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diff --git a/internal/ceres/gradient_problem_solver_test.cc b/internal/ceres/gradient_problem_solver_test.cc
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+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2015 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: strandmark@google.com (Petter Strandmark)
+
+#include "ceres/gradient_problem.h"
+#include "ceres/gradient_problem_solver.h"
+
+#include "gtest/gtest.h"
+
+namespace ceres {
+namespace internal {
+
+// Rosenbrock function; see http://en.wikipedia.org/wiki/Rosenbrock_function .
+class Rosenbrock : public ceres::FirstOrderFunction {
+ public:
+ virtual ~Rosenbrock() {}
+
+ virtual bool Evaluate(const double* parameters,
+ double* cost,
+ double* gradient) const {
+ const double x = parameters[0];
+ const double y = parameters[1];
+
+ cost[0] = (1.0 - x) * (1.0 - x) + 100.0 * (y - x * x) * (y - x * x);
+ if (gradient != NULL) {
+ gradient[0] = -2.0 * (1.0 - x) - 200.0 * (y - x * x) * 2.0 * x;
+ gradient[1] = 200.0 * (y - x * x);
+ }
+ return true;
+ }
+
+ virtual int NumParameters() const { return 2; }
+};
+
+TEST(GradientProblemSolver, SolvesRosenbrockWithDefaultOptions) {
+ const double expected_tolerance = 1e-9;
+ double parameters[2] = {-1.2, 0.0};
+
+ ceres::GradientProblemSolver::Options options;
+ ceres::GradientProblemSolver::Summary summary;
+ ceres::GradientProblem problem(new Rosenbrock());
+ ceres::Solve(options, problem, parameters, &summary);
+
+ EXPECT_EQ(CONVERGENCE, summary.termination_type);
+ EXPECT_NEAR(1.0, parameters[0], expected_tolerance);
+ EXPECT_NEAR(1.0, parameters[1], expected_tolerance);
+}
+
+class QuadraticFunction : public ceres::FirstOrderFunction {
+ virtual ~QuadraticFunction() {}
+ virtual bool Evaluate(const double* parameters,
+ double* cost,
+ double* gradient) const {
+ const double x = parameters[0];
+ *cost = 0.5 * (5.0 - x) * (5.0 - x);
+ if (gradient != NULL) {
+ gradient[0] = x - 5.0;
+ }
+
+ return true;
+ }
+ virtual int NumParameters() const { return 1; }
+};
+
+struct RememberingCallback : public IterationCallback {
+ explicit RememberingCallback(double *x) : calls(0), x(x) {}
+ virtual ~RememberingCallback() {}
+ virtual CallbackReturnType operator()(const IterationSummary& summary) {
+ x_values.push_back(*x);
+ return SOLVER_CONTINUE;
+ }
+ int calls;
+ double *x;
+ std::vector<double> x_values;
+};
+
+
+TEST(Solver, UpdateStateEveryIterationOption) {
+ double x = 50.0;
+ const double original_x = x;
+
+ ceres::GradientProblem problem(new QuadraticFunction);
+ ceres::GradientProblemSolver::Options options;
+ RememberingCallback callback(&x);
+ options.callbacks.push_back(&callback);
+ ceres::GradientProblemSolver::Summary summary;
+
+ int num_iterations;
+
+ // First try: no updating.
+ ceres::Solve(options, problem, &x, &summary);
+ num_iterations = summary.iterations.size() - 1;
+ EXPECT_GT(num_iterations, 1);
+ for (int i = 0; i < callback.x_values.size(); ++i) {
+ EXPECT_EQ(50.0, callback.x_values[i]);
+ }
+
+ // Second try: with updating
+ x = 50.0;
+ options.update_state_every_iteration = true;
+ callback.x_values.clear();
+ ceres::Solve(options, problem, &x, &summary);
+ num_iterations = summary.iterations.size() - 1;
+ EXPECT_GT(num_iterations, 1);
+ EXPECT_EQ(original_x, callback.x_values[0]);
+ EXPECT_NE(original_x, callback.x_values[1]);
+}
+
+} // namespace internal
+} // namespace ceres