Add support for dynamic autodiff
Change-Id: I17d573696172ab691a9653db99a620e4bc1bd0d0
diff --git a/internal/ceres/dynamic_autodiff_cost_function_test.cc b/internal/ceres/dynamic_autodiff_cost_function_test.cc
new file mode 100644
index 0000000..5d743a7
--- /dev/null
+++ b/internal/ceres/dynamic_autodiff_cost_function_test.cc
@@ -0,0 +1,166 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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: thadh@gmail.com (Thad Hughes)
+// mierle@gmail.com (Keir Mierle)
+// sameeragarwal@google.com (Sameer Agarwal)
+
+#include "ceres/dynamic_autodiff_cost_function.h"
+
+#include <cstddef>
+
+#include "gtest/gtest.h"
+
+namespace ceres {
+namespace internal {
+
+// Takes 2 parameter blocks:
+// parameters[0] is size 10.
+// parameters[1] is size 5.
+// Emits 21 residuals:
+// A: i - parameters[0][i], for i in [0,10) -- this is 10 residuals
+// B: parameters[0][i] - i, for i in [0,10) -- this is another 10.
+// C: sum(parameters[0][i]^2 - 8*parameters[0][i]) + sum(parameters[1][i])
+class MyCostFunctor {
+ public:
+ template <typename T>
+ bool operator()(T const* const* parameters, T* residuals) const {
+ const T* params0 = parameters[0];
+ int r = 0;
+ for (int i = 0; i < 10; ++i) {
+ residuals[r++] = T(i) - params0[i];
+ residuals[r++] = params0[i] - T(i);
+ }
+
+ T c_residual(0.0);
+ for (int i = 0; i < 10; ++i) {
+ c_residual += pow(params0[i], 2) - T(8) * params0[i];
+ }
+
+ const T* params1 = parameters[1];
+ for (int i = 0; i < 5; ++i) {
+ c_residual += params1[i];
+ }
+ residuals[r++] = c_residual;
+ return true;
+ }
+};
+
+TEST(DynamicAutodiffCostFunctionTest, TestResiduals) {
+ vector<double> param_block_0(10, 0.0);
+ vector<double> param_block_1(5, 0.0);
+ DynamicAutoDiffCostFunction<MyCostFunctor, 3> cost_function(
+ new MyCostFunctor());
+ cost_function.AddParameterBlock(param_block_0.size());
+ cost_function.AddParameterBlock(param_block_1.size());
+ cost_function.SetNumResiduals(21);
+
+ // Test residual computation.
+ vector<double> residuals(21, -100000);
+ vector<double*> parameter_blocks(2);
+ parameter_blocks[0] = ¶m_block_0[0];
+ parameter_blocks[1] = ¶m_block_1[0];
+ EXPECT_TRUE(cost_function.Evaluate(¶meter_blocks[0],
+ residuals.data(),
+ NULL));
+ for (int r = 0; r < 10; ++r) {
+ EXPECT_EQ(1.0 * r, residuals.at(r * 2));
+ EXPECT_EQ(-1.0 * r, residuals.at(r * 2 + 1));
+ }
+ EXPECT_EQ(0, residuals.at(20));
+}
+
+TEST(DynamicAutodiffCostFunctionTest, TestJacobian) {
+ // Test the residual counting.
+ vector<double> param_block_0(10, 0.0);
+ for (int i = 0; i < 10; ++i) {
+ param_block_0[i] = 2 * i;
+ }
+ vector<double> param_block_1(5, 0.0);
+ DynamicAutoDiffCostFunction<MyCostFunctor, 3> cost_function(
+ new MyCostFunctor());
+ cost_function.AddParameterBlock(param_block_0.size());
+ cost_function.AddParameterBlock(param_block_1.size());
+ cost_function.SetNumResiduals(21);
+
+ // Prepare the residuals.
+ vector<double> residuals(21, -100000);
+
+ // Prepare the parameters.
+ vector<double*> parameter_blocks(2);
+ parameter_blocks[0] = ¶m_block_0[0];
+ parameter_blocks[1] = ¶m_block_1[0];
+
+ // Prepare the jacobian.
+ vector<vector<double> > jacobian_vect(2);
+ jacobian_vect[0].resize(21 * 10, -100000);
+ jacobian_vect[1].resize(21 * 5, -100000);
+ vector<double*> jacobian;
+ jacobian.push_back(jacobian_vect[0].data());
+ jacobian.push_back(jacobian_vect[1].data());
+
+ // Test jacobian computation.
+ EXPECT_TRUE(cost_function.Evaluate(parameter_blocks.data(),
+ residuals.data(),
+ jacobian.data()));
+
+ for (int r = 0; r < 10; ++r) {
+ EXPECT_EQ(-1.0 * r, residuals.at(r * 2));
+ EXPECT_EQ(+1.0 * r, residuals.at(r * 2 + 1));
+ }
+ EXPECT_EQ(420, residuals.at(20));
+ for (int p = 0; p < 10; ++p) {
+ // Check "A" Jacobian.
+ EXPECT_EQ(-1.0, jacobian_vect[0][2*p * 10 + p]);
+ // Check "B" Jacobian.
+ EXPECT_EQ(+1.0, jacobian_vect[0][(2*p+1) * 10 + p]);
+ jacobian_vect[0][2*p * 10 + p] = 0.0;
+ jacobian_vect[0][(2*p+1) * 10 + p] = 0.0;
+ }
+
+ // Check "C" Jacobian for first parameter block.
+ for (int p = 0; p < 10; ++p) {
+ EXPECT_EQ(4 * p - 8, jacobian_vect[0][20 * 10 + p]);
+ jacobian_vect[0][20 * 10 + p] = 0.0;
+ }
+ for (int i = 0; i < jacobian_vect[0].size(); ++i) {
+ EXPECT_EQ(0.0, jacobian_vect[0][i]);
+ }
+
+ // Check "C" Jacobian for second parameter block.
+ for (int p = 0; p < 5; ++p) {
+ EXPECT_EQ(1.0, jacobian_vect[1][20 * 5 + p]);
+ jacobian_vect[1][20 * 5 + p] = 0.0;
+ }
+ for (int i = 0; i < jacobian_vect[1].size(); ++i) {
+ EXPECT_EQ(0.0, jacobian_vect[1][i]);
+ }
+}
+
+} // namespace internal
+} // namespace ceres
