Change iteration logging to VLOG(3)
Change-Id: I6847162447eb46381403b6ada063f03db4c9d257
diff --git a/internal/ceres/conjugate_gradients_solver.cc b/internal/ceres/conjugate_gradients_solver.cc
index 71d49d5..09a0279 100644
--- a/internal/ceres/conjugate_gradients_solver.cc
+++ b/internal/ceres/conjugate_gradients_solver.cc
@@ -114,7 +114,7 @@
for (summary.num_iterations = 1;
summary.num_iterations < options_.max_num_iterations;
++summary.num_iterations) {
- VLOG(2) << "cg iteration " << summary.num_iterations;
+ VLOG(3) << "cg iteration " << summary.num_iterations;
// Apply preconditioner
if (per_solve_options.preconditioner != NULL) {
@@ -201,13 +201,13 @@
// 1. Stephen G. Nash & Ariela Sofer, Assessing A Search
// Direction Within A Truncated Newton Method, Operation
// Research Letters 9(1990) 219-221.
- //
+ //
// 2. Stephen G. Nash, A Survey of Truncated Newton Methods,
// Journal of Computational and Applied Mathematics,
// 124(1-2), 45-59, 2000.
//
double zeta = summary.num_iterations * (Q1 - Q0) / Q1;
- VLOG(2) << "Q termination: zeta " << zeta
+ VLOG(3) << "Q termination: zeta " << zeta
<< " " << per_solve_options.q_tolerance;
if (zeta < per_solve_options.q_tolerance) {
summary.termination_type = TOLERANCE;
@@ -217,7 +217,7 @@
// Residual based termination.
norm_r = r. norm();
- VLOG(2) << "R termination: norm_r " << norm_r
+ VLOG(3) << "R termination: norm_r " << norm_r
<< " " << tol_r;
if (norm_r <= tol_r) {
summary.termination_type = TOLERANCE;