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[Jenkins] auto-formatting by clang-format version 10.0.0-4ubuntu1
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Lines changed: 6 additions & 11 deletions

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stan/math/mix/functor/laplace_marginal_density_estimator.hpp

Lines changed: 6 additions & 11 deletions
Original file line numberDiff line numberDiff line change
@@ -394,8 +394,7 @@ struct NewtonState {
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*/
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template <typename ObjFun, typename ThetaGradFun, typename ThetaInitializer>
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NewtonState(int theta_size, ObjFun&& obj_fun, ThetaGradFun&& theta_grad_f,
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const Eigen::VectorXd& a_init,
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ThetaInitializer&& theta_init)
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const Eigen::VectorXd& a_init, ThetaInitializer&& theta_init)
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: wolfe_info(std::forward<ObjFun>(obj_fun), a_init,
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std::forward<ThetaInitializer>(theta_init),
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std::forward<ThetaGradFun>(theta_grad_f), 0),
@@ -1018,9 +1017,7 @@ inline auto run_newton_loop(SolverPolicy& solver, NewtonStateT& state,
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double obj_change = std::abs(state.curr().obj() - state.prev().obj());
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bool objective_converged
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= obj_change < options.tolerance
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&& obj_change
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< options.tolerance
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* std::abs(state.prev().obj());
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&& obj_change < options.tolerance * std::abs(state.prev().obj());
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finish_update = objective_converged || search_failed;
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}
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if (finish_update) {
@@ -1218,13 +1215,11 @@ inline auto laplace_marginal_density_est(
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// first Newton step.
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auto make_state = [&](auto&& theta_0) {
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if constexpr (InitTheta) {
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Eigen::VectorXd a_init = covariance.llt().solve(
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Eigen::VectorXd(theta_0));
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return internal::NewtonState(theta_size, obj_fun, theta_grad_f,
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a_init, theta_0);
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} else {
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return internal::NewtonState(theta_size, obj_fun, theta_grad_f,
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Eigen::VectorXd a_init = covariance.llt().solve(Eigen::VectorXd(theta_0));
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return internal::NewtonState(theta_size, obj_fun, theta_grad_f, a_init,
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theta_0);
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} else {
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return internal::NewtonState(theta_size, obj_fun, theta_grad_f, theta_0);
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}
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};
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auto state = make_state(theta_init);

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