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Compute & report timing information for line searches.

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- We now compute & report the cumulative time spent performing the
  following tasks as part of a line search:
  - Evaluation of the univariate cost function value & gradient.
  - Minimization of the interpolating polynomial.
  - Total time spent performing line searches.
- This information is now reported for all minimizers, although only in
  the case of a constrained problem for the TR minimizer.
- Remove LineSearch::Function abstraction in place of using
  LineSearchFunction implementation directly, and remove virtual
  functions from LineSearchFunction.
-- LineSearch::Function added an unnecessary level of abstraction since
   the user always had to create a LineSearchFunction anyway to use a
   Ceres Evaluator, and it added an unncessary virtual function call.

Change-Id: Ia4e1921d78f351ae119875aa97a3ea5e8b5d9877
This commit is contained in:
Alex Stewart
2014-11-17 22:20:46 +00:00
committed by Sameer Agarwal
parent 19d7ce97fe
commit 9ad59a760a
8 changed files with 235 additions and 73 deletions
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internal/ceres/solver.cc
+26
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@@ -349,6 +349,10 @@ void PreSolveSummarize(const Solver::Options& options,
summary->dense_linear_algebra_library_type = options.dense_linear_algebra_library_type; // NOLINT
summary->dogleg_type = options.dogleg_type;
summary->inner_iteration_time_in_seconds = 0.0;
summary->line_search_cost_evaluation_time_in_seconds = 0.0;
summary->line_search_gradient_evaluation_time_in_seconds = 0.0;
summary->line_search_polynomial_minimization_time_in_seconds = 0.0;
summary->line_search_total_time_in_seconds = 0.0;
summary->inner_iterations_given = options.use_inner_iterations;
summary->line_search_direction_type = options.line_search_direction_type; // NOLINT
summary->line_search_interpolation_type = options.line_search_interpolation_type; // NOLINT
@@ -558,6 +562,10 @@ Solver::Summary::Summary()
residual_evaluation_time_in_seconds(-1.0),
jacobian_evaluation_time_in_seconds(-1.0),
inner_iteration_time_in_seconds(-1.0),
line_search_cost_evaluation_time_in_seconds(-1.0),
line_search_gradient_evaluation_time_in_seconds(-1.0),
line_search_polynomial_minimization_time_in_seconds(-1.0),
line_search_total_time_in_seconds(-1.0),
num_parameter_blocks(-1),
num_parameters(-1),
num_effective_parameters(-1),
@@ -568,6 +576,7 @@ Solver::Summary::Summary()
num_effective_parameters_reduced(-1),
num_residual_blocks_reduced(-1),
num_residuals_reduced(-1),
is_constrained(false),
num_threads_given(-1),
num_threads_used(-1),
num_linear_solver_threads_given(-1),
@@ -773,14 +782,26 @@ string Solver::Summary::FullReport() const {
num_inner_iteration_steps);
}
const bool print_line_search_timing_information =
minimizer_type == LINE_SEARCH ||
(minimizer_type == TRUST_REGION && is_constrained);
StringAppendF(&report, "\nTime (in seconds):\n");
StringAppendF(&report, "Preprocessor %25.4f\n",
preprocessor_time_in_seconds);
StringAppendF(&report, "\n Residual evaluation %23.4f\n",
residual_evaluation_time_in_seconds);
if (print_line_search_timing_information) {
StringAppendF(&report, " Line search cost evaluation %10.4f\n",
line_search_cost_evaluation_time_in_seconds);
}
StringAppendF(&report, " Jacobian evaluation %23.4f\n",
jacobian_evaluation_time_in_seconds);
if (print_line_search_timing_information) {
StringAppendF(&report, " Line search gradient evaluation %6.4f\n",
line_search_gradient_evaluation_time_in_seconds);
}
if (minimizer_type == TRUST_REGION) {
StringAppendF(&report, " Linear solver %23.4f\n",
@@ -792,6 +813,11 @@ string Solver::Summary::FullReport() const {
inner_iteration_time_in_seconds);
}
if (print_line_search_timing_information) {
StringAppendF(&report, " Line search polynomial minimization %.4f\n",
line_search_polynomial_minimization_time_in_seconds);
}
StringAppendF(&report, "Minimizer %25.4f\n\n",
minimizer_time_in_seconds);