Lines Matching full:cost
63 const double cost,
96 line_search->Search(1.0, cost, gradient.dot(delta), &summary);
101 line_search->Search(1.0, cost, -gradient.squaredNorm(), &summary);
196 // Do initial cost and Jacobian evaluation.
197 double cost = 0.0;
199 &cost,
219 summary->initial_cost = cost + summary->fixed_cost;
220 iteration_summary.cost = cost + summary->fixed_cost;
250 double minimum_cost = cost;
251 double reference_cost = cost;
253 double candidate_cost = cost;
328 // = cost - new_model_cost
338 << "Invalid step: current_cost: " << cost
340 << " relative difference " << (model_cost_change / cost);
366 iteration_summary.cost = cost + summary->fixed_cost;
389 DoLineSearch(options, x, gradient, cost, delta, evaluator);
403 << "Treating it as a step with infinite cost";
408 << "Treating it as a step with infinite cost";
433 << "Inner iteration succeeded; Current cost: " << cost
434 << " Trust region step cost: " << x_plus_delta_cost
435 << " Inner iteration cost: " << new_cost;
437 inner_iterations_were_useful = new_cost < cost;
472 iteration_summary.cost_change = cost - new_cost;
474 options_.function_tolerance * cost;
478 "|cost_change|/cost: %e <= %e",
479 fabs(iteration_summary.cost_change) / cost,
495 // divided by the change in model cost.
500 // from a reference iteration. The model cost change is
501 // estimated by accumulating the model cost changes since the
543 // when inner iterations lead to a net decrease in the cost.
576 &cost,
622 if (cost < minimum_cost) {
625 minimum_cost = cost;
627 candidate_cost = cost;
632 if (cost > candidate_cost) {
633 // The current iterate is has a higher cost than the
637 candidate_cost = cost;
666 iteration_summary.cost = cost + summary->fixed_cost;
