Compute the gradient if requested in the evaluator
This extends the Evaluator interface to support evaluating the
gradient in addition to the residuals and jacobian, if requested.
bool Evaluate(const double* state,
double* cost,
double* residuals,
double* gradient, <----------- NEW
SparseMatrix* jacobian) = 0;
The ProgramEvaluator is extended to support the new gradient
evaluation. This required some gymnastics around the block
evaluate preparer, which now contains a scratch evaluate preparer
for the case that no jacobian is requested but the gradient is.
Gradient evaluation is a prerequisite for the planned suite of
first order methods, including nonlinear conjugate gradient,
CG_DESCENT, L-BFGS, trust region with line search, and more.
This also considerably refactors the evaluator_test to make it
shorter and check the results for all combinations of the optional
parameters [residuals, gradient, jacobian].
Change-Id: Ic7d0fec028dc5ffebc08ee079ad04eeaf6e02582
diff --git a/internal/ceres/trust_region_minimizer_test.cc b/internal/ceres/trust_region_minimizer_test.cc
index 03297c0..414567a 100644
--- a/internal/ceres/trust_region_minimizer_test.cc
+++ b/internal/ceres/trust_region_minimizer_test.cc
@@ -83,6 +83,7 @@
virtual bool Evaluate(const double* state,
double* cost,
double* residuals,
+ double* /* gradient */,
SparseMatrix* jacobian) {
double x1 = state[0];
double x2 = state[1];
