Add the GradientChecker.
The GradientChecker is a utility class written by
William Rucklidge that can be used to check that the
derivatives returned by a cost function match those
returned by numerically differentiating the residuals
returned by the same cost function.
This is useful when developing CostFunction objects
and testing them before plugging them into an optimization
problem.
Change-Id: Ic60f859b48b6246406448555d25556784e097b81
diff --git a/internal/ceres/CMakeLists.txt b/internal/ceres/CMakeLists.txt
index a457768..adad6dc 100644
--- a/internal/ceres/CMakeLists.txt
+++ b/internal/ceres/CMakeLists.txt
@@ -220,6 +220,7 @@
CERES_TEST(corrector)
CERES_TEST(dense_sparse_matrix)
CERES_TEST(evaluator)
+ CERES_TEST(gradient_checker)
CERES_TEST(gradient_checking_cost_function)
CERES_TEST(graph)
CERES_TEST(graph_algorithms)
diff --git a/internal/ceres/gradient_checker_test.cc b/internal/ceres/gradient_checker_test.cc
new file mode 100644
index 0000000..cf7ee20
--- /dev/null
+++ b/internal/ceres/gradient_checker_test.cc
@@ -0,0 +1,193 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2010, 2011, 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: wjr@google.com (William Rucklidge)
+//
+// This file contains tests for the GradientChecker class.
+
+#include "ceres/gradient_checker.h"
+
+#include <cmath>
+#include <cstdlib>
+#include <glog/logging.h>
+#include <vector>
+
+#include "ceres/cost_function.h"
+#include "ceres/random.h"
+#include "gtest/gtest.h"
+
+namespace ceres {
+namespace internal {
+
+// We pick a (non-quadratic) function whose derivative are easy:
+//
+// f = exp(- a' x).
+// df = - f a.
+//
+// where 'a' is a vector of the same size as 'x'. In the block
+// version, they are both block vectors, of course.
+class GoodTestTerm : public CostFunction {
+ public:
+ GoodTestTerm(int arity, int const *dim) : arity_(arity) {
+ // Make 'arity' random vectors.
+ a_.resize(arity_);
+ for (int j = 0; j < arity_; ++j) {
+ a_[j].resize(dim[j]);
+ for (int u = 0; u < dim[j]; ++u) {
+ a_[j][u] = 2.0 * RandDouble() - 1.0;
+ }
+ }
+
+ for (int i = 0; i < arity_; i++) {
+ mutable_parameter_block_sizes()->push_back(dim[i]);
+ }
+ set_num_residuals(1);
+ }
+
+ bool Evaluate(double const* const* parameters,
+ double* residuals,
+ double** jacobians) const {
+ // Compute a . x.
+ double ax = 0;
+ for (int j = 0; j < arity_; ++j) {
+ for (int u = 0; u < parameter_block_sizes()[j]; ++u) {
+ ax += a_[j][u] * parameters[j][u];
+ }
+ }
+
+ // This is the cost, but also appears as a factor
+ // in the derivatives.
+ double f = *residuals = exp(-ax);
+
+ // Accumulate 1st order derivatives.
+ if (jacobians) {
+ for (int j = 0; j < arity_; ++j) {
+ if (jacobians[j]) {
+ for (int u = 0; u < parameter_block_sizes()[j]; ++u) {
+ // See comments before class.
+ jacobians[j][u] = - f * a_[j][u];
+ }
+ }
+ }
+ }
+
+ return true;
+ }
+
+ private:
+ int arity_;
+ vector<vector<double> > a_; // our vectors.
+};
+
+class BadTestTerm : public CostFunction {
+ public:
+ BadTestTerm(int arity, int const *dim) : arity_(arity) {
+ // Make 'arity' random vectors.
+ a_.resize(arity_);
+ for (int j = 0; j < arity_; ++j) {
+ a_[j].resize(dim[j]);
+ for (int u = 0; u < dim[j]; ++u) {
+ a_[j][u] = 2.0 * RandDouble() - 1.0;
+ }
+ }
+
+ for (int i = 0; i < arity_; i++) {
+ mutable_parameter_block_sizes()->push_back(dim[i]);
+ }
+ set_num_residuals(1);
+ }
+
+ bool Evaluate(double const* const* parameters,
+ double* residuals,
+ double** jacobians) const {
+ // Compute a . x.
+ double ax = 0;
+ for (int j = 0; j < arity_; ++j) {
+ for (int u = 0; u < parameter_block_sizes()[j]; ++u) {
+ ax += a_[j][u] * parameters[j][u];
+ }
+ }
+
+ // This is the cost, but also appears as a factor
+ // in the derivatives.
+ double f = *residuals = exp(-ax);
+
+ // Accumulate 1st order derivatives.
+ if (jacobians) {
+ for (int j = 0; j < arity_; ++j) {
+ if (jacobians[j]) {
+ for (int u = 0; u < parameter_block_sizes()[j]; ++u) {
+ // See comments before class.
+ jacobians[j][u] = - f * a_[j][u] + 0.001;
+ }
+ }
+ }
+ }
+
+ return true;
+ }
+
+ private:
+ int arity_;
+ vector<vector<double> > a_; // our vectors.
+};
+
+TEST(GradientChecker, SmokeTest) {
+ srand(5);
+
+ // Test with 3 blocks of size 2, 3 and 4.
+ int const arity = 3;
+ int const dim[arity] = { 2, 3, 4 };
+
+ // Make a random set of blocks.
+ FixedArray<double*> parameters(arity);
+ for (int j = 0; j < arity; ++j) {
+ parameters[j] = new double[dim[j]];
+ for (int u = 0; u < dim[j]; ++u) {
+ parameters[j][u] = 2.0 * RandDouble() - 1.0;
+ }
+ }
+
+ // Make a term and probe it.
+ GoodTestTerm good_term(arity, dim);
+ typedef GradientChecker<GoodTestTerm, 1, 2, 3, 4> GoodTermGradientChecker;
+ EXPECT_TRUE(GoodTermGradientChecker::Probe(
+ parameters.get(), 1e-6, &good_term, NULL));
+
+ BadTestTerm bad_term(arity, dim);
+ typedef GradientChecker<BadTestTerm, 1, 2, 3, 4> BadTermGradientChecker;
+ EXPECT_FALSE(BadTermGradientChecker::Probe(
+ parameters.get(), 1e-6, &bad_term, NULL));
+
+ for (int j = 0; j < arity; j++) {
+ delete[] parameters[j];
+ }
+}
+
+} // namespace internal
+} // namespace ceres
