1 #ifndef STAN_MATH_REV_SCAL_FUN_MULTIPLY_LOG_HPP 2 #define STAN_MATH_REV_SCAL_FUN_MULTIPLY_LOG_HPP 22 avi_->
adj_ = std::numeric_limits<double>::quiet_NaN();
23 bvi_->
adj_ = std::numeric_limits<double>::quiet_NaN();
27 bvi_->
adj_ +=
adj_ * std::numeric_limits<double>::infinity();
40 avi_->
adj_ = std::numeric_limits<double>::quiet_NaN();
51 bvi_->
adj_ +=
adj_ * std::numeric_limits<double>::infinity();
multiply_log_dv_vari(double a, vari *bvi)
fvar< T > log(const fvar< T > &x)
The variable implementation base class.
bool is_any_nan(const T &x)
Returns true if the input is NaN and false otherwise.
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
Independent (input) and dependent (output) variables for gradients.
const double val_
The value of this variable.
multiply_log_vv_vari(vari *avi, vari *bvi)
vari * vi_
Pointer to the implementation of this variable.
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
multiply_log_vd_vari(vari *avi, double b)
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...