Add GradientProblemSolver::Options::update_state_every_iteration

The non-linear least squares solver had the ability to update the
user's parameters every iteration. Now GradientProblemSolver can
do the same.

Also a few minor Sphinx markup related cleanup to the documentation
which were found in the process of updating Sphinx on my machine
and adding the docs for this feature.

This fixes https://github.com/ceres-solver/ceres-solver/issues/246

Change-Id: Ib6b90ac22be8bfb60b14f25ad52082ba371af164

docs/source/nnls_tutorial.rst

@@ -710,7 +710,7 @@ objective function per observation.
 Since this is a large sparse problem (well large for ``DENSE_QR``
 anyways), one way to solve this problem is to set
 :member:`Solver::Options::linear_solver_type` to
-``SPARSE_NORMAL_CHOLESKY`` and call :member:`Solve`. And while this is
+``SPARSE_NORMAL_CHOLESKY`` and call :func:`Solve`. And while this is
 a reasonable thing to do, bundle adjustment problems have a special
 sparsity structure that can be exploited to solve them much more
 efficiently. Ceres provides three specialized solvers (collectively