float64_t CKLDualInferenceMethod::adjust_step(void *obj,
const float64_t *parameters, const float64_t *direction,
const int dim, const float64_t step)
{
/* Note that parameters = parameters_pre_iter - step * gradient_pre_iter */
CKLDualInferenceMethod * obj_prt
= static_cast<CKLDualInferenceMethod *>(obj);
ASSERT(obj_prt != NULL);
float64_t *non_const_direction=const_cast<float64_t *>(direction);
SGVector<float64_t> sg_direction(non_const_direction, dim, false);
CDualVariationalGaussianLikelihood* lik= obj_prt->get_dual_variational_likelihood();
float64_t adjust_stp=lik->adjust_step_wrt_dual_parameter(sg_direction, step);
return adjust_stp;
}
float64_t CKLDualInferenceMethodMinimizer::adjust_step(void *obj, const float64_t *parameters,
const float64_t *direction, const int dim, const float64_t step)
{
/* Note that parameters = parameters_pre_iter - step * gradient_pre_iter */
CKLDualInferenceMethodMinimizer * obj_prt
= static_cast<CKLDualInferenceMethodMinimizer *>(obj);
REQUIRE(obj_prt, "The instance object passed to L-BFGS optimizer should not be NULL\n");
float64_t *non_const_direction=const_cast<float64_t *>(direction);
SGVector<float64_t> sg_direction(non_const_direction, dim, false);
KLDualInferenceMethodCostFunction* fun=dynamic_cast<KLDualInferenceMethodCostFunction*>(obj_prt->m_fun);
REQUIRE(fun, "The cost function must be KLDualInferenceMethodCostFunction\n");
CDualVariationalGaussianLikelihood* lik=fun->get_dual_variational_likelihood();
float64_t adjust_stp=lik->adjust_step_wrt_dual_parameter(sg_direction, step);
return adjust_stp;
}
