Stan Math Library  2.11.0
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/core.hpp>
5 
7 
8 namespace stan {
9 
10  namespace math {
11 
12  template <typename T>
13  inline
14  fvar<T>
15  log_sum_exp(const fvar<T>& x1, const fvar<T>& x2) {
17  using std::exp;
18  return fvar<T>(log_sum_exp(x1.val_, x2.val_),
19  x1.d_ / (1 + exp(x2.val_ - x1.val_))
20  + x2.d_ / (exp(x1.val_ - x2.val_) + 1));
21  }
22 
23  template <typename T>
24  inline
25  fvar<T>
26  log_sum_exp(const double x1, const fvar<T>& x2) {
28  using std::exp;
29  return fvar<T>(log_sum_exp(x1, x2.val_),
30  x2.d_ / (exp(x1 - x2.val_) + 1));
31  }
32 
33  template <typename T>
34  inline
35  fvar<T>
36  log_sum_exp(const fvar<T>& x1, const double x2) {
38  using std::exp;
39  return fvar<T>(log_sum_exp(x1.val_, x2),
40  x1.d_ / (1 + exp(x2 - x1.val_)));
41  }
42 
43  }
44 }
45 #endif
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10

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