log_sum_exp.hpp

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#ifndef STAN_MATH_FWD_FUN_LOG_SUM_EXP_HPP
#define STAN_MATH_FWD_FUN_LOG_SUM_EXP_HPP
 
#include <stan/math/fwd/meta.hpp>
#include <stan/math/fwd/core.hpp>
#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/fun/Eigen.hpp>
#include <stan/math/prim/fun/constants.hpp>
#include <stan/math/prim/fun/log_sum_exp.hpp>
#include <stan/math/prim/fun/to_ref.hpp>
#include <cmath>
#include <vector>
 
namespace stan {
namespace math {
 
template <typename T>
inline fvar<T> log_sum_exp(const fvar<T>& x1, const fvar<T>& x2) {
  using std::exp;
  return fvar<T>(log_sum_exp(x1.val_, x2.val_),
                 x1.d_ * inv_logit(-(x2.val_ - x1.val_))
                     + x2.d_ * inv_logit(-(x1.val_ - x2.val_)));
}
 
template <typename T>
inline fvar<T> log_sum_exp(double x1, const fvar<T>& x2) {
  using std::exp;
  if (x1 == NEGATIVE_INFTY) {
    return fvar<T>(x2.val_, x2.d_);
  }
  return fvar<T>(log_sum_exp(x1, x2.val_), x2.d_ * inv_logit(-(x1 - x2.val_)));
}
 
template <typename T>
inline fvar<T> log_sum_exp(const fvar<T>& x1, double x2) {
  return log_sum_exp(x2, x1);
}
 
template <typename T, require_container_st<is_fvar, T>* = nullptr>
inline auto log_sum_exp(const T& x) {
  return apply_vector_unary<ref_type_t<T>>::reduce(
      to_ref(x), [&](const auto& v) {
        using T_fvar_inner = typename value_type_t<decltype(v)>::Scalar;
        using mat_type = Eigen::Matrix<T_fvar_inner, -1, -1>;
        mat_type vals = v.val();
        mat_type exp_vals = vals.array().exp();
 
        return fvar<T_fvar_inner>(
            log_sum_exp(vals),
            v.d().cwiseProduct(exp_vals).sum() / exp_vals.sum());
      });
}
 
}  // namespace math
}  // namespace stan
#endif