text: #ifndef STAN_MATH_FWD_MAT_FUNCTOR_GRADIENT_HPP
  #define STAN_MATH_FWD_MAT_FUNCTOR_GRADIENT_HPP
  
  #include <stan/math/fwd/core.hpp>
  #include <stan/math/prim/mat/fun/Eigen.hpp>
  
  namespace stan {
  namespace math {
  
  /**
   * Calculate the value and the gradient of the specified function
   * at the specified argument.
   *
   * <p>The functor must implement
   *
   * <code>
   * fvar<T>
   * operator()(const Eigen::Matrix<T, Eigen::Dynamic, 1>&)
   * </code>
   *
   * using only operations that are defined for
   * <code>fvar</code>.  This latter constraint usually
   * requires the functions to be defined in terms of the libraries
   * defined in Stan or in terms of functions with appropriately
   * general namespace imports that eventually depend on functions
   * defined in Stan.
   *
   * <p>Time and memory usage is on the order of the size of the
   * fully unfolded expression for the function applied to the
   * argument, independently of dimension.
   *
   * @tparam F Type of function
   * @param[in] f Function
   * @param[in] x Argument to function
   * @param[out] fx Function applied to argument
   * @param[out] grad_fx Gradient of function at argument
   */
  template <typename T, typename F>
  void gradient(const F& f, const Eigen::Matrix<T, Eigen::Dynamic, 1>& x, T& fx,
                Eigen::Matrix<T, Eigen::Dynamic, 1>& grad_fx) {
    Eigen::Matrix<fvar<T>, Eigen::Dynamic, 1> x_fvar(x.size());
    grad_fx.resize(x.size());
    for (int i = 0; i < x.size(); ++i) {
      for (int k = 0; k < x.size(); ++k)
        x_fvar(k) = fvar<T>(x(k), k == i);
      fvar<T> fx_fvar = f(x_fvar);
      if (i == 0)
        fx = fx_fvar.val_;
      grad_fx(i) = fx_fvar.d_;
    }
  }
  
  }  // namespace math
  }  // namespace stan
  #endif
  