Stan Math Library  2.20.0
reverse mode automatic differentiation
exp2.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_EXP2_HPP
2 #define STAN_MATH_REV_SCAL_FUN_EXP2_HPP
3 
4 #include <stan/math/rev/meta.hpp>
5 #include <stan/math/rev/core.hpp>
7 #include <cmath>
8 
9 namespace stan {
10 namespace math {
11 
12 namespace internal {
13 class exp2_vari : public op_v_vari {
14  public:
15  explicit exp2_vari(vari* avi) : op_v_vari(std::pow(2.0, avi->val_), avi) {}
16  void chain() { avi_->adj_ += adj_ * val_ * LOG_2; }
17 };
18 } // namespace internal
19 
46 inline var exp2(const var& a) { return var(new internal::exp2_vari(a.vi_)); }
47 
48 } // namespace math
49 } // namespace stan
50 #endif
const double LOG_2
The natural logarithm of 2, .
Definition: constants.hpp:37
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
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
Definition: exp2.hpp:16
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:45
fvar< T > exp2(const fvar< T > &x)
Definition: exp2.hpp:14
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
Definition: vari.hpp:44
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:16

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