| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2023 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/reorder_program.h" |
| |
| #include <algorithm> |
| #include <memory> |
| #include <random> |
| #include <string> |
| #include <unordered_set> |
| #include <vector> |
| |
| #include "ceres/internal/config.h" |
| #include "ceres/ordered_groups.h" |
| #include "ceres/parameter_block.h" |
| #include "ceres/problem.h" |
| #include "ceres/problem_impl.h" |
| #include "ceres/program.h" |
| #include "ceres/sized_cost_function.h" |
| #include "ceres/solver.h" |
| #include "ceres/types.h" |
| #include "gmock/gmock.h" |
| #include "gtest/gtest.h" |
| |
| namespace ceres { |
| namespace internal { |
| |
| // Templated base class for the CostFunction signatures. |
| template <int kNumResiduals, int... Ns> |
| class MockCostFunctionBase : public SizedCostFunction<kNumResiduals, Ns...> { |
| public: |
| bool Evaluate(double const* const* parameters, |
| double* residuals, |
| double** jacobians) const final { |
| // Do nothing. This is never called. |
| return true; |
| } |
| }; |
| |
| class UnaryCostFunction : public MockCostFunctionBase<2, 1> {}; |
| class BinaryCostFunction : public MockCostFunctionBase<2, 1, 1> {}; |
| class TernaryCostFunction : public MockCostFunctionBase<2, 1, 1, 1> {}; |
| |
| TEST(_, ReorderResidualBlockNormalFunction) { |
| ProblemImpl problem; |
| double x; |
| double y; |
| double z; |
| |
| problem.AddParameterBlock(&x, 1); |
| problem.AddParameterBlock(&y, 1); |
| problem.AddParameterBlock(&z, 1); |
| |
| problem.AddResidualBlock(new UnaryCostFunction(), nullptr, &x); |
| problem.AddResidualBlock(new BinaryCostFunction(), nullptr, &z, &x); |
| problem.AddResidualBlock(new BinaryCostFunction(), nullptr, &z, &y); |
| problem.AddResidualBlock(new UnaryCostFunction(), nullptr, &z); |
| problem.AddResidualBlock(new BinaryCostFunction(), nullptr, &x, &y); |
| problem.AddResidualBlock(new UnaryCostFunction(), nullptr, &y); |
| |
| auto linear_solver_ordering = std::make_shared<ParameterBlockOrdering>(); |
| linear_solver_ordering->AddElementToGroup(&x, 0); |
| linear_solver_ordering->AddElementToGroup(&y, 0); |
| linear_solver_ordering->AddElementToGroup(&z, 1); |
| |
| Solver::Options options; |
| options.linear_solver_type = DENSE_SCHUR; |
| options.linear_solver_ordering = linear_solver_ordering; |
| |
| const std::vector<ResidualBlock*>& residual_blocks = |
| problem.program().residual_blocks(); |
| |
| std::vector<ResidualBlock*> expected_residual_blocks; |
| |
| // This is a bit fragile, but it serves the purpose. We know the |
| // bucketing algorithm that the reordering function uses, so we |
| // expect the order for residual blocks for each e_block to be |
| // filled in reverse. |
| expected_residual_blocks.push_back(residual_blocks[4]); |
| expected_residual_blocks.push_back(residual_blocks[1]); |
| expected_residual_blocks.push_back(residual_blocks[0]); |
| expected_residual_blocks.push_back(residual_blocks[5]); |
| expected_residual_blocks.push_back(residual_blocks[2]); |
| expected_residual_blocks.push_back(residual_blocks[3]); |
| |
| Program* program = problem.mutable_program(); |
| program->SetParameterOffsetsAndIndex(); |
| |
| std::string message; |
| EXPECT_TRUE(LexicographicallyOrderResidualBlocks( |
| 2, problem.mutable_program(), &message)); |
| EXPECT_EQ(residual_blocks.size(), expected_residual_blocks.size()); |
| for (int i = 0; i < expected_residual_blocks.size(); ++i) { |
| EXPECT_EQ(residual_blocks[i], expected_residual_blocks[i]); |
| } |
| } |
| |
| TEST(_, ApplyOrderingOrderingTooSmall) { |
| ProblemImpl problem; |
| double x; |
| double y; |
| double z; |
| |
| problem.AddParameterBlock(&x, 1); |
| problem.AddParameterBlock(&y, 1); |
| problem.AddParameterBlock(&z, 1); |
| |
| ParameterBlockOrdering linear_solver_ordering; |
| linear_solver_ordering.AddElementToGroup(&x, 0); |
| linear_solver_ordering.AddElementToGroup(&y, 1); |
| |
| Program program(problem.program()); |
| std::string message; |
| EXPECT_FALSE(ApplyOrdering( |
| problem.parameter_map(), linear_solver_ordering, &program, &message)); |
| } |
| |
| TEST(_, ApplyOrderingNormal) { |
| ProblemImpl problem; |
| double x; |
| double y; |
| double z; |
| |
| problem.AddParameterBlock(&x, 1); |
| problem.AddParameterBlock(&y, 1); |
| problem.AddParameterBlock(&z, 1); |
| |
| ParameterBlockOrdering linear_solver_ordering; |
| linear_solver_ordering.AddElementToGroup(&x, 0); |
| linear_solver_ordering.AddElementToGroup(&y, 2); |
| linear_solver_ordering.AddElementToGroup(&z, 1); |
| |
| Program* program = problem.mutable_program(); |
| std::string message; |
| |
| EXPECT_TRUE(ApplyOrdering( |
| problem.parameter_map(), linear_solver_ordering, program, &message)); |
| const std::vector<ParameterBlock*>& parameter_blocks = |
| program->parameter_blocks(); |
| |
| EXPECT_EQ(parameter_blocks.size(), 3); |
| EXPECT_EQ(parameter_blocks[0]->user_state(), &x); |
| EXPECT_EQ(parameter_blocks[1]->user_state(), &z); |
| EXPECT_EQ(parameter_blocks[2]->user_state(), &y); |
| } |
| |
| #ifndef CERES_NO_SUITESPARSE |
| class ReorderProgramForSparseCholeskyUsingSuiteSparseTest |
| : public ::testing::Test { |
| protected: |
| void SetUp() override { |
| problem_.AddResidualBlock(new UnaryCostFunction(), nullptr, &x_); |
| problem_.AddResidualBlock(new BinaryCostFunction(), nullptr, &z_, &x_); |
| problem_.AddResidualBlock(new BinaryCostFunction(), nullptr, &z_, &y_); |
| problem_.AddResidualBlock(new UnaryCostFunction(), nullptr, &z_); |
| problem_.AddResidualBlock(new BinaryCostFunction(), nullptr, &x_, &y_); |
| problem_.AddResidualBlock(new UnaryCostFunction(), nullptr, &y_); |
| } |
| |
| void ComputeAndValidateOrdering( |
| const ParameterBlockOrdering& linear_solver_ordering) { |
| Program* program = problem_.mutable_program(); |
| std::vector<ParameterBlock*> unordered_parameter_blocks = |
| program->parameter_blocks(); |
| |
| std::string error; |
| EXPECT_TRUE(ReorderProgramForSparseCholesky(ceres::SUITE_SPARSE, |
| ceres::AMD, |
| linear_solver_ordering, |
| 0, /* use all rows */ |
| program, |
| &error)); |
| const std::vector<ParameterBlock*>& ordered_parameter_blocks = |
| program->parameter_blocks(); |
| EXPECT_EQ(ordered_parameter_blocks.size(), |
| unordered_parameter_blocks.size()); |
| |
| EXPECT_THAT(unordered_parameter_blocks, |
| ::testing::UnorderedElementsAreArray(ordered_parameter_blocks)); |
| } |
| |
| ProblemImpl problem_; |
| double x_; |
| double y_; |
| double z_; |
| }; |
| |
| TEST_F(ReorderProgramForSparseCholeskyUsingSuiteSparseTest, |
| EverythingInGroupZero) { |
| ParameterBlockOrdering linear_solver_ordering; |
| linear_solver_ordering.AddElementToGroup(&x_, 0); |
| linear_solver_ordering.AddElementToGroup(&y_, 0); |
| linear_solver_ordering.AddElementToGroup(&z_, 0); |
| |
| ComputeAndValidateOrdering(linear_solver_ordering); |
| } |
| |
| TEST_F(ReorderProgramForSparseCholeskyUsingSuiteSparseTest, ContiguousGroups) { |
| ParameterBlockOrdering linear_solver_ordering; |
| linear_solver_ordering.AddElementToGroup(&x_, 0); |
| linear_solver_ordering.AddElementToGroup(&y_, 1); |
| linear_solver_ordering.AddElementToGroup(&z_, 2); |
| |
| ComputeAndValidateOrdering(linear_solver_ordering); |
| } |
| |
| TEST_F(ReorderProgramForSparseCholeskyUsingSuiteSparseTest, GroupsWithGaps) { |
| ParameterBlockOrdering linear_solver_ordering; |
| linear_solver_ordering.AddElementToGroup(&x_, 0); |
| linear_solver_ordering.AddElementToGroup(&y_, 2); |
| linear_solver_ordering.AddElementToGroup(&z_, 2); |
| |
| ComputeAndValidateOrdering(linear_solver_ordering); |
| } |
| |
| TEST_F(ReorderProgramForSparseCholeskyUsingSuiteSparseTest, |
| NonContiguousStartingAtTwo) { |
| ParameterBlockOrdering linear_solver_ordering; |
| linear_solver_ordering.AddElementToGroup(&x_, 2); |
| linear_solver_ordering.AddElementToGroup(&y_, 4); |
| linear_solver_ordering.AddElementToGroup(&z_, 4); |
| |
| ComputeAndValidateOrdering(linear_solver_ordering); |
| } |
| #endif // CERES_NO_SUITESPARSE |
| |
| TEST(_, ReorderResidualBlocksbyPartition) { |
| ProblemImpl problem; |
| double x; |
| double y; |
| double z; |
| |
| problem.AddParameterBlock(&x, 1); |
| problem.AddParameterBlock(&y, 1); |
| problem.AddParameterBlock(&z, 1); |
| |
| problem.AddResidualBlock(new UnaryCostFunction(), nullptr, &x); |
| problem.AddResidualBlock(new BinaryCostFunction(), nullptr, &z, &x); |
| problem.AddResidualBlock(new BinaryCostFunction(), nullptr, &z, &y); |
| problem.AddResidualBlock(new UnaryCostFunction(), nullptr, &z); |
| problem.AddResidualBlock(new BinaryCostFunction(), nullptr, &x, &y); |
| problem.AddResidualBlock(new UnaryCostFunction(), nullptr, &y); |
| |
| std::vector<ResidualBlockId> residual_block_ids; |
| problem.GetResidualBlocks(&residual_block_ids); |
| std::vector<ResidualBlock*> residual_blocks = |
| problem.program().residual_blocks(); |
| auto rng = std::mt19937{}; |
| for (int i = 1; i < 6; ++i) { |
| std::shuffle( |
| std::begin(residual_block_ids), std::end(residual_block_ids), rng); |
| std::unordered_set<ResidualBlockId> bottom(residual_block_ids.begin(), |
| residual_block_ids.begin() + i); |
| const int start_bottom = |
| ReorderResidualBlocksByPartition(bottom, problem.mutable_program()); |
| std::vector<ResidualBlock*> actual_residual_blocks = |
| problem.program().residual_blocks(); |
| EXPECT_THAT(actual_residual_blocks, |
| testing::UnorderedElementsAreArray(residual_blocks)); |
| EXPECT_EQ(start_bottom, residual_blocks.size() - i); |
| for (int j = start_bottom; j < residual_blocks.size(); ++j) { |
| EXPECT_THAT(bottom, ::testing::Contains(actual_residual_blocks[j])); |
| } |
| } |
| } |
| |
| } // namespace internal |
| } // namespace ceres |