inv_sqrt.hpp

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#ifndef STAN_MATH_PRIM_FUN_INV_SQRT_HPP
#define STAN_MATH_PRIM_FUN_INV_SQRT_HPP
 
#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/fun/Eigen.hpp>
#include <stan/math/prim/fun/inv.hpp>
#include <stan/math/prim/fun/sqrt.hpp>
#include <stan/math/prim/functor/apply_scalar_unary.hpp>
#include <stan/math/prim/functor/apply_vector_unary.hpp>
#include <cmath>
 
namespace stan {
namespace math {
 
template <typename T, require_arithmetic_t<T>* = nullptr>
inline auto inv_sqrt(const T x) {
  return inv(std::sqrt(x));
}
 
template <typename T, require_complex_t<T>* = nullptr>
inline auto inv_sqrt(const T x) {
  return inv(sqrt(x));
}
 
struct inv_sqrt_fun {
  template <typename T>
  static inline auto fun(const T& x) {
    return inv_sqrt(x);
  }
};
 
template <typename Container, require_ad_container_t<Container>* = nullptr>
inline auto inv_sqrt(const Container& x) {
  return apply_scalar_unary<inv_sqrt_fun, Container>::apply(x);
}
 
template <typename Container, require_not_var_matrix_t<Container>* = nullptr,
          require_container_bt<std::is_arithmetic, Container>* = nullptr>
inline auto inv_sqrt(const Container& x) {
// Eigen 3.4.0 has precision issues on ARM64 with vectorised rsqrt
// Resolved in current master branch, below can be removed on next release
#ifdef __aarch64__
  return apply_scalar_unary<inv_sqrt_fun, Container>::apply(x);
#else
  return apply_vector_unary<Container>::apply(
      x, [](const auto& v) { return v.array().rsqrt(); });
#endif
}
 
}  // namespace math
}  // namespace stan
 
#endif