preconditioner.cc
+++ b/internal/ceres/schur_jacobi_preconditioner.cc
@@ -36,7 +36,6 @@
#include "ceres/block_random_access_diagonal_matrix.h"
#include "ceres/block_sparse_matrix.h"
#include "ceres/collections_port.h"
-#include "ceres/detect_structure.h"
#include "ceres/internal/scoped_ptr.h"
#include "ceres/linear_solver.h"
#include "ceres/schur_eliminator.h"
@@ -71,18 +70,14 @@
// Initialize the SchurEliminator.
void SchurJacobiPreconditioner::InitEliminator(
const CompressedRowBlockStructure& bs) {
- LinearSolver::Options eliminator_options;
-
+ LinearSolver::Options eliminator_options;
eliminator_options.elimination_groups = options_.elimination_groups;
eliminator_options.num_threads = options_.num_threads;
-
- DetectStructure(bs, options_.elimination_groups[0],
- &eliminator_options.row_block_size,
- &eliminator_options.e_block_size,
- &eliminator_options.f_block_size);
-
+ eliminator_options.e_block_size = options_.e_block_size;
+ eliminator_options.f_block_size = options_.f_block_size;
+ eliminator_options.row_block_size = options_.row_block_size;
eliminator_.reset(SchurEliminatorBase::Create(eliminator_options));
- eliminator_->Init(options_.elimination_groups[0], &bs);
+ eliminator_->Init(eliminator_options.elimination_groups[0], &bs);
}
// Update the values of the preconditioner matrix and factorize it.
diff --git a/internal/ceres/visibility_based_preconditioner.cc b/internal/ceres/visibility_based_preconditioner.cc
index 7af1339..6535b42 100644
--- a/internal/ceres/visibility_based_preconditioner.cc
+++ b/internal/ceres/visibility_based_preconditioner.cc
@@ -43,7 +43,6 @@
#include "ceres/block_sparse_matrix.h"
#include "ceres/canonical_views_clustering.h"
#include "ceres/collections_port.h"
-#include "ceres/detect_structure.h"
#include "ceres/graph.h"
#include "ceres/graph_algorithms.h"
#include "ceres/internal/scoped_ptr.h"
@@ -313,14 +312,11 @@
LinearSolver::Options eliminator_options;
eliminator_options.elimination_groups = options_.elimination_groups;
eliminator_options.num_threads = options_.num_threads;
-
- DetectStructure(bs, options_.elimination_groups[0],
- &eliminator_options.row_block_size,
- &eliminator_options.e_block_size,
- &eliminator_options.f_block_size);
-
+ eliminator_options.e_block_size = options_.e_block_size;
+ eliminator_options.f_block_size = options_.f_block_size;
+ eliminator_options.row_block_size = options_.row_block_size;
eliminator_.reset(SchurEliminatorBase::Create(eliminator_options));
- eliminator_->Init(options_.elimination_groups[0], &bs);
+ eliminator_->Init(eliminator_options.elimination_groups[0], &bs);
}
// Update the values of the preconditioner matrix and factorize it.
diff --git a/jni/Android.mk b/jni/Android.mk
index c68f79b..3f37f35 100644
--- a/jni/Android.mk
+++ b/jni/Android.mk
@@ -63,8 +63,7 @@
#
# -DCERES_RESTRICT_SCHUR_SPECIALIZATION
#
-# to the LOCAL_CFLAGS variable below, and commenting out all the
-# generated/schur_eliminator_2_2_2.cc-alike files, leaving only the _d_d_d one.
+# to the LOCAL_CFLAGS variable below.
#
# Similarly if you do not need the line search minimizer, consider adding
#
@@ -195,7 +194,23 @@
$(CERES_SRC_PATH)/generated/schur_eliminator_4_4_2.cc \
$(CERES_SRC_PATH)/generated/schur_eliminator_4_4_3.cc \
$(CERES_SRC_PATH)/generated/schur_eliminator_4_4_4.cc \
- $(CERES_SRC_PATH)/generated/schur_eliminator_4_4_d.cc
+ $(CERES_SRC_PATH)/generated/schur_eliminator_4_4_d.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_d_d_d.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_2_2_2.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_2_2_3.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_2_2_4.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_2_2_d.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_2_3_3.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_2_3_4.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_2_3_9.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_2_3_d.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_2_4_3.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_2_4_4.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_2_4_d.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_4_4_2.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_4_4_3.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_4_4_4.cc \
+ $(CERES_SRC_PATH)/generated/partitioned_matrix_view_4_4_d.cc
ifndef CERES_GLOG_DIR
LOCAL_SRC_FILES += $(CERES_SRC_PATH)/miniglog/glog/logging.cc
