Automatic Differentiation
 
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lmultiply.hpp
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1#ifndef STAN_MATH_PRIM_FUN_LMULTIPLY_HPP
2#define STAN_MATH_PRIM_FUN_LMULTIPLY_HPP
3
7#include <cmath>
8
9namespace stan {
10namespace math {
11
24template <typename T1, typename T2, require_all_arithmetic_t<T1, T2>* = nullptr>
25inline return_type_t<T1, T2> lmultiply(const T1 a, const T2 b) {
26 using std::log;
27 if (a == 0 && b == 0) {
28 return 0;
29 }
30 return a * log(b);
31}
32
44template <typename T1, typename T2, require_any_container_t<T1, T2>* = nullptr,
45 require_all_not_var_matrix_t<T1, T2>* = nullptr>
46inline auto lmultiply(const T1& a, const T2& b) {
48 a, b, [&](const auto& c, const auto& d) { return lmultiply(c, d); });
49}
50
51} // namespace math
52} // namespace stan
53
54#endif
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
fvar< T > log(const fvar< T > &x)
Definition log.hpp:15
fvar< T > lmultiply(const fvar< T > &x1, const fvar< T > &x2)
Definition lmultiply.hpp:13
auto apply_scalar_binary(const T1 &x, const T2 &y, const F &f)
Base template function for vectorization of binary scalar functions defined by applying a functor to ...
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...