Add DynamicSparseNormalCholeskySolver
This code was currently buried under a bool inside SparseNormalCholeskySolver.
Pulling this out in its own solver makes the code simpler more readable
and more performant in the case of SuiteSparse.
Change-Id: I72379ca9ca162abbb83c12f7ee8ff92bc71e772c
diff --git a/internal/ceres/CMakeLists.txt b/internal/ceres/CMakeLists.txt
index 4159e39..7c42442 100644
--- a/internal/ceres/CMakeLists.txt
+++ b/internal/ceres/CMakeLists.txt
@@ -61,6 +61,7 @@
dogleg_strategy.cc
dynamic_compressed_row_jacobian_writer.cc
dynamic_compressed_row_sparse_matrix.cc
+ dynamic_sparse_normal_cholesky_solver.cc
evaluator.cc
file.cc
gradient_checker.cc
diff --git a/internal/ceres/dynamic_sparse_normal_cholesky_solver.cc b/internal/ceres/dynamic_sparse_normal_cholesky_solver.cc
new file mode 100644
index 0000000..2c893b4
--- /dev/null
+++ b/internal/ceres/dynamic_sparse_normal_cholesky_solver.cc
@@ -0,0 +1,292 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2017 Google Inc. All rights reserved.
+// http://ceres-solver.org/
+//
+// 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/dynamic_sparse_normal_cholesky_solver.h"
+
+#include <algorithm>
+#include <cstring>
+#include <ctime>
+#include <sstream>
+
+#include "Eigen/SparseCore"
+#include "ceres/compressed_row_sparse_matrix.h"
+#include "ceres/cxsparse.h"
+#include "ceres/internal/eigen.h"
+#include "ceres/internal/scoped_ptr.h"
+#include "ceres/linear_solver.h"
+#include "ceres/suitesparse.h"
+#include "ceres/triplet_sparse_matrix.h"
+#include "ceres/types.h"
+#include "ceres/wall_time.h"
+
+#ifdef CERES_USE_EIGEN_SPARSE
+#include "Eigen/SparseCholesky"
+#endif
+
+namespace ceres {
+namespace internal {
+
+DynamicSparseNormalCholeskySolver::DynamicSparseNormalCholeskySolver(
+ const LinearSolver::Options& options)
+ : options_(options) {}
+
+LinearSolver::Summary DynamicSparseNormalCholeskySolver::SolveImpl(
+ CompressedRowSparseMatrix* A,
+ const double* b,
+ const LinearSolver::PerSolveOptions& per_solve_options,
+ double* x) {
+ const int num_cols = A->num_cols();
+ VectorRef(x, num_cols).setZero();
+ A->LeftMultiply(b, x);
+
+ if (per_solve_options.D != NULL) {
+ // Temporarily append a diagonal block to the A matrix, but undo
+ // it before returning the matrix to the user.
+ scoped_ptr<CompressedRowSparseMatrix> regularizer;
+ if (A->col_blocks().size() > 0) {
+ regularizer.reset(CompressedRowSparseMatrix::CreateBlockDiagonalMatrix(
+ per_solve_options.D, A->col_blocks()));
+ } else {
+ regularizer.reset(
+ new CompressedRowSparseMatrix(per_solve_options.D, num_cols));
+ }
+ A->AppendRows(*regularizer);
+ }
+
+ LinearSolver::Summary summary;
+ switch (options_.sparse_linear_algebra_library_type) {
+ case SUITE_SPARSE:
+ summary = SolveImplUsingSuiteSparse(A, x);
+ break;
+ case CX_SPARSE:
+ summary = SolveImplUsingCXSparse(A, x);
+ break;
+ case EIGEN_SPARSE:
+ summary = SolveImplUsingEigen(A, x);
+ break;
+ default:
+ LOG(FATAL) << "Unknown sparse linear algebra library : "
+ << options_.sparse_linear_algebra_library_type;
+ }
+
+ if (per_solve_options.D != NULL) {
+ A->DeleteRows(num_cols);
+ }
+
+ return summary;
+}
+
+LinearSolver::Summary DynamicSparseNormalCholeskySolver::SolveImplUsingEigen(
+ CompressedRowSparseMatrix* A, double* rhs_and_solution) {
+#ifndef CERES_USE_EIGEN_SPARSE
+
+ LinearSolver::Summary summary;
+ summary.num_iterations = 0;
+ summary.termination_type = LINEAR_SOLVER_FATAL_ERROR;
+ summary.message =
+ "SPARSE_NORMAL_CHOLESKY cannot be used with EIGEN_SPARSE "
+ "because Ceres was not built with support for "
+ "Eigen's SimplicialLDLT decomposition. "
+ "This requires enabling building with -DEIGENSPARSE=ON.";
+ return summary;
+
+#else
+
+ EventLogger event_logger("DynamicSparseNormalCholeskySolver::Eigen::Solve");
+
+ Eigen::MappedSparseMatrix<double, Eigen::RowMajor> a(A->num_rows(),
+ A->num_cols(),
+ A->num_nonzeros(),
+ A->mutable_rows(),
+ A->mutable_cols(),
+ A->mutable_values());
+
+ Eigen::SparseMatrix<double> lhs = a.transpose() * a;
+ Eigen::SimplicialLDLT<Eigen::SparseMatrix<double> > solver;
+
+ LinearSolver::Summary summary;
+ summary.num_iterations = 1;
+ summary.termination_type = LINEAR_SOLVER_SUCCESS;
+ summary.message = "Success.";
+
+ solver.analyzePattern(lhs);
+ if (VLOG_IS_ON(2)) {
+ std::stringstream ss;
+ solver.dumpMemory(ss);
+ VLOG(2) << "Symbolic Analysis\n" << ss.str();
+ }
+
+ event_logger.AddEvent("Analyze");
+ if (solver.info() != Eigen::Success) {
+ summary.termination_type = LINEAR_SOLVER_FATAL_ERROR;
+ summary.message = "Eigen failure. Unable to find symbolic factorization.";
+ return summary;
+ }
+
+ solver.factorize(lhs);
+ event_logger.AddEvent("Factorize");
+ if (solver.info() != Eigen::Success) {
+ summary.termination_type = LINEAR_SOLVER_FAILURE;
+ summary.message = "Eigen failure. Unable to find numeric factorization.";
+ return summary;
+ }
+
+ const Vector rhs = VectorRef(rhs_and_solution, lhs.cols());
+ VectorRef(rhs_and_solution, lhs.cols()) = solver.solve(rhs);
+ event_logger.AddEvent("Solve");
+ if (solver.info() != Eigen::Success) {
+ summary.termination_type = LINEAR_SOLVER_FAILURE;
+ summary.message = "Eigen failure. Unable to do triangular solve.";
+ return summary;
+ }
+
+ return summary;
+#endif // CERES_USE_EIGEN_SPARSE
+}
+
+LinearSolver::Summary DynamicSparseNormalCholeskySolver::SolveImplUsingCXSparse(
+ CompressedRowSparseMatrix* A, double* rhs_and_solution) {
+#ifdef CERES_NO_CXSPARSE
+
+ LinearSolver::Summary summary;
+ summary.num_iterations = 0;
+ summary.termination_type = LINEAR_SOLVER_FATAL_ERROR;
+ summary.message =
+ "SPARSE_NORMAL_CHOLESKY cannot be used with CX_SPARSE "
+ "because Ceres was not built with support for CXSparse. "
+ "This requires enabling building with -DCXSPARSE=ON.";
+
+ return summary;
+
+#else
+ EventLogger event_logger(
+ "DynamicSparseNormalCholeskySolver::CXSparse::Solve");
+
+ LinearSolver::Summary summary;
+ summary.num_iterations = 1;
+ summary.termination_type = LINEAR_SOLVER_SUCCESS;
+ summary.message = "Success.";
+
+ CXSparse cxsparse;
+
+ // Wrap the augmented Jacobian in a compressed sparse column matrix.
+ cs_di a_transpose = cxsparse.CreateSparseMatrixTransposeView(A);
+
+ // Compute the normal equations. J'J delta = J'f and solve them
+ // using a sparse Cholesky factorization. Notice that when compared
+ // to SuiteSparse we have to explicitly compute the transpose of Jt,
+ // and then the normal equations before they can be
+ // factorized. CHOLMOD/SuiteSparse on the other hand can just work
+ // off of Jt to compute the Cholesky factorization of the normal
+ // equations.
+ cs_di* a = cxsparse.TransposeMatrix(&a_transpose);
+ cs_di* lhs = cxsparse.MatrixMatrixMultiply(&a_transpose, a);
+ cxsparse.Free(a);
+ event_logger.AddEvent("NormalEquations");
+
+ cs_dis* factor = cxsparse.AnalyzeCholesky(lhs);
+ event_logger.AddEvent("Analysis");
+
+ if (factor == NULL) {
+ summary.termination_type = LINEAR_SOLVER_FATAL_ERROR;
+ summary.message = "CXSparse::AnalyzeCholesky failed.";
+ } else if (!cxsparse.SolveCholesky(lhs, factor, rhs_and_solution)) {
+ summary.termination_type = LINEAR_SOLVER_FAILURE;
+ summary.message = "CXSparse::SolveCholesky failed.";
+ }
+ event_logger.AddEvent("Solve");
+
+ cxsparse.Free(lhs);
+ cxsparse.Free(factor);
+ event_logger.AddEvent("TearDown");
+ return summary;
+#endif
+}
+
+LinearSolver::Summary
+DynamicSparseNormalCholeskySolver::SolveImplUsingSuiteSparse(
+ CompressedRowSparseMatrix* A, double* rhs_and_solution) {
+#ifdef CERES_NO_SUITESPARSE
+
+ LinearSolver::Summary summary;
+ summary.num_iterations = 0;
+ summary.termination_type = LINEAR_SOLVER_FATAL_ERROR;
+ summary.message =
+ "SPARSE_NORMAL_CHOLESKY cannot be used with SUITE_SPARSE "
+ "because Ceres was not built with support for SuiteSparse. "
+ "This requires enabling building with -DSUITESPARSE=ON.";
+ return summary;
+
+#else
+
+ EventLogger event_logger(
+ "DynamicSparseNormalCholeskySolver::SuiteSparse::Solve");
+ LinearSolver::Summary summary;
+ summary.termination_type = LINEAR_SOLVER_SUCCESS;
+ summary.num_iterations = 1;
+ summary.message = "Success.";
+
+ SuiteSparse ss;
+ const int num_cols = A->num_cols();
+ cholmod_sparse lhs = ss.CreateSparseMatrixTransposeView(A, 0);
+ event_logger.AddEvent("Setup");
+ cholmod_factor* factor = ss.AnalyzeCholesky(&lhs, &summary.message);
+ event_logger.AddEvent("Analysis");
+
+ if (factor == NULL) {
+ summary.termination_type = LINEAR_SOLVER_FATAL_ERROR;
+ return summary;
+ }
+
+ summary.termination_type = ss.Cholesky(&lhs, factor, &summary.message);
+ if (summary.termination_type == LINEAR_SOLVER_SUCCESS) {
+ cholmod_dense* rhs =
+ ss.CreateDenseVector(rhs_and_solution, num_cols, num_cols);
+ cholmod_dense* solution = ss.Solve(factor, rhs, &summary.message);
+ event_logger.AddEvent("Solve");
+ ss.Free(rhs);
+ if (solution != NULL) {
+ memcpy(
+ rhs_and_solution, solution->x, num_cols * sizeof(*rhs_and_solution));
+ ss.Free(solution);
+ } else {
+ summary.termination_type = LINEAR_SOLVER_FAILURE;
+ }
+ }
+
+ ss.Free(factor);
+ event_logger.AddEvent("Teardown");
+ return summary;
+
+#endif
+}
+
+} // namespace internal
+} // namespace ceres
diff --git a/internal/ceres/dynamic_sparse_normal_cholesky_solver.h b/internal/ceres/dynamic_sparse_normal_cholesky_solver.h
new file mode 100644
index 0000000..9861f6b
--- /dev/null
+++ b/internal/ceres/dynamic_sparse_normal_cholesky_solver.h
@@ -0,0 +1,85 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2017 Google Inc. All rights reserved.
+// http://ceres-solver.org/
+//
+// 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)
+//
+// A solver for sparse linear least squares problem based on solving
+// the normal equations via a sparse cholesky factorization.
+
+#ifndef CERES_INTERNAL_DYNAMIC_SPARSE_NORMAL_CHOLESKY_SOLVER_H_
+#define CERES_INTERNAL_DYNAMIC_SPARSE_NORMAL_CHOLESKY_SOLVER_H_
+
+// This include must come before any #ifndef check on Ceres compile options.
+#include "ceres/internal/port.h"
+
+#include "ceres/internal/macros.h"
+#include "ceres/linear_solver.h"
+
+namespace ceres {
+namespace internal {
+
+class CompressedRowSparseMatrix;
+
+// A variant of SparseNormalCholeskySolver in the case where matrix
+// sparsity is not constant across calls to Solve. This means that
+// there is no benefit to symbolically factorizing the matrix and
+// caching this factorization.
+class DynamicSparseNormalCholeskySolver
+ : public CompressedRowSparseMatrixSolver {
+ public:
+ explicit DynamicSparseNormalCholeskySolver(
+ const LinearSolver::Options& options);
+ virtual ~DynamicSparseNormalCholeskySolver() {}
+
+ private:
+ virtual LinearSolver::Summary SolveImpl(
+ CompressedRowSparseMatrix* A,
+ const double* b,
+ const LinearSolver::PerSolveOptions& options,
+ double* x);
+
+ LinearSolver::Summary SolveImplUsingSuiteSparse(
+ CompressedRowSparseMatrix* A,
+ double* rhs_and_solution);
+
+ LinearSolver::Summary SolveImplUsingCXSparse(
+ CompressedRowSparseMatrix* A,
+ double* rhs_and_solution);
+
+ LinearSolver::Summary SolveImplUsingEigen(
+ CompressedRowSparseMatrix* A,
+ double* rhs_and_solution);
+
+ const LinearSolver::Options options_;
+ CERES_DISALLOW_COPY_AND_ASSIGN(DynamicSparseNormalCholeskySolver);
+};
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_INTERNAL_DYNAMIC_SPARSE_NORMAL_CHOLESKY_SOLVER_H_
diff --git a/internal/ceres/linear_solver.cc b/internal/ceres/linear_solver.cc
index 38e4625..81acc38 100644
--- a/internal/ceres/linear_solver.cc
+++ b/internal/ceres/linear_solver.cc
@@ -35,6 +35,7 @@
#include "ceres/dense_qr_solver.h"
#include "ceres/iterative_schur_complement_solver.h"
#include "ceres/schur_complement_solver.h"
+#include "ceres/dynamic_sparse_normal_cholesky_solver.h"
#include "ceres/sparse_normal_cholesky_solver.h"
#include "ceres/types.h"
#include "glog/logging.h"
@@ -80,6 +81,10 @@
!defined(CERES_USE_EIGEN_SPARSE)
return NULL;
#else
+ if (options.dynamic_sparsity) {
+ return new DynamicSparseNormalCholeskySolver(options);
+ }
+
return new SparseNormalCholeskySolver(options);
#endif
diff --git a/jni/Android.mk b/jni/Android.mk
index d60c0fc..9967885 100644
--- a/jni/Android.mk
+++ b/jni/Android.mk
@@ -144,6 +144,7 @@
$(CERES_SRC_PATH)/dogleg_strategy.cc \
$(CERES_SRC_PATH)/dynamic_compressed_row_jacobian_writer.cc \
$(CERES_SRC_PATH)/dynamic_compressed_row_sparse_matrix.cc \
+ $(CERES_SRC_PATH)/dynamic_sparse_normal_cholesky_solver.cc \
$(CERES_SRC_PATH)/evaluator.cc \
$(CERES_SRC_PATH)/file.cc \
$(CERES_SRC_PATH)/gradient_checker.cc \
