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;