Stan Math Library  2.20.0
reverse mode automatic differentiation
inv_square.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_INV_SQUARE_HPP
2 #define STAN_MATH_REV_SCAL_FUN_INV_SQUARE_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 inv_square_vari : public op_v_vari {
13  public:
14  explicit inv_square_vari(vari* avi) : op_v_vari(inv_square(avi->val_), avi) {}
15  void chain() {
16  avi_->adj_ -= 2 * adj_ / (avi_->val_ * avi_->val_ * avi_->val_);
17  }
18 };
19 } // namespace internal
20 
40 inline var inv_square(const var& a) {
41  return var(new internal::inv_square_vari(a.vi_));
42 }
43 
44 } // namespace math
45 } // namespace stan
46 #endif
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 > inv_square(const fvar< T > &x)
Definition: inv_square.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
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
Definition: inv_square.hpp:15

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