Update Ceres to latest upstream version 2.1.0temp-ceres_update

This release deprecated the Parameterization API and the new Manifolds
API is to be used instead. This is what was done in the Libmv as part
of this change.

Additionally, remove the bundling scripts. Nowadays those are only
leading to a duplicated work to maintain.

1 files changed, 8 insertions, 12 deletions

diff --git a/extern/ceres/internal/ceres/trust_region_minimizer.cc b/extern/ceres/internal/ceres/trust_region_minimizer.cc
index bcf05b3ddfb..9ef5167ba6c 100644
--- a/extern/ceres/internal/ceres/trust_region_minimizer.cc
+++ b/extern/ceres/internal/ceres/trust_region_minimizer.cc
@@ -62,8 +62,6 @@
 namespace ceres {
 namespace internal {
 
-TrustRegionMinimizer::~TrustRegionMinimizer() {}
-
 void TrustRegionMinimizer::Minimize(const Minimizer::Options& options,
                                     double* parameters,
                                     Solver::Summary* solver_summary) {
@@ -75,11 +73,11 @@ void TrustRegionMinimizer::Minimize(const Minimizer::Options& options,
   // Create the TrustRegionStepEvaluator. The construction needs to be
   // delayed to this point because we need the cost for the starting
   // point to initialize the step evaluator.
-  step_evaluator_.reset(new TrustRegionStepEvaluator(
+  step_evaluator_ = std::make_unique<TrustRegionStepEvaluator>(
       x_cost_,
       options_.use_nonmonotonic_steps
           ? options_.max_consecutive_nonmonotonic_steps
-          : 0));
+          : 0);
 
   while (FinalizeIterationAndCheckIfMinimizerCanContinue()) {
     iteration_start_time_in_secs_ = WallTimeInSeconds();
@@ -750,14 +748,12 @@ bool TrustRegionMinimizer::FunctionToleranceReached() {
 // Compute candidate_x_ = Plus(x_, delta_)
 // Evaluate the cost of candidate_x_ as candidate_cost_.
 //
-// Failure to compute the step or the cost mean that candidate_cost_
-// is set to std::numeric_limits<double>::max(). Unlike
-// EvaluateGradientAndJacobian, failure in this function is not fatal
-// as we are only computing and evaluating a candidate point, and if
-// for some reason we are unable to evaluate it, we consider it to be
-// a point with very high cost. This allows the user to deal with edge
-// cases/constraints as part of the LocalParameterization and
-// CostFunction objects.
+// Failure to compute the step or the cost mean that candidate_cost_ is set to
+// std::numeric_limits<double>::max(). Unlike EvaluateGradientAndJacobian,
+// failure in this function is not fatal as we are only computing and evaluating
+// a candidate point, and if for some reason we are unable to evaluate it, we
+// consider it to be a point with very high cost. This allows the user to deal
+// with edge cases/constraints as part of the Manifold and CostFunction objects.
 void TrustRegionMinimizer::ComputeCandidatePointAndEvaluateCost() {
   if (!evaluator_->Plus(x_.data(), delta_.data(), candidate_x_.data())) {
     if (is_not_silent_) {