Boost C++ Libraries

This header provides default policy implementations for using the gradient-based optimizers with boost::math::differentiation::reverse_mode::rvar These policies handle:

Synopsis

#include <boost/math/optimization/detail/rdiff_optimization_policies>

namespace boost {
namespace math {
namespace optimization {

namespace rdiff = boost::math::differentiation::reverse_mode;

/**
 * @brief> function evaluation policy for reverse mode autodiff
 * @arg objective> objective function to evaluate
 * @arg x> argument list
 */
template<typename RealType>
struct reverse_mode_function_eval_policy
{
  template<typename Objective, class ArgumentContainer>
  rdiff::rvar<RealType, 1> operator()(Objective&& objective,
                                      ArgumentContainer& x);
};

/**
 * @brief> gradient evaluation policy
 * @arg obj_f> objective
 * @arg x> argument list
 * @arg f_eval_olicy> funciton evaluation policy. These need to be
 *                    done in tandem
 * @arg obj_v> reference to variable inside gradient class
 */
template<typename RealType>
struct reverse_mode_gradient_evaluation_policy
{
  template<class Objective,
           class ArgumentContainer,
           class FunctionEvaluationPolicy>
  void operator()(Objective&& obj_f,
                  ArgumentContainer& x,
                  FunctionEvaluationPolicy&& f_eval_pol,
                  RealType& obj_v,
                  std::vector<RealType>& g)
};
 /*
 * init policies
 */

/* default rvar policy */
template<typename RealType>
struct tape_initializer_rvar
{
    template<class ArgumentContainer>
    void operator()(ArgumentContainer& x) const noexcept;
};

/* random uniform */
template<typename RealType>
struct random_uniform_initializer_rvar
{
  RealType low_, high_;
  size_t seed_;
  random_uniform_initializer_rvar(RealType low = 0,
                                  RealType high = 1,
                                  size_t seed = std::random_device{}());

  template<class ArgumentContainer>
  void operator()(ArgumentContainer& x) const;
};

/* constant initializer */
template<typename RealType>
struct costant_initializer_rvar
{
  RealType constant;
  explicit costant_initializer_rvar(RealType v = 0);

  template<class ArgumentContainer>
  void operator()(ArgumentContainer& x) const;
};
} // namespace optimization
} // namespace math
} // namespace boost

Function evaluation policies

A function evaluation policy defines how an objective is evaluated at the current parameters, and is responsible for any AD bookkeeping required before the call.

reverse_mode_function_eval_policy

template<typename RealType> struct reverse_mode_function_eval_policy { template<typename Objective, class ArgumentContainer> rdiff::rvar<RealType, 1> operator()(Objective&& objective, ArgumentContainer& x); };

This policy evaluates the objective objective(x) using reverse-mode AD and ensures the active tape is in a valid state before evaluation:

ArgumentContainer must contain rdiff::rvar<RealType,1> values.

Gradient evaluation policies

A gradient evaluation policy defines how gradients are computed and extracted into an ordinary numeric container.

reverse_mode_gradient_evaluation_policy

template<typename RealType> struct reverse_mode_gradient_evaluation_policy { template<class Objective, class ArgumentContainer, class FunctionEvaluationPolicy> void operator()(Objective&& obj_f, ArgumentContainer& x, FunctionEvaluationPolicy&& f_eval_pol, RealType& obj_v, std::vector<RealType>& g); };

This policy computes the objective value and gradient using reverse-mode autodiff

Initialization policies

Initialization policies prepare the argument container and the reverse-mode tape for optimization. They establish tape checkpoints that are later used by function/gradient evaluation policies.

tape_initializer_rvar

template<typename RealType> struct tape_initializer_rvar { template<class ArgumentContainer> void operator()(ArgumentContainer& x) const noexcept; };

This policy: * statically requires ArgumentContainer::value_type to be rdiff::rvar<RealType,1>, * adds a checkpoint to the active reverse-mode tape via tape.add_checkpoint()

random_uniform_initializer_rvar

template<typename RealType>
struct random_uniform_initializer_rvar
{
random_uniform_initializer_rvar(RealType low = 0,
RealType high = 1,
size_t seed = std::random_device{}());

template<class ArgumentContainer>
void operator()(ArgumentContainer& x) const;
};

This policy initializes each element of x independently as:

x[i] = rdiff::rvar<RealType,1>(U(low, high))

using

boost::random::mt19937

and

boost::random::uniform_real_distribution<RealType>

costant_initializer_rvar

template<typename RealType>
struct costant_initializer_rvar
{
explicit costant_initializer_rvar(RealType v = 0);

template<class ArgumentContainer>
void operator()(ArgumentContainer& x) const;
};

This policy initializes each element of x to the constant value v