mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 16:40:38 +08:00
39ec5e8f99
With this change, the user can now choose between Approximate Minimum Degree and Nested Dissection as a fill reducing algorithm when using a sparse direct factorization based linear solver like SPARSE_NORMAL_CHOLESKY or SPARSE_SCHUR. Currenly only SUITE_SPARSE is supported. It requires that SuiteSparse be compiled with Metis support enabled. On most problems AMD is still the better choice, but in some cases like the grid3D dataset from https://lucacarlone.mit.edu/datasets/ the solution time with AMD is 57s and with NESDIS 38 on my M1 Mac. On some other problems at Google we have observed speedups of 10x, there is also a corresponding decrease in the total amount of memory used. This patch is based on the original work done by NeroBurner in https://ceres-solver-review.googlesource.com/c/ceres-solver/+/20580 1. Add a new enum to the public api LinearSolverOrderingType and a setting Solver::Options::linear_solver_ordering_type. 2. TrustRegionPreprocessor had some complicated logic which determined when linear solvers should reorder their matrices on their own and not this has been refactored into a more readable function that lives inside reorder_program.h/cc. 3. Plumbing in reorder_program.cc and trust_region_processor.cc to use nested dissection. 4. Update bundle_adjuster.cc to use nested dissection. Change-Id: I388b027934f86c58b4da2b65a4fa5204ea73bf40
462 lines
11 KiB
C++
462 lines
11 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2015 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: sameeragarwal@google.com (Sameer Agarwal)
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#include "ceres/types.h"
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#include <algorithm>
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#include <cctype>
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#include <string>
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#include "ceres/internal/config.h"
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#include "glog/logging.h"
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namespace ceres {
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using std::string;
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// clang-format off
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#define CASESTR(x) case x: return #x
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#define STRENUM(x) if (value == #x) { *type = x; return true; }
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// clang-format on
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static void UpperCase(string* input) {
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std::transform(input->begin(), input->end(), input->begin(), ::toupper);
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}
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const char* LinearSolverTypeToString(LinearSolverType type) {
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switch (type) {
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CASESTR(DENSE_NORMAL_CHOLESKY);
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CASESTR(DENSE_QR);
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CASESTR(SPARSE_NORMAL_CHOLESKY);
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CASESTR(DENSE_SCHUR);
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CASESTR(SPARSE_SCHUR);
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CASESTR(ITERATIVE_SCHUR);
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CASESTR(CGNR);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToLinearSolverType(string value, LinearSolverType* type) {
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UpperCase(&value);
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STRENUM(DENSE_NORMAL_CHOLESKY);
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STRENUM(DENSE_QR);
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STRENUM(SPARSE_NORMAL_CHOLESKY);
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STRENUM(DENSE_SCHUR);
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STRENUM(SPARSE_SCHUR);
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STRENUM(ITERATIVE_SCHUR);
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STRENUM(CGNR);
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return false;
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}
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const char* PreconditionerTypeToString(PreconditionerType type) {
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switch (type) {
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CASESTR(IDENTITY);
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CASESTR(JACOBI);
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CASESTR(SCHUR_JACOBI);
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CASESTR(CLUSTER_JACOBI);
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CASESTR(CLUSTER_TRIDIAGONAL);
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CASESTR(SUBSET);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToPreconditionerType(string value, PreconditionerType* type) {
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UpperCase(&value);
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STRENUM(IDENTITY);
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STRENUM(JACOBI);
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STRENUM(SCHUR_JACOBI);
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STRENUM(CLUSTER_JACOBI);
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STRENUM(CLUSTER_TRIDIAGONAL);
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STRENUM(SUBSET);
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return false;
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}
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const char* SparseLinearAlgebraLibraryTypeToString(
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SparseLinearAlgebraLibraryType type) {
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switch (type) {
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CASESTR(SUITE_SPARSE);
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CASESTR(CX_SPARSE);
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CASESTR(EIGEN_SPARSE);
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CASESTR(ACCELERATE_SPARSE);
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CASESTR(NO_SPARSE);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToSparseLinearAlgebraLibraryType(
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string value, SparseLinearAlgebraLibraryType* type) {
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UpperCase(&value);
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STRENUM(SUITE_SPARSE);
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STRENUM(CX_SPARSE);
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STRENUM(EIGEN_SPARSE);
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STRENUM(ACCELERATE_SPARSE);
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STRENUM(NO_SPARSE);
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return false;
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}
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const char* LinearSolverOrderingTypeToString(LinearSolverOrderingType type) {
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switch (type) {
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CASESTR(AMD);
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CASESTR(NESDIS);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToLinearSolverOrderingType(string value,
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LinearSolverOrderingType* type) {
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UpperCase(&value);
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STRENUM(AMD);
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STRENUM(NESDIS);
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return false;
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}
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const char* DenseLinearAlgebraLibraryTypeToString(
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DenseLinearAlgebraLibraryType type) {
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switch (type) {
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CASESTR(EIGEN);
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CASESTR(LAPACK);
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CASESTR(CUDA);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToDenseLinearAlgebraLibraryType(
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string value, DenseLinearAlgebraLibraryType* type) {
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UpperCase(&value);
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STRENUM(EIGEN);
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STRENUM(LAPACK);
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STRENUM(CUDA);
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return false;
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}
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const char* TrustRegionStrategyTypeToString(TrustRegionStrategyType type) {
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switch (type) {
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CASESTR(LEVENBERG_MARQUARDT);
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CASESTR(DOGLEG);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToTrustRegionStrategyType(string value,
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TrustRegionStrategyType* type) {
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UpperCase(&value);
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STRENUM(LEVENBERG_MARQUARDT);
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STRENUM(DOGLEG);
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return false;
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}
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const char* DoglegTypeToString(DoglegType type) {
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switch (type) {
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CASESTR(TRADITIONAL_DOGLEG);
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CASESTR(SUBSPACE_DOGLEG);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToDoglegType(string value, DoglegType* type) {
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UpperCase(&value);
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STRENUM(TRADITIONAL_DOGLEG);
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STRENUM(SUBSPACE_DOGLEG);
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return false;
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}
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const char* MinimizerTypeToString(MinimizerType type) {
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switch (type) {
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CASESTR(TRUST_REGION);
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CASESTR(LINE_SEARCH);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToMinimizerType(string value, MinimizerType* type) {
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UpperCase(&value);
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STRENUM(TRUST_REGION);
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STRENUM(LINE_SEARCH);
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return false;
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}
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const char* LineSearchDirectionTypeToString(LineSearchDirectionType type) {
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switch (type) {
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CASESTR(STEEPEST_DESCENT);
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CASESTR(NONLINEAR_CONJUGATE_GRADIENT);
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CASESTR(LBFGS);
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CASESTR(BFGS);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToLineSearchDirectionType(string value,
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LineSearchDirectionType* type) {
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UpperCase(&value);
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STRENUM(STEEPEST_DESCENT);
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STRENUM(NONLINEAR_CONJUGATE_GRADIENT);
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STRENUM(LBFGS);
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STRENUM(BFGS);
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return false;
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}
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const char* LineSearchTypeToString(LineSearchType type) {
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switch (type) {
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CASESTR(ARMIJO);
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CASESTR(WOLFE);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToLineSearchType(string value, LineSearchType* type) {
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UpperCase(&value);
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STRENUM(ARMIJO);
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STRENUM(WOLFE);
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return false;
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}
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const char* LineSearchInterpolationTypeToString(
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LineSearchInterpolationType type) {
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switch (type) {
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CASESTR(BISECTION);
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CASESTR(QUADRATIC);
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CASESTR(CUBIC);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToLineSearchInterpolationType(string value,
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LineSearchInterpolationType* type) {
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UpperCase(&value);
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STRENUM(BISECTION);
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STRENUM(QUADRATIC);
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STRENUM(CUBIC);
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return false;
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}
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const char* NonlinearConjugateGradientTypeToString(
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NonlinearConjugateGradientType type) {
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switch (type) {
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CASESTR(FLETCHER_REEVES);
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CASESTR(POLAK_RIBIERE);
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CASESTR(HESTENES_STIEFEL);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToNonlinearConjugateGradientType(
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string value, NonlinearConjugateGradientType* type) {
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UpperCase(&value);
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STRENUM(FLETCHER_REEVES);
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STRENUM(POLAK_RIBIERE);
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STRENUM(HESTENES_STIEFEL);
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return false;
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}
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const char* CovarianceAlgorithmTypeToString(CovarianceAlgorithmType type) {
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switch (type) {
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CASESTR(DENSE_SVD);
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CASESTR(SPARSE_QR);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToCovarianceAlgorithmType(string value,
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CovarianceAlgorithmType* type) {
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UpperCase(&value);
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STRENUM(DENSE_SVD);
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STRENUM(SPARSE_QR);
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return false;
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}
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const char* NumericDiffMethodTypeToString(NumericDiffMethodType type) {
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switch (type) {
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CASESTR(CENTRAL);
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CASESTR(FORWARD);
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CASESTR(RIDDERS);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToNumericDiffMethodType(string value, NumericDiffMethodType* type) {
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UpperCase(&value);
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STRENUM(CENTRAL);
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STRENUM(FORWARD);
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STRENUM(RIDDERS);
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return false;
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}
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const char* VisibilityClusteringTypeToString(VisibilityClusteringType type) {
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switch (type) {
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CASESTR(CANONICAL_VIEWS);
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CASESTR(SINGLE_LINKAGE);
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default:
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return "UNKNOWN";
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}
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}
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bool StringToVisibilityClusteringType(string value,
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VisibilityClusteringType* type) {
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UpperCase(&value);
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STRENUM(CANONICAL_VIEWS);
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STRENUM(SINGLE_LINKAGE);
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return false;
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}
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const char* TerminationTypeToString(TerminationType type) {
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switch (type) {
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CASESTR(CONVERGENCE);
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CASESTR(NO_CONVERGENCE);
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CASESTR(FAILURE);
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CASESTR(USER_SUCCESS);
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CASESTR(USER_FAILURE);
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default:
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return "UNKNOWN";
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}
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}
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const char* LoggingTypeToString(LoggingType type) {
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switch (type) {
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CASESTR(SILENT);
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CASESTR(PER_MINIMIZER_ITERATION);
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default:
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return "UNKNOWN";
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}
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}
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bool StringtoLoggingType(std::string value, LoggingType* type) {
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UpperCase(&value);
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STRENUM(SILENT);
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STRENUM(PER_MINIMIZER_ITERATION);
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return false;
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}
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const char* DumpFormatTypeToString(DumpFormatType type) {
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switch (type) {
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CASESTR(CONSOLE);
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CASESTR(TEXTFILE);
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default:
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return "UNKNOWN";
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}
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}
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bool StringtoDumpFormatType(std::string value, DumpFormatType* type) {
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UpperCase(&value);
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STRENUM(CONSOLE);
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STRENUM(TEXTFILE);
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return false;
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}
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#undef CASESTR
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#undef STRENUM
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bool IsSchurType(LinearSolverType type) {
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// clang-format off
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return ((type == SPARSE_SCHUR) ||
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(type == DENSE_SCHUR) ||
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(type == ITERATIVE_SCHUR));
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// clang-format on
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}
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bool IsSparseLinearAlgebraLibraryTypeAvailable(
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SparseLinearAlgebraLibraryType type) {
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if (type == SUITE_SPARSE) {
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#ifdef CERES_NO_SUITESPARSE
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return false;
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#else
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return true;
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#endif
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}
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if (type == CX_SPARSE) {
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#ifdef CERES_NO_CXSPARSE
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return false;
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#else
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return true;
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#endif
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}
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if (type == ACCELERATE_SPARSE) {
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#ifdef CERES_NO_ACCELERATE_SPARSE
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return false;
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#else
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return true;
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#endif
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}
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if (type == EIGEN_SPARSE) {
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#ifdef CERES_USE_EIGEN_SPARSE
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return true;
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#else
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return false;
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#endif
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}
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LOG(WARNING) << "Unknown sparse linear algebra library " << type;
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return false;
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}
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bool IsDenseLinearAlgebraLibraryTypeAvailable(
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DenseLinearAlgebraLibraryType type) {
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if (type == EIGEN) {
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return true;
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}
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if (type == LAPACK) {
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#ifdef CERES_NO_LAPACK
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return false;
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#else
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return true;
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#endif
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}
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if (type == CUDA) {
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#ifdef CERES_NO_CUDA
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return false;
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#else
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return true;
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#endif
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}
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LOG(WARNING) << "Unknown dense linear algebra library " << type;
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return false;
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}
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} // namespace ceres
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