Stan Math Library  2.12.0
reverse mode automatic differentiation
operator_unary_decrement.hpp
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1 #ifndef STAN_MATH_REV_CORE_OPERATOR_UNARY_DECREMENT_HPP
2 #define STAN_MATH_REV_CORE_OPERATOR_UNARY_DECREMENT_HPP
3 
7 #include <limits>
8 
9 namespace stan {
10  namespace math {
11 
12  namespace {
13  class decrement_vari : public op_v_vari {
14  public:
15  explicit decrement_vari(vari* avi) :
16  op_v_vari(avi->val_ - 1.0, avi) {
17  }
18  void chain() {
19  if (unlikely(is_nan(avi_->val_)))
20  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
21  else
22  avi_->adj_ += adj_;
23  }
24  };
25  }
26 
40  inline var& operator--(var& a) {
41  a.vi_ = new decrement_vari(a.vi_);
42  return a;
43  }
44 
56  inline var operator--(var& a, int /*dummy*/) {
57  var temp(a);
58  a.vi_ = new decrement_vari(a.vi_);
59  return temp;
60  }
61 
62  }
63 }
64 #endif
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:30
var & operator--(var &a)
Prefix decrement operator for variables (C++).
#define unlikely(x)
Definition: likely.hpp:9
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:42
int is_nan(const fvar< T > &x)
Returns 1 if the input's value is NaN and 0 otherwise.
Definition: is_nan.hpp:21

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