mirror of
https://github.com/ceres-solver/ceres-solver.git
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806af056fe
This change restructures the `TinySolver` template and its associated adapters (`AutoDiff` and `CostFunction`) to make maximum sizing attributes first-class parameters. This enables the entire `TinySolver` stack to be used in restricted environments (e.g., small MCUs) without dynamic memory allocation, even when the number of residuals or parameters is only known at runtime (`Eigen::Dynamic`). Specifically: - Adds `kMaxResiduals` and `kMaxParameters` template parameters to `TinySolver`. - Updated `TinySolverAutoDiffFunction` and `TinySolverCostFunctionAdapter` to support optional maximum size template parameters for their internal buffers. - The new API maintains backward compatibility for existing users by defaulting to the sizes defined in the `Function`'s enums. - This structure also supports reducing code bloat by allowing `TinySolver` to be instantiated with an abstract base class, using dynamic dispatch for cost function evaluation. New test cases for `TinySolver` and its adapters verify the zero-allocation behavior and the unified API flexibility. Change-Id: Ic6f43984d384dbe71472b31c5ebd2b538d61f19d
230 lines
7.1 KiB
C++
230 lines
7.1 KiB
C++
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// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2023 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: mierle@gmail.com (Keir Mierle)
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#define EIGEN_RUNTIME_NO_MALLOC // Needed for enabling memory allocation
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// assertions in Eigen.
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#include "ceres/tiny_solver.h"
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#include <algorithm>
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#include <cmath>
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#include "Eigen/Core"
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#include "ceres/tiny_solver_test_util.h"
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#include "gtest/gtest.h"
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namespace ceres {
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using Vec2 = Eigen::Matrix<double, 2, 1>;
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using Vec3 = Eigen::Matrix<double, 3, 1>;
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using VecX = Eigen::VectorXd;
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class ExampleStatic {
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public:
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using Scalar = double;
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enum {
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// Can also be Eigen::Dynamic.
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NUM_RESIDUALS = 2,
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NUM_PARAMETERS = 3,
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};
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bool operator()(const double* parameters,
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double* residuals,
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double* jacobian) const {
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return EvaluateResidualsAndJacobians(parameters, residuals, jacobian);
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}
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};
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class ExampleParametersDynamic {
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public:
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using Scalar = double;
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enum {
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NUM_RESIDUALS = 2,
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NUM_PARAMETERS = Eigen::Dynamic,
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};
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int NumParameters() const { return 3; }
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bool operator()(const double* parameters,
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double* residuals,
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double* jacobian) const {
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return EvaluateResidualsAndJacobians(parameters, residuals, jacobian);
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}
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};
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class ExampleResidualsDynamic {
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public:
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using Scalar = double;
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enum {
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NUM_RESIDUALS = Eigen::Dynamic,
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NUM_PARAMETERS = 3,
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};
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int NumResiduals() const { return 2; }
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bool operator()(const double* parameters,
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double* residuals,
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double* jacobian) const {
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return EvaluateResidualsAndJacobians(parameters, residuals, jacobian);
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}
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};
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class ExampleAllDynamic {
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public:
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using Scalar = double;
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enum {
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NUM_RESIDUALS = Eigen::Dynamic,
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NUM_PARAMETERS = Eigen::Dynamic,
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};
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int NumResiduals() const { return 2; }
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int NumParameters() const { return 3; }
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bool operator()(const double* parameters,
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double* residuals,
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double* jacobian) const {
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return EvaluateResidualsAndJacobians(parameters, residuals, jacobian);
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}
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};
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template <typename Function, typename Vector,
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int kMaxResiduals = Function::NUM_RESIDUALS,
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int kMaxParameters = Function::NUM_PARAMETERS>
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void TestHelper(const Function& f, const Vector& x0) {
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Vector x = x0;
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Vec2 residuals;
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f(x.data(), residuals.data(), nullptr);
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EXPECT_GT(residuals.squaredNorm() / 2.0, 1e-10);
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TinySolver<Function, kMaxResiduals, kMaxParameters> solver;
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solver.Solve(f, &x);
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EXPECT_NEAR(0.0, solver.summary.final_cost, 1e-10);
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// Getter methods for residuals and jacobian should match the corresponding
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// values evaluated at the converged parameter value.
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Vec2 expected_residuals;
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Eigen::Matrix<double, 2, 3> expected_jacobian;
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f(x.data(), expected_residuals.data(), expected_jacobian.data());
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EXPECT_TRUE(expected_residuals.isApprox(solver.Residuals()));
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EXPECT_TRUE(expected_jacobian.isApprox(solver.Jacobian()));
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}
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// A test case for when the cost function is statically sized.
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TEST(TinySolver, SimpleExample) {
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Vec3 x0(0.76026643, -30.01799744, 0.55192142);
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ExampleStatic f;
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TestHelper(f, x0);
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}
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// A test case for when the number of parameters is dynamically sized.
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TEST(TinySolver, ParametersDynamic) {
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VecX x0(3);
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x0 << 0.76026643, -30.01799744, 0.55192142;
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ExampleParametersDynamic f;
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TestHelper(f, x0);
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}
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// A test case for when the number of residuals is dynamically sized.
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TEST(TinySolver, ResidualsDynamic) {
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Vec3 x0(0.76026643, -30.01799744, 0.55192142);
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ExampleResidualsDynamic f;
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TestHelper(f, x0);
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}
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// A test case for when the number of parameters and residuals is
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// dynamically sized.
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TEST(TinySolver, ParametersAndResidualsDynamic) {
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VecX x0(3);
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x0 << 0.76026643, -30.01799744, 0.55192142;
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ExampleAllDynamic f;
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TestHelper(f, x0);
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}
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// A test case for when the number of parameters and residuals is dynamically
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// sized, but the maximum number of parameters and residuals is statically
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// sized.
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TEST(TinySolver, AllDynamicWithMaxNumResidualsAndParameters) {
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// Enable assertions for memory allocation in Eigen.
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Eigen::internal::set_is_malloc_allowed(false);
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Eigen::Matrix<double, Eigen::Dynamic, 1, 0, 5, 1> x0(3);
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x0 << 0.76026643, -30.01799744, 0.55192142;
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ExampleAllDynamic f;
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TestHelper<ExampleAllDynamic, decltype(x0), 5, 5>(f, x0);
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// Re-enable dynamic memory allocation in Eigen.
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Eigen::internal::set_is_malloc_allowed(true);
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}
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// A test case to make sure dynamic memory allocation assertions can be enabled
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// in Eigen. Eigen assertions are only enabled when NDEBUG is not defined.
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// Otherwise, the assertions are compiled out as no-op.
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#if !defined(EIGEN_NO_DEBUG)
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TEST(TinySolver, EigenMallocAssertions) {
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// Enable assertions for memory allocation in Eigen.
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Eigen::internal::set_is_malloc_allowed(false);
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// Make sure dynamic memory allocation is not allowed.
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ASSERT_DEATH(VecX x0(10), "EIGEN_RUNTIME_NO_MALLOC is defined");
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// Re-enable dynamic memory allocation in Eigen.
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Eigen::internal::set_is_malloc_allowed(true);
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}
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// A test case for when the number of parameters and residuals is
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// dynamically sized requires dynamic allocation.
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TEST(TinySolver, ParametersAndResidualsDynamicNeedsDynamicAllocation) {
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VecX x0(3);
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x0 << 0.76026643, -30.01799744, 0.55192142;
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ExampleAllDynamic f;
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// Enable assertions for memory allocation in Eigen.
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Eigen::internal::set_is_malloc_allowed(false);
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ASSERT_DEATH(TestHelper(f, x0), "EIGEN_RUNTIME_NO_MALLOC is defined");
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// Re-enable dynamic memory allocation in Eigen.
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Eigen::internal::set_is_malloc_allowed(true);
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}
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#endif // !defined(EIGEN_NO_DEBUG)
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} // namespace ceres
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