Refactoring of the LineSearchMinimizer.
1. New LineSearchDirection interface, factory and instances.
2. Cleanup of LineSearchMinimizer to use the State and Direction objects.
3. LBFGS -> LowRankInverseHessian.
4. Refactoring of the RunCallbacks function and share it across
LineSearchMinimizer and TrustRegionMinimizer.
Change-Id: I19354afc6f5d6567b28918710c2012dc30ef8f32
diff --git a/internal/ceres/trust_region_minimizer.cc b/internal/ceres/trust_region_minimizer.cc
index db2641d..5ea9374 100644
--- a/internal/ceres/trust_region_minimizer.cc
+++ b/internal/ceres/trust_region_minimizer.cc
@@ -58,21 +58,6 @@
const double kEpsilon = 1e-12;
} // namespace
-// Execute the list of IterationCallbacks sequentially. If any one of
-// the callbacks does not return SOLVER_CONTINUE, then stop and return
-// its status.
-CallbackReturnType TrustRegionMinimizer::RunCallbacks(
- const IterationSummary& iteration_summary) {
- for (int i = 0; i < options_.callbacks.size(); ++i) {
- const CallbackReturnType status =
- (*options_.callbacks[i])(iteration_summary);
- if (status != SOLVER_CONTINUE) {
- return status;
- }
- }
- return SOLVER_CONTINUE;
-}
-
// Compute a scaling vector that is used to improve the conditioning
// of the Jacobian.
void TrustRegionMinimizer::EstimateScale(const SparseMatrix& jacobian,
@@ -182,16 +167,16 @@
// The initial gradient max_norm is bounded from below so that we do
// not divide by zero.
- const double gradient_max_norm_0 =
+ const double initial_gradient_max_norm =
max(iteration_summary.gradient_max_norm, kEpsilon);
const double absolute_gradient_tolerance =
- options_.gradient_tolerance * gradient_max_norm_0;
+ options_.gradient_tolerance * initial_gradient_max_norm;
if (iteration_summary.gradient_max_norm <= absolute_gradient_tolerance) {
summary->termination_type = GRADIENT_TOLERANCE;
VLOG(1) << "Terminating: Gradient tolerance reached."
<< "Relative gradient max norm: "
- << iteration_summary.gradient_max_norm / gradient_max_norm_0
+ << iteration_summary.gradient_max_norm / initial_gradient_max_norm
<< " <= " << options_.gradient_tolerance;
return;
}
@@ -203,24 +188,12 @@
+ summary->preprocessor_time_in_seconds;
summary->iterations.push_back(iteration_summary);
- // Call the various callbacks.
- switch (RunCallbacks(iteration_summary)) {
- case SOLVER_TERMINATE_SUCCESSFULLY:
- summary->termination_type = USER_SUCCESS;
- VLOG(1) << "Terminating: User callback returned USER_SUCCESS.";
- return;
- case SOLVER_ABORT:
- summary->termination_type = USER_ABORT;
- VLOG(1) << "Terminating: User callback returned USER_ABORT.";
- return;
- case SOLVER_CONTINUE:
- break;
- default:
- LOG(FATAL) << "Unknown type of user callback status";
- }
-
- int num_consecutive_invalid_steps = 0;
+ int num_consecutive_invalid_steps = 0;
while (true) {
+ if (!RunCallbacks(options.callbacks, iteration_summary, summary)) {
+ return;
+ }
+
iteration_start_time = WallTimeInSeconds();
if (iteration_summary.iteration >= options_.max_num_iterations) {
summary->termination_type = NO_CONVERGENCE;
@@ -356,7 +329,7 @@
new_cost = x_plus_delta_cost;
} else {
x_plus_delta = inner_iteration_x;
- // Bost the model_cost_change, since the inner iteration
+ // Boost the model_cost_change, since the inner iteration
// improvements are not accounted for by the trust region.
model_cost_change += x_plus_delta_cost - new_cost;
VLOG(2) << "Inner iteration succeeded; current cost: " << cost
@@ -461,7 +434,7 @@
summary->termination_type = GRADIENT_TOLERANCE;
VLOG(1) << "Terminating: Gradient tolerance reached."
<< "Relative gradient max norm: "
- << iteration_summary.gradient_max_norm / gradient_max_norm_0
+ << iteration_summary.gradient_max_norm / initial_gradient_max_norm
<< " <= " << options_.gradient_tolerance;
return;
}
@@ -534,21 +507,6 @@
WallTimeInSeconds() - start_time
+ summary->preprocessor_time_in_seconds;
summary->iterations.push_back(iteration_summary);
-
- switch (RunCallbacks(iteration_summary)) {
- case SOLVER_TERMINATE_SUCCESSFULLY:
- summary->termination_type = USER_SUCCESS;
- VLOG(1) << "Terminating: User callback returned USER_SUCCESS.";
- return;
- case SOLVER_ABORT:
- summary->termination_type = USER_ABORT;
- VLOG(1) << "Terminating: User callback returned USER_ABORT.";
- return;
- case SOLVER_CONTINUE:
- break;
- default:
- LOG(FATAL) << "Unknown type of user callback status";
- }
}
}
