Stan Math Library  2.12.0
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 #include <cmath>
8 
9 #ifdef _MSC_VER
10 #include <boost/math/special_functions/expm1.hpp>
11 using boost::math::expm1;
12 #endif
13 
14 namespace stan {
15  namespace math {
16 
17  namespace {
18  class log1m_exp_v_vari : public op_v_vari {
19  public:
20  explicit log1m_exp_v_vari(vari* avi) :
21  op_v_vari(log1m_exp(avi->val_),
22  avi) {
23  }
24  void chain() {
25  // derivative of
26  // log(1-exp(x)) = -exp(x)/(1-exp(x))
27  // = -1/(exp(-x)-1)
28  // = -1/expm1(-x)
29  avi_->adj_ -= adj_ / ::expm1(-(avi_->val_));
30  }
31  };
32  }
33 
38  inline var log1m_exp(const var& a) {
39  return var(new log1m_exp_v_vari(a.vi_));
40  }
41 
42  }
43 }
44 #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)
Definition: log1m_exp.hpp:16
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:42

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