|  | // Ceres Solver - A fast non-linear least squares minimizer | 
|  | // Copyright 2019 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 | 
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|  | // 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/autodiff_cost_function.h" | 
|  |  | 
|  | #include <memory> | 
|  |  | 
|  | #include "ceres/array_utils.h" | 
|  | #include "ceres/cost_function.h" | 
|  | #include "gtest/gtest.h" | 
|  |  | 
|  | namespace ceres { | 
|  | namespace internal { | 
|  |  | 
|  | class BinaryScalarCost { | 
|  | public: | 
|  | explicit BinaryScalarCost(double a) : a_(a) {} | 
|  | template <typename T> | 
|  | bool operator()(const T* const x, const T* const y, T* cost) const { | 
|  | cost[0] = x[0] * y[0] + x[1] * y[1] - T(a_); | 
|  | return true; | 
|  | } | 
|  |  | 
|  | private: | 
|  | double a_; | 
|  | }; | 
|  |  | 
|  | TEST(AutodiffCostFunction, BilinearDifferentiationTest) { | 
|  | CostFunction* cost_function = | 
|  | new AutoDiffCostFunction<BinaryScalarCost, 1, 2, 2>( | 
|  | new BinaryScalarCost(1.0)); | 
|  |  | 
|  | auto** parameters = new double*[2]; | 
|  | parameters[0] = new double[2]; | 
|  | parameters[1] = new double[2]; | 
|  |  | 
|  | parameters[0][0] = 1; | 
|  | parameters[0][1] = 2; | 
|  |  | 
|  | parameters[1][0] = 3; | 
|  | parameters[1][1] = 4; | 
|  |  | 
|  | auto** jacobians = new double*[2]; | 
|  | jacobians[0] = new double[2]; | 
|  | jacobians[1] = new double[2]; | 
|  |  | 
|  | double residuals = 0.0; | 
|  |  | 
|  | cost_function->Evaluate(parameters, &residuals, nullptr); | 
|  | EXPECT_EQ(10.0, residuals); | 
|  |  | 
|  | cost_function->Evaluate(parameters, &residuals, jacobians); | 
|  | EXPECT_EQ(10.0, residuals); | 
|  |  | 
|  | EXPECT_EQ(3, jacobians[0][0]); | 
|  | EXPECT_EQ(4, jacobians[0][1]); | 
|  | EXPECT_EQ(1, jacobians[1][0]); | 
|  | EXPECT_EQ(2, jacobians[1][1]); | 
|  |  | 
|  | delete[] jacobians[0]; | 
|  | delete[] jacobians[1]; | 
|  | delete[] parameters[0]; | 
|  | delete[] parameters[1]; | 
|  | delete[] jacobians; | 
|  | delete[] parameters; | 
|  | delete cost_function; | 
|  | } | 
|  |  | 
|  | struct TenParameterCost { | 
|  | template <typename T> | 
|  | bool operator()(const T* const x0, | 
|  | const T* const x1, | 
|  | const T* const x2, | 
|  | const T* const x3, | 
|  | const T* const x4, | 
|  | const T* const x5, | 
|  | const T* const x6, | 
|  | const T* const x7, | 
|  | const T* const x8, | 
|  | const T* const x9, | 
|  | T* cost) const { | 
|  | cost[0] = *x0 + *x1 + *x2 + *x3 + *x4 + *x5 + *x6 + *x7 + *x8 + *x9; | 
|  | return true; | 
|  | } | 
|  | }; | 
|  |  | 
|  | TEST(AutodiffCostFunction, ManyParameterAutodiffInstantiates) { | 
|  | CostFunction* cost_function = | 
|  | new AutoDiffCostFunction<TenParameterCost, | 
|  | 1, | 
|  | 1, | 
|  | 1, | 
|  | 1, | 
|  | 1, | 
|  | 1, | 
|  | 1, | 
|  | 1, | 
|  | 1, | 
|  | 1, | 
|  | 1>(new TenParameterCost); | 
|  |  | 
|  | auto** parameters = new double*[10]; | 
|  | auto** jacobians = new double*[10]; | 
|  | for (int i = 0; i < 10; ++i) { | 
|  | parameters[i] = new double[1]; | 
|  | parameters[i][0] = i; | 
|  | jacobians[i] = new double[1]; | 
|  | } | 
|  |  | 
|  | double residuals = 0.0; | 
|  |  | 
|  | cost_function->Evaluate(parameters, &residuals, nullptr); | 
|  | EXPECT_EQ(45.0, residuals); | 
|  |  | 
|  | cost_function->Evaluate(parameters, &residuals, jacobians); | 
|  | EXPECT_EQ(residuals, 45.0); | 
|  | for (int i = 0; i < 10; ++i) { | 
|  | EXPECT_EQ(1.0, jacobians[i][0]); | 
|  | } | 
|  |  | 
|  | for (int i = 0; i < 10; ++i) { | 
|  | delete[] jacobians[i]; | 
|  | delete[] parameters[i]; | 
|  | } | 
|  | delete[] jacobians; | 
|  | delete[] parameters; | 
|  | delete cost_function; | 
|  | } | 
|  |  | 
|  | struct OnlyFillsOneOutputFunctor { | 
|  | template <typename T> | 
|  | bool operator()(const T* x, T* output) const { | 
|  | output[0] = x[0]; | 
|  | return true; | 
|  | } | 
|  | }; | 
|  |  | 
|  | TEST(AutoDiffCostFunction, PartiallyFilledResidualShouldFailEvaluation) { | 
|  | double parameter = 1.0; | 
|  | double jacobian[2]; | 
|  | double residuals[2]; | 
|  | double* parameters[] = {¶meter}; | 
|  | double* jacobians[] = {jacobian}; | 
|  |  | 
|  | std::unique_ptr<CostFunction> cost_function( | 
|  | new AutoDiffCostFunction<OnlyFillsOneOutputFunctor, 2, 1>( | 
|  | new OnlyFillsOneOutputFunctor)); | 
|  | InvalidateArray(2, jacobian); | 
|  | InvalidateArray(2, residuals); | 
|  | EXPECT_TRUE(cost_function->Evaluate(parameters, residuals, jacobians)); | 
|  | EXPECT_FALSE(IsArrayValid(2, jacobian)); | 
|  | EXPECT_FALSE(IsArrayValid(2, residuals)); | 
|  | } | 
|  |  | 
|  | }  // namespace internal | 
|  | }  // namespace ceres |