Add IterationSummary::gradient_norm.
Iteration summary now reports the 2-norm of the gradient also.
Change-Id: I1ed7f1456ee4f546c9b42423d7a4ec3079ec078f
diff --git a/internal/ceres/line_search_minimizer.cc b/internal/ceres/line_search_minimizer.cc
index 6ee514a..b7e96c8 100644
--- a/internal/ceres/line_search_minimizer.cc
+++ b/internal/ceres/line_search_minimizer.cc
@@ -119,6 +119,7 @@
iteration_summary.step_is_successful = false;
iteration_summary.cost_change = 0.0;
iteration_summary.gradient_max_norm = 0.0;
+ iteration_summary.gradient_norm = 0.0;
iteration_summary.step_norm = 0.0;
iteration_summary.linear_solver_iterations = 0;
iteration_summary.step_solver_time_in_seconds = 0;
@@ -135,6 +136,7 @@
iteration_summary.cost = current_state.cost + summary->fixed_cost;
iteration_summary.gradient_max_norm = current_state.gradient_max_norm;
+ iteration_summary.gradient_norm = sqrt(current_state.gradient_squared_norm);
// The initial gradient max_norm is bounded from below so that we do
// not divide by zero.
@@ -331,6 +333,8 @@
}
iteration_summary.gradient_max_norm = current_state.gradient_max_norm;
+ iteration_summary.gradient_norm = sqrt(current_state.gradient_squared_norm);
+
if (iteration_summary.gradient_max_norm <= absolute_gradient_tolerance) {
VLOG_IF(1, is_not_silent)
<< "Terminating: Gradient tolerance reached."
