Stan Math Library  2.14.0
reverse mode automatic differentiation
log1m_exp.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_LOG1M_EXP_HPP
2 #define STAN_MATH_REV_SCAL_FUN_LOG1M_EXP_HPP
3 
4 #include <stan/math/rev/core.hpp>
7 
8 namespace stan {
9  namespace math {
10 
11  namespace {
12  class log1m_exp_v_vari : public op_v_vari {
13  public:
14  explicit log1m_exp_v_vari(vari* avi) :
15  op_v_vari(log1m_exp(avi->val_), avi) { }
16 
17  void chain() {
18  avi_->adj_ -= adj_ / expm1(-(avi_->val_));
19  }
20  };
21  }
22 
34  inline var log1m_exp(const var& x) {
35  return var(new log1m_exp_v_vari(x.vi_));
36  }
37 
38  }
39 }
40 #endif
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:30
fvar< T > expm1(const fvar< T > &x)
Definition: expm1.hpp:12
fvar< T > log1m_exp(const fvar< T > &x)
Return the natural logarithm of one minus the exponentiation of the specified argument.
Definition: log1m_exp.hpp:23
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:42

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