Stan Math Library  2.20.0
reverse mode automatic differentiation
log_sum_exp.hpp
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG_SUM_EXP_HPP
2 #define STAN_MATH_FWD_SCAL_FUN_LOG_SUM_EXP_HPP
3 
4 #include <stan/math/fwd/meta.hpp>
5 #include <stan/math/fwd/core.hpp>
7 
8 namespace stan {
9 namespace math {
10 
11 template <typename T>
12 inline fvar<T> log_sum_exp(const fvar<T>& x1, const fvar<T>& x2) {
13  using std::exp;
14  return fvar<T>(log_sum_exp(x1.val_, x2.val_),
15  x1.d_ / (1 + exp(x2.val_ - x1.val_))
16  + x2.d_ / (exp(x1.val_ - x2.val_) + 1));
17 }
18 
19 template <typename T>
20 inline fvar<T> log_sum_exp(double x1, const fvar<T>& x2) {
21  using std::exp;
22  return fvar<T>(log_sum_exp(x1, x2.val_), x2.d_ / (exp(x1 - x2.val_) + 1));
23 }
24 
25 template <typename T>
26 inline fvar<T> log_sum_exp(const fvar<T>& x1, double x2) {
27  using std::exp;
28  return fvar<T>(log_sum_exp(x1.val_, x2), x1.d_ / (1 + exp(x2 - x1.val_)));
29 }
30 
31 } // namespace math
32 } // namespace stan
33 #endif
T d_
The tangent (derivative) of this variable.
Definition: fvar.hpp:50
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:12
T val_
The value of this variable.
Definition: fvar.hpp:45
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:11
This template class represents scalars used in forward-mode automatic differentiation, which consist of values and directional derivatives of the specified template type.
Definition: fvar.hpp:41

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