11 #ifndef EIGEN_MATHFUNCTIONSIMPL_H
12 #define EIGEN_MATHFUNCTIONSIMPL_H
29 T generic_fast_tanh_float(
const T& a_x)
32 #ifdef EIGEN_VECTORIZE_FMA
33 const T plus_clamp = pset1<T>(7.99881172180175781f);
34 const T minus_clamp = pset1<T>(-7.99881172180175781f);
36 const T plus_clamp = pset1<T>(7.90531110763549805f);
37 const T minus_clamp = pset1<T>(-7.90531110763549805f);
39 const T tiny = pset1<T>(0.0004f);
40 const T x = pmax(pmin(a_x, plus_clamp), minus_clamp);
41 const T tiny_mask = pcmp_lt(pabs(a_x), tiny);
43 const T alpha_1 = pset1<T>(4.89352455891786e-03f);
44 const T alpha_3 = pset1<T>(6.37261928875436e-04f);
45 const T alpha_5 = pset1<T>(1.48572235717979e-05f);
46 const T alpha_7 = pset1<T>(5.12229709037114e-08f);
47 const T alpha_9 = pset1<T>(-8.60467152213735e-11f);
48 const T alpha_11 = pset1<T>(2.00018790482477e-13f);
49 const T alpha_13 = pset1<T>(-2.76076847742355e-16f);
52 const T beta_0 = pset1<T>(4.89352518554385e-03f);
53 const T beta_2 = pset1<T>(2.26843463243900e-03f);
54 const T beta_4 = pset1<T>(1.18534705686654e-04f);
55 const T beta_6 = pset1<T>(1.19825839466702e-06f);
58 const T x2 = pmul(x, x);
61 T p = pmadd(x2, alpha_13, alpha_11);
62 p = pmadd(x2, p, alpha_9);
63 p = pmadd(x2, p, alpha_7);
64 p = pmadd(x2, p, alpha_5);
65 p = pmadd(x2, p, alpha_3);
66 p = pmadd(x2, p, alpha_1);
70 T q = pmadd(x2, beta_6, beta_4);
71 q = pmadd(x2, q, beta_2);
72 q = pmadd(x2, q, beta_0);
75 return pselect(tiny_mask, x, pdiv(p, q));
78 template<
typename RealScalar>
79 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
80 RealScalar positive_real_hypot(
const RealScalar& x,
const RealScalar& y)
82 EIGEN_USING_STD(sqrt);
84 p = numext::maxi(x,y);
85 if(p==RealScalar(0))
return RealScalar(0);
86 qp = numext::mini(y,x) / p;
87 return p * sqrt(RealScalar(1) + qp*qp);
90 template<
typename Scalar>
94 static EIGEN_DEVICE_FUNC
95 inline RealScalar run(
const Scalar& x,
const Scalar& y)
98 return positive_real_hypot<RealScalar>(abs(x), abs(y));
106 #endif // EIGEN_MATHFUNCTIONSIMPL_H