Problem::Evaluate implementation.
1. Add Problem::Evaluate and tests.
2. Remove Solver::Summary::initial/final_*
3. Remove Solver::Options::return_* members.
4. Various cpplint cleanups.
Change-Id: I4266de53489896f72d9c6798c5efde6748d68a47
diff --git a/internal/ceres/solver_impl.cc b/internal/ceres/solver_impl.cc
index 803b711..7f85fbe 100644
--- a/internal/ceres/solver_impl.cc
+++ b/internal/ceres/solver_impl.cc
@@ -77,20 +77,6 @@
double* parameters_;
};
-// Macro used to evaluate initial and final residuals, gradient and
-// jacobian if requested by the user.
-//
-// We need a macro here, instead of a simple function call, since the
-// multiplexing happens on variable names.
-#define CERES_EVALUATE(which) \
- Evaluator::Evaluate( \
- original_program, \
- options.num_threads, \
- &summary->which ## _cost, \
- options.return_ ## which ## _residuals ? &summary->which ## _residuals : NULL, \
- options.return_ ## which ## _gradient ? &summary->which ## _gradient : NULL, \
- options.return_ ## which ## _jacobian ? &summary->which ## _jacobian : NULL)
-
void SetSummaryFinalCost(Solver::Summary* summary) {
summary->final_cost = summary->initial_cost;
// We need the loop here, instead of just looking at the last
@@ -240,7 +226,8 @@
file_logging_callback.get());
}
- TrustRegionLoggingCallback logging_callback(options.minimizer_progress_to_stdout);
+ TrustRegionLoggingCallback logging_callback(
+ options.minimizer_progress_to_stdout);
if (options.logging_type != SILENT) {
minimizer_options.callbacks.insert(minimizer_options.callbacks.begin(),
&logging_callback);
@@ -299,7 +286,8 @@
file_logging_callback.get());
}
- LineSearchLoggingCallback logging_callback(options.minimizer_progress_to_stdout);
+ LineSearchLoggingCallback logging_callback(
+ options.minimizer_progress_to_stdout);
if (options.logging_type != SILENT) {
minimizer_options.callbacks.insert(minimizer_options.callbacks.begin(),
&logging_callback);
@@ -400,21 +388,6 @@
event_logger.AddEvent("Init");
- // Evaluate the initial cost, residual vector and the jacobian
- // matrix if requested by the user.
- if (options.return_initial_residuals ||
- options.return_initial_gradient ||
- options.return_initial_jacobian) {
- if (!CERES_EVALUATE(initial)) {
- summary->termination_type = NUMERICAL_FAILURE;
- summary->error = "Unable to evaluate the initial cost.";
- LOG(ERROR) << summary->error;
- return;
- }
- }
-
- event_logger.AddEvent("InitialEvaluate");
-
original_program->SetParameterBlockStatePtrsToUserStatePtrs();
event_logger.AddEvent("SetParameterBlockPtrs");
@@ -463,6 +436,7 @@
problem_impl,
&summary->fixed_cost,
&summary->error));
+
event_logger.AddEvent("CreateReducedProgram");
if (reduced_program == NULL) {
return;
@@ -480,33 +454,21 @@
summary->preprocessor_time_in_seconds =
WallTimeInSeconds() - solver_start_time;
+ double post_process_start_time = WallTimeInSeconds();
LOG(INFO) << "Terminating: FUNCTION_TOLERANCE reached. "
<< "No non-constant parameter blocks found.";
+ summary->initial_cost = summary->fixed_cost;
+ summary->final_cost = summary->fixed_cost;
+
// FUNCTION_TOLERANCE is the right convergence here, as we know
// that the objective function is constant and cannot be changed
// any further.
summary->termination_type = FUNCTION_TOLERANCE;
- double post_process_start_time = WallTimeInSeconds();
-
- // Evaluate the final cost, residual vector and the jacobian
- // matrix if requested by the user.
- if (options.return_final_residuals ||
- options.return_final_gradient ||
- options.return_final_jacobian) {
- if (!CERES_EVALUATE(final)) {
- summary->termination_type = NUMERICAL_FAILURE;
- summary->error = "Unable to evaluate the final cost.";
- LOG(ERROR) << summary->error;
- return;
- }
- }
-
// Ensure the program state is set to the user parameters on the way out.
original_program->SetParameterBlockStatePtrsToUserStatePtrs();
- event_logger.AddEvent("FinalEvaluate");
summary->postprocessor_time_in_seconds =
WallTimeInSeconds() - post_process_start_time;
return;
@@ -612,42 +574,21 @@
double post_process_start_time = WallTimeInSeconds();
- // Push the contiguous optimized parameters back to the user's parameters.
+ // Push the contiguous optimized parameters back to the user's
+ // parameters.
reduced_program->StateVectorToParameterBlocks(parameters.data());
reduced_program->CopyParameterBlockStateToUserState();
- // Evaluate the final cost, residual vector and the jacobian
- // matrix if requested by the user.
- if (options.return_final_residuals ||
- options.return_final_gradient ||
- options.return_final_jacobian) {
- if (!CERES_EVALUATE(final)) {
- // This failure requires careful handling.
- //
- // At this point, we have modified the user's state, but the
- // evaluation failed and we inform him of NUMERICAL_FAILURE. Ceres
- // guarantees that user's state is not modified if the solver
- // returns with NUMERICAL_FAILURE. Thus, we need to restore the
- // user's state to their original values.
- reduced_program->StateVectorToParameterBlocks(original_parameters.data());
- reduced_program->CopyParameterBlockStateToUserState();
-
- summary->termination_type = NUMERICAL_FAILURE;
- summary->error = "Unable to evaluate the final cost.";
- LOG(ERROR) << summary->error;
-
- event_logger.AddEvent("PostProcess");
- return;
- }
- }
-
- // Ensure the program state is set to the user parameters on the way out.
+ // Ensure the program state is set to the user parameters on the way
+ // out.
original_program->SetParameterBlockStatePtrsToUserStatePtrs();
const map<string, double>& linear_solver_time_statistics =
linear_solver->TimeStatistics();
summary->linear_solver_time_in_seconds =
- FindWithDefault(linear_solver_time_statistics, "LinearSolver::Solve", 0.0);
+ FindWithDefault(linear_solver_time_statistics,
+ "LinearSolver::Solve",
+ 0.0);
const map<string, double>& evaluator_time_statistics =
evaluator->TimeStatistics();
@@ -675,7 +616,8 @@
*CHECK_NOTNULL(summary) = Solver::Summary();
summary->minimizer_type = LINE_SEARCH;
- summary->line_search_direction_type = original_options.line_search_direction_type;
+ summary->line_search_direction_type =
+ original_options.line_search_direction_type;
summary->max_lbfgs_rank = original_options.max_lbfgs_rank;
summary->line_search_type = original_options.line_search_type;
summary->num_parameter_blocks = problem_impl->NumParameterBlocks();
@@ -738,19 +680,6 @@
}
}
- // Evaluate the initial cost, residual vector and the jacobian
- // matrix if requested by the user.
- if (options.return_initial_residuals ||
- options.return_initial_gradient ||
- options.return_initial_jacobian) {
- if (!CERES_EVALUATE(initial)) {
- summary->termination_type = NUMERICAL_FAILURE;
- summary->error = "Unable to evaluate the initial cost.";
- LOG(ERROR) << summary->error;
- return;
- }
- }
-
original_program->SetParameterBlockStatePtrsToUserStatePtrs();
// If the user requests gradient checking, construct a new
@@ -802,19 +731,6 @@
SetSummaryFinalCost(summary);
- // Evaluate the final cost, residual vector and the jacobian
- // matrix if requested by the user.
- if (options.return_final_residuals ||
- options.return_final_gradient ||
- options.return_final_jacobian) {
- if (!CERES_EVALUATE(final)) {
- summary->termination_type = NUMERICAL_FAILURE;
- summary->error = "Unable to evaluate the final cost.";
- LOG(ERROR) << summary->error;
- return;
- }
- }
-
// Ensure the program state is set to the user parameters on the way out.
original_program->SetParameterBlockStatePtrsToUserStatePtrs();
summary->postprocessor_time_in_seconds =
@@ -865,33 +781,6 @@
SetSummaryFinalCost(summary);
- // Evaluate the final cost, residual vector and the jacobian
- // matrix if requested by the user.
- if (options.return_final_residuals ||
- options.return_final_gradient ||
- options.return_final_jacobian) {
- if (!CERES_EVALUATE(final)) {
- // This failure requires careful handling.
- //
- // At this point, we have modified the user's state, but the
- // evaluation failed and we inform him of NUMERICAL_FAILURE. Ceres
- // guarantees that user's state is not modified if the solver
- // returns with NUMERICAL_FAILURE. Thus, we need to restore the
- // user's state to their original values.
-
- reduced_program->StateVectorToParameterBlocks(original_parameters.data());
- reduced_program->CopyParameterBlockStateToUserState();
-
- summary->termination_type = NUMERICAL_FAILURE;
- summary->error = "Unable to evaluate the final cost.";
- LOG(ERROR) << summary->error;
-
- summary->postprocessor_time_in_seconds =
- WallTimeInSeconds() - post_process_start_time;
- return;
- }
- }
-
// Ensure the program state is set to the user parameters on the way out.
original_program->SetParameterBlockStatePtrsToUserStatePtrs();
@@ -947,8 +836,9 @@
return true;
}
-bool SolverImpl::IsParameterBlockSetIndependent(const set<double*>& parameter_block_ptrs,
- const vector<ResidualBlock*>& residual_blocks) {
+bool SolverImpl::IsParameterBlockSetIndependent(
+ const set<double*>& parameter_block_ptrs,
+ const vector<ResidualBlock*>& residual_blocks) {
// Loop over each residual block and ensure that no two parameter
// blocks in the same residual block are part of
// parameter_block_ptrs as that would violate the assumption that it
@@ -1168,8 +1058,8 @@
event_logger.AddEvent("AlternateSolver");
- // Since the transformed program is the "active" program, and it is mutated,
- // update the parameter offsets and indices.
+ // Since the transformed program is the "active" program, and it is
+ // mutated, update the parameter offsets and indices.
transformed_program->SetParameterOffsetsAndIndex();
event_logger.AddEvent("SetOffsets");
@@ -1292,10 +1182,11 @@
return LinearSolver::Create(linear_solver_options);
}
-bool SolverImpl::ApplyUserOrdering(const ProblemImpl::ParameterMap& parameter_map,
- const ParameterBlockOrdering* ordering,
- Program* program,
- string* error) {
+bool SolverImpl::ApplyUserOrdering(
+ const ProblemImpl::ParameterMap& parameter_map,
+ const ParameterBlockOrdering* ordering,
+ Program* program,
+ string* error) {
if (ordering->NumElements() != program->NumParameterBlocks()) {
*error = StringPrintf("User specified ordering does not have the same "
"number of parameters as the problem. The problem"
@@ -1323,8 +1214,8 @@
parameter_map.find(*parameter_block_ptr_it);
if (parameter_block_it == parameter_map.end()) {
*error = StringPrintf("User specified ordering contains a pointer "
- "to a double that is not a parameter block in the "
- "problem. The invalid double is in group: %d",
+ "to a double that is not a parameter block in "
+ "the problem. The invalid double is in group: %d",
group_it->first);
return false;
}
@@ -1356,9 +1247,10 @@
// Reorder the residuals for program, if necessary, so that the residuals
// involving each E block occur together. This is a necessary condition for the
// Schur eliminator, which works on these "row blocks" in the jacobian.
-bool SolverImpl::LexicographicallyOrderResidualBlocks(const int num_eliminate_blocks,
- Program* program,
- string* error) {
+bool SolverImpl::LexicographicallyOrderResidualBlocks(
+ const int num_eliminate_blocks,
+ Program* program,
+ string* error) {
CHECK_GE(num_eliminate_blocks, 1)
<< "Congratulations, you found a Ceres bug! Please report this error "
<< "to the developers.";
@@ -1435,10 +1327,11 @@
return true;
}
-Evaluator* SolverImpl::CreateEvaluator(const Solver::Options& options,
- const ProblemImpl::ParameterMap& parameter_map,
- Program* program,
- string* error) {
+Evaluator* SolverImpl::CreateEvaluator(
+ const Solver::Options& options,
+ const ProblemImpl::ParameterMap& parameter_map,
+ Program* program,
+ string* error) {
Evaluator::Options evaluator_options;
evaluator_options.linear_solver_type = options.linear_solver_type;
evaluator_options.num_eliminate_blocks =
@@ -1479,7 +1372,7 @@
// Iterate over each group and verify that it is an independent
// set.
map<int, set<double*> >::const_iterator it = group_to_elements.begin();
- for ( ;it != group_to_elements.end(); ++it) {
+ for ( ; it != group_to_elements.end(); ++it) {
if (!IsParameterBlockSetIndependent(it->second,
program.residual_blocks())) {
summary->error =
