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/program.cc b/internal/ceres/program.cc
index 3d62272..f6704e4 100644
--- a/internal/ceres/program.cc
+++ b/internal/ceres/program.cc
@@ -201,6 +201,15 @@
return max_parameters;
}
+int Program::MaxResidualsPerResidualBlock() const {
+ int max_residuals = 0;
+ for (int i = 0; i < residual_blocks_.size(); ++i) {
+ max_residuals = max(max_residuals,
+ residual_blocks_[i]->NumResiduals());
+ }
+ return max_residuals;
+}
+
bool Program::Evaluate(double* cost, double* residuals) {
*cost = 0.0;
