1 files changed, 16 insertions, 8 deletions

diff --git a/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.cc b/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.cc
index c85c8e5cbf5..f29376db793 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.cc
@@ -99,7 +99,7 @@ TrustRegionStrategy::Summary DoglegStrategy::ComputeStep(
     }
     TrustRegionStrategy::Summary summary;
     summary.num_iterations = 0;
-    summary.termination_type = TOLERANCE;
+    summary.termination_type = LINEAR_SOLVER_SUCCESS;
     return summary;
   }
 
@@ -135,7 +135,11 @@ TrustRegionStrategy::Summary DoglegStrategy::ComputeStep(
   summary.num_iterations = linear_solver_summary.num_iterations;
   summary.termination_type = linear_solver_summary.termination_type;
 
-  if (linear_solver_summary.termination_type != FAILURE) {
+  if (linear_solver_summary.termination_type == LINEAR_SOLVER_FATAL_ERROR) {
+    return summary;
+  }
+
+  if (linear_solver_summary.termination_type != LINEAR_SOLVER_FAILURE) {
     switch (dogleg_type_) {
       // Interpolate the Cauchy point and the Gauss-Newton step.
       case TRADITIONAL_DOGLEG:
@@ -146,7 +150,7 @@ TrustRegionStrategy::Summary DoglegStrategy::ComputeStep(
       // Cauchy point and the (Gauss-)Newton step.
       case SUBSPACE_DOGLEG:
         if (!ComputeSubspaceModel(jacobian)) {
-          summary.termination_type = FAILURE;
+          summary.termination_type = LINEAR_SOLVER_FAILURE;
           break;
         }
         ComputeSubspaceDoglegStep(step);
@@ -513,7 +517,7 @@ LinearSolver::Summary DoglegStrategy::ComputeGaussNewtonStep(
     const double* residuals) {
   const int n = jacobian->num_cols();
   LinearSolver::Summary linear_solver_summary;
-  linear_solver_summary.termination_type = FAILURE;
+  linear_solver_summary.termination_type = LINEAR_SOLVER_FAILURE;
 
   // The Jacobian matrix is often quite poorly conditioned. Thus it is
   // necessary to add a diagonal matrix at the bottom to prevent the
@@ -526,7 +530,7 @@ LinearSolver::Summary DoglegStrategy::ComputeGaussNewtonStep(
   // If the solve fails, the multiplier to the diagonal is increased
   // up to max_mu_ by a factor of mu_increase_factor_ every time. If
   // the linear solver is still not successful, the strategy returns
-  // with FAILURE.
+  // with LINEAR_SOLVER_FAILURE.
   //
   // Next time when a new Gauss-Newton step is requested, the
   // multiplier starts out from the last successful solve.
@@ -579,17 +583,21 @@ LinearSolver::Summary DoglegStrategy::ComputeGaussNewtonStep(
       }
     }
 
-    if (linear_solver_summary.termination_type == FAILURE ||
+    if (linear_solver_summary.termination_type == LINEAR_SOLVER_FATAL_ERROR) {
+      return linear_solver_summary;
+    }
+
+    if (linear_solver_summary.termination_type == LINEAR_SOLVER_FAILURE ||
         !IsArrayValid(n, gauss_newton_step_.data())) {
       mu_ *= mu_increase_factor_;
       VLOG(2) << "Increasing mu " << mu_;
-      linear_solver_summary.termination_type = FAILURE;
+      linear_solver_summary.termination_type = LINEAR_SOLVER_FAILURE;
       continue;
     }
     break;
   }
 
-  if (linear_solver_summary.termination_type != FAILURE) {
+  if (linear_solver_summary.termination_type != LINEAR_SOLVER_FAILURE) {
     // The scaled Gauss-Newton step is D * GN:
     //
     //     - (D^-1 J^T J D^-1)^-1 (D^-1 g)