Stan Math Library  2.20.0
reverse mode automatic differentiation
log1p.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_LOG1P_HPP
2 #define STAN_MATH_REV_SCAL_FUN_LOG1P_HPP
3 
4 #include <stan/math/rev/meta.hpp>
5 #include <stan/math/rev/core.hpp>
7 
8 namespace stan {
9 namespace math {
10 
11 namespace internal {
12 class log1p_vari : public op_v_vari {
13  public:
14  explicit log1p_vari(vari* avi) : op_v_vari(log1p(avi->val_), avi) {}
15  void chain() { avi_->adj_ += adj_ / (1 + avi_->val_); }
16 };
17 } // namespace internal
18 
29 inline var log1p(const var& a) { return var(new internal::log1p_vari(a.vi_)); }
30 
31 } // namespace math
32 } // namespace stan
33 #endif
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
Definition: log1p.hpp:15
The variable implementation base class.
Definition: vari.hpp:30
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:33
friend class var
Definition: vari.hpp:32
const double val_
The value of this variable.
Definition: vari.hpp:38
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:45
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:12
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
Definition: vari.hpp:44

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